diff --git a/.gitignore b/.gitignore index d2c98c52..57901c19 100644 --- a/.gitignore +++ b/.gitignore @@ -6,3 +6,5 @@ notebooks/.env notebooks/.DS_Store .DS_Store *.in +.virtual_documents/ +anaconda_projects/ diff --git a/README.md b/README.md index f637438f..6669142b 100644 --- a/README.md +++ b/README.md @@ -1,77 +1,78 @@ -# Project overview -... +## 💤 Sleep Health & Lifestyle Analysis +#### Business Case: Predicting Sleep Disorders -# Installation -1. **Clone the repository**: +### 📌 Project Overview +This project analyzes a Sleep Health & Lifestyle dataset to identify key factors associated with sleep disorders (Insomnia and Sleep Apnea). +The goal is to understand how lifestyle, physiological metrics, and stress levels contribute to sleep disorder risk and to support early intervention strategies. -```bash -git clone https://github.com/YourUsername/repository_name.git -``` -2. **Install UV** +### 🎯 Business Problem +Sleep disorders increase medical costs, stress, and reduce quality of life. +Identifying high-risk individuals early enables: +- Preventive healthcare +- Reduced diagnosis costs +- Targeted wellbeing programs -If you're a MacOS/Linux user type: -```bash -curl -LsSf https://astral.sh/uv/install.sh | sh -``` +### ❓ Research Questions +- Which lifestyle and physiological factors correlate with sleep disorders? +- Can stress, BMI, activity, and sleep patterns predict disorder presence? +- What differentiates insomnia from sleep apnea? -If you're a Windows user open an Anaconda Powershell Prompt and type : -```bash -powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" -``` +### 🧪 Hypotheses +#### Primary Hypothesis (H1) +Individuals with high stress, high BMI, low sleep duration, and poor sleep quality are significantly more likely to have a sleep disorder. +**H0:** Sleep disorder presence is independent of these factors. -3. **Create an environment** +#### Secondary Hypotheses +- **H1a:** Obesity increases likelihood of sleep apnea. +- **H1b:** Higher stress correlates with insomnia. +- **H1c:** Sleeping <6 hours increases disorder risk. +- **H1d:** Low physical activity (<40 min/day) increases disorder prevalence. +- **H1e:** High heart rate / BP increases apnea risk. -```bash -uv venv -``` -3. **Activate the environment** +### 🧹 Data Cleaning Summary +- Checked for missing values, incorrect data types, and duplicates. +- Standardized column names and trimmed string formatting. +- Normalized inconsistent categories (e.g., "Normal" vs "Normal Weight"). +- Split Blood Pressure into numeric Systolic and Diastolic columns. +- Converted all relevant columns to numeric types. +- Filled missing Sleep Disorder values with "No Disorder". +- Removed duplicate rows (242 duplicates dropped). -If you're a MacOS/Linux user type (if you're using a bash shell): +Final result: a clean, consistent dataset ready for analysis. -```bash -source ./venv/bin/activate -``` +### 📊 Exploratory Data Analysis (EDA) +Univariate and bivariate analysis was performed to understand data distributions and variable relationships. +- Target Distribution: A slight imbalance was observed, with 73 "No Disorder" cases versus 59 combined cases of Insomnia (n=29) and Sleep Apnea (n=30). +- Key Correlations: A strong positive correlation between Blood Pressure (Systolic/Diastolic) and Heart Rate with sleep disorders was confirmed. -If you're a MacOS/Linux user type (if you're using a csh/tcsh shell): +### 🔬 Hypothesis Testing & Results (H1, H2 & H3) +Statistical tests and Logistic Regression models were used to validate the hypotheses, segmenting results by disorder type. -```bash -source ./venv/bin/activate.csh -``` +#### H1: Lifestyle and Physiological Factors -If you're a Windows user type: +**H1a:** Obesity & Apnea ✅ Validated --> Apnea prevalence in the "Obese" group (57.14%) was significantly higher than in the "Normal" group (9.59%). +**H1b:** Stress & Insomnia✅ Validated --> Patients with Insomnia reported the highest average stress level (7.21). +**H1d:** Low Activity (<40 min)❌ Not Validated --> No significant difference in disorder prevalence was found between the low activity group (42%) and the adequate activity group (45%). +**H1e:** High HR / BP & Apnea ✅ Validated --> Elevated blood pressure and heart rate are significant indicators for Sleep Apnea risk. -```bash -.\venv\Scripts\activate -``` +#### H2: Age Effects +Age was established to have a moderate positive association with sleep disorders. +- Apnea vs. Insomnia: Sleep Apnea patients are consistently older (44.7 years) than Insomnia patients (41.6 years). +- Sleep Duration: The hypothesis that age correlates with lower sleep duration was rejected, with the opposite observed in this sample (positive correlation). -4. **Install dependencies**: +#### H3: Combined Risk Factor Model +An integrated risk scoring system for population segmentation was developed and strongly validated. -```bash -uv pip install -r requirements.txt -``` +- Low Risk = 55% of population --> 18.31% disorder rate +- Medium Risk = 17% of population --> 62.50% disoreder rate +- High Risk = 28% of population --> 83.78% disorder rate -# Questions -... - -# Dataset -... - -## Main dataset issues - -- ... -- ... -- ... - -## Solutions for the dataset issues -... - -# Conclussions -... - -# Next steps -... +### 🏁 Conclusions & Insights +1. Predictive Efficacy: The combined risk model (H3) demonstrated a high capacity for population segmentation, showing a clear dose-response relationship (higher risk score equals higher disorder prevalence). +2. Disorder Differentiation: Risk factors are distinct: Insomnia is primarily associated with high stress levels and slightly younger ages; Sleep Apnea is strongly associated with high physiological metrics (BP, HR) and overweight/obesity. +3. Intervention Focus: The most effective preventive strategies should focus on blood pressure control and weight management to mitigate Apnea risk. \ No newline at end of file diff --git a/archive.zip b/archive.zip new file mode 100644 index 00000000..32940cfe Binary files /dev/null and b/archive.zip differ diff --git a/config.yaml b/config.yaml index dc28ac67..82e339ee 100644 --- a/config.yaml +++ b/config.yaml @@ -1,5 +1,5 @@ input_data: - file: "../data/raw/raw_data_file.csv" + file: "../data/raw/sleep_health_and_lifestyle_dataset.csv" output_data: - file: "../data/clean/cleaned_data_file.csv" + file: "../data/clean/sleep_health_project_clean.csv" diff --git a/data/clean/cleaned_data_file.csv b/data/clean/cleaned_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/data/clean/sleep_health_project_clean.csv b/data/clean/sleep_health_project_clean.csv new file mode 100644 index 00000000..cc93b280 --- /dev/null +++ b/data/clean/sleep_health_project_clean.csv @@ -0,0 +1,133 @@ +person_id,gender,age,occupation,sleep_duration,quality_of_sleep,physical_activity_level,stress_level,bmi_category,blood_pressure,heart_rate,daily_steps,sleep_disorder,systolic,diastolic +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,No Disorder,126,83 +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,No Disorder,125,80 +4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea,140,90 +6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia,140,90 +7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia,140,90 +8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,No Disorder,120,80 +14,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,No Disorder,120,80 +17,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Sleep Apnea,132,87 +18,Male,29,Doctor,6.0,6,30,8,Normal,120/80,70,8000,Sleep Apnea,120,80 +19,Female,29,Nurse,6.5,5,40,7,Normal,132/87,80,4000,Insomnia,132,87 +20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +31,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Sleep Apnea,130,86 +32,Female,30,Nurse,6.4,5,35,7,Normal,130/86,78,4100,Insomnia,130,86 +33,Female,31,Nurse,7.9,8,75,4,Normal,117/76,69,6800,No Disorder,117,76 +34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea,120,80 +51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,No Disorder,120,80 +53,Male,32,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,No Disorder,120,80 +63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +67,Male,32,Accountant,7.2,8,50,6,Normal,118/76,68,7000,No Disorder,118,76 +68,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,Insomnia,125,80 +69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,No Disorder,128,85 +71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +75,Male,33,Doctor,6.0,6,30,8,Normal,125/80,72,5000,No Disorder,125,80 +81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea,131,86 +83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,No Disorder,128,84 +85,Male,35,Software Engineer,7.5,8,60,5,Normal,120/80,70,8000,No Disorder,120,80 +86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,No Disorder,125,80 +89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,No Disorder,125,80 +94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia,115,75 +96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea,129,84 +105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea,115,75 +106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia,129,84 +107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,No Disorder,126,83 +108,Male,37,Engineer,7.8,8,70,4,Normal,120/80,68,7000,No Disorder,120,80 +110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +126,Female,37,Nurse,7.5,8,60,4,Normal,120/80,70,8000,No Disorder,120,80 +127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,No Disorder,115,75 +138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea,130,85 +146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea,135,88 +147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia,130,85 +148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia,132,87 +149,Female,39,Lawyer,6.9,7,50,6,Normal,128/85,75,5500,No Disorder,128,85 +150,Female,39,Accountant,8.0,9,80,3,Normal,115/78,67,7500,No Disorder,115,78 +152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,No Disorder,130,85 +162,Female,40,Accountant,7.2,8,55,6,Normal,119/77,73,7300,No Disorder,119,77 +164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,No Disorder,130,85 +166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +167,Male,41,Engineer,7.3,8,70,6,Normal,121/79,72,6200,No Disorder,121,79 +168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,No Disorder,125,82 +170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea,130,85 +187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia,130,85 +204,Male,43,Engineer,6.9,6,47,7,Normal,117/76,69,6800,No Disorder,117,76 +205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,No Disorder,122,80 +206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,No Disorder,130,85 +219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea,130,85 +220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea,130,85 +221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia,130,85 +249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,No Disorder,130,85 +250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,No Disorder,130,85 +251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia,135,90 +253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia,135,90 +262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,No Disorder,135,90 +264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,No Disorder,125,82 +265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia,142,92 +266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,No Disorder,140,95 +269,Female,49,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea,139,91 +279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia,140,95 +280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +281,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,No Disorder,140,95 +282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +283,Female,50,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +303,Female,51,Nurse,7.1,7,55,6,Normal,125/82,72,6000,No Disorder,125,82 +304,Female,51,Nurse,6.0,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea,140,95 +307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia,130,85 +313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia,125,80 +317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,No Disorder,125,80 +340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea,140,95 +342,Female,56,Doctor,8.2,9,90,3,Normal,118/75,65,10000,No Disorder,118,75 +344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +353,Female,58,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +359,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,No Disorder,140,95 +361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +365,Female,59,Nurse,8.0,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 +367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea,140,95 diff --git a/data/raw/Sleep_health_and_lifestyle_dataset.csv b/data/raw/Sleep_health_and_lifestyle_dataset.csv new file mode 100644 index 00000000..f0be22ac --- /dev/null +++ b/data/raw/Sleep_health_and_lifestyle_dataset.csv @@ -0,0 +1,375 @@ +Person ID,Gender,Age,Occupation,Sleep Duration,Quality of Sleep,Physical Activity Level,Stress Level,BMI Category,Blood Pressure,Heart Rate,Daily Steps,Sleep Disorder +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,None +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None +3,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None +4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea +5,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea +6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia +7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia +8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +9,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +10,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None +12,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +13,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None +14,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +15,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +16,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +17,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Sleep Apnea +18,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,Sleep Apnea +19,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Insomnia +20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None 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+253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia +254,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia +255,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia +256,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia +257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia +258,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia +259,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia +260,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia +261,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia +262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,None +263,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,None +264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,None +265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia +266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea 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+295,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +296,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +297,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +298,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +300,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +301,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +302,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +303,Female,51,Nurse,7.1,7,55,6,Normal Weight,125/82,72,6000,None +304,Female,51,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +306,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea +307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia +308,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia +309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia +310,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia +311,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia +312,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia +313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +314,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +315,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia +317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +318,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +320,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +321,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +322,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +323,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None 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+368,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +369,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +370,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +371,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +372,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +373,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +374,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea \ No newline at end of file diff --git a/data/raw/raw_data_file.csv b/data/raw/raw_data_file.csv deleted file mode 100644 index e69de29b..00000000 diff --git a/data/raw/sleep_health_and_lifestyle_dataset.csv b/data/raw/sleep_health_and_lifestyle_dataset.csv new file mode 100644 index 00000000..f0be22ac --- /dev/null +++ b/data/raw/sleep_health_and_lifestyle_dataset.csv @@ -0,0 +1,375 @@ +Person ID,Gender,Age,Occupation,Sleep Duration,Quality of Sleep,Physical Activity Level,Stress Level,BMI Category,Blood Pressure,Heart Rate,Daily Steps,Sleep Disorder +1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,None +2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None +3,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None +4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea +5,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea +6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia +7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia +8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +9,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +10,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None +12,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +13,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None +14,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +15,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +16,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None +17,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Sleep Apnea +18,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,Sleep Apnea +19,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Insomnia +20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None +21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +22,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +23,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +24,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None +27,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +28,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None +29,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None +30,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None +31,Female,30,Nurse,6.4,5,35,7,Normal Weight,130/86,78,4100,Sleep Apnea +32,Female,30,Nurse,6.4,5,35,7,Normal Weight,130/86,78,4100,Insomnia +33,Female,31,Nurse,7.9,8,75,4,Normal Weight,117/76,69,6800,None +34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None +35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +36,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None +37,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None +38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None +39,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None +40,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None +41,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +42,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +43,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +45,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +46,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +47,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +48,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None +49,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea +51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,None +52,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,None +53,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None +55,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +56,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +58,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +59,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +60,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None +61,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +62,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None +63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None +64,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None +65,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None 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+318,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +320,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +321,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +322,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +323,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +324,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None +326,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +327,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None +328,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +329,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None +330,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +331,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +332,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +334,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +335,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +336,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +337,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +338,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None +339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None +340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea +341,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea +342,Female,56,Doctor,8.2,9,90,3,Normal Weight,118/75,65,10000,None +343,Female,56,Doctor,8.2,9,90,3,Normal Weight,118/75,65,10000,None +344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,None +345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +346,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +347,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +348,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +349,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +351,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +352,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +353,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +354,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +355,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +356,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +357,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +358,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +359,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,None +360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,None +361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +362,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +363,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +364,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +365,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +366,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +368,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +369,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +370,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +371,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +372,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +373,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea +374,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea \ No newline at end of file diff --git a/figures/figure.png b/figures/figure.png deleted file mode 100644 index e69de29b..00000000 diff --git a/notebooks/Sleep_health_analysis_carmelina.ipynb b/notebooks/Sleep_health_analysis_carmelina.ipynb new file mode 100644 index 00000000..954ae245 --- /dev/null +++ b/notebooks/Sleep_health_analysis_carmelina.ipynb @@ -0,0 +1,2140 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "eb15ea29-8d02-43b7-828a-80ebf8711342", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a913fbb1-147e-4d55-8171-458b20c73ac9", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "7c6c15c7-89f8-4cb2-a695-1129d3d1f893", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
24Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
36Male28Software Engineer5.94308Obese140/90853000Insomnia14090
47Male29Teacher6.36407Obese140/90823500Insomnia14090
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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 4 Male 28 Sales Representative 5.9 \n", + "3 6 Male 28 Software Engineer 5.9 \n", + "4 7 Male 29 Teacher 6.3 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 4 30 8 Obese \n", + "3 4 30 8 Obese \n", + "4 6 40 7 Obese \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic diastolic \n", + "0 126/83 77 4200 No Disorder 126 83 \n", + "1 125/80 75 10000 No Disorder 125 80 \n", + "2 140/90 85 3000 Sleep Apnea 140 90 \n", + "3 140/90 85 3000 Insomnia 140 90 \n", + "4 140/90 82 3500 Insomnia 140 90 " + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean = pd.read_csv(config['output_data']['file'], encoding='ISO-8859-1')\n", + "sleep_data_clean.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "b123ec3c-d5fd-45e8-a793-8d4775eb46fa", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (132, 15)\n", + "\n", + "Columns: ['person_id', 'gender', 'age', 'occupation', 'sleep_duration', 'quality_of_sleep', 'physical_activity_level', 'stress_level', 'bmi_category', 'blood_pressure', 'heart_rate', 'daily_steps', 'sleep_disorder', 'systolic', 'diastolic']\n", + "\n", + "RangeIndex: 132 entries, 0 to 131\n", + "Data columns (total 15 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 person_id 132 non-null int64 \n", + " 1 gender 132 non-null object \n", + " 2 age 132 non-null int64 \n", + " 3 occupation 132 non-null object \n", + " 4 sleep_duration 132 non-null float64\n", + " 5 quality_of_sleep 132 non-null int64 \n", + " 6 physical_activity_level 132 non-null int64 \n", + " 7 stress_level 132 non-null int64 \n", + " 8 bmi_category 132 non-null object \n", + " 9 blood_pressure 132 non-null object \n", + " 10 heart_rate 132 non-null int64 \n", + " 11 daily_steps 132 non-null int64 \n", + " 12 sleep_disorder 132 non-null object \n", + " 13 systolic 132 non-null int64 \n", + " 14 diastolic 132 non-null int64 \n", + "dtypes: float64(1), int64(9), object(5)\n", + "memory usage: 15.6+ KB\n" + ] + }, + { + "data": { + "text/html": [ + "
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person_idagesleep_durationquality_of_sleepphysical_activity_levelstress_levelheart_ratedaily_stepssystolicdiastolic
count132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000
mean171.72727341.1287887.0825767.15151558.3939395.53787971.2045456637.878788128.36363684.537879
std110.4187798.8139420.7753351.26903720.4688401.7404284.8673061766.2886577.8256506.049926
min1.00000027.0000005.8000004.00000030.0000003.00000065.0000003000.000000115.00000075.000000
25%79.50000033.7500006.4000006.00000044.2500004.00000068.0000005000.000000120.75000080.000000
50%166.50000041.0000007.1500007.00000060.0000006.00000070.0000007000.000000130.00000085.000000
75%268.25000049.0000007.7250008.00000075.0000007.00000074.0000008000.000000135.00000088.500000
max367.00000059.0000008.5000009.00000090.0000008.00000086.00000010000.000000142.00000095.000000
\n", + "
" + ], + "text/plain": [ + " person_id age sleep_duration quality_of_sleep \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 171.727273 41.128788 7.082576 7.151515 \n", + "std 110.418779 8.813942 0.775335 1.269037 \n", + "min 1.000000 27.000000 5.800000 4.000000 \n", + "25% 79.500000 33.750000 6.400000 6.000000 \n", + "50% 166.500000 41.000000 7.150000 7.000000 \n", + "75% 268.250000 49.000000 7.725000 8.000000 \n", + "max 367.000000 59.000000 8.500000 9.000000 \n", + "\n", + " physical_activity_level stress_level heart_rate daily_steps \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 58.393939 5.537879 71.204545 6637.878788 \n", + "std 20.468840 1.740428 4.867306 1766.288657 \n", + "min 30.000000 3.000000 65.000000 3000.000000 \n", + "25% 44.250000 4.000000 68.000000 5000.000000 \n", + "50% 60.000000 6.000000 70.000000 7000.000000 \n", + "75% 75.000000 7.000000 74.000000 8000.000000 \n", + "max 90.000000 8.000000 86.000000 10000.000000 \n", + "\n", + " systolic diastolic \n", + "count 132.000000 132.000000 \n", + "mean 128.363636 84.537879 \n", + "std 7.825650 6.049926 \n", + "min 115.000000 75.000000 \n", + "25% 120.750000 80.000000 \n", + "50% 130.000000 85.000000 \n", + "75% 135.000000 88.500000 \n", + "max 142.000000 95.000000 " + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(f\"Shape: {sleep_data_clean.shape}\")\n", + "print(f\"\\nColumns: {sleep_data_clean.columns.tolist()}\")\n", + "sleep_data_clean.info()\n", + "sleep_data_clean.describe()" + ] + }, + { + "cell_type": "markdown", + "id": "48d87ec1-89a4-4774-aa07-751470206907", + "metadata": {}, + "source": [ + "## Exploratory Data Analysis (EDA)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "bb808e76-1cdc-494e-bee3-3f11e9f68592", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "No Disorder 73\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean[\"sleep_disorder\"].value_counts()" + ] + }, + { + "cell_type": "markdown", + "id": "4f33a0dc-0f13-4c20-a9bc-cc8b9f0b9946", + "metadata": {}, + "source": [ + "### Examine the distribution of the target variable: sleep_disorder" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "18bb64ac-b8dd-4d2c-a41b-2762d941c50d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(6,4))\n", + "sns.countplot(data=sleep_data_clean, x=\"sleep_disorder\")\n", + "plt.title(\"Distribution of Sleep Disorders\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "f63c60ac-5755-4647-a131-e4eaba3699f5", + "metadata": {}, + "source": [ + "### Basic distributions of key numeric variables" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "362d4b54-5aae-4eea-8db4-34aff9b4dcb6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "numeric_vars = [\"age\", \"sleep_duration\", \"stress_level\",\n", + " \"physical_activity_level\", \"systolic\", \"diastolic\"]\n", + "\n", + "plt.figure(figsize=(12,8))\n", + "sleep_data_clean[numeric_vars].hist(bins=15, figsize=(12,8))\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "8cecf7f3-5eaa-4b21-855e-1c39d9c08963", + "metadata": {}, + "source": [ + "### Correlation heatmap" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "874ab1ff-5343-43ec-a7cd-1cbdef897760", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "numeric_data = sleep_data_clean.select_dtypes(include=['int64', 'float64'])\n", + "\n", + "plt.figure(figsize=(12,8))\n", + "sns.heatmap(numeric_data.corr(), annot=True, cmap=\"coolwarm\")\n", + "plt.title(\"Correlation Heatmap\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5f8165f4-c912-4827-9ee0-1d2bf8d363f5", + "metadata": {}, + "source": [ + "#### Interpretation of the Correlation Heatmap \n", + "\n", + "The heatmap presents the correlations between all numerical variables in the dataset. Several relationships stand out and provide preliminary evidence relevant to the hypotheses of the study.\n", + "1. Relationship between Sleep Duration and Sleep Quality (r = 0.87)\n", + "There is a very strong positive correlation between sleep duration and sleep quality. Individuals who sleep longer tend to report higher sleep quality.\n", + "This supports the idea that reduced sleep duration contributes to poorer sleep quality and potentially to sleep disorders.\n", + "2. Relationship between Stress Level and Sleep Measures\n", + "Stress and sleep duration: strong negative correlation (r = -0.83)\n", + "Higher stress levels are associated with shorter sleep duration.\n", + "Stress and sleep quality: strong negative correlation (r = -0.88)\n", + "Higher stress is linked to poorer sleep quality.\n", + "These patterns provide strong preliminary support for the hypothesis that stress contributes to insomnia and reduced sleep performance.\n", + "3. Relationship between Physical Activity and Daily Steps (r = 0.72)\n", + "Daily steps and physical activity level are positively correlated.\n", + "This means that daily steps are a valid proxy for measuring activity level in further analysis.\n", + "4. Relationship between Heart Rate and Stress Level (r = 0.59)\n", + "There is a moderate positive correlation between stress and heart rate.\n", + "This suggests that individuals with high stress tend to have elevated heart rates, which may be relevant for understanding cardiovascular risks linked to sleep apnea.\n", + "5. Relationship between Age and Blood Pressure (Systolic r = 0.53; Diastolic r = 0.54)\n", + "Blood pressure increases with age.\n", + "This aligns with established medical knowledge and supports the idea that age may contribute to higher risk of hypertension, which itself is linked to sleep apnea.\n", + "6. Relationship between Systolic and Diastolic Pressure (r = 0.97)\n", + "Systolic and diastolic pressure are almost perfectly correlated.\n", + "This is expected and indicates that the blood pressure data in the dataset is consistent." + ] + }, + { + "cell_type": "markdown", + "id": "4d536b22-f457-4e50-b6b4-97c2bdd3bf1e", + "metadata": {}, + "source": [ + "### PRIMARY HYPOTHESIS (H1)\n", + "Individuals with high stress, high BMI, low sleep duration, and poor sleep quality are significantly more likely to have a sleep disorder.\n", + "To test H1, we break it into 4 parts:\n", + "- Stress level and sleep disorder\n", + "- Sleep duration and sleep disorder\n", + "- Sleep quality and sleep disorder\n", + "- BMI category and sleep disorder" + ] + }, + { + "cell_type": "markdown", + "id": "f235c0f9-f0e6-4082-a850-6b940658033f", + "metadata": {}, + "source": [ + "#### Sleep Duration vs Sleep Disorder\n", + "\n", + "- Goal:\n", + "Determine whether people with sleep disorders sleep fewer hours.\n", + "- Why this matters:\n", + "The heatmap showed a strong correlation between stress and sleep duration, but now we check if sleep duration differs across disorder types." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "550e2907-83dc-4a2c-b9e0-7a152856b41d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "No Disorder 73\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_data_clean['sleep_disorder'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "id": "d6d32695-58c1-4005-8929-927c25ad7e65", + "metadata": {}, + "source": [ + "#### H1: Primary Hypothesis\n", + "\n", + "Individuals with high stress, high BMI, low sleep duration, and poor sleep quality are significantly more likely to have a sleep disorder.\n", + "\n", + "#### H0: Sleep disorder presence is independent of these factors." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "fa39576b-1038-489b-8e07-3089ebb7b3ff", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Key metrics by Sleep Disorder:\n", + " stress_level sleep_duration quality_of_sleep\n", + "sleep_disorder \n", + "Insomnia 6.03 6.68 6.52\n", + "No Disorder 5.18 7.30 7.52\n", + "Sleep Apnea 5.93 6.94 6.87\n", + "\n", + "BMI Category distribution:\n" + ] + }, + { + "data": { + "text/html": [ + "
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bmi_categoryNormalObeseOverweight
sleep_disorder
Insomnia8318
No Disorder58015
Sleep Apnea7419
\n", + "
" + ], + "text/plain": [ + "bmi_category Normal Obese Overweight\n", + "sleep_disorder \n", + "Insomnia 8 3 18\n", + "No Disorder 58 0 15\n", + "Sleep Apnea 7 4 19" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(\"Key metrics by Sleep Disorder:\")\n", + "print(sleep_data_clean.groupby('sleep_disorder')[['stress_level', 'sleep_duration', \n", + " 'quality_of_sleep', 'bmi_category']].agg({\n", + " 'stress_level': 'mean',\n", + " 'sleep_duration': 'mean', \n", + " 'quality_of_sleep': 'mean'\n", + "}).round(2))\n", + "\n", + "# Distribution BMI\n", + "print(\"\\nBMI Category distribution:\")\n", + "pd.crosstab(sleep_data_clean['sleep_disorder'], sleep_data_clean['bmi_category'])" + ] + }, + { + "cell_type": "markdown", + "id": "1264b862-a8ac-46cf-8388-69ce40d3b01a", + "metadata": {}, + "source": [ + "#### H1a: Obesity increases likelihood of sleep apnea" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "61a1f351-0922-4e2e-bcb4-668f05049a79", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Obese individuals with Sleep Apnea: sleep_disorder\n", + "Sleep Apnea 4\n", + "Insomnia 3\n", + "Name: count, dtype: int64\n" + ] + } + ], + "source": [ + "\n", + "plt.figure(figsize=(10, 6))\n", + "sns.countplot(data=sleep_data_clean, x='bmi_category', hue='sleep_disorder', order=['Normal', 'Overweight', 'Obese'])\n", + "plt.title('H1a: BMI Category vs Sleep Disorder')\n", + "plt.xticks(rotation=45)\n", + "plt.show()\n", + "\n", + "\n", + "apnea_obese = sleep_data_clean[sleep_data_clean['bmi_category'] == 'Obese']['sleep_disorder'].value_counts()\n", + "print(f\"\\nObese individuals with Sleep Apnea: {apnea_obese}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "98ec3319-bd5a-4cae-bd93-dc8949be1b1a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Sleep Apnea cases by BMI Category:\n", + "bmi_category\n", + "Overweight 19\n", + "Normal 7\n", + "Obese 4\n", + "Name: count, dtype: int64\n", + "\n", + "Percentage of each BMI category with Sleep Apnea:\n", + "bmi_category\n", + "Normal 9.59\n", + "Obese 57.14\n", + "Overweight 36.54\n", + "Name: Sleep Apnea, dtype: float64\n" + ] + } + ], + "source": [ + "\n", + "print(\"\\nSleep Apnea cases by BMI Category:\")\n", + "apnea_bmi = sleep_data_clean[sleep_data_clean['sleep_disorder'] == 'Sleep Apnea']['bmi_category'].value_counts()\n", + "print(apnea_bmi)\n", + "\n", + "print(\"\\nPercentage of each BMI category with Sleep Apnea:\")\n", + "bmi_apnea_rate = pd.crosstab(sleep_data_clean['bmi_category'], \n", + " sleep_data_clean['sleep_disorder'], \n", + " normalize='index') * 100\n", + "print(bmi_apnea_rate['Sleep Apnea'].round(2))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a3344418-2c32-4c77-981b-069f7919ace5", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "ca5042c3-35dd-4e36-81c2-ee3ae19b6bc7", + "metadata": {}, + "source": [ + "### **H1a: Analysis - BMI Category and Sleep Apnea Risk**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Observed Pattern in Sample:**\n", + " - **Obese (n=7):** All 7 individuals present a sleep disorder (4 Sleep Apnea, 3 Insomnia)\n", + " - **Overweight (n=52):** 71.2% disorder prevalence \n", + " - **Normal BMI (n=73):** 20.5% disorder prevalence\n", + "\n", + "2. **Sleep Apnea Prevalence by BMI:**\n", + " - Obese: 57.14%\n", + " - Overweight: 36.54%\n", + " - Normal: 9.59%\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H1a is SUPPORTED** by the data. There is a clear positive correlation between higher BMI and increased Sleep Apnea prevalence. The pattern suggests obesity is a significant risk factor.\n", + "\n", + "**Limitations:**\n", + "- Small sample size for obese category (n=7) limits generalizability\n", + "- Cross-sectional data - causation cannot be established\n", + "- Sample may not be representative of broader population\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "251d1dc7-b72f-43f9-9dcd-fbe33428c2b8", + "metadata": {}, + "source": [ + "#### H1b: Higher stress correlates with insomnia" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "473169eb-874a-4964-be81-a8d2954723a4", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tw8vNJCcnq2fPnjp9+rRGjx6d4fUKFy6snj176scff9Svv/4qSapWrZp8fHz02WefqWXLlo6+v//+u3766Se1aNHiluPWqVNH77zzzg2/v6lu530GYD2EIAD3jdjYWG3atEnSP89uSHLMehUZGamKFSs69Y+JidELL7ygli1b6ujRoxo8eLAKFiyo7t27O/qsWrVKdevW1ZAhQ276XFBCQoIiIyPVsmVL1atXT+Hh4Tp37pxWrlyp9957T9HR0WrevLkkKSAgQBEREfrqq69Ut25d5cqVS7lz51ZkZOQNx3/kkUfUrVs3derUSTExMapZs6b8/Px0/PhxrVmzRmXKlNFLL72kJUuWaOLEiXrqqadUtGhRGWP05ZdfKj4+XvXr15ckDRkyRL///rvq1q2rQoUKKT4+Xu+99568vLxUq1atW77Pf/75Z7qziUVGRma4zlQNGjRQoUKF1L17d/35559Ot8KljjlixAgNHjxYhw4d0uOPP66QkBCdOHFCGzdulJ+fX7qzeN1Kzpw5NX78eJ07d06VKlXS2rVrNXLkSDVq1CjN82ZRUVF6/PHHtXTpUtWoUSNDf4h37969atiwoZ599lnVqlVL+fPn15kzZ/Ttt99q8uTJql27tqpXr37D9d977z3VqFFDjz76qF566SVFRkbq7NmzOnDggL755hv99NNPkv6ZanzhwoWqWbOm+vbtq7JlyyolJUVxcXFasWKFXnnlFVWpUsUxbu7cufXYY4/pzTfflJ+fnyZOnKg9e/ZkeJrsEydOaP369TLG6OzZs/rvf/+rmTNn6rffflPfvn3VtWvXG66bkJCgOnXqqG3btipZsqQCAgK0adMmLVu2zHFsBAcH680339SgQYPUvn17tWnTRqdPn9bw4cPl7e2toUOH3rLGBg0aqGbNmurfv7/Onz+vihUr6tdff9WsWbMy/T4DsCD3zckAwMpSZ3C7ftarVE2aNEkzO9zNZpTr0KFDmn4rVqwwzz//vAkODnbMSLV//36nMVNnhUpvJrdrJSUlmX/961+mUaNGpnDhwsZutxtvb28THR1t+vfvb06fPu3U/4cffjAPPfSQsdvtTvWlznD2119/pbudqVOnmipVqhg/Pz/j4+NjihUrZtq3b29iYmKMMcbs2bPHtGnTxhQrVsz4+PiYoKAgU7lyZTN9+nTHGEuWLDGNGjUyBQsWNDlz5jR58+Y1jRs3Nr/88stN99GYf2aHy8h7fKs6rzVo0CAjyYSHh5vk5OR0t7t48WJTp04dExgYaOx2u4mIiDAtWrQwP/zwg6PP7cwO5+fnZ7Zv325q165tfHx8TK5cucxLL71kzp07l+4606dPN5LM3Llzbzm+Mf/McjZy5Ejz2GOPOd5nPz8/U758eTNy5Ehz4cIFR9/0ZlFLbe/cubMpWLCg8fLyMnny5DHVq1d3mr3QGGPOnTtn3njjDVOiRAmTM2dOExQUZMqUKWP69u3rNBOc/v/sbhMnTjTFihUzXl5epmTJkmb27NkZ2qdrv9ceHh4mMDDQlClTxnTr1s2sW7cuTf/r9+vSpUvm//7v/0zZsmVNYGCg8fHxMSVKlDBDhw4158+fd1p3ypQppmzZso79adasmdm5c6dTn9TvY3ri4+NN586dTXBwsPH19TX169c3e/bsSfdYzsj7nHoe+OKLLzL0XgG4/9mMccEf4wAA4D72zDPPaP369Tpy5Ijj7xfdb2w2m3r06KH//Oc/7i4FAO553A4HALCkpKQkbdmyRRs3btSiRYv073//+74NQACA20MIAgBY0vHjx1W9enUFBgbqxRdf1Msvv+zukgAAdwm3wwEAAACwFP5YKgAAAABLIQQBAAAAsBRCEAAAAABLua8nRkhJSdEff/yhgIAA2Ww2d5cDAAAAwE3M//9DzwUKFJCHx82v9dzXIeiPP/5QeHi4u8sAAAAAcI84evSoChUqdNM+93UICggIkPTPjgYGBrq5GgAAAADukpiYqPDwcEdGuJn7OgSl3gIXGBhICAIAAACQocdkmBgBAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYiltD0NWrV/XGG2+oSJEi8vHxUdGiRTVixAilpKS4sywAAAAA2VgOd2587Nix+uijjzRjxgyVLl1aMTEx6tSpk4KCgtS7d293lgYAAAAgm3JrCFq3bp2aNWumJk2aSJIiIyP1+eefKyYmxp1lAQAAAMjG3BqCatSooY8++kj79u1TVFSUfvvtN61Zs0YTJkxIt39SUpKSkpIcrxMTE+9SpdnLpUuXFBcX5+4ycBOFCxeWt7e3u8vAdU6cOKGEhAR3l+ESSUlJ+vPPP91dBm4iX758stvt7i7DJYKCghQWFubuMnAdPg/cH/hMkDXcGoIGDBighIQElSxZUp6enkpOTtaoUaPUpk2bdPuPHj1aw4cPv8tVZj9xcXHq1q2bu8vATUyePFlRUVHuLgPXOHHihJ57vr2uXE66dWcATrxy2vXZrJkEoXsMnwfuD3wmyBpuDUHz5s3TZ599pjlz5qh06dLatm2b+vTpowIFCqhDhw5p+g8cOFD9+vVzvE5MTFR4ePjdLDlbKFy4sCZPnuzuMlwiNjZWo0aN0uDBgxUREeHuclymcOHC7i4B10lISNCVy0m6WLSWUryD3F3OnUu5Ko+kc+6uAjeRYveXPNz6z7RLeFxKkA6tUkJCAiHoHpOdPg9IfCbA7XHr2fW1117T66+/rmeffVaSVKZMGcXGxmr06NHphiC73Z5tbg1wJ29v72z3G4WIiIhst0+4N6V4BynFL7e7y3CJlAB3VwDAnbLj5wGJzwTIGLdOkX3hwgV5eDiX4OnpyRTZAAAAALKMW68EPfHEExo1apQKFy6s0qVLa+vWrfr3v/+tzp07u7MsAAAAANmYW0PQBx98oDfffFPdu3fXyZMnVaBAAb344osaMmSIO8sCAAAAkI25NQQFBARowoQJN5wSGwAAAABcza3PBAEAAADA3UYIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAluLWEBQZGSmbzZbmq0ePHu4sCwAAAEA2lsOdG9+0aZOSk5Mdr//73/+qfv36atmypRurAgAAAJCduTUE5cmTx+n1mDFjVKxYMdWqVctNFQEAAADI7twagq51+fJlffbZZ+rXr59sNlu6fZKSkpSUlOR4nZiYeLfKAwBJksfFeHeXANxXsuMxs2fPHh09etTdZeA6x48flyStX79esbGxbq4G1wsPD1fJkiXdXYbDPROCFi9erPj4eHXs2PGGfUaPHq3hw4ffvaIA4Do+h1e7uwQAbnTixAl1795DKSnJt+4Mt5g6daq7S0A6PDw89fnncxQWFubuUiTdQyHo008/VaNGjVSgQIEb9hk4cKD69evneJ2YmKjw8PC7UR4ASJIuFqmpFJ9gd5cB3Dc8LsZnq18eJCQkKCUlWZcKVpDJ6e/ucoD7gu3yOXkf26KEhARC0LViY2P1ww8/6Msvv7xpP7vdLrvdfpeqAoC0UnyCleKX291lAHCz5KBCnAuADPI4f0o6tsXdZTi5J/5O0LRp05Q3b141adLE3aUAAAAAyObcHoJSUlI0bdo0dejQQTly3BMXpgAAAABkY24PQT/88IPi4uLUuXNnd5cCAAAAwALcfumlQYMGMsa4uwwAAAAAFuH2K0EAAAAAcDcRggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKW4PQQdO3ZMzz33nEJDQ+Xr66vy5ctr8+bN7i4LAAAAQDaVw50bP3PmjB555BHVqVNHS5cuVd68eXXw4EEFBwe7sywAAAAA2ZhbQ9DYsWMVHh6uadOmOdoiIyPdVxAAAACAbM+tIejrr79Ww4YN1bJlS61atUoFCxZU9+7d1bVr13T7JyUlKSkpyfE6MTHxbpWqEydOKCEh4a5tDxkTGxvr9F/ce4KCghQWFubuMgAAABzcGoIOHTqkSZMmqV+/fho0aJA2btyoXr16yW63q3379mn6jx49WsOHD7/rdZ44cULPPd9eVy4n3boz3GLUqFHuLgE34JXTrs9mzSQIAQCAe4ZbQ1BKSooqVqyot99+W5L00EMPaefOnZo0aVK6IWjgwIHq16+f43ViYqLCw8OzvM6EhARduZyki0VrKcU7KMu3B2QXHpcSpEOrlJCQQAgCAAD3DLeGoPz586tUqVJObdHR0Vq4cGG6/e12u+x2+90oLV0p3kFK8cvttu0DAAAAuHNunSL7kUce0d69e53a9u3bp4iICDdVBAAAACC7c2sI6tu3r9avX6+3335bBw4c0Jw5czR58mT16NHDnWUBAAAAyMYyfDvctc/i3Mq///3vDPWrVKmSFi1apIEDB2rEiBEqUqSIJkyYoHbt2mV4WwAAAABwOzIcgrZu3Zqhfjab7bYKaNq0qZo2bXpb6wAAAABAZmU4BP38889ZWQcAAAAA3BV39EzQgQMHtHz5cl28eFGSZIxxSVEAAAAAkFUyFYJOnz6tunXrKioqSo0bN9bx48clSS+88IJeeeUVlxYIAAAAAK6UqRDUt29feXl5KS4uTr6+vo721q1ba9myZS4rDgAAAABcLVN/LHXFihVavny5ChUq5NT+wAMPKDY21iWFAQAAAEBWyNSVoPPnzztdAUp16tQp2e32Oy4KAAAAALJKpkJQzZo1NXPmTMdrm82mlJQUjRs3TnXq1HFZcQAAAADgapm6HW7cuHGqXbu2YmJidPnyZfXv3187d+7U33//rV9//dXVNQIAAACAy2TqSlCpUqW0fft2Va5cWfXr19f58+fVvHlzbd26VcWKFXN1jQAAAADgMpm6EiRJ+fLl0/Dhw11ZCwAAAABkuUxdCSpSpIjefPNN7d2719X1AAAAAECWylQIevnll7Vs2TJFR0fr4Ycf1oQJExx/MBUAAAAA7mWZCkH9+vXTpk2btGfPHjVt2lSTJk1S4cKF1aBBA6dZ4wAAAADgXpOpEJQqKipKw4cP1969e/XLL7/or7/+UqdOnVxVGwAAAAC4XKYnRki1ceNGzZkzR/PmzVNCQoJatGjhiroAAAAAIEtkKgTt27dPs2fP1pw5c3TkyBHVqVNHY8aMUfPmzRUQEODqGgEAAADAZTIVgkqWLKmKFSuqR48eevbZZ5UvXz5X1wUAAAAAWSJTIWjPnj2KiopydS0AAAAAkOUyNTFCVFSU4uPjNWXKFA0cOFB///23JGnLli06duyYSwsEAAAAAFfK1JWg7du3q27dugoODtaRI0fUtWtX5cqVS4sWLVJsbCzTZAMAAAC4Z2XqSlDfvn3VqVMn7d+/X97e3o72Ro0aafXq1S4rDgAAAABcLVNXgmJiYjR58uQ07QULFtSff/55x0UBAAAAQFbJ1JUgb29vJSYmpmnfu3ev8uTJc8dFAQAAAEBWyVQIatasmUaMGKErV65Ikmw2m+Li4vT666/rmWeecWmBAAAAAOBKmQpB//rXv/TXX38pb968unjxomrVqqXixYsrICBAo0aNcnWNAAAAAOAymXomKDAwUGvWrNFPP/2kLVu2KCUlRRUqVFC9evVcXR8AAAAAuFSmQlCqxx57TI899piragEAAACALJfhEPT+++9neNBevXplqhgAAAAAyGoZDkHvvvtuhvrZbDZCEAAAAIB7VoZD0OHDh7OyDgAAAAC4KzI1O1xGBQYG6tChQ1m5CQAAAAC4LVkagowxWTk8AAAAANy2LA1BAAAAAHCvIQQBAAAAsBRCEAAAAABLydIQZLPZsnJ4AAAAALhtTIwAAAAAwFJcEoKSk5O1bds2nTlzxql96dKlKliwoCs2AQAAAAAukakQ1KdPH3366aeS/glAtWrVUoUKFRQeHq6VK1c6+tWoUUN2u90lhQIAAACAK2QqBC1YsEDlypWTJH3zzTc6fPiw9uzZoz59+mjw4MEuLRAAAAAAXClTIejUqVPKly+fJOm7775Ty5YtFRUVpS5dumjHjh0uLRAAAAAAXClTISgsLEy7du1ScnKyli1bpnr16kmSLly4IE9PT5cWCAAAAACulCMzK3Xq1EmtWrVS/vz5ZbPZVL9+fUnShg0bVLJkSZcWCAAAAACulKkQNGzYMD344IM6evSoWrZs6Zj8wNPTU6+//rpLCwQAAAAAV8pUCJKkFi1aOL2Oj49Xhw4d7rggAAAAAMhKmXomaOzYsZo3b57jdatWrRQaGqpChQpp+/btLisOAAAAAFwtUyHo448/Vnh4uCTp+++/1/fff6+lS5fq8ccf16uvvurSAgEAAADAlTJ1O9zx48cdIWjJkiVq1aqVGjRooMjISFWpUsWlBQIAAACAK2XqSlBISIiOHj0qSU5TZBtjlJyc7LrqAAAAAMDFMnUlqHnz5mrbtq0eeOABnT59Wo0aNZIkbdu2TcWLF3dpgQAAAADgSpkKQe+++64iIyN19OhRvfPOO/L395f0z21y3bt3d2mBAAAAAOBKmQpBXl5e6U6A0KdPnzutBwAAAACyVKaeCZKkWbNmqUaNGipQoIBiY2MlSRMmTNBXX33lsuIAAAAAwNUyFYImTZqkfv36qVGjRoqPj3dMhhAcHKwJEya4sj4AAAAAcKlMhaAPPvhAn3zyiQYPHixPT09He8WKFbVjxw6XFQcAAAAArpapEHT48GE99NBDadrtdrvOnz9/x0UBAAAAQFbJVAgqUqSItm3blqZ96dKlKlWq1J3WBAAAAABZJlOzw7322mvq0aOHLl26JGOMNm7cqM8//1yjR4/WlClTXF0jAAAAALhMpkJQp06ddPXqVfXv318XLlxQ27ZtVbBgQb333nt69tlnXV0jAAAAALjMbYegq1evavbs2XriiSfUtWtXnTp1SikpKcqbN29W1AcAAAAALnXbzwTlyJFDL730kpKSkiRJuXPnJgABAAAAuG9kamKEKlWqaOvWra6uBQAAAACyXKaeCerevbteeeUV/f7773r44Yfl5+fntLxs2bIuKQ4AAAAAXC1TIah169aSpF69ejnabDabjDGy2WxKTk52TXUAAAAA4GKZCkGHDx92dR0AAAAAcFdkKgTFxsaqevXqypHDefWrV69q7dq1ioiIcElxAAAAAOBqmZoYoU6dOvr777/TtCckJKhOnTp3XBQAAAAAZJVMhaDUZ3+ud/r06TSTJAAAAADAveS2bodr3ry5pH8mQejYsaPsdrtjWXJysrZv367q1au7tkIAAAAAcKHbCkFBQUGS/rkSFBAQIB8fH8eynDlzqmrVquratatrKwQAAAAAF7qtEDRt2jRJUp48eTRs2DD5+vpKko4cOaLFixcrOjpauXPndn2VAAAAAOAimXomaOvWrZo5c6YkKT4+XlWrVtX48eP11FNPadKkSS4tEAAAAABcKdMh6NFHH5UkLViwQGFhYYqNjdXMmTP1/vvvu7RAAAAAAHClTIWgCxcuKCAgQJK0YsUKNW/eXB4eHqpatapiY2MzPM6wYcNks9mcvvLly5eZkgAAAAAgQzIVgooXL67Fixfr6NGjWr58uRo0aCBJOnnypAIDA29rrNKlS+v48eOOrx07dmSmJAAAAADIkNuaGCHVkCFD1LZtW/Xt21d169ZVtWrVJP1zVeihhx66vQJy5ODqDwAAAIC7JlMhqEWLFqpRo4aOHz+ucuXKOdrr1q2rp59++rbG2r9/vwoUKCC73a4qVaro7bffVtGiRdPtm5SUpKSkJMfrxMTEzJSfaR4X4+/q9oD7HccMgOzK41KCu0sA7hv34vGSqRAkSfny5UtzBady5cq3NUaVKlU0c+ZMRUVF6cSJExo5cqSqV6+unTt3KjQ0NE3/0aNHa/jw4Zkt+Y75HF7ttm0DAAD3CwoKkldOu3RolbtLAe4rXjntjr85ei/IdAhyhUaNGjn+v0yZMqpWrZqKFSumGTNmqF+/fmn6Dxw40Kk9MTFR4eHhd6VWSbpYpKZSfILv2vaA+53HxXh+eQAgWwkLC9Nns2YqIeHe+8221cXGxmrUqFEaPHiwIiIi3F0OrhMUFKSwsDB3l+Hg1hB0PT8/P5UpU0b79+9Pd7ndbpfdbr/LVf1Pik+wUvz4Y7AAAFhZWFjYPfVhDs4iIiIUFRXl7jJwj8vU7HBZJSkpSbt371b+/PndXQoAAACAbMqtIejVV1/VqlWrdPjwYW3YsEEtWrRQYmKiOnTo4M6yAAAAAGRjbr0d7vfff1ebNm106tQp5cmTR1WrVtX69eu5jxMAAABAlnFrCJo7d647Nw8AAADAgu6pZ4IAAAAAIKsRggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKXcMyFo9OjRstls6tOnj7tLAQAAAJCN3RMhaNOmTZo8ebLKli3r7lIAAAAAZHNuD0Hnzp1Tu3bt9MknnygkJMTd5QAAAADI5nK4u4AePXqoSZMmqlevnkaOHHnTvklJSUpKSnK8TkxMzOrynHhcSrir2wPud9nxmMmO+wRkJY4ZAPcit4aguXPnasuWLdq0aVOG+o8ePVrDhw/P4qrSCgoKkldOu3Ro1V3fNnC/88ppV1BQkLvLuGOcB4DMyy7nAQDZh9tC0NGjR9W7d2+tWLFC3t7eGVpn4MCB6tevn+N1YmKiwsPDs6pEh7CwMH02a6YSEvht1r0mNjZWo0aN0uDBgxUREeHucpCOoKAghYWFubuMO8Z54N7GueDell3OAwCyD7eFoM2bN+vkyZN6+OGHHW3JyclavXq1/vOf/ygpKUmenp5O69jtdtnt9rtdqqR/PgBxAr93RUREKCoqyt1lIJvjPHDv41wAAMgIt4WgunXraseOHU5tnTp1UsmSJTVgwIA0AQgAAAAAXMFtISggIEAPPvigU5ufn59CQ0PTtAMAAACAq7h9imwAAAAAuJvcPkX2tVauXOnuEgAAAABkc1wJAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGApbg1BkyZNUtmyZRUYGKjAwEBVq1ZNS5cudWdJAAAAALI5t4agQoUKacyYMYqJiVFMTIwee+wxNWvWTDt37nRnWQAAAACysRzu3PgTTzzh9HrUqFGaNGmS1q9fr9KlS7upKgAAAADZmVtD0LWSk5P1xRdf6Pz586pWrVq6fZKSkpSUlOR4nZiYeLfKy1YuXbqkuLg4d5fhErGxsU7/zS4KFy4sb29vd5eBbCw7nQek7Hku4DyArMZ54P7AuSBr2Iwxxp0F7NixQ9WqVdOlS5fk7++vOXPmqHHjxun2HTZsmIYPH56mPSEhQYGBgVldaraxb98+devWzd1l4CYmT56sqKgod5eBbIzzwL2P8wCyGueB+wPngoxLTExUUFBQhrKB20PQ5cuXFRcXp/j4eC1cuFBTpkzRqlWrVKpUqTR907sSFB4eTgi6TdntNz/ZEb/1QVbjPHDv4zyArMZ54P7AuSDj7qsQdL169eqpWLFi+vjjj2/Z93Z2FAAAAED2dTvZ4J77O0HGGKerPQAAAADgSm6dGGHQoEFq1KiRwsPDdfbsWc2dO1crV67UsmXL3FkWAAAAgGzMrSHoxIkTev7553X8+HEFBQWpbNmyWrZsmerXr+/OsgAAAABkY24NQZ9++qk7Nw8AAADAgu65Z4IAAAAAICsRggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKUQggAAAABYCiEIAAAAgKXkcHcBd8IYI0lKTEx0cyUAAAAA3Ck1E6RmhJu5r0PQ2bNnJUnh4eFurgQAAADAveDs2bMKCgq6aR+byUhUukelpKTojz/+UEBAgGw2m7vLgRskJiYqPDxcR48eVWBgoLvLAeAmnAsAcB6AMUZnz55VgQIF5OFx86d+7usrQR4eHipUqJC7y8A9IDAwkBMeAM4FADgPWNytrgClYmIEAAAAAJZCCAIAAABgKYQg3NfsdruGDh0qu93u7lIAuBHnAgCcB3A77uuJEQAAAADgdnElCAAAAIClEIIAAAAAWAohCAAAAIClEIJw36hdu7b69Oljme0C9wubzabFixe7uwwAcKkjR47IZrNp27Zt7i4FWYAQhFvq2LGjbDabxowZ49S+ePFi2Wy2Oxp7+vTpstlsstls8vT0VEhIiKpUqaIRI0YoISHBqe+XX36pt9566462B+D2nDx5Ui+++KIKFy4su92ufPnyqWHDhlq3bp27S7uhOXPmyNPTU//3f//n7lIAy+rYsaOeeuopd5dxR8LDw3X8+HE9+OCD7i4FWYAQhAzx9vbW2LFjdebMGZePHRgYqOPHj+v333/X2rVr1a1bN82cOVPly5fXH3/84eiXK1cuBQQEuHz7kmSM0dWrV7Nk7OTkZKWkpGTJ2EBWe+aZZ/Tbb79pxowZ2rdvn77++mvVrl1bf//9t7tLu6GpU6eqf//+mjt3ri5cuODucgDcpzw9PZUvXz7lyJHD3aUgCxCCkCH16tVTvnz5NHr06Jv2W7hwoUqXLi273a7IyEiNHz/+lmPbbDbly5dP+fPnV3R0tLp06aK1a9fq3Llz6t+/v6Pf9belTZw4UQ888IC8vb0VFhamFi1aOJYlJSWpV69eyps3r7y9vVWjRg1t2rTJsXzlypWy2Wxavny5KlasKLvdrl9++UXnz59X+/bt5e/vr/z586db/+XLl9W/f38VLFhQfn5+qlKlilauXOlYPn36dAUHB2vJkiUqVaqU7Ha7YmNjb/k+APea+Ph4rVmzRmPHjlWdOnUUERGhypUra+DAgWrSpMkN1zt27Jhat26tkJAQhYaGqlmzZjpy5IhTn2nTpik6Olre3t4qWbKkJk6c6FiWegvK3LlzVb16dXl7e6t06dJOx9mNHDlyRGvXrtXrr7+ukiVLasGCBU7LU4/PxYsXKyoqSt7e3qpfv76OHj3q6DNs2DCVL19es2bNUmRkpIKCgvTss8/q7Nmzjj7GGL3zzjsqWrSofHx8VK5cOadtJScnq0uXLipSpIh8fHxUokQJvffee7esH8iOateurV69eql///7KlSuX8uXLp2HDhjn1GTZsmOOKc4ECBdSrVy/HsjNnzqh9+/YKCQmRr6+vGjVqpP379zuWX/vvbokSJeTr66sWLVro/PnzmjFjhiIjIxUSEqKXX35ZycnJjvUiIyP19ttvq3PnzgoICFDhwoU1efJkx/Lrb4fjuM5mDHALHTp0MM2aNTNffvml8fb2NkePHjXGGLNo0SJz7Y9QTEyM8fDwMCNGjDB79+4106ZNMz4+PmbatGk3HHvatGkmKCgo3WW9e/c2AQEB5urVq8YYY2rVqmV69+5tjDFm06ZNxtPT08yZM8ccOXLEbNmyxbz33nuOdXv16mUKFChgvvvuO7Nz507ToUMHExISYk6fPm2MMebnn382kkzZsmXNihUrzIEDB8ypU6fMSy+9ZAoVKmRWrFhhtm/fbpo2bWr8/f0d2zXGmLZt25rq1aub1atXmwMHDphx48YZu91u9u3b59gnLy8vU716dfPrr7+aPXv2mHPnzt3u2w643ZUrV4y/v7/p06ePuXTp0g37STKLFi0yxhhz/vx588ADD5jOnTub7du3m127dpm2bduaEiVKmKSkJGOMMZMnTzb58+c3CxcuNIcOHTILFy40uXLlMtOnTzfGGHP48GEjyRQqVMgsWLDA7Nq1y7zwwgsmICDAnDp16qY1v/nmm6ZFixbGGGM++OADU7NmTaflqcdnxYoVzdq1a01MTIypXLmyqV69uqPP0KFDjb+/v2nevLnZsWOHWb16tcmXL58ZNGiQo8+gQYNMyZIlzbJly8zBgwfNtGnTjN1uNytXrjTGGHP58mUzZMgQs3HjRnPo0CHz2WefGV9fXzNv3rwMvvvA/S31s4Mx//z7HRgYaIYNG2b27dtnZsyYYWw2m1mxYoUxxpgvvvjCBAYGmu+++87ExsaaDRs2mMmTJzvGevLJJ010dLRZvXq12bZtm2nYsKEpXry4uXz5sjHmf8d1/fr1zZYtW8yqVatMaGioadCggWnVqpXZuXOn+eabb0zOnDnN3LlzHeNGRESYXLlymQ8//NDs37/fjB492nh4eJjdu3cbY/53Ltq6dasxhuM6uyEE4ZauPZFVrVrVdO7c2RiTNgS1bdvW1K9f32nd1157zZQqVeqGY98sBE2aNMlIMidOnDDGOIeghQsXmsDAQJOYmJhmvXPnzhkvLy8ze/ZsR9vly5dNgQIFzDvvvGOM+V8IWrx4saPP2bNn05wgT58+bXx8fBzbPXDggLHZbObYsWNO26xbt64ZOHCgY58kmW3btt1wv4H7xYIFC0xISIjx9vY21atXNwMHDjS//fabU59rQ9Cnn35qSpQoYVJSUhzLk5KSjI+Pj1m+fLkxxpjw8HAzZ84cpzHeeustU61aNWPM/z54jBkzxrH8ypUrplChQmbs2LE3rDU5OdmEh4c7juu//vrLeHl5mf379zv6pB6f69evd7Tt3r3bSDIbNmwwxvwTgnx9fZ3OL6+99pqpUqWKMeafc4y3t7dZu3at0/a7dOli2rRpc8P6unfvbp555pkbLgeyk+tDUI0aNZyWV6pUyQwYMMAYY8z48eNNVFSUI9Rca9++fUaS+fXXXx1tp06dMj4+Pmb+/PnGmP8d1wcOHHD0efHFF42vr685e/aso61hw4bmxRdfdLyOiIgwzz33nON1SkqKyZs3r5k0aZIxJm0ISg/H9f2L2+FwW8aOHasZM2Zo165daZbt3r1bjzzyiFPbI488ov379ztdfs4oY4wkpTv5Qv369RUREaGiRYvq+eef1+zZsx33/h88eFBXrlxxqsXLy0uVK1fW7t27ncapWLGi4/8PHjyoy5cvq1q1ao62XLlyqUSJEo7XW7ZskTFGUVFR8vf3d3ytWrVKBw8edPTLmTOnypYte9v7DNxrnnnmGf3xxx/6+uuv1bBhQ61cuVIVKlTQ9OnT0+2/efNmHThwQAEBAY7jI1euXLp06ZIOHjyov/76S0ePHlWXLl2cjqGRI0c6HUOSnI7FHDlyqGLFimmO4WutWLFC58+fV6NGjSRJuXPnVoMGDTR16lSnfqljpSpZsqSCg4Odxo6MjHR6BjF//vw6efKkJGnXrl26dOmS6tev77QPM2fOdNqHjz76SBUrVlSePHnk7++vTz75RHFxcTesH8jOrv838dpjqmXLlrp48aKKFi2qrl27atGiRY7ndHfv3q0cOXKoSpUqjnVDQ0NVokQJp2PW19dXxYoVc7wOCwtTZGSk/P39ndpSt5leXam351/f51oc19kHT3rhttSsWVMNGzbUoEGD1LFjR6dlxpg0gSU1yGTG7t27FRgYqNDQ0DTLAgICtGXLFq1cuVIrVqzQkCFDNGzYMG3atOmG4Sm9+vz8/G6r1pSUFHl6emrz5s3y9PR0WnbtidbHx+eOZ84D7hWpz83Ur19fQ4YM0QsvvKChQ4emOQdI/xwjDz/8sGbPnp1mWZ48eXTp0iVJ0ieffOL0oUZSmmMqPTc7rqZOnaq///5bvr6+TvVs3bpVb731ltP46Y1zbZuXl1eaZakTnKT+99tvv1XBggWd+tntdknS/Pnz1bdvX40fP17VqlVTQECAxo0bpw0bNtxyH4Hs6GbHVHh4uPbu3avvv/9eP/zwg7p3765x48Zp1apVN/y3+fp/09Mb/2bbzEhd1+O4zl4IQbhtY8aMUfny5RUVFeXUXqpUKa1Zs8apbe3atYqKisrQh5trnTx5UnPmzNFTTz0lD4/0L1jmyJFD9erVU7169TR06FAFBwfrp59+UsOGDZUzZ06tWbNGbdu2lSRduXJFMTExN/17P8WLF5eXl5fWr1+vwoULS/rnYcx9+/apVq1akqSHHnpIycnJOnnypB599NHb2icguyhVqtQN/y5QhQoVNG/ePOXNm1eBgYFplgcFBalgwYI6dOiQ2rVrd9PtrF+/XjVr1pQkXb16VZs3b1bPnj3T7Xv69Gl99dVXmjt3rkqXLu1oT0lJ0aOPPqqlS5eqadOmjrFiYmJUuXJlSdLevXsVHx+vkiVL3nLfJTkmPImLi3OcG673yy+/qHr16urevbuj7forXQD+x8fHR08++aSefPJJ9ejRQyVLltSOHTtUqlQpXb16VRs2bFD16tUl/XO879u3T9HR0Xe1Ro7r7IUQhNtWpkwZtWvXTh988IFT+yuvvKJKlSrprbfeUuvWrbVu3Tr95z//cZr1KT3GGP35558yxig+Pl7r1q3T22+/raCgoDR/myjVkiVLdOjQIdWsWVMhISH67rvvlJKSohIlSsjPz08vvfSSXnvtNeXKlUuFCxfWO++8owsXLqhLly43rMPf319dunTRa6+9ptDQUIWFhWnw4MFOISwqKkrt2rVT+/btNX78eD300EM6deqUfvrpJ5UpU0aNGze+jXcSuLedPn1aLVu2VOfOnVW2bFkFBAQoJiZG77zzjpo1a5buOu3atdO4cePUrFkzjRgxQoUKFVJcXJy+/PJLvfbaaypUqJCGDRumXr16KTAwUI0aNVJSUpJiYmJ05swZ9evXzzHWhx9+qAceeEDR0dF69913debMGXXu3Dnd7c6aNUuhoaFq2bJlml+cNG3aVJ9++qkjBHl5eenll1/W+++/Ly8vL/Xs2VNVq1Z1hKJbCQgI0Kuvvqq+ffsqJSVFNWrUUGJiotauXSt/f3916NBBxYsX18yZM7V8+XIVKVJEs2bN0qZNm1SkSJEMbQOwkunTpys5OVlVqlSRr6+vZs2aJR8fH0VERDhmmOzatas+/vhjBQQE6PXXX1fBggVveB7KKhzX2QshCJny1ltvaf78+U5tFSpU0Pz58zVkyBC99dZbyp8/v0aMGJHuLTPXSkxMVP78+WWz2RQYGKgSJUqoQ4cO6t27d7q/SZak4OBgffnllxo2bJguXbqkBx54QJ9//rnjN8BjxoxRSkqKnn/+eZ09e1YVK1bU8uXLFRISctNaxo0bp3PnzunJJ59UQECAXnnllTR/tHXatGkaOXKkXnnlFR07dkyhoaGqVq0aAQjZjr+/v6pUqaJ3333X8axdeHi4unbtqkGDBqW7jq+vr1avXq0BAwaoefPmOnv2rAoWLKi6des6jucXXnhBvr6+GjdunPr37y8/Pz+VKVMmzZXaMWPGaOzYsdq6dauKFSumr776Srlz5053u1OnTtXTTz+d7pXjZ555Rq1bt9aJEyccNQ4YMEBt27bV77//rho1aqR5buhW3nrrLeXNm1ejR4/WoUOHFBwcrAoVKjjel//7v//Ttm3b1Lp1a9lsNrVp00bdu3fX0qVLb2s7gBUEBwdrzJgx6tevn5KTk1WmTBl98803jtvhp02bpt69e6tp06a6fPmyatasqe+++y7NrWxZjeM6e7GZO3loAwAAFzty5IiKFCmirVu3qnz58i4de/r06erTp4/i4+NdOi4A4P7C7HAAAAAALIUQBAAAAMBSuB0OAAAAgKVwJQgAAACApRCCAAAAAFgKIQgAAACApRCCAAAAAFgKIQgAAACApRCCAAA31LFjRz311FPuLuOWIiMjNWHCBMdrm82mxYsX3/U63LVdAMDtyeHuAgAAcLXjx48rJCTE3WUAAO5RXAkCAGQ7+fLlk91uz5Kxr1y5kiXjStLly5ezbGwAwP8QggAAWrBggcqUKSMfHx+FhoaqXr16On/+fJp+xhi98847Klq0qHx8fFSuXDktWLDAqc+uXbvUuHFj+fv7KywsTM8//7xOnTrlWF67dm317NlTPXv2VHBwsEJDQ/XGG28oo3+7++TJk3riiSfk4+OjIkWKaPbs2Wn6XHtb2uXLl9WzZ0/lz59f3t7eioyM1OjRox194+Li1KxZM/n7+yswMFCtWrXSiRMnHMuHDRum8uXLa+rUqSpatKjsdruMMdq/f79q1qwpb29vlSpVSt9//32aOo4dO6bWrVsrJCREoaGhatasmY4cOeJYnnq74ejRo1WgQAFFRUVl6D0AANwZQhAAWNzx48fVpk0bde7cWbt379bKlSvVvHnzdEPJG2+8oWnTpmnSpEnauXOn+vbtq+eee06rVq1yjFWrVi2VL19eMTExWrZsmU6cOKFWrVo5jTNjxgzlyJFDGzZs0Pvvv693331XU6ZMyVC9HTt21JEjR/TTTz9pwYIFmjhxok6ePHnD/u+//76+/vprzZ8/X3v37tVnn32myMhISf+Euqeeekp///23Vq1ape+//14HDx5U69atncY4cOCA5s+fr4ULF2rbtm1KSUlR8+bN5enpqfXr1+ujjz7SgAEDnNa5cOGC6tSpI39/f61evVpr1qyRv7+/Hn/8cacrPj/++KN2796t77//XkuWLMnQewAAuEMGAGBpmzdvNpLMkSNH0izr0KGDadasmTHGmHPnzhlvb2+zdu1apz5dunQxbdq0McYY8+abb5oGDRo4LT969KiRZPbu3WuMMaZWrVomOjrapKSkOPoMGDDAREdH37LWvXv3Gklm/fr1jrbdu3cbSebdd991tEkyixYtMsYY8/LLL5vHHnvMaXupVqxYYTw9PU1cXJyjbefOnUaS2bhxozHGmKFDhxovLy9z8uRJR5/ly5cbT09Pc/ToUUfb0qVLnbb76aefmhIlSjhtNykpyfj4+Jjly5cbY/55f8PCwkxSUtIt9x0A4DpcCQIAiytXrpzq1q2rMmXKqGXLlvrkk0905syZNP127dqlS5cuqX79+vL393d8zZw5UwcPHpQkbd68WT///LPT8pIlS0qSo48kVa1aVTabzfG6WrVq2r9/v5KTk29a6+7du5UjRw5VrFjR0VayZEkFBwffcJ2OHTtq27ZtKlGihHr16qUVK1Y4jRceHq7w8HBHW6lSpRQcHKzdu3c72iIiIpQnTx6n9QoXLqxChQo57cO1Nm/erAMHDiggIMDxXuTKlUuXLl1yei/KlCmjnDlz3nS/AQCuxexwAGBxnp6e+v7777V27VqtWLFCH3zwgQYPHqwNGzY49UtJSZEkffvttypYsKDTstRJCFJSUvTEE09o7NixabaTP3/+O67V/P9b9K4NULdSoUIFHT58WEuXLtUPP/ygVq1aqV69elqwYIGMMemOdX27n59funVc6/pxUlJS9PDDD6f7zNK1ger6sQEAWY8QBACQzWbTI488okceeURDhgxRRESEFi1a5NSnVKlSstvtiouLU61atdIdp0KFClq4cKEiIyOVI8eN/4lZv359mtcPPPCAPD09b1pndHS0rl69qpiYGFWuXFmStHfvXsXHx990vcDAQLVu3VqtW7dWixYt9Pjjj+vvv/9WqVKlFBcXp6NHjzquBu3atUsJCQmKjo6+4Xip6/3xxx8qUKCAJGndunVOfSpUqKB58+Ypb968CgwMvGl9AIC7i9vhAMDiNmzYoLffflsxMTGKi4vTl19+qb/++itNCAgICNCrr76qvn37asaMGTp48KC2bt2qDz/8UDNmzJAk9ejRQ3///bfatGmjjRs36tChQ1qxYoU6d+7sdKvb0aNH1a9fP+3du1eff/65PvjgA/Xu3fuWtZYoUUKPP/64unbtqg0bNmjz5s164YUX5OPjc8N13n33Xc2dO1d79uzRvn379MUXXyhfvnwKDg5WvXr1VLZsWbVr105btmzRxo0b1b59e9WqVcvplrvr1atXTyVKlFD79u3122+/6ZdfftHgwYOd+rRr1065c+dWs2bN9Msvv+jw4cNatWqVevfurd9///2W+woAyDqEIACwuMDAQK1evVqNGzdWVFSU3njjDY0fP16NGjVK0/ett97SkCFDNHr0aEVHR6thw4b65ptvVKRIEUlSgQIF9Ouvvyo5OVkNGzbUgw8+qN69eysoKEgeHv/7J6d9+/a6ePGiKleurB49eujll19Wt27dMlTvtGnTFB4erlq1aql58+bq1q2b8ubNe8P+/v7+Gjt2rCpWrKhKlSrpyJEj+u677+Th4eGYSjskJEQ1a9ZUvXr1VLRoUc2bN++mNXh4eGjRokVKSkpS5cqV9cILL2jUqFFOfXx9fbV69WoVLlxYzZs3V3R0tDp37qyLFy9yZQgA3Mxm0ruxGQCALFK7dm2VL19eEyZMcHcpAACL4koQAAAAAEshBAEA7hm//PKL0/Ta138BAOAK3A4HALhnXLx4UceOHbvh8uLFi9/FagAA2RUhCAAAAIClcDscAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEv5f4n/BssP4s3hAAAAAElFTkSuQmCC", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " count mean std min 25% 50% 75% max\n", + "sleep_disorder \n", + "Insomnia 29.0 6.034483 1.499589 3.0 5.0 7.0 7.0 8.0\n", + "No Disorder 73.0 5.178082 1.618834 3.0 4.0 5.0 6.0 8.0\n", + "Sleep Apnea 30.0 5.933333 2.066704 3.0 4.0 7.0 8.0 8.0\n" + ] + } + ], + "source": [ + "plt.figure(figsize=(10, 6))\n", + "sns.boxplot(data=sleep_data_clean, x='sleep_disorder', y='stress_level')\n", + "plt.title('H1b: Stress Level by Sleep Disorder')\n", + "plt.show()\n", + "\n", + "# Stats\n", + "print(sleep_data_clean.groupby('sleep_disorder')['stress_level'].describe())" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "4e994289-877c-4f35-8093-7d7ce092331f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H1b Analysis: Stress Level vs Insomnia\n", + "\n", + "Mean stress level by disorder:\n", + "sleep_disorder\n", + "Insomnia 6.03\n", + "No Disorder 5.18\n", + "Sleep Apnea 5.93\n", + "Name: stress_level, dtype: float64\n", + "\n", + "Stress level distribution for Insomnia patients:\n", + "Mean: 6.03\n", + "Median: 7.00\n", + "Std: 1.50\n" + ] + } + ], + "source": [ + "\n", + "print(\"H1b Analysis: Stress Level vs Insomnia\")\n", + "print(\"\\nMean stress level by disorder:\")\n", + "print(sleep_data_clean.groupby('sleep_disorder')['stress_level'].mean().round(2))\n", + "\n", + "print(\"\\nStress level distribution for Insomnia patients:\")\n", + "insomnia_stress = sleep_data_clean[sleep_data_clean['sleep_disorder'] == 'Insomnia']['stress_level']\n", + "print(f\"Mean: {insomnia_stress.mean():.2f}\")\n", + "print(f\"Median: {insomnia_stress.median():.2f}\")\n", + "print(f\"Std: {insomnia_stress.std():.2f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "e03c3c19-821e-4d4b-9329-bf7ac006b837", + "metadata": {}, + "source": [ + "### **H1b: Analysis - Stress Level and Insomnia Correlation**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Mean Stress Levels by Group:**\n", + " - Insomnia: 6.03 (median: 7.0)\n", + " - Sleep Apnea: 5.93 (median: 7.0)\n", + " - No Disorder: 5.18 (median: 5.0)\n", + "\n", + "2. **Observed Difference:**\n", + " - Insomnia patients show **0.85 points higher** average stress compared to individuals without disorders\n", + " - Standard deviation: 1.50 (indicating substantial variation within groups)\n", + "\n", + "3. **Distribution Overlap:**\n", + " - Boxplots reveal significant overlap across all three groups (range 3-8 for all categories)\n", + " - No clear separation between disorder types based on stress alone\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H1b is WEAKLY SUPPORTED.** While insomnia patients exhibit marginally higher average stress levels (6.03 vs 5.18), the difference is modest and distributions overlap considerably.\n", + "\n", + "**⚠️ Key Observations:**\n", + "- Sleep Apnea patients show nearly identical stress levels (5.93) to Insomnia patients (6.03)\n", + "- High variability within groups (σ = 1.50) suggests stress alone is not a strong discriminator\n", + "- Median values (7.0 for both disorders) indicate stress may be elevated for any sleep disorder, not specifically insomnia\n" + ] + }, + { + "cell_type": "markdown", + "id": "c8ec9846-69bf-4051-92b9-a6cfda60be27", + "metadata": {}, + "source": [ + "#### H1c: Sleeping <6 hours increases disorder risk" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "c618d143-2a4d-49fd-b0ff-2b84ca3774d4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "sleep_deprived \n", + "False 21.875 57.03125 21.09375\n", + "True 25.000 0.00000 75.00000\n" + ] + } + ], + "source": [ + "\n", + "sleep_data_clean['sleep_deprived'] = sleep_data_clean['sleep_duration'] < 6\n", + "\n", + "# Visualisation\n", + "plt.figure(figsize=(10, 6))\n", + "pd.crosstab(sleep_data_clean['sleep_deprived'], sleep_data_clean['sleep_disorder']).plot(kind='bar')\n", + "plt.title('H1c: Sleep Duration <6h vs Sleep Disorder')\n", + "plt.xlabel('Sleep Deprived (<6h)')\n", + "plt.ylabel('Count')\n", + "plt.xticks(rotation=0)\n", + "plt.legend(title='Sleep Disorder')\n", + "plt.show()\n", + "\n", + "# Stats\n", + "print(pd.crosstab(sleep_data_clean['sleep_deprived'], sleep_data_clean['sleep_disorder'], normalize='index') * 100)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "f979f631-ff74-4d65-bc10-d3bf25ba232e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H1c Analysis: Sleep Duration < 6 hours\n", + "\n", + "Disorder rate for sleep-deprived individuals:\n", + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "sleep_deprived \n", + "False 21.875 57.03125 21.09375\n", + "True 25.000 0.00000 75.00000\n", + "\n", + "% of people sleeping <6h: 3.03%\n" + ] + } + ], + "source": [ + "print(\"H1c Analysis: Sleep Duration < 6 hours\")\n", + "print(\"\\nDisorder rate for sleep-deprived individuals:\")\n", + "print(pd.crosstab(sleep_data_clean['sleep_deprived'], \n", + " sleep_data_clean['sleep_disorder'], \n", + " normalize='index') * 100)\n", + "\n", + "print(f\"\\n% of people sleeping <6h: {(sleep_data_clean['sleep_deprived'].sum() / len(sleep_data_clean) * 100):.2f}%\")" + ] + }, + { + "cell_type": "markdown", + "id": "a136ea09-6fc1-4258-b4a3-7628cb8b210d", + "metadata": {}, + "source": [ + "### **H1c: Analysis - Sleep Duration < 6 Hours and Disorder Risk**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Critical Threshold Identified:**\n", + " - **Sleep-deprived (<6h): 100% have a sleep disorder** (n=4)\n", + " - Sleep Apnea: 75.0% (3 cases)\n", + " - Insomnia: 25.0% (1 case)\n", + " - No Disorder: 0%\n", + " \n", + " - **Adequate sleep (≥6h): 42.97% have a sleep disorder** (n=128)\n", + " - No Disorder: 57.03%\n", + " - Sleep Apnea: 21.09%\n", + " - Insomnia: 21.88%\n", + "\n", + "2. **Population Distribution:**\n", + " - Only 3.03% of sample sleeps <6 hours (4 individuals)\n", + " - 96.97% maintain ≥6 hours sleep duration\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H1c is SUPPORTED but requires validation.** The data suggests sleeping <6 hours is strongly associated with sleep disorder presence (100% in this sample).\n", + "\n", + "**Critical Limitations:**\n", + "- **Extremely small sample size** for sleep-deprived group (n=4) - statistically unreliable\n", + "- Cannot establish causation: does short sleep cause disorders, or do disorders cause short sleep?\n", + "- Selection bias possible: individuals with disorders may naturally sleep less\n", + "- 100% rate likely reflects small sample noise rather than true population parameter\n" + ] + }, + { + "cell_type": "markdown", + "id": "47f3cd69-9abb-473f-9ae4-444d9ae19cd7", + "metadata": {}, + "source": [ + "#### H1d: Low physical activity (<40 min/day) increases disorder prevalence" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "43b9a772-aa6b-4231-aa7e-cb7a5b852558", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sleep_data_clean['low_activity'] = sleep_data_clean['physical_activity_level'] < 40\n", + "\n", + "# Visualisation\n", + "plt.figure(figsize=(10, 6))\n", + "pd.crosstab(sleep_data_clean['low_activity'], sleep_data_clean['sleep_disorder']).plot(kind='bar')\n", + "plt.title('H1d: Physical Activity <40min vs Sleep Disorder')\n", + "plt.xlabel('Low Activity (<40min)')\n", + "plt.xticks(rotation=0)\n", + "plt.legend(title='Sleep Disorder')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "149ab0b7-ed97-4f51-bcf7-8a732205124b", + "metadata": {}, + "source": [ + "### **H1d: Analysis - Low Physical Activity (<40 min/day) and Sleep Disorder Prevalence**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Activity Groups Distribution:**\n", + " - **Low Activity (<40 min/day):** ~20% of sample (n≈26)\n", + " - Insomnia: ~23% (6 cases)\n", + " - No Disorder: ~58% (15 cases)\n", + " - Sleep Apnea: ~19% (5 cases)\n", + " \n", + " - **Adequate Activity (≥40 min/day):** ~80% of sample (n≈106)\n", + " - Insomnia: ~22% (23 cases)\n", + " - No Disorder: ~55% (58 cases)\n", + " - Sleep Apnea: ~24% (25 cases)\n", + "\n", + "2. **Disorder Prevalence Comparison:**\n", + " - Low Activity group: ~42% have a sleep disorder\n", + " - Adequate Activity group: ~45% have a sleep disorder\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H1d is NOT SUPPORTED.** Contrary to the hypothesis, low physical activity (<40 min/day) does NOT show increased sleep disorder prevalence in this dataset. In fact, disorder rates are similar across both activity levels (~42-45%).\n", + "\n", + "**Key Observations:**\n", + "- No meaningful difference in disorder prevalence between activity groups\n", + "- Distribution of disorder types (Insomnia vs Sleep Apnea) is consistent across both groups\n", + "- Correlation heatmap shows weak relationship between physical_activity_level and sleep quality (r = 0.29)\n", + "\n", + "#### **Alternative Interpretations:**\n", + "\n", + "1. **Threshold May Be Inappropriate:** 40 min/day cutoff may not capture meaningful activity differences\n", + "2. **Non-Linear Relationship:** Activity effects may only manifest at extreme sedentary levels (<20 min) or high activity levels (>60 min)\n", + "3. **Confounding Variables:** Other factors (BMI, age, stress) may overshadow activity effects\n", + "4. **Bidirectional Causation:** Sleep disorders may reduce physical activity capacity, not vice versa\n" + ] + }, + { + "cell_type": "markdown", + "id": "830445c8-7934-4792-9bbc-dd33326e0996", + "metadata": {}, + "source": [ + "#### H1e: High heart rate / BP increases apnea risk" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "8887e92f-3eaa-4a88-808b-038833c22613", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# High heart rate: >80 bpm\n", + "sleep_data_clean['high_hr'] = sleep_data_clean['heart_rate'] > 80\n", + "\n", + "# High BP: Systolic >130\n", + "sleep_data_clean['high_bp'] = sleep_data_clean['systolic'] > 130\n", + "\n", + "# Visualisation\n", + "fig, axes = plt.subplots(1, 2, figsize=(14, 6))\n", + "\n", + "# Heart Rate\n", + "pd.crosstab(sleep_data_clean['high_hr'], sleep_data_clean['sleep_disorder']).plot(kind='bar', ax=axes[0])\n", + "axes[0].set_title('H1e: High Heart Rate (>80) vs Sleep Disorder')\n", + "axes[0].set_xlabel('High Heart Rate')\n", + "\n", + "# Blood Pressure\n", + "pd.crosstab(sleep_data_clean['high_bp'], sleep_data_clean['sleep_disorder']).plot(kind='bar', ax=axes[1])\n", + "axes[1].set_title('H1e: High BP (>130) vs Sleep Disorder')\n", + "axes[1].set_xlabel('High Systolic BP')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d84c0d58-2eb4-4470-8531-7351c98cf6a9", + "metadata": {}, + "source": [ + "### **H1e: Analysis - High Heart Rate / Blood Pressure and Sleep Apnea Risk**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **High Heart Rate (>80 bpm):**\n", + " - **100% of individuals with HR >80 have a sleep disorder** (n=8)\n", + " - Sleep Apnea: 62.5% (5 cases)\n", + " - Insomnia: 37.5% (3 cases)\n", + " - No Disorder: 0%\n", + " \n", + " - Normal HR (≤80): 40.5% have a disorder (n=126)\n", + " - Sleep Apnea: 19.8%\n", + " - Insomnia: 20.6%\n", + "\n", + "2. **High Blood Pressure (Systolic >130):**\n", + " - **84.6% of individuals with BP >130 have a sleep disorder** (n=39)\n", + " - Sleep Apnea: 53.8% (21 cases)\n", + " - Insomnia: 30.8% (12 cases)\n", + " - No Disorder: 15.4% (6 cases)\n", + " \n", + " - Normal BP (≤130): 28.0% have a disorder (n=93)\n", + " - Sleep Apnea: 9.7%\n", + " - Insomnia: 18.3%\n", + "\n", + "3. **Sleep Apnea Specific Risk:**\n", + " - High HR >80: **3.2x higher** Sleep Apnea rate (62.5% vs 19.8%)\n", + " - High BP >130: **5.5x higher** Sleep Apnea rate (53.8% vs 9.7%)\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H1e is STRONGLY VALIDATED** Elevated heart rate and blood pressure are powerful indicators of sleep disorder risk, particularly Sleep Apnea.\n", + "\n", + "**Key Findings:**\n", + "- Cardiovascular stress markers (HR, BP) show strongest association with Sleep Apnea among all tested variables\n", + "- High BP demonstrates clearer separation than high HR (larger sample: n=39 vs n=8)\n", + "- Elevated BP is particularly predictive: 85% disorder rate vs 28% in normal BP group\n", + "\n", + "**Limitations:**\n", + "- Small sample for high HR group (n=8) - requires validation\n", + "- Cannot establish causation: does cardiovascular stress cause apnea, or does apnea elevate CV metrics?\n", + "- Sleep apnea is known to cause hypertension (bidirectional relationship likely)" + ] + }, + { + "cell_type": "markdown", + "id": "fe9ac04e-339b-4592-a0c6-18aaeaa4b66e", + "metadata": {}, + "source": [ + "### H2: Age and Sleep Disorder Relationship" + ] + }, + { + "cell_type": "markdown", + "id": "58da6135-2b15-436a-9afe-959f389a6425", + "metadata": {}, + "source": [ + "### H2: Age and Sleep Disorder Relationship" + ] + }, + { + "cell_type": "markdown", + "id": "f1df1635-c978-4ee3-953a-665587f97b35", + "metadata": {}, + "source": [ + "#### H2 Primary + H2a + H2b: Age distribution by disorder type" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "b8bef6bc-0f4e-4df5-bcb4-812c6d75dba1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H2 Analysis: Age by Sleep Disorder\n", + "\n", + "Age statistics by disorder type:\n", + " count mean std min 25% 50% 75% max\n", + "sleep_disorder \n", + "Insomnia 29.0 41.620690 6.863016 28.0 39.0 43.0 45.0 53.0\n", + "No Disorder 73.0 39.452055 8.496799 27.0 32.0 37.0 44.0 59.0\n", + "Sleep Apnea 30.0 44.733333 10.268577 28.0 36.0 48.5 51.0 59.0\n", + "\n", + "Mean age by disorder:\n", + "sleep_disorder\n", + "Sleep Apnea 44.733333\n", + "Insomnia 41.620690\n", + "No Disorder 39.452055\n", + "Name: age, dtype: float64\n" + ] + } + ], + "source": [ + "plt.figure(figsize=(12, 6))\n", + "sns.violinplot(data=sleep_data_clean, x='sleep_disorder', y='age')\n", + "plt.title('H2: Age Distribution by Sleep Disorder Type')\n", + "plt.ylabel('Age (years)')\n", + "plt.show()\n", + "\n", + "# Stats\n", + "print(\"H2 Analysis: Age by Sleep Disorder\")\n", + "print(\"\\nAge statistics by disorder type:\")\n", + "print(sleep_data_clean.groupby('sleep_disorder')['age'].describe())\n", + "\n", + "print(\"\\nMean age by disorder:\")\n", + "age_means = sleep_data_clean.groupby('sleep_disorder')['age'].mean().sort_values(ascending=False)\n", + "print(age_means)" + ] + }, + { + "cell_type": "markdown", + "id": "5ee4888f-4626-43b9-9657-0776c4a86757", + "metadata": {}, + "source": [ + "### **H2: Analysis - Age and Sleep Disorder Relationship**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Mean Age by Disorder Type:**\n", + " - Sleep Apnea: 44.7 years (highest)\n", + " - Insomnia: 41.6 years\n", + " - No Disorder: 39.5 years (youngest)\n", + " \n", + "2. **Age Distribution Characteristics:**\n", + " - **Sleep Apnea:** Widest distribution (28-59 years), median 48.5, higher concentration in 45+ range\n", + " - **Insomnia:** Tighter distribution (28-53 years), median 43.0, more concentrated around 40-45\n", + " - **No Disorder:** Youngest cohort (27-59 years), median 37.0, skewed toward younger ages\n", + "\n", + "3. **Age Differences:**\n", + " - Sleep Apnea vs No Disorder: **5.3 years difference**\n", + " - Sleep Apnea vs Insomnia: **3.1 years difference**\n", + " - Insomnia vs No Disorder: **2.2 years difference**\n", + "\n", + "#### **Hypothesis Testing:**\n", + "\n", + "**H2a: Older individuals are more likely to develop a sleep disorder** **SUPPORTED**\n", + "- Mean age increases progressively: No Disorder (39.5) < Insomnia (41.6) < Sleep Apnea (44.7)\n", + "- However, effect is modest (5.3 year difference) with substantial overlap between groups\n", + "\n", + "**H2b: Age is more strongly associated with sleep apnea than with insomnia** **SUPPORTED** \n", + "- Sleep Apnea patients are 3.1 years older on average than Insomnia patients\n", + "- Sleep Apnea shows wider age distribution and higher median (48.5 vs 43.0)\n", + "- Aligns with medical understanding: apnea often linked to age-related tissue changes\n", + "\n", + "**H2c: Younger individuals show a higher proportion of insomnia cases** **PARTIALLY SUPPORTED**\n", + "- Insomnia patients are younger than Sleep Apnea patients (41.6 vs 44.7)\n", + "- However, No Disorder group is youngest (39.5), not Insomnia group\n", + "- Distribution shows Insomnia concentrated in 35-45 age range, not necessarily \"young\"\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "Age demonstrates a **moderate positive association** with sleep disorder presence and type. The relationship follows expected patterns (older → more apnea) but with significant limitations.\n", + "\n", + "**Critical Limitations:**\n", + "- **Substantial overlap:** All three groups span similar age ranges (27-59), limiting discriminatory power\n", + "- **Small effect size:** 5.3 year difference between extremes is modest\n", + "- **Cannot establish causation:** Correlation does not prove age causes disorders\n", + "- **Sample characteristics:** Age range (27-59) excludes elderly population (>65) where effects may be stronger\n" + ] + }, + { + "cell_type": "markdown", + "id": "f356f74b-f5dc-4a23-a332-1e90ebe75511", + "metadata": {}, + "source": [ + "#### H2c: Age distribution for Insomnia vs Sleep Apnea (exclude No Disorder)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "03cd8029-42fb-4e8c-ab21-3ad6751dc6b6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H2b & H2c: Direct comparison Insomnia vs Sleep Apnea\n", + "\n", + "Insomnia:\n", + " Mean age: 41.6\n", + " Median age: 43.0\n", + " Age range: 28-53\n", + "\n", + "Sleep Apnea:\n", + " Mean age: 44.7\n", + " Median age: 48.5\n", + " Age range: 28-59\n" + ] + } + ], + "source": [ + "disorders_only = sleep_data_clean[sleep_data_clean['sleep_disorder'] != 'No Disorder']\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "sns.boxplot(data=disorders_only, x='sleep_disorder', y='age')\n", + "plt.title('H2c: Age Comparison - Insomnia vs Sleep Apnea')\n", + "plt.ylabel('Age (years)')\n", + "plt.show()\n", + "\n", + "# Stats comparison\n", + "print(\"H2b & H2c: Direct comparison Insomnia vs Sleep Apnea\")\n", + "for disorder in ['Insomnia', 'Sleep Apnea']:\n", + " subset = sleep_data_clean[sleep_data_clean['sleep_disorder'] == disorder]\n", + " print(f\"\\n{disorder}:\")\n", + " print(f\" Mean age: {subset['age'].mean():.1f}\")\n", + " print(f\" Median age: {subset['age'].median():.1f}\")\n", + " print(f\" Age range: {subset['age'].min()}-{subset['age'].max()}\")" + ] + }, + { + "cell_type": "markdown", + "id": "db3c5348-d51b-4bf7-82e4-72accff03b05", + "metadata": {}, + "source": [ + "#### H2d: Age vs Sleep Duration correlation" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "baaa4803-d2c5-486c-963b-017078fd9366", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "📊 H2d: Age vs Sleep Duration Correlation\n", + "Correlation coefficient: 0.348\n", + "P-value: 0.0000\n" + ] + } + ], + "source": [ + "\n", + "plt.figure(figsize=(10, 6))\n", + "sns.scatterplot(data=sleep_data_clean, x='age', y='sleep_duration', hue='sleep_disorder', alpha=0.6)\n", + "plt.title('H2d: Age vs Sleep Duration')\n", + "plt.xlabel('Age (years)')\n", + "plt.ylabel('Sleep Duration (hours)')\n", + "\n", + "# Add regression line\n", + "from scipy import stats\n", + "slope, intercept, r_value, p_value, std_err = stats.linregress(sleep_data_clean['age'], sleep_data_clean['sleep_duration'])\n", + "line = slope * sleep_data_clean['age'] + intercept\n", + "plt.plot(sleep_data_clean['age'], line, 'r--', label=f'r = {r_value:.3f}')\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "print(\"\\n📊 H2d: Age vs Sleep Duration Correlation\")\n", + "print(f\"Correlation coefficient: {sleep_data_clean['age'].corr(sleep_data_clean['sleep_duration']):.3f}\")\n", + "print(f\"P-value: {p_value:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "15007d53-3dbf-42fe-bee8-3bf3ad072ead", + "metadata": {}, + "source": [ + "### **H2d: Analysis - Age vs Sleep Duration Correlation**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "1. **Correlation Statistics:**\n", + " - Correlation coefficient: **r = 0.348** (POSITIVE correlation)\n", + " - P-value: 0.0000 (highly statistically significant)\n", + " - Regression line shows upward trend\n", + "\n", + "2. **Observed Pattern:**\n", + " - **Younger individuals (27-35):** Cluster around 6.0-7.5 hours sleep\n", + " - **Older individuals (50-59):** Cluster around 7.5-8.5 hours sleep\n", + " - Clear positive relationship: as age increases, sleep duration increases\n", + "\n", + "3. **Disorder Distribution:**\n", + " - Sleep disorders (Apnea/Insomnia) present across all age ranges\n", + " - No clear age-based separation in sleep duration between disorder types\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H2d is REJECTED ** \n", + "\n", + "**The hypothesis predicted negative correlation (older → less sleep), but data shows POSITIVE correlation (older → more sleep).**\n", + "\n", + "**Critical Analysis:**\n", + "\n", + "This finding **contradicts** both:\n", + "1. The original hypothesis (negative correlation expected)\n", + "2. General medical literature (elderly typically sleep less)\n", + "\n", + "**Possible Explanations:**\n", + "\n", + "1. **Sample Bias:** \n", + " - Age range limited to 27-59 (excludes elderly 65+)\n", + " - True age-related sleep decline may occur after 60\n", + " - Working-age sample may not capture retirement effects\n", + "\n", + "2. **Cohort Effects:**\n", + " - Younger individuals (27-35) may be in high-stress career phase with reduced sleep\n", + " - Older individuals (50-59) may have more established routines, better work-life balance\n", + "\n", + "3. **Selection Bias:**\n", + " - Dataset may over-represent younger individuals with sleep problems\n", + " - Older individuals without sleep issues may be under-represented\n", + "\n", + "4. **Measurement Limitations:**\n", + " - Self-reported sleep duration may not reflect sleep quality\n", + " - Older individuals may spend more time in bed but have fragmented sleep" + ] + }, + { + "cell_type": "markdown", + "id": "648b0ead-6e17-448b-a53e-1546e4052a11", + "metadata": {}, + "source": [ + "### **Research Question Evolution**\n", + "\n", + "Initial research questions (1-3) successfully identified individual risk factors. However, to fully address the business objective of **\"identifying high-risk individuals for targeted intervention,\"** we must test whether combining these factors creates a more effective predictive tool.\n", + "\n", + "This leads to another research question:\n", + "\n", + "**4. Can we develop an integrated risk model that efficiently identifies high-risk individuals for resource-optimized screening?**\n", + "\n", + "This question is addressed through Hypothesis 3." + ] + }, + { + "cell_type": "markdown", + "id": "35c7c8dd-59a3-4b69-b89b-9eb6415cec04", + "metadata": {}, + "source": [ + " ### **Primary Hypothesis (H3): Combined Risk Factor Model**\n", + "\n", + "**Multiple risk factors demonstrate cumulative effects on sleep disorder likelihood, enabling the creation of a practical risk stratification model for targeted healthcare delivery.**\n", + "\n", + "**H0 (Null Hypothesis):** Risk factors act independently without cumulative effects; combined scoring provides no additional predictive value over individual factors.\n", + "\n", + "\n", + "#### **Secondary Hypotheses:**\n", + "\n", + "**H3a:** Individuals with multiple risk factors (BMI > 30 + BP > 130 + Age > 45) have significantly higher disorder prevalence than those with single risk factors\n", + "\n", + "**H3b:** A simple risk score based on BMI, BP, and age can effectively stratify individuals into low/medium/high risk categories\n", + "\n", + "**H3c:** High-risk profiles (combining 2+ risk factors) represent a minority of the population but account for the majority of sleep disorder cases\n", + "\n", + "**H3d:** Different risk factor combinations predict different disorder types:\n", + "- BMI + BP + Older age → Sleep Apnea\n", + "- Stress + Younger age → Insomnia" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "916c4375-5fba-4d9e-b74f-e7a49fa9e4a7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H3: Disorder Prevalence by Risk Category\n", + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "risk_category \n", + "Low Risk 9.86 81.69 8.45\n", + "Medium Risk 45.83 37.50 16.67\n", + "High Risk 29.73 16.22 54.05\n" + ] + }, + { + "data": { + "text/plain": [ + "
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k7Nu3D40aNYK7u3uh6qpUqRKAd4e8CuP06dNo3rw5AGD58uU4ceIEzpw5gwkTJgAo3DZ/9OgRLl26lOO7ZmBgACGE4vv25MkTaGhowNTUVGn690M28HH7TG5t5XI5BgwYgHXr1iE5ORmPHz/Ghg0b0K9fv1K7mEBVeDXTf0DFihVRvnx53Lhxo9jmKZPJMHLkSEydOhX//PNPnu3Mzc0hk8lw7NixXL9M2cOyr5L57bff8rwS4sM/AImJiahQoYLi/du3b/HkyZOPuvz8fdu3bwfw7kTZ/HTo0AEdOnRAeno6Tp06heDgYHTv3h22trZo1KgRzMzMcvSGAVCc2Pn+lUFAzhOpTUxMIJPJcvzBB5BjWGG3c17L+hTFtb0KUtSa89tu2ftIdo9Xenq60jb6MPwVhYmJCdTU1Ir02X+K3Pb7D9cTAIyMjBSBYvTo0QgJCUH37t1hbGxcqOVoa2vD1dUVwLueNm9vb9SsWRMBAQFo27Ztvve7MTc3x4IFC7BgwQLEx8dj+/bt+PHHH5GUlIS9e/cq2lWqVAnz5s3D119/DV9fX/z1119KvZK5cXV1hampKbZt24bg4OAC95Pw8HBoampi586dSvPeunVrIbbC/18fHR0drFy5Ms/xwLvt//btWzx9+lQp0Hy4b37MPpPXeg4aNAgzZszAypUr8fr1a7x9+xYDBw4s9LpJFXtm/gOyu9WrVq36UdPn9gUD3n3JUlNT8/0fedu2bSGEwIMHD3LtXapduzYAwMPDA8bGxrh69Wqu7VxdXaGlpaU07+x7XmTbsGED3r59W+CPan4uXryIoKAg2Nra5ugazotcLoenpydmzpwJ4N19eYB3hzmuXr2K8+fPK7XPvrLA29s73/nq6emhYcOG2Lx5M16/fq0Y/vz5c+zYsUOpbWG3c3Erzu1VlN6Iwjh06JDSic+ZmZn4888/UaVKFVSsWBEAFCfAX7p0SWnaD7dvdn2FqU1PTw9ubm7YvHmzUvusrCysWbMGFStWRPXq1T9mlfL04Xdh3bp1AHIGzOHDh+Pff/9Fp06dkJyc/Ek3FjQzM8OMGTPw6NEj/Pbbb4WerlKlShg6dCh8fHxyfDcAoHnz5ti3bx+OHj2Ktm3b5ji8/CFNTU2MHTsW165dUzqB931JSUk4ceIEgHchQENDA+rq6orxaWlpWL16dY7p8vrM27Zti9jYWJiZmeX6fcverzw9PQEgxwm8H/ZmFec+Y21tjc6dO2Px4sVYunQp2rVrp+i9+pyxZ+YzcunSJYwcORKdOnWCvb091NTUcPnyZcyfPx9mZmYYPXq0UvvscFPQeTPfffcdkpOT0bFjR9SqVQvq6uq4du0a5s+fDzU1NYwdOzbPaT08PPDdd9+hd+/eOHv2LBo3bgw9PT0kJCTg+PHjqF27NgYNGgR9fX389ttv8PPzw9OnT9GpUydYWFjg8ePHuHjxIh4/fowlS5YozXvz5s3Q0NCAj48Prly5gokTJ6JOnTqF/lE9d+4cjIyM8ObNG8VN4FavXg0LCwvs2LEjR3h636RJk3D//n00bdoUFStWRHJyMn755Rdoamoq/oCNHDkSq1atQps2bTB16lRUrlwZu3btwuLFizFo0KBC/XGaNm0aWrZsCR8fH3z//ffIzMzEzJkzoaenp3TYrbDb+VOU9PaqUqUKdHR0sHbtWjg6OkJfXx/ly5fPNyznx9zcHE2aNMHEiROhp6eHxYsX49q1a0o/JK1bt4apqSn69u2LqVOnQkNDA6Ghobh3716O+dWuXRvh4eH4888/FXfCziskBgcHw8fHB97e3hg9ejS0tLSwePFi/PPPP1i/fn2x9oxpaWlh7ty5ePHiBRo0aICoqChMnz4drVq1ynFeXfXq1dGyZUvs2bMHX375pdKNDj/Gt99+i3nz5mHOnDkYMmRIrocBU1JS4O3tje7du6NGjRowMDDAmTNnsHfv3hxXWGb78ssvcejQIbRs2RLNmzfH7t278zysDgA//PADYmJiMHnyZJw+fRrdu3dX3DTv6NGjWLZsGaZMmQIPDw+0adMG8+bNQ/fu3fHdd9/hyZMnmDNnTq49mnl95gEBAdi0aRMaN26MkSNHwtnZGVlZWYiPj8f+/fvx/fffK65a8vDwwPfff4/U1FTUr18fJ0+exKpVqwC8O5cpW3HuMyNGjICbmxsA5Hrl42dJRSceUyFkn5n+4Rnz2dq0aaN0FUdiYqLo2bOnqFKlitDV1RVaWlrC3t5eDBw4UMTHx+eYvnLlyrleDfWhffv2iT59+ggnJydhZGQkNDQ0hLW1tfD19RUnT55UapvblSVCCLFy5Urh5uYm9PT0hI6OjqhSpYr49ttvxdmzZ5XaRUZGijZt2ghTU1OhqakpKlSoINq0aSP++usvRZvsK1DOnTsn2rVrJ/T19YWBgYHo1q2bePToUYHrkz199ksulwtra2vRvHlz8csvv4jU1NQc03y4Xjt37hStWrUSFSpUEFpaWsLCwkK0bt1aHDt2TGm6u3fviu7duwszMzOhqakpHBwcxOzZs0VmZqaiTfbVH7Nnz8613u3btwtnZ2ehpaUlKlWqJGbMmJHnVTiF2c7ZV40UVmlur/Xr14saNWoITU1Npas9/Pz8hJ6eXq715XU105AhQ8TixYtFlSpVhKampqhRo4ZYu3ZtjulPnz4t3N3dhZ6enqhQoYKYPHmy+OOPP3JczXTnzh3RvHlzYWBgoHQlYW5X7wghxLFjx0STJk0Un8UXX3whduzYodQmr+/4kSNHBABx5MiRXNf5/XXX09MTly5dEl5eXkJHR0eYmpqKQYMGiRcvXuQ6TWhoqAAgwsPD8533+/LbZ7Kv2JkyZYoQIuf2eP36tRg4cKBwdnYWhoaGQkdHRzg4OIjJkyeLly9f5ruMf/75R1hZWYl69erleTXd+7Zt2ybatGkjypUrJzQ0NISJiYnw9vYWS5cuFenp6Yp2K1euFA4ODkIulwt7e3sRHBwsVqxYUejPXAghXrx4IX766Sfh4OAgtLS0hJGRkahdu7YYOXKk0lV0T58+Fb179xbGxsZCV1dX+Pj4iFOnTuV6Fdqn7DMfsrW1FY6OjgVus8+FTAiJ3r6V/rMCAwMxZcoUPH78uFjPPSD6L+jYsSNOnTqFO3fuKF09R6Vn3bp16NGjB06cOFHoE52L4tKlS6hTpw4WLVr0SfeQkhIeZiIi+sylp6fj/PnzOH36NLZs2YJ58+YxyJSS9evX48GDB6hduzbU1NRw6tQpzJ49G40bNy72IBMbG4u7d+9i/PjxsLa2/k89U4phhojoM5eQkAB3d3cYGhpiwIABGDZsmKpL+s/Ivnv39OnT8fLlS0XImD59erEva9q0aVi9ejUcHR3x119/Ffi8tc8JDzMRERGRpPHSbCIiIpI0hhkiIiKSNIYZIiIikrTP/gTgrKwsPHz4EAYGBsV6oyoiIiIqOUIIPH/+HOXLl1e6wWBuPvsw8/DhQ9jY2Ki6DCIiIvoI9+7dUzyCJC8qDzMPHjzA2LFjsWfPHqSlpaF69epYsWIF6tevD+BdMpsyZQqWLVuGZ8+ewc3NDYsWLULNmjULNX8DAwMA7zZGUZ64S0RERKqTmpoKGxsbxe94flQaZp49ewYPDw94e3tjz549sLCwQGxsrNJTXGfNmoV58+YhNDQU1atXx/Tp0+Hj44Pr168XagWzDy0ZGhoyzBAREUlMYU4RUel9Zn788UecOHECx44dy3W8EALly5dHQECA4mGG6enpsLS0xMyZMzFgwIACl5GamgojIyOkpKQwzBAREUlEUX6/VXo10/bt2+Hq6orOnTvDwsICdevWxfLlyxXj4+LikJiYiObNmyuGyeVyeHp6IioqShUlExERURmj0jBz+/ZtLFmyBNWqVcO+ffswcOBADB8+XPF49MTERACApaWl0nSWlpaKcR9KT09Hamqq0ouIiIg+Xyo9ZyYrKwuurq4ICgoCANStWxdXrlzBkiVL8O233yrafXi8TAiR5zG04OBgTJkypeSKJiKiIsvMzMSbN29UXQaVIZqamlBXVy+Weak0zFhbW8PJyUlpmKOjIzZt2gQAsLKyAvCuh8ba2lrRJikpKUdvTbZx48Zh1KhRivfZZ0MTEVHpE0IgMTERycnJqi6FyiBjY2NYWVl98n3gVBpmPDw8cP36daVhN27cQOXKlQEAdnZ2sLKywoEDB1C3bl0AQEZGBiIjIzFz5sxc5ymXyyGXy0u2cCIiKpTsIGNhYQFdXV3evJQAvAu5r169QlJSEgAodVh8DJWGmZEjR8Ld3R1BQUHo0qULTp8+jWXLlmHZsmUA3h1eCggIQFBQEKpVq4Zq1aohKCgIurq66N69uypLJyKiAmRmZiqCjJmZmarLoTJGR0cHwLujLRYWFp90yEmlYaZBgwbYsmULxo0bh6lTp8LOzg4LFixAjx49FG3GjBmDtLQ0DB48WHHTvP379xfqHjNERKQ62efI6OrqqrgSKquy9403b958UphR6X1mSgPvM0NEpBqvX79GXFwc7OzsoK2trepyqAzKbx+RzH1miIiIiD4VwwwREX02ZDIZtm7dquoyCu3OnTuQyWSIjo7+Tyy3pDDMEBGRJCQlJWHAgAGoVKkS5HI5rKys0KJFC5w8eVLVpeXg5eUFmUwGmUwGuVyOChUqoF27dti8ebNSOxsbGyQkJKBWrVoqqvTzwDBDRESS0LFjR1y8eBFhYWG4ceMGtm/fDi8vLzx9+lTVpeWqf//+SEhIwK1bt7Bp0yY4OTnhm2++wXfffadoo66uDisrK2holMz1OBkZGSUy35Ked1ExzBARUZmXnJyM48ePY+bMmfD29kblypXRsGFDjBs3Dm3atMlzugcPHqBr164wMTGBmZkZOnTogDt37ii1CQkJgaOjI7S1tVGjRg0sXrxYMS77cEx4eDjc3d2hra2NmjVrIiIiosCadXV1YWVlBRsbG3zxxReYOXMmfv/9dyxfvhwHDx5Umn/24Z5nz56hR48eKFeuHHR0dFCtWjWEhIQo5nn58mU0adIEOjo6MDMzw3fffYcXL14oxvv7++Orr75CcHAwypcvj+rVqwMATp8+jbp160JbWxuurq64cOFCjnqvXr2K1q1bQ19fH5aWlujVqxf+/fdfxXgvLy8MHToUo0aNgrm5OXx8fArcBqWFYYaIiMo8fX196OvrY+vWrUhPTy/UNK9evYK3tzf09fVx9OhRHD9+HPr6+mjZsqWiV2H58uWYMGECfv75Z8TExCAoKAgTJ05EWFiY0rx++OEHfP/997hw4QLc3d3Rvn17PHnypMjr4efnBxMTkxyHm7JNnDgRV69exZ49exATE4MlS5bA3NxcsT4tW7aEiYkJzpw5g7/++gsHDx7E0KFDleZx6NAhxMTE4MCBA9i5cydevnyJtm3bwsHBAefOnUNgYCBGjx6tNE1CQgI8PT3h4uKCs2fPYu/evXj06BG6dOmi1C4sLAwaGho4ceIEfv/99yKvf0lR6X1mSIUCjUpxWSmltywi+ixpaGggNDQU/fv3x9KlS1GvXj14enrim2++gbOzc67ThIeHQ01NDX/88YfizsMhISEwNjZGREQEmjdvjmnTpmHu3Lnw9fUF8O7O81evXsXvv/8OPz8/xbyGDh2Kjh07AgCWLFmCvXv3YsWKFRgzZkyR1kNNTQ3Vq1fP0TuULT4+HnXr1oWrqysAwNbWVjFu7dq1SEtLw6pVq6CnpwcAWLhwIdq1a4eZM2cqHvOjp6eHP/74A1paWgCAZcuWITMzEytXroSuri5q1qyJ+/fvY9CgQYp5L1myBPXq1VM8KxEAVq5cCRsbG9y4cUPRw1O1alXMmjWrSOtcGtgzQ0REktCxY0c8fPgQ27dvR4sWLRAREYF69eohNDQ01/bnzp3DrVu3YGBgoOjZMTU1xevXrxEbG4vHjx/j3r176Nu3r2K8vr4+pk+fjtjYWKV5NWrUSPFvDQ0NuLq6IiYm5qPWI7+HJQ8aNAjh4eFwcXHBmDFjEBUVpRgXExODOnXqKIIM8O6xQFlZWUqPBqpdu7YiyLw/3fs3L3x/fYB32+rIkSNK26FGjRoAoLQtskNWWcOeGSIikgxtbW34+PjAx8cHkyZNQr9+/TB58mT4+/vnaJuVlYX69etj7dq1OcaVK1cOr1+/BvDuUJObm5vS+MLcjfZjnjOVmZmJmzdvokGDBrmOb9WqFe7evYtdu3bh4MGDaNq0KYYMGYI5c+bkG4LeH/5+2AHehaeCZGVlKXp4PvT+c5M+nHdZwZ4ZIiKSLCcnJ7x8+TLXcfXq1cPNmzdhYWGBqlWrKr2MjIxgaWmJChUq4Pbt2znG29nZKc3r1KlTin+/ffsW586dU/RcFEVYWBiePXumOGSVm3LlysHf3x9r1qzBggULFM8rdHJyQnR0tNL6njhxQnHoKi9OTk64ePEi0tLScl0f4N22unLlCmxtbXNsi7IaYN7HMENERGXekydP0KRJE6xZswaXLl1CXFwc/vrrL8yaNQsdOnTIdZoePXrA3NwcHTp0wLFjxxAXF4fIyEiMGDEC9+/fBwAEBgYiODgYv/zyC27cuIHLly8jJCQE8+bNU5rXokWLsGXLFly7dg1DhgzBs2fP0KdPn3xrfvXqFRITE3H//n38/fffGDt2LAYOHIhBgwbB29s712kmTZqEbdu24datW7hy5Qp27twJR0dHxfpoa2vDz88P//zzD44cOYJhw4ahV69eivNlctO9e3eoqamhb9++uHr1Knbv3o05c+YotRkyZAiePn2Kbt264fTp07h9+zb279+PPn36IDMzM9/1LAt4mImIiMo8fX19uLm5Yf78+YiNjcWbN29gY2OD/v37Y/z48blOo6uri6NHj2Ls2LHw9fXF8+fPUaFCBTRt2lTxrJ9+/fpBV1cXs2fPxpgxY6Cnp4fatWsjICBAaV4zZszAzJkzceHCBVSpUgXbtm1TXGWUl+XLl2P58uXQ0tKCmZkZ6tevjz///BNff/11ntNoaWlh3LhxuHPnDnR0dPC///0P4eHhivXZt28fRowYgQYNGkBXVxcdO3bMEbxy23Y7duzAwIEDUbduXTg5OWHmzJlKvUPly5fHiRMnMHbsWLRo0QLp6emoXLkyWrZsCTW1st/vwQdN/lfxaiYiKmGfw4Mm79y5Azs7O1y4cAEuLi6qLuezwwdNEhEREYFhhoiIiCSO58wQERHlwdbWtlCXNpNqsWeGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIjoM3Tnzh3IZDJER0erupQSx/vMEBFRqbP9cVepLevOjDZFnsbf3x/JycnYunVr8RdUSmxsbJCQkFDgM6Q+BwwzREREnyF1dXVYWVmpuoxSwcNMRERE+fDy8sLw4cMxZswYmJqawsrKCoGBgUptAgMDUalSJcjlcpQvXx7Dhw9XjHv27Bm+/fZbmJiYQFdXF61atcLNmzcV40NDQ2FsbIydO3fCwcEBurq66NSpE16+fImwsDDY2trCxMQEw4YNQ2ZmpmI6W1tbBAUFoU+fPjAwMEClSpWwbNkyxfgPDzNlZmaib9++sLOzg46ODhwcHPDLL7+UzEYrZQwzREREBQgLC4Oenh7+/vtvzJo1C1OnTsWBAwcAABs3bsT8+fPx+++/4+bNm9i6dStq166tmNbf3x9nz57F9u3bcfLkSQgh0Lp1a7x580bR5tWrV/j1118RHh6OvXv3IiIiAr6+vti9ezd2796N1atXY9myZdi4caNSXXPnzoWrqysuXLiAwYMHY9CgQbh27Vqu65CVlYWKFStiw4YNuHr1KiZNmoTx48djw4YNJbDFShcPMxERERXA2dkZkydPBgBUq1YNCxcuxKFDh+Dj44P4+HhYWVmhWbNm0NTURKVKldCwYUMAwM2bN7F9+3acOHEC7u7uAIC1a9fCxsYGW7duRefOnQEAb968wZIlS1ClShUAQKdOnbB69Wo8evQI+vr6cHJygre3N44cOYKuXbsq6mrdujUGDx4MABg7dizmz5+PiIgI1KhRI8c6aGpqYsqUKYr3dnZ2iIqKwoYNG9ClS5cS2Gqlhz0zREREBXB2dlZ6b21tjaSkJABA586dkZaWBnt7e/Tv3x9btmzB27dvAQAxMTHQ0NCAm5ubYlozMzM4ODggJiZGMUxXV1cRZADA0tIStra20NfXVxqWvczc6pLJZLCyssrR5n1Lly6Fq6srypUrB319fSxfvhzx8fFF2RRlEsMMERFRATQ1NZXey2QyZGVlAXh31dD169exaNEi6OjoYPDgwWjcuDHevHmT5xO3hRCQyWT5zj+/ZRamrg9t2LABI0eORJ8+fbB//35ER0ejd+/eyMjIyGfNpYGHmYiIiD6Rjo4O2rdvj/bt22PIkCGoUaMGLl++DCcnJ7x9+xZ///234jDTkydPcOPGDTg6OpZqjceOHYO7u7visBQAxMbGlmoNJYVhhoiI6BOEhoYiMzMTbm5u0NXVxerVq6Gjo4PKlSvDzMwMHTp0QP/+/fH777/DwMAAP/74IypUqIAOHTqUap1Vq1bFqlWrsG/fPtjZ2WH16tU4c+YM7OzsSrWOksDDTERERJ/A2NgYy5cvh4eHB5ydnXHo0CHs2LEDZmZmAICQkBDUr18fbdu2RaNGjSCEwO7du3McIippAwcOhK+vL7p27Qo3Nzc8efJEqZdGymQirwN6n4nU1FQYGRkhJSUFhoaGqi6n7Ag0KsVlpZTesoiozHj9+jXi4uJgZ2cHbW1tVZdDZVB++0hRfr/ZM0NERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERFQGeXl5ISAg4D+z3E/BB00SEVHpK8OPVPH390dYWBiCg4Px448/KoZv3boVX3/9NT7lKUChoaHo3bs3AEBNTQ2GhoaoXr062rRpgxEjRsDI6P9vl82bN5f685ukij0zREREH9DW1sbMmTPx7NmzYp+3oaEhEhIScP/+fURFReG7777DqlWr4OLigocPHyramZqawsDAoNiXDwBCCLx9+7ZE5p2ZmYmsrKwSmXdeGGaIiIg+0KxZM1hZWSE4ODjfdps2bULNmjUhl8tha2uLuXPnFjhvmUwGKysrWFtbw9HREX379kVUVBRevHiBMWPGKNp9eLhn8eLFqFatGrS1tWFpaYlOnTopxqWnp2P48OGwsLCAtrY2vvzyS5w5c0YxPiIiAjKZDPv27YOrqyvkcjmOHTuGly9f4ttvv4W+vj6sra1zrT8jIwNjxoxBhQoVoKenBzc3N0RERCjGh4aGwtjYGDt37oSTkxPkcjnu3r1b4HYoTgwzREREH1BXV0dQUBB+++033L9/P9c2586dQ5cuXfDNN9/g8uXLCAwMxMSJExEaGlrk5VlYWKBHjx7Yvn07MjMzc4w/e/Yshg8fjqlTp+L69evYu3cvGjdurBg/ZswYbNq0CWFhYTh//jyqVq2KFi1a4OnTp0rzGTNmDIKDgxETEwNnZ2f88MMPOHLkCLZs2YL9+/cjIiIC586dU5qmd+/eOHHiBMLDw3Hp0iV07twZLVu2xM2bNxVtXr16heDgYPzxxx+4cuUKLCwsirwNPgXPmSEiIsrF119/DRcXF0yePBkrVqzIMX7evHlo2rQpJk6cCACoXr06rl69itmzZ8Pf37/Iy6tRowaeP3+OJ0+e5AgD8fHx0NPTQ9u2bWFgYIDKlSujbt26AICXL19iyZIlCA0NRatWrQAAy5cvx4EDB7BixQr88MMPivlMnToVPj4+AIAXL15gxYoVWLVqlWJYWFgYKlasqGgfGxuL9evX4/79+yhfvjwAYPTo0di7dy9CQkIQFBQEAHjz5g0WL16MOnXqFHm9iwN7ZoiIiPIwc+ZMhIWF4erVqznGxcTEwMPDQ2mYh4cHbt68mWvvSkGyTyyWyWQ5xvn4+KBy5cqwt7dHr169sHbtWrx69QrAu8Dx5s0bpVo0NTXRsGFDxMTEKM3H1dVV8e/Y2FhkZGSgUaNGimGmpqZwcHBQvD9//jyEEKhevTr09fUVr8jISMTGxiraaWlpwdnZucjrXFxUGmYCAwMhk8mUXlZWVorxQggEBgaifPny0NHRgZeXF65cuaLCiomI6L+kcePGaNGiBcaPH59jnBAiR/D4lCudYmJiYGhoCDMzsxzjDAwMcP78eaxfvx7W1taYNGkS6tSpg+Tk5DxDUG716enpFanWrKwsqKur49y5c4iOjla8YmJi8Msvvyja6ejo5BrCSovKe2Zq1qyJhIQExevy5cuKcbNmzcK8efOwcOFCnDlzBlZWVvDx8cHz589VWDEREf2XzJgxAzt27EBUVJTScCcnJxw/flxpWFRUFKpXrw51dfUiLSMpKQnr1q3DV199BTW13H+aNTQ00KxZM8yaNQuXLl3CnTt3cPjwYVStWhVaWlpKtbx58wZnz56Fo6NjnsusWrUqNDU1cerUKcWwZ8+e4caNG4r3devWRWZmJpKSklC1alWl1/udD6qm8nNmNDQ0ct0gQggsWLAAEyZMgK+vL4B3x/IsLS2xbt06DBgwoLRLJSKi/6DatWujR48e+O2335SGf//992jQoAGmTZuGrl274uTJk1i4cCEWL16c7/yEEEhMTIQQAsnJyTh58iSCgoJgZGSEGTNm5DrNzp07cfv2bTRu3BgmJibYvXs3srKy4ODgAD09PQwaNAg//PADTE1NUalSJcyaNQuvXr1C375986xDX18fffv2xQ8//AAzMzNYWlpiwoQJSmGqevXq6NGjB7799lvMnTsXdevWxb///ovDhw+jdu3aaN26dRG2ZMlReZi5efMmypcvD7lcDjc3NwQFBcHe3h5xcXFITExE8+bNFW3lcjk8PT0RFRWVZ5hJT09Henq64n1qamqJrwMREX3epk2bhg0bNigNq1evHjZs2IBJkyZh2rRpsLa2xtSpUws8+Tc1NRXW1taQyWQwNDSEg4MD/Pz8MGLECBgaGuY6jbGxMTZv3ozAwEC8fv0a1apVw/r161GzZk0A73qPsrKy0KtXLzx//hyurq7Yt28fTExM8q1l9uzZePHiBdq3bw8DAwN8//33SElRvslgSEgIpk+fju+//x4PHjyAmZkZGjVqVGaCDADIxKcc4PtEe/bswatXr1C9enU8evQI06dPx7Vr13DlyhVcv34dHh4eePDggeIMagD47rvvcPfuXezbty/XeQYGBmLKlCk5hqekpOS5k/wnleG7bxLR5+H169eIi4uDnZ0dtLW1VV0OlUH57SOpqakwMjIq1O+3Ss+ZadWqFTp27IjatWujWbNm2LVrF4B3h5OyFeaEpveNGzcOKSkpite9e/dKpngiIiIqE1R+AvD79PT0ULt2bdy8eVNxHk1iYqJSm6SkJFhaWuY5D7lcDkNDQ6UXERERfb7KVJhJT09HTEwMrK2tYWdnBysrKxw4cEAxPiMjA5GRkXB3d1dhlURERFSWqPQE4NGjR6Ndu3aoVKkSkpKSMH36dKSmpsLPzw8ymQwBAQEICgpCtWrVUK1aNQQFBUFXVxfdu3dXZdlERERUhqg0zNy/fx/dunXDv//+i3LlyuGLL77AqVOnULlyZQDvniGRlpaGwYMH49mzZ3Bzc8P+/ftL7CmiREREJD0qDTPh4eH5jpfJZAgMDERgYGDpFERERESSU6bOmSEiIiIqKoYZIiIikjSGGSIiIpI0hhkiIqIikslk2Lp1q6rLoP+j8mczERHRf0/tsNqltqzLfpeL1D4pKQkTJ07Enj178OjRI5iYmKBOnToIDAxEo0aNSqjKT7Nu3Tr06tUL/fv3x9KlS1VdTqljzwwREdF7OnbsiIsXLyIsLAw3btzA9u3b4eXlhadPn6q6tDytXLkSY8aMQXh4OF69eqXqckodwwwREdH/SU5OxvHjxzFz5kx4e3ujcuXKaNiwIcaNG4c2bdrkOd2DBw/QtWtXmJiYwMzMDB06dMCdO3eU2oSEhMDR0RHa2tqoUaMGFi9erBh3584dyGQyhIeHw93dHdra2qhZsyYiIiIKrPnOnTuIiorCjz/+iBo1amDjxo1K40NDQ2FsbIytW7eievXq0NbWho+Pj9KzCwMDA+Hi4oLVq1fD1tYWRkZG+Oabb/D8+XNFGyEEZs2aBXt7e+jo6KBOnTpKy8rMzETfvn1hZ2cHHR0dODg44Jdffimw/uLAMENERPR/9PX1oa+vj61btyI9Pb1Q07x69Qre3t7Q19fH0aNHcfz4cejr66Nly5bIyMgAACxfvhwTJkzAzz//jJiYGAQFBWHixIlKD1YGgB9++AHff/89Lly4AHd3d7Rv3x5PnjzJd/krV65EmzZtYGRkhJ49e2LFihW51vjzzz8jLCwMJ06cQGpqKr755hulNrGxsdi6dSt27tyJnTt3IjIyEjNmzFCM/+mnnxASEoIlS5bgypUrGDlyJHr27InIyEgAQFZWFipWrIgNGzbg6tWrmDRpEsaPH48NGzYUajt+CoYZIiKi/6OhoYHQ0FCEhYXB2NgYHh4eGD9+PC5dupTnNOHh4VBTU8Mff/yB2rVrw9HRESEhIYiPj1f0rEybNg1z586Fr68v7Ozs4Ovri5EjR+L3339XmtfQoUPRsWNHODo6YsmSJTAyMso1nGTLyspCaGgoevbsCQD45ptvcPLkSdy6dUup3Zs3b7Bw4UI0atQI9evXR1hYGKKionD69Okc86pVqxb+97//oVevXjh06BAA4OXLl5g3bx5WrlyJFi1awN7eHv7+/ujZs6diHTQ1NTFlyhQ0aNAAdnZ26NGjB/z9/RlmiIiISlvHjh3x8OFDbN++HS1atEBERATq1auH0NDQXNufO3cOt27dgoGBgaJnx9TUFK9fv0ZsbCweP36Me/fuoW/fvorx+vr6mD59OmJjY5Xm9f4JxhoaGnB1dUVMTEyete7fvx8vX75Eq1atAADm5uZo3rw5Vq5cqdQue17ZatSoAWNjY6V529raKj0uyNraGklJSQCAq1ev4vXr1/Dx8VFah1WrVimtw9KlS+Hq6opy5cpBX18fy5cvR3x8fJ71FxdezURERPSB7PNKfHx8MGnSJPTr1w+TJ0+Gv79/jrZZWVmoX78+1q5dm2NcuXLl8Pr1awDvDjW5ubkpjVdXVy+wFplMlue4lStX4unTp9DV1VWq58KFC5g2bZrS/HObz/vDNDU1c4zLyspSzBMAdu3ahQoVKii1k8vlAIANGzZg5MiRmDt3Lho1agQDAwPMnj0bf//9d4Hr+KkYZoiIiArg5OSU531l6tWrhz///BMWFhYwNDTMMd7IyAgVKlTA7du30aNHj3yXc+rUKTRu3BgA8PbtW5w7dw5Dhw7Nte2TJ0+wbds2hIeHo2bNmorhWVlZ+N///oc9e/agbdu2inmdPXsWDRs2BABcv34dycnJqFGjRoHrDrxbf7lcjvj4eHh6euba5tixY3B3d8fgwYMVwz7seSopDDNERET/58mTJ+jcuTP69OkDZ2dnGBgY4OzZs5g1axY6dOiQ6zQ9evTA7Nmz0aFDB0ydOhUVK1ZEfHw8Nm/ejB9++AEVK1ZEYGAghg8fDkNDQ7Rq1Qrp6ek4e/Ysnj17hlGjRinmtWjRIlSrVg2Ojo6YP38+nj17hj59+uS63NWrV8PMzAydO3eGmpryWSNt27bFihUrFGFGU1MTw4YNw6+//gpNTU0MHToUX3zxhSLcFMTAwACjR4/GyJEjkZWVhS+//BKpqamIioqCvr4+/Pz8ULVqVaxatQr79u2DnZ0dVq9ejTNnzsDOzq5Qy/gUDDNERFTqinoju9Kir68PNzc3zJ8/H7GxsXjz5g1sbGzQv39/jB8/PtdpdHV1cfToUYwdOxa+vr54/vw5KlSogKZNmyp6avr16wddXV3Mnj0bY8aMgZ6eHmrXro2AgAClec2YMQMzZ87EhQsXUKVKFWzbtg3m5ua5LnflypX4+uuvcwQZ4N15P127dsWjR48UNY4dOxbdu3fH/fv38eWXX+Y4r6Yg06ZNg4WFBYKDg3H79m0YGxujXr16iu0ycOBAREdHo2vXrpDJZOjWrRsGDx6MPXv2FGk5H0MmhBAlvhQVSk1NhZGREVJSUnLt/vvPCjQqxWWllN6yiKjMeP36NeLi4mBnZwdtbW1Vl1Om3blzB3Z2drhw4QJcXFyKdd6hoaEICAhAcnJysc63OOS3jxTl95tXMxEREZGkMcwQERGRpDHMEBERqZitrS2EEMV+iAkA/P39y+QhpuLEMENERESSxjBDREQl6jO/zoQ+QXHtGwwzRERUIrLvKPvq1SsVV0JlVfa+8eHdh4uK95khIqISoa6uDmNjY8XzfXR1dfO9NT/9dwgh8OrVKyQlJcHY2LhQj3XID8MMERGVGCsrKwBQBBqi9xkbGyv2kU/BMENERCVGJpPB2toaFhYWePPmjarLoTJEU1Pzk3tksjHMEBFRiVNXVy+2Hy6iD/EEYCIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpK0MhNmgoODIZPJEBAQoBgmhEBgYCDKly8PHR0deHl54cqVK6orkoiIiMqcMhFmzpw5g2XLlsHZ2Vlp+KxZszBv3jwsXLgQZ86cgZWVFXx8fPD8+XMVVUpERERljcrDzIsXL9CjRw8sX74cJiYmiuFCCCxYsAATJkyAr68vatWqhbCwMLx69Qrr1q1TYcVERERUlqg8zAwZMgRt2rRBs2bNlIbHxcUhMTERzZs3VwyTy+Xw9PREVFRUnvNLT09Hamqq0ouIiIg+XxqqXHh4eDjOnz+PM2fO5BiXmJgIALC0tFQabmlpibt37+Y5z+DgYEyZMqV4CyUiIqIyS2U9M/fu3cOIESOwZs0aaGtr59lOJpMpvRdC5Bj2vnHjxiElJUXxunfvXrHVTERERGWPynpmzp07h6SkJNSvX18xLDMzE0ePHsXChQtx/fp1AO96aKytrRVtkpKScvTWvE8ul0Mul5dc4URERFSmqKxnpmnTprh8+TKio6MVL1dXV/To0QPR0dGwt7eHlZUVDhw4oJgmIyMDkZGRcHd3V1XZREREVMaorGfGwMAAtWrVUhqmp6cHMzMzxfCAgAAEBQWhWrVqqFatGoKCgqCrq4vu3buromQiIiIqg1R6AnBBxowZg7S0NAwePBjPnj2Dm5sb9u/fDwMDA1WXRkRERGWETAghVF1ESUpNTYWRkRFSUlJgaGio6nLKjkCjUlxWSukti4iIPgtF+f1W+X1miIiIiD4FwwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSdpHhRl7e3s8efIkx/Dk5GTY29t/clFEREREhfVRYebOnTvIzMzMMTw9PR0PHjz45KKIiIiICkujKI23b9+u+Pe+fftgZGSkeJ+ZmYlDhw7B1ta22IojIiIiKkiRwsxXX30FAJDJZPDz81Map6mpCVtbW8ydO7fYiiMiIiIqSJHCTFZWFgDAzs4OZ86cgbm5eYkURURERFRYRQoz2eLi4oq7DiIiIqKP8lFhBgAOHTqEQ4cOISkpSdFjk23lypWfXBgRERFRYXxUmJkyZQqmTp0KV1dXWFtbQyaTFXddRERERIXyUWFm6dKlCA0NRa9evYq7HiIiIqIi+aj7zGRkZMDd3b24ayEiIiIqso8KM/369cO6deuKuxYiIiKiIvuow0yvX7/GsmXLcPDgQTg7O0NTU1Np/Lx584qlOCIiIqKCfFSYuXTpElxcXAAA//zzj9I4ngxMREREpemjwsyRI0eKuw4iIiKij/JR58wQERERlRUf1TPj7e2d7+Gkw4cPf3RBREREREXxUT0zLi4uqFOnjuLl5OSEjIwMnD9/HrVr1y70fJYsWQJnZ2cYGhrC0NAQjRo1wp49exTjhRAIDAxE+fLloaOjAy8vL1y5cuVjSiYiIqLP1Ef1zMyfPz/X4YGBgXjx4kWh51OxYkXMmDEDVatWBQCEhYWhQ4cOuHDhAmrWrIlZs2Zh3rx5CA0NRfXq1TF9+nT4+Pjg+vXrMDAw+JjSiYiI6DMjE0KI4prZrVu30LBhQzx9+vSj52FqaorZs2ejT58+KF++PAICAjB27FgAQHp6OiwtLTFz5kwMGDCgUPNLTU2FkZERUlJSYGho+NF1fXYCjUpxWSmltywiIvosFOX3u1hPAD558iS0tbU/atrMzEyEh4fj5cuXaNSoEeLi4pCYmIjmzZsr2sjlcnh6eiIqKqq4SiYiIiKJ+6jDTL6+vkrvhRBISEjA2bNnMXHixCLN6/Lly2jUqBFev34NfX19bNmyBU5OTorAYmlpqdTe0tISd+/ezXN+6enpSE9PV7xPTU0tUj1EREQkLR8VZoyMlA9RqKmpwcHBAVOnTlXqSSkMBwcHREdHIzk5GZs2bYKfnx8iIyMV4z+8akoIke+VVMHBwZgyZUqRaiAiIiLpKtZzZopDs2bNUKVKFYwdOxZVqlTB+fPnUbduXcX4Dh06wNjYGGFhYblOn1vPjI2NDc+Z+RDPmSEiojKsKOfMfFTPTLZz584hJiYGMpkMTk5OSqHjYwkhkJ6eDjs7O1hZWeHAgQOK+WZkZCAyMhIzZ87Mc3q5XA65XP7JdRAREZE0fFSYSUpKwjfffIOIiAgYGxtDCIGUlBR4e3sjPDwc5cqVK9R8xo8fj1atWsHGxgbPnz9HeHg4IiIisHfvXshkMgQEBCAoKAjVqlVDtWrVEBQUBF1dXXTv3v1jyiYiIqLP0EeFmWHDhiE1NRVXrlyBo6MjAODq1avw8/PD8OHDsX79+kLN59GjR+jVqxcSEhJgZGQEZ2dn7N27Fz4+PgCAMWPGIC0tDYMHD8azZ8/g5uaG/fv38x4zREREpPBR58wYGRnh4MGDaNCggdLw06dPo3nz5khOTi6u+j4Z7zOTB54zQ0REZViJ32cmKysLmpqaOYZramoiKyvrY2ZJRERE9FE+Ksw0adIEI0aMwMOHDxXDHjx4gJEjR6Jp06bFVhwRERFRQT4qzCxcuBDPnz+Hra0tqlSpgqpVq8LOzg7Pnz/Hb7/9Vtw1EhEREeXpo04AtrGxwfnz53HgwAFcu3YNQgg4OTmhWbNmxV0fERERUb6K1DNz+PBhODk5KR4R4OPjg2HDhmH48OFo0KABatasiWPHjpVIoURERES5KVKYWbBgAfr375/rWcVGRkYYMGAA5s2bV2zFERERERWkSGHm4sWLaNmyZZ7jmzdvjnPnzn1yUURERESFVaQw8+jRo1wvyc6moaGBx48ff3JRRERERIVVpDBToUIFXL58Oc/xly5dgrW19ScXRURERFRYRQozrVu3xqRJk/D69esc49LS0jB58mS0bdu22IojIiIiKkiRHmfw6NEj1KtXD+rq6hg6dCgcHBwgk8kQExODRYsWITMzE+fPn4elpWVJ1lwkfJxBHvg4AyIiKsOK8vtdpPvMWFpaIioqCoMGDcK4ceOQnYNkMhlatGiBxYsXl6kgQ0RERJ+/It80r3Llyti9ezeePXuGW7duQQiBatWqwcTEpCTqIyIiIsrXR90BGABMTExyPDWbiIiIqLR91LOZiIiIiMoKhhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSVhpng4GA0aNAABgYGsLCwwFdffYXr168rtRFCIDAwEOXLl4eOjg68vLxw5coVFVVMREREZY1Kw0xkZCSGDBmCU6dO4cCBA3j79i2aN2+Oly9fKtrMmjUL8+bNw8KFC3HmzBlYWVnBx8cHz58/V2HlREREVFbIhBBC1UVke/z4MSwsLBAZGYnGjRtDCIHy5csjICAAY8eOBQCkp6fD0tISM2fOxIABAwqcZ2pqKoyMjJCSkgJDQ8OSXgXpCDQqxWWllN6yiIjos1CU3+8ydc5MSsq7Hz1TU1MAQFxcHBITE9G8eXNFG7lcDk9PT0RFReU6j/T0dKSmpiq9iIiI6POloeoCsgkhMGrUKHz55ZeoVasWACAxMREAYGlpqdTW0tISd+/ezXU+wcHBmDJlSskWS0REVMxqh9Uu1eVd9rtcqssrSWWmZ2bo0KG4dOkS1q9fn2OcTCZTei+EyDEs27hx45CSkqJ43bt3r0TqJSIiorKhTPTMDBs2DNu3b8fRo0dRsWJFxXArKysA73porK2tFcOTkpJy9NZkk8vlkMvlJVswERERlRkq7ZkRQmDo0KHYvHkzDh8+DDs7O6XxdnZ2sLKywoEDBxTDMjIyEBkZCXd399Iul4iIiMoglfbMDBkyBOvWrcO2bdtgYGCgOEfGyMgIOjo6kMlkCAgIQFBQEKpVq4Zq1aohKCgIurq66N69uypLJyIiojJCpWFmyZIlAAAvLy+l4SEhIfD39wcAjBkzBmlpaRg8eDCePXsGNzc37N+/HwYGBqVcLREREZVFKg0zhbnFjUwmQ2BgIAIDA0u+ICIiIpKcMnM1ExEREdHHYJghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIknTUHUBRFR22f64q9SWdWdGm1JbFklXae6TAPdLqWDPDBEREUmaSsPM0aNH0a5dO5QvXx4ymQxbt25VGi+EQGBgIMqXLw8dHR14eXnhypUrqimWiIiIyiSVhpmXL1+iTp06WLhwYa7jZ82ahXnz5mHhwoU4c+YMrKys4OPjg+fPn5dypURERFRWqfScmVatWqFVq1a5jhNCYMGCBZgwYQJ8fX0BAGFhYbC0tMS6deswYMCA0iyViIiIyqgye85MXFwcEhMT0bx5c8UwuVwOT09PREVF5Tldeno6UlNTlV5ERET0+SqzYSYxMREAYGlpqTTc0tJSMS43wcHBMDIyUrxsbGxKtE4iIiJSrTIbZrLJZDKl90KIHMPeN27cOKSkpChe9+7dK+kSiYiISIXK7H1mrKysALzrobG2tlYMT0pKytFb8z65XA65XF7i9REREVHZUGZ7Zuzs7GBlZYUDBw4ohmVkZCAyMhLu7u4qrIyIiIjKEpX2zLx48QK3bt1SvI+Li0N0dDRMTU1RqVIlBAQEICgoCNWqVUO1atUQFBQEXV1ddO/eXYVVExERUVmi0jBz9uxZeHt7K96PGjUKAODn54fQ0FCMGTMGaWlpGDx4MJ49ewY3Nzfs378fBgYGqiqZiIiIyhiVhhkvLy8IIfIcL5PJEBgYiMDAwNIriohUI9ColJeXUrrLI6ISU2bPmSEiIiIqDIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSVPpuJ/j/bH3eV6vLuaJfq4oiIiEoMe2aIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNJ4NROVuNphtUt1eZf9Lpfq8ojoMxZoVHrLsqtUesv6zLBnhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjc9mIqL/pNJ8ZhifF0ZUstgzQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJImiTCzePFi2NnZQVtbG/Xr18exY8dUXRIRERGVEWU+zPz5558ICAjAhAkTcOHCBfzvf/9Dq1atEB8fr+rSiIiIqAwo82Fm3rx56Nu3L/r16wdHR0csWLAANjY2WLJkiapLIyIiojKgTIeZjIwMnDt3Ds2bN1ca3rx5c0RFRamoKiIiIipLNFRdQH7+/fdfZGZmwtLSUmm4paUlEhMTc50mPT0d6enpivcpKSkAgNTU1JIrtBhkpb8q1eWlykSpLSszLbPUlgWU/c9aSkpzvyzNfRIo3f2S+2Tx4d/K4lPW98vs+oQo+DMo02Emm0wmU3ovhMgxLFtwcDCmTJmSY7iNjU2J1CZVRqW6tJhSXZrRoNJdOyoepf+pld5+yX1Suvi3UvWeP38OI6P8ay3TYcbc3Bzq6uo5emGSkpJy9NZkGzduHEaNGqV4n5WVhadPn8LMzCzPAESFk5qaChsbG9y7dw+GhoaqLoeI+ySVOdwni48QAs+fP0f58uULbFumw4yWlhbq16+PAwcO4Ouvv1YMP3DgADp06JDrNHK5HHK5XGmYsbFxSZb5n2NoaMgvKZUp3CeprOE+WTwK6pHJVqbDDACMGjUKvXr1gqurKxo1aoRly5YhPj4eAwcOVHVpREREVAaU+TDTtWtXPHnyBFOnTkVCQgJq1aqF3bt3o3LlyqoujYiIiMqAMh9mAGDw4MEYPHiwqsv4z5PL5Zg8eXKOw3hEqsJ9ksoa7pOqIROFueaJiIiIqIwq0zfNIyIiIioIwwwRERFJGsMMERERSRrDDJWYiIgIyGQyJCcnF2tb+jx8+JmHhoaW6XtC3blzBzKZDNHR0cXallTrY/Y7f39/fPXVVyVSj5eXFwICAoq97eeOYUaiSvLLVBi2traQyWSQyWTQ0dFBjRo1MHv2bKVnaLi7uyMhIaHQNz2issPf3x8ymSzX+zkNHjwYMpkM/v7+xbrMrl274saNG8U6z8Ly8vJS7M9aWlqoUqUKxo0bp/ScNxsbG8XtIajsy+tv5IchurT2u9DQUMU+JpPJYGlpiXbt2uHKlStK7TZv3oxp06aVeD2fG4YZ+mjZ9/6JiYnB6NGjMX78eCxbtkwxXktLC1ZWVnyMhETZ2NggPDwcaWlpimGvX7/G+vXrUalSpWJfno6ODiwsLIp9voXVv39/JCQk4NatW5g1axYWLVqEwMBAxXh1dXVYWVlBQ0MSd7SgQirN/c7Q0BAJCQl4+PAhdu3ahZcvX6JNmzbIyMhQtDE1NYWBgUGp1PM5YZj5TEVGRqJhw4aQy+WwtrbGjz/+iLdv3wIAduzYAWNjY2RlZQEAoqOjIZPJ8MMPPyimHzBgALp165bvMgwMDGBlZQVbW1v069cPzs7O2L9/v2L8h/8Dunv3Ltq1awcTExPo6emhZs2a2L17d67zTktLQ5s2bfDFF1/g6dOnn7Ip6CPVq1cPlSpVwubNmxXDNm/eDBsbG9StW1eprRACs2bNgr29PXR0dFCnTh1s3LhRqc3u3btRvXp16OjowNvbG3fu3FEa/2F3f27/sw4ICICXl5fivZeXF4YNG4aAgACYmJjA0tISy5Ytw8uXL9G7d28YGBigSpUq2LNnT4Hrq6urCysrK1SqVAkdO3aEj4+P0v784aGjZ8+eoUePHihXrhx0dHRQrVo1hISE5DrvrKws9O/fH9WrV8fdu3cLrIVKT26HmaZPnw4LCwsYGBigX79++PHHH+Hi4pJj2jlz5sDa2hpmZmYYMmQI3rx5k++yZDIZrKysYG1tDVdXV4wcORJ3797F9evXFW0+PHS0ePFiVKtWDdra2rC0tESnTp3ynP/evXthZGSEVatWFWrdPycMM5+hBw8eoHXr1mjQoAEuXryIJUuWYMWKFZg+fToAoHHjxnj+/DkuXLgA4F3wMTc3R2RkpGIeERER8PT0LNTyhBCIiIhATEwMNDU182w3ZMgQpKen4+jRo7h8+TJmzpwJfX39HO1SUlLQvHlzZGRk4NChQzA1NS3K6lMx6t27t9IP9MqVK9GnT58c7X766SeEhIRgyZIluHLlCkaOHImePXsq9ql79+7B19cXrVu3RnR0tOIHojiEhYXB3Nwcp0+fxrBhwzBo0CB07twZ7u7uOH/+PFq0aIFevXrh1atXhZ7nxYsXceLEiXz354kTJ+Lq1avYs2cPYmJisGTJEpibm+dol5GRgS5duuDs2bM4fvw4715exq1duxY///wzZs6ciXPnzqFSpUpYsmRJjnZHjhxBbGwsjhw5grCwMISGhiI0NLTQy0lOTsa6desAIM/97OzZsxg+fDimTp2K69evY+/evWjcuHGubcPDw9GlSxesWrUK3377baHr+GwIkiQ/Pz/RoUOHXMeNHz9eODg4iKysLMWwRYsWCX19fZGZmSmEEKJevXpizpw5QgghvvrqK/Hzzz8LLS0tkZqaKhISEgQAERMTk+fyK1euLLS0tISenp7Q1NQUAIS2trY4ceKEos2RI0cEAPHs2TMhhBC1a9cWgYGBuc4vu+21a9dEnTp1hK+vr0hPTy/KJqFilL1/PX78WMjlchEXFyfu3LkjtLW1xePHj0WHDh2En5+fEEKIFy9eCG1tbREVFaU0j759+4pu3boJIYQYN26ccHR0VNonx44dq7R/hISECCMjoxw1vG/EiBHC09NT8d7T01N8+eWXivdv374Venp6olevXoph2fvzyZMn81xfT09PoampKfT09ISWlpYAINTU1MTGjRsVbeLi4gQAceHCBSGEEO3atRO9e/fOdX7ZbY8dOyaaNWsmPDw8RHJycp7Lp+Ln5+cn1NXVhZ6entJLW1s73/3Ozc1NDBkyRGleHh4eok6dOkrzrly5snj79q1iWOfOnUXXrl3zrCckJEQAEHp6ekJXV1cAEABE+/btldp5enqKESNGCCGE2LRpkzA0NBSpqam5zjO77aJFi4SRkZE4fPhwIbbM54k9M5+hmJgYNGrUSOlcFQ8PD7x48QL3798H8K4rMyIiAkIIHDt2DB06dECtWrVw/PhxHDlyBJaWlqhRo0a+y/nhhx8QHR2NyMhIeHt7Y8KECXB3d8+z/fDhwzF9+nR4eHhg8uTJuHTpUo42zZo1g729PTZs2AAtLa2P3AJUXMzNzdGmTRuEhYUhJCQEbdq0ydH7cPXqVbx+/Ro+Pj7Q19dXvFatWoXY2FgA7/bJL774QmmfbNSoUbHU6OzsrPi3uro6zMzMULt2bcUwS0tLAEBSUlK+8+nRoweio6Nx8uRJdOnSBX369EHHjh3zbD9o0CCEh4fDxcUFY8aMQVRUVI423bp1w4sXL7B//36eCK8C3t7eiI6OVnr98ccf+U5z/fp1NGzYUGnYh+8BoGbNmlBXV1e8t7a2LnAfMzAwQHR0NM6dO4elS5eiSpUqWLp0aZ7tfXx8ULlyZdjb26NXr15Yu3Ztjh7GTZs2ISAgAPv374e3t3e+y/+cMcx8hoQQOU66Ff93lVH2cC8vLxw7dgwXL16EmpoanJyc4OnpicjIyEIfYjI3N0fVqlXRqFEjbNq0CfPnz8fBgwfzbN+vXz/cvn0bvXr1wuXLl+Hq6orffvtNqU2bNm1w7NgxXL16tairTSWkT58+CA0NRVhYWK6HmLLPvdq1a5fSj8bVq1cV582Ij3hqipqaWo7pcjsn4cMueplMpjQse5/PrjMvRkZGqFq1KurVq4c1a9YgMjISK1asyLN9q1atcPfuXQQEBODhw4do2rQpRo8erdSmdevWuHTpEk6dOpXvsqlk6OnpoWrVqkqvChUqFDhdXn8/35fbflfQPqampoaqVauiRo0aGDBgAHr16oWuXbvm2d7AwADnz5/H+vXrYW1tjUmTJqFOnTpKt7BwcXFBuXLlEBIS8lHfs88Fw8xnyMnJCVFRUUo7dlRUFAwMDBRf5OzzZhYsWABPT0/IZDJ4enoiIiKiSOfLZDMxMcGwYcMwevTofL9QNjY2GDhwIDZv3ozvv/8ey5cvVxo/Y8YM+Pn5oWnTpgw0ZUTLli2RkZGBjIwMtGjRIsd4JycnyOVyxMfH5/jhsLGxUbT58Ae9oB/4cuXKISEhQWlYad23RVNTE+PHj8dPP/2U77k25cqVg7+/P9asWYMFCxYoXc0HvOu9mTFjBtq3b690ThqVXQ4ODjh9+rTSsLNnz5bIskaOHImLFy9iy5YtebbR0NBAs2bNMGvWLFy6dAl37tzB4cOHFeOrVKmCI0eOYNu2bRg2bFiJ1CkFDDMSlpKSkqMLNT4+HoMHD8a9e/cwbNgwXLt2Ddu2bcPkyZMxatQoqKm9+8iNjIzg4uKCNWvWKK4Oady4Mc6fP48bN24oXTFSWEOGDMH169exadOmXMcHBARg3759iIuLw/nz53H48GE4OjrmaDdnzhz06NEDTZo0wbVr14pcBxUvdXV1xMTEICYmRqlbPZuBgQFGjx6NkSNHIiwsDLGxsbhw4QIWLVqEsLAwAMDAgQMRGxuLUaNG4fr161i3bl2BJ0s2adIEZ8+exapVq3Dz5k1MnjwZ//zzT0msYq66d+8OmUyGxYsX5zp+0qRJ2LZtG27duoUrV65g586due7Pw4YNw/Tp09G2bVscP368pMumTzRs2DCsWLECYWFhuHnzJqZPn45Lly6VyC0mDA0N0a9fP0yePDnX/wTu3LkTv/76K6Kjo3H37l2sWrUKWVlZcHBwUGpXvXp1HDlyRHHI6b+IYUbCIiIiULduXaXXpEmTUKFCBezevRunT59GnTp1MHDgQPTt2xc//fST0vTe3t7IzMxUBBcTExM4OTmhXLlyuf5RLki5cuXQq1cvBAYG5trdmpmZiSFDhsDR0REtW7aEg4NDnj8U8+fPR5cuXdCkSROV3UiN/j9DQ0MYGhrmOX7atGmYNGkSgoOD4ejoiBYtWmDHjh2ws7MDAFSqVAmbNm3Cjh07UKdOHSxduhRBQUH5LrNFixaYOHEixowZgwYNGuD58+elepWGlpYWhg4dilmzZuHFixe5jh83bhycnZ3RuHFjqKurIzw8PNd5BQQEYMqUKWjdunWu59ZQ2dGjRw+MGzcOo0ePRr169RAXFwd/f39oa2uXyPJGjBiBmJgY/PXXXznGGRsbY/PmzWjSpAkcHR2xdOlSrF+/HjVr1szR1sHBAYcPH8b69evx/fffl0itZZlM/JcPshERERXAx8cHVlZWWL16tapLoTzwVpZERET/59WrV1i6dClatGgBdXV1rF+/HgcPHsSBAwdUXRrlgz0zRERE/yctLQ3t2rXD+fPnkZ6eDgcHB/z000/w9fVVdWmUD4YZIiIikjSeAExERESSxjBDREREksYwQ0RERJLGMENERESSxjBDRIUmk8mwdevWYm9LRPQpGGaICP7+/pDJZJDJZNDQ0EClSpUwaNAgPHv2TKldQkICWrVqVWJ1ZGRkYNasWahTpw50dXVhbm4ODw8PhISE5PqQydzcuXMHMpms1J7jRESqx5vmERGAdw+UDAkJwdu3b3H16lX06dMHycnJWL9+vaKNlZVViS0/+0GWFy9exLRp0+Dh4QFDQ0OcOnUKc+bMQd26deHi4lJiyy8pGRkZ0NLSUnUZRJ819swQEQBALpfDysoKFStWRPPmzdG1a1fs379fqc37h44yMjIwdOhQWFtbQ1tbG7a2tggODs5z/lOnToWlpWWePSYLFizA0aNHcejQIQwZMgQuLi6wt7dH9+7d8ffff6NatWoAgL179+LLL7+EsbExzMzM0LZtW8TGxirmk/08qLp160Imkyk9NDUkJASOjo7Q1tZGjRo1cjwbLCoqCi4uLtDW1oarqyu2bt2ao5cnMjISDRs2hFwuh7W1NX788Ue8fftWMd7LywtDhw7FqFGjYG5uDh8fH/Tp0wdt27ZVWtbbt29hZWWFlStX5rnNiKhw2DNDRDncvn0be/fuhaamZp5tfv31V2zfvh0bNmxApUqVcO/ePdy7dy9HOyEEAgICsHXrVhw/flwRSj60du1aNGvWDHXr1s0xTlNTU1HLy5cvMWrUKNSuXRsvX77EpEmT8PXXXyM6Ohpqamo4ffo0GjZsiIMHD6JmzZqKXpHly5dj8uTJWLhwIerWrYsLFy6gf//+0NPTg5+fH54/f4527dqhdevWWLduHe7evZvjCcQPHjxA69at4e/vj1WrVuHatWvo378/tLW1ERgYqGgXFhaGQYMG4cSJExBC4OnTp2jcuDESEhJgbW0NANi9ezdevHiBLl265PtZEFEhCCL6z/Pz8xPq6upCT09PaGtrCwACgJg3b55SOwBiy5YtQgghhg0bJpo0aSKysrJynScA8ddff4mePXuKGjVqiHv37uVbg46Ojhg+fHiRa09KShIAxOXLl4UQQsTFxQkA4sKFC0rtbGxsxLp165SGTZs2TTRq1EgIIcSSJUuEmZmZSEtLU4xfvny50rzGjx8vHBwclNZ50aJFQl9fX2RmZgohhPD09BQuLi456nRychIzZ85UvP/qq6+Ev79/kdeXiHLiYSYiAgB4e3sjOjoaf//9N4YNG4YWLVpg2LBhebb39/dHdHQ0HBwcMHz48ByHpABg5MiROHnyJI4dO4aKFSvmu3whBGQyWYF1xsbGonv37rC3t4ehoaHisFJ8fHye0zx+/Bj37t1D3759oa+vr3hNnz5dcYjq+vXrcHZ2hra2tmK6hg0bKs0nJiYGjRo1UqrTw8MDL168wP379xXDXF1dc9TQr18/hISEAACSkpKwa9cu9OnTp8D1JaKCMcwQEQBAT08PVatWhbOzM3799Vekp6djypQpebavV68e4uLiMG3aNKSlpaFLly7o1KmTUhsfHx88ePAA+/btK3D51atXR0xMTIHt2rVrhydPnmD58uX4+++/8ffffwN4dw5PXrKysgC8O9QUHR2teP3zzz84deoUgNzDlPjg0XX5tXl/uJ6eXo4avv32W9y+fRsnT57EmjVrYGtri//9738Fri8RFYxhhohyNXnyZMyZMwcPHz7Ms42hoSG6du2K5cuX488//8SmTZvw9OlTxfj27dtj3bp16NevH8LDw/NdXvfu3XHw4EFcuHAhx7i3b9/i5cuXePLkCWJiYvDTTz+hadOmcHR0zHH5ePY5MpmZmYphlpaWqFChAm7fvo2qVasqvbJ7dmrUqIFLly4hPT1dMd3Zs2eV5u3k5ISoqCilkBMVFQUDAwNUqFAh3/UzMzPDV199hZCQEISEhKB37975tieiwmOYIaJceXl5oWbNmggKCsp1/Pz58xEeHo5r167hxo0b+Ouvv2BlZQVjY2Oldl9//TVWr16N3r17Y+PGjXkuLyAgAB4eHmjatCkWLVqEixcv4vbt29iwYQPc3Nxw8+ZNmJiYwMzMDMuWLcOtW7dw+PBhjBo1Smk+FhYW0NHRwd69e/Ho0SOkpKQAAAIDAxEcHIxffvkFN27cwOXLlxESEoJ58+YBeBemsrKy8N133yEmJgb79u3DnDlzAPz/XpfBgwfj3r17GDZsGK5du4Zt27Zh8uTJGDVqFNTUCv5z2q9fP4SFhSEmJgZ+fn4FtieiQlLlCTtEVDb4+fmJDh065Bi+du1aoaWlJeLj44UQyicAL1u2TLi4uAg9PT1haGgomjZtKs6fP6+Y9v22Qgjx559/Cm1tbbFp06Y863j9+rUIDg4WtWvXFtra2sLU1FR4eHiI0NBQ8ebNGyGEEAcOHBCOjo5CLpcLZ2dnERERkWNZy5cvFzY2NkJNTU14enoqrY+Li4vQ0tISJiYmonHjxmLz5s2K8SdOnBDOzs5CS0tL1K9fX6xbt04AENeuXVO0iYiIEA0aNBBaWlrCyspKjB07VlGbEO9OAB4xYkSu65eVlSUqV64sWrdunec2IKKikwnxwUFhIiIC8O5y8d69eyMlJQU6OjqfPL9Xr16hfPnyWLlyJXx9fYuhQiICeJ8ZIiKFVatWwd7eHhUqVMDFixcxduxYdOnS5ZODTFZWFhITEzF37lwYGRmhffv2xVQxEQEMM0REComJiZg0aRISExNhbW2Nzp074+eff/7k+cbHx8POzg4VK1ZEaGgoNDT4p5eoOPEwExEREUkar2YiIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJ+39JshaikbpOdgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "H3c: High-Risk Population Concentration\n", + "High-risk population: 37 (28.0% of total)\n", + "Disorder cases in high-risk: 31 (83.8%)\n" + ] + } + ], + "source": [ + "### H3: Combined Risk Factor Analysis\n", + "\n", + "# Create risk score\n", + "sleep_data_clean['risk_score'] = 0\n", + "sleep_data_clean['risk_score'] += (sleep_data_clean['bmi_category'] == 'Obese').astype(int) * 3\n", + "sleep_data_clean['risk_score'] += (sleep_data_clean['bmi_category'] == 'Overweight').astype(int) * 2\n", + "sleep_data_clean['risk_score'] += (sleep_data_clean['high_bp']).astype(int) * 2\n", + "sleep_data_clean['risk_score'] += (sleep_data_clean['age'] > 45).astype(int) * 1\n", + "sleep_data_clean['risk_score'] += (sleep_data_clean['high_hr']).astype(int) * 1\n", + "\n", + "# Risk categories\n", + "sleep_data_clean['risk_category'] = pd.cut(sleep_data_clean['risk_score'], \n", + " bins=[-1, 1, 3, 10], \n", + " labels=['Low Risk', 'Medium Risk', 'High Risk'])\n", + "\n", + "# H3a & H3b: Disorder rate by risk category\n", + "print(\"H3: Disorder Prevalence by Risk Category\")\n", + "risk_analysis = pd.crosstab(sleep_data_clean['risk_category'], \n", + " sleep_data_clean['sleep_disorder'], \n", + " normalize='index') * 100\n", + "print(risk_analysis.round(2))\n", + "\n", + "# Visualization\n", + "plt.figure(figsize=(12, 6))\n", + "pd.crosstab(sleep_data_clean['risk_category'], sleep_data_clean['sleep_disorder']).plot(kind='bar', stacked=False)\n", + "plt.title('H3: Sleep Disorder Distribution by Risk Category')\n", + "plt.xlabel('Risk Category')\n", + "plt.ylabel('Count')\n", + "plt.legend(title='Sleep Disorder')\n", + "plt.xticks(rotation=0)\n", + "plt.show()\n", + "\n", + "# H3c: High-risk population analysis\n", + "print(\"\\nH3c: High-Risk Population Concentration\")\n", + "total_pop = len(sleep_data_clean)\n", + "high_risk_pop = (sleep_data_clean['risk_category'] == 'High Risk').sum()\n", + "high_risk_disorders = sleep_data_clean[sleep_data_clean['risk_category'] == 'High Risk']['sleep_disorder'] != 'No Disorder'\n", + "\n", + "print(f\"High-risk population: {high_risk_pop} ({high_risk_pop/total_pop*100:.1f}% of total)\")\n", + "print(f\"Disorder cases in high-risk: {high_risk_disorders.sum()} ({high_risk_disorders.sum()/high_risk_pop*100:.1f}%)\")" + ] + }, + { + "cell_type": "markdown", + "id": "f6909537-84ad-4dd6-af0c-c250660557f4", + "metadata": {}, + "source": [ + "### **H3: Analysis - Combined Risk Factor Model for Targeted Intervention**\n", + "\n", + "#### **Key Findings:**\n", + "\n", + "**1. Progressive Risk Stratification:**\n", + "\n", + "| Risk Category | % of Population | No Disorder | Sleep Disorder Rate | Insomnia | Sleep Apnea |\n", + "|--------------|----------------|-------------|---------------------|----------|-------------|\n", + "| **Low Risk** | 55% (n=71) | 81.69% | **18.31%** | 9.86% | 8.45% |\n", + "| **Medium Risk** | 17% (n=24) | 37.50% | **62.50%** | 45.83% | 16.67% |\n", + "| **High Risk** | 28% (n=37) | 16.22% | **83.78%** | 29.73% | 54.05% |\n", + "\n", + "**2. Risk Score Validation:**\n", + "\n", + "The combined risk model demonstrates **clear dose-response relationship:**\n", + "- Low → Medium Risk: **3.4x increase** in disorder prevalence (18% → 62%)\n", + "- Medium → High Risk: **1.3x increase** in disorder prevalence (62% → 84%)\n", + "- Low → High Risk: **4.6x increase** in disorder prevalence (18% → 84%)\n", + "\n", + "**3. Population Concentration Analysis (H3c):**\n", + "\n", + "**Critical Finding:** High-risk group represents **28% of population** but accounts for **52.5% of all disorder cases** (31 of 59 total cases).\n", + "\n", + "- **Efficiency Metric:** Targeting 28% of population captures 53% of disorder burden\n", + "- **High-risk disorder rate:** 83.8% (31 of 37 individuals)\n", + "- **Resource optimization:** 3.6x higher yield compared to population-wide screening\n", + "\n", + "**4. Disorder Type by Risk Category (H3d):**\n", + "\n", + "- **High Risk → Sleep Apnea dominant:** 54% Sleep Apnea vs 30% Insomnia\n", + " - Driven by BMI + BP + age factors\n", + "- **Medium Risk → Insomnia dominant:** 46% Insomnia vs 17% Sleep Apnea\n", + " - Suggests stress/lifestyle factors more prominent\n", + "- **Low Risk → Balanced:** Similar rates (10% each)\n", + "\n", + "#### **Statistical Conclusion:**\n", + "\n", + "**H3 is STRONGLY VALIDATED**\n" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "1b9bf285-b8f1-4de0-886e-29045d0d56fb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "H3d: Testing Disorder-Specific Risk Factor Combinations\n", + "\n", + "============================================================\n", + "SLEEP APNEA RISK PROFILE (BMI + BP + Age>45)\n", + "============================================================\n", + "\n", + "Individuals matching profile: 23\n", + "Percentage of total population: 17.4%\n", + "\n", + "Disorder distribution in Sleep Apnea Risk Profile:\n", + "sleep_disorder\n", + "Sleep Apnea 16\n", + "No Disorder 5\n", + "Insomnia 2\n", + "Name: count, dtype: int64\n", + "\n", + "Percentages:\n", + "sleep_disorder\n", + "Sleep Apnea 69.57\n", + "No Disorder 21.74\n", + "Insomnia 8.70\n", + "Name: count, dtype: float64\n", + "\n", + "✓ Sleep Apnea rate in this profile: 69.6%\n", + "✓ Sleep Apnea rate in general population: 22.7%\n", + "✓ Risk elevation: 3.06x\n", + "\n", + "============================================================\n", + "INSOMNIA RISK PROFILE (High Stress + Age≤40)\n", + "============================================================\n", + "\n", + "Individuals matching profile: 21\n", + "Percentage of total population: 15.9%\n", + "\n", + "Disorder distribution in Insomnia Risk Profile:\n", + "sleep_disorder\n", + "No Disorder 8\n", + "Insomnia 7\n", + "Sleep Apnea 6\n", + "Name: count, dtype: int64\n", + "\n", + "Percentages:\n", + "sleep_disorder\n", + "No Disorder 38.10\n", + "Insomnia 33.33\n", + "Sleep Apnea 28.57\n", + "Name: count, dtype: float64\n", + "\n", + "✓ Insomnia rate in this profile: 33.3%\n", + "✓ Insomnia rate in general population: 22.0%\n", + "✓ Risk elevation: 1.52x\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "============================================================\n", + "CROSS-PROFILE COMPARISON\n", + "============================================================\n", + "\n", + "Disorder distribution by risk profile (%):\n", + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "disorder_profile \n", + "Apnea Profile 8.70 21.74 69.57\n", + "Insomnia Profile 33.33 38.10 28.57\n", + "No Specific Profile 22.73 68.18 9.09\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "### H3d: Disorder-Specific Risk Profiles\n", + "\n", + "# Create disorder-specific risk profiles\n", + "print(\"H3d: Testing Disorder-Specific Risk Factor Combinations\\n\")\n", + "\n", + "# Profile 1: Sleep Apnea Risk Profile\n", + "# Hypothesis: BMI + BP + Older age → Sleep Apnea\n", + "sleep_data_clean['apnea_risk_profile'] = (\n", + " ((sleep_data_clean['bmi_category'] == 'Obese') | (sleep_data_clean['bmi_category'] == 'Overweight')) &\n", + " (sleep_data_clean['high_bp'] == True) &\n", + " (sleep_data_clean['age'] > 45)\n", + ")\n", + "\n", + "# Profile 2: Insomnia Risk Profile \n", + "# Hypothesis: Stress + Younger age → Insomnia\n", + "sleep_data_clean['insomnia_risk_profile'] = (\n", + " (sleep_data_clean['stress_level'] >= 7) &\n", + " (sleep_data_clean['age'] <= 40)\n", + ")\n", + "\n", + "# Analysis: Sleep Apnea Profile\n", + "print(\"=\" * 60)\n", + "print(\"SLEEP APNEA RISK PROFILE (BMI + BP + Age>45)\")\n", + "print(\"=\" * 60)\n", + "\n", + "apnea_profile = sleep_data_clean[sleep_data_clean['apnea_risk_profile'] == True]\n", + "print(f\"\\nIndividuals matching profile: {len(apnea_profile)}\")\n", + "print(f\"Percentage of total population: {len(apnea_profile)/len(sleep_data_clean)*100:.1f}%\\n\")\n", + "\n", + "if len(apnea_profile) > 0:\n", + " apnea_profile_disorders = apnea_profile['sleep_disorder'].value_counts()\n", + " print(\"Disorder distribution in Sleep Apnea Risk Profile:\")\n", + " print(apnea_profile_disorders)\n", + " print(f\"\\nPercentages:\")\n", + " print((apnea_profile_disorders / len(apnea_profile) * 100).round(2))\n", + " \n", + " # Calculate specificity for Sleep Apnea\n", + " sleep_apnea_rate = (apnea_profile['sleep_disorder'] == 'Sleep Apnea').sum() / len(apnea_profile) * 100\n", + " print(f\"\\n✓ Sleep Apnea rate in this profile: {sleep_apnea_rate:.1f}%\")\n", + " \n", + " # Compare to general population\n", + " general_apnea_rate = (sleep_data_clean['sleep_disorder'] == 'Sleep Apnea').sum() / len(sleep_data_clean) * 100\n", + " print(f\"✓ Sleep Apnea rate in general population: {general_apnea_rate:.1f}%\")\n", + " print(f\"✓ Risk elevation: {sleep_apnea_rate/general_apnea_rate:.2f}x\")\n", + "\n", + "# Analysis: Insomnia Profile\n", + "print(\"\\n\" + \"=\" * 60)\n", + "print(\"INSOMNIA RISK PROFILE (High Stress + Age≤40)\")\n", + "print(\"=\" * 60)\n", + "\n", + "insomnia_profile = sleep_data_clean[sleep_data_clean['insomnia_risk_profile'] == True]\n", + "print(f\"\\nIndividuals matching profile: {len(insomnia_profile)}\")\n", + "print(f\"Percentage of total population: {len(insomnia_profile)/len(sleep_data_clean)*100:.1f}%\\n\")\n", + "\n", + "if len(insomnia_profile) > 0:\n", + " insomnia_profile_disorders = insomnia_profile['sleep_disorder'].value_counts()\n", + " print(\"Disorder distribution in Insomnia Risk Profile:\")\n", + " print(insomnia_profile_disorders)\n", + " print(f\"\\nPercentages:\")\n", + " print((insomnia_profile_disorders / len(insomnia_profile) * 100).round(2))\n", + " \n", + " # Calculate specificity for Insomnia\n", + " insomnia_rate = (insomnia_profile['sleep_disorder'] == 'Insomnia').sum() / len(insomnia_profile) * 100\n", + " print(f\"\\n✓ Insomnia rate in this profile: {insomnia_rate:.1f}%\")\n", + " \n", + " # Compare to general population\n", + " general_insomnia_rate = (sleep_data_clean['sleep_disorder'] == 'Insomnia').sum() / len(sleep_data_clean) * 100\n", + " print(f\"✓ Insomnia rate in general population: {general_insomnia_rate:.1f}%\")\n", + " print(f\"✓ Risk elevation: {insomnia_rate/general_insomnia_rate:.2f}x\")\n", + "\n", + "# Visualization\n", + "fig, axes = plt.subplots(1, 2, figsize=(14, 6))\n", + "\n", + "# Sleep Apnea Profile\n", + "if len(apnea_profile) > 0:\n", + " apnea_profile['sleep_disorder'].value_counts().plot(kind='bar', ax=axes[0], color=['#FF6B6B', '#4ECDC4', '#95E1D3'])\n", + " axes[0].set_title('H3d: Sleep Apnea Risk Profile\\n(BMI + BP + Age>45)', fontsize=12, fontweight='bold')\n", + " axes[0].set_xlabel('Sleep Disorder')\n", + " axes[0].set_ylabel('Count')\n", + " axes[0].tick_params(axis='x', rotation=45)\n", + "\n", + "# Insomnia Profile\n", + "if len(insomnia_profile) > 0:\n", + " insomnia_profile['sleep_disorder'].value_counts().plot(kind='bar', ax=axes[1], color=['#FF6B6B', '#4ECDC4', '#95E1D3'])\n", + " axes[1].set_title('H3d: Insomnia Risk Profile\\n(High Stress + Age≤40)', fontsize=12, fontweight='bold')\n", + " axes[1].set_xlabel('Sleep Disorder')\n", + " axes[1].set_ylabel('Count')\n", + " axes[1].tick_params(axis='x', rotation=45)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "# Cross-tabulation analysis\n", + "print(\"\\n\" + \"=\" * 60)\n", + "print(\"CROSS-PROFILE COMPARISON\")\n", + "print(\"=\" * 60)\n", + "\n", + "# Create profile categories\n", + "sleep_data_clean['disorder_profile'] = 'No Specific Profile'\n", + "sleep_data_clean.loc[sleep_data_clean['apnea_risk_profile'] == True, 'disorder_profile'] = 'Apnea Profile'\n", + "sleep_data_clean.loc[sleep_data_clean['insomnia_risk_profile'] == True, 'disorder_profile'] = 'Insomnia Profile'\n", + "\n", + "# Crosstab\n", + "profile_disorders = pd.crosstab(sleep_data_clean['disorder_profile'], \n", + " sleep_data_clean['sleep_disorder'], \n", + " normalize='index') * 100\n", + "\n", + "print(\"\\nDisorder distribution by risk profile (%):\")\n", + "print(profile_disorders.round(2))\n", + "\n", + "# Visualization: Stacked bar\n", + "profile_disorders.plot(kind='bar', stacked=False, figsize=(12, 6))\n", + "plt.title('H3d: Disorder Type by Specific Risk Profile', fontsize=14, fontweight='bold')\n", + "plt.xlabel('Risk Profile')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.legend(title='Sleep Disorder')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "ae39b048-6f15-4904-9fe1-3fc985768971", + "metadata": {}, + "source": [ + "H3d is PARTIALLY VALIDATED \n", + "\n", + "VALIDATED for Sleep Apnea:\n", + "\n", + "BMI + BP + Age>45 profile strongly predicts Sleep Apnea (69.6%, 3x elevation)\n", + "Clear disorder specificity with 8:1 ratio (Sleep Apnea vs Insomnia)\n", + "Clinically meaningful and actionable profile\n", + "\n", + "WEAKLY SUPPORTED for Insomnia:\n", + "\n", + "High Stress + Young Age shows modest elevation (1.52x)\n", + "38% still have no disorder - poor positive predictive value\n", + "Mixed disorder presentation (33% Insomnia, 29% Sleep Apnea, 38% None)\n", + "Profile lacks specificity for Insomnia diagnosis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "57478f1a-a551-4316-8b32-aa46e585332f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "eea7c84a-2aba-4039-8c33-d513241f756c", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "### **Executive Summary**\n", + "\n", + "This analysis successfully addressed the core business objective: **identifying high-risk individuals for sleep disorders to enable targeted preventive healthcare and optimize resource allocation.**\n", + "\n", + "Through systematic hypothesis testing across 132 individuals, we established that:\n", + "\n", + "1. **Individual risk factors vary significantly in predictive power**\n", + " - Strong predictors: BMI (obesity), blood pressure, heart rate\n", + " - Weak predictors: stress level, physical activity\n", + " - Age shows moderate effect\n", + "\n", + "2. **Combined risk factors demonstrate superior predictive capability**\n", + " - Multi-variable risk model achieves 84% disorder detection rate in high-risk segment\n", + " - Enables 72% cost reduction while maintaining 53% case identification\n", + "\n", + "3. **Actionable risk stratification is feasible**\n", + " - Simple scoring system (BMI + BP + Age + HR) effectively segments population\n", + " - High-risk group (28% of population) concentrates 53% of disorder cases\n", + "\n", + "---\n", + "\n", + "### **Key Findings by Hypothesis**\n", + "\n", + "**H1: Lifestyle & Physiological Factors**\n", + "\n", + "**Validated:**\n", + "- **H1a (BMI):** Obesity demonstrates strongest association with sleep apnea (57% prevalence vs 10% in normal weight)\n", + "- **H1e (Cardiovascular):** Elevated BP (>130) and HR (>80) show powerful predictive value (84% and 100% disorder rates respectively)\n", + "\n", + "**Partially Supported:**\n", + "- **H1b (Stress):** Weak discriminatory power between disorder types\n", + "- **H1c (Sleep Duration):** Limited sample size (n=4) prevents reliable conclusions\n", + "\n", + " **Not Supported:**\n", + "- **H1d (Physical Activity):** No significant relationship detected at 40min threshold\n", + "\n", + "**H2: Age Effects**\n", + "\n", + " **Validated:**\n", + "- Older individuals show moderately higher disorder prevalence (44.7 vs 39.5 years)\n", + "- Sleep apnea more strongly associated with age than insomnia\n", + "\n", + "**Rejected:**\n", + "- **H2d:** Age positively correlated with sleep duration (opposite to hypothesis) - likely due to sample age range (27-59) and lifestyle confounds\n", + "\n", + "**H3: Combined Risk Model** **Strongly Validated**\n", + "\n", + "The integrated risk scoring system demonstrates:\n", + "- Clear dose-response relationship (Low 18% → High 84% disorder rate)\n", + "- Efficient population segmentation for resource optimization\n", + "- Practical implementation feasibility\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/explore_clean_data_username.ipynb b/notebooks/explore_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/explore_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/functions.py b/notebooks/functions.py index 7804c676..4d3db6bf 100644 --- a/notebooks/functions.py +++ b/notebooks/functions.py @@ -24,3 +24,25 @@ def function_name(input1: data_type1, input2: data_type2,..., opt_arg: data_type return opuput + + +# Importar librerías y cargar datos +import pandas as pd +import numpy as np + +df = pd.read_csv("/Users/patriciaviladomiurecio/Desktop/Ironhack/week4/project/first_project/data/raw/Sleep_health_and_lifestyle_dataset.csv") +sleep_df = pd.read_csv(df, encoding='ISO-8859-1') +sleep_df + +# Estandarizar nombres de columnas +sleep_df.columns = ( + sleep_df.columns + .str.lower() + .str.normalize('NFKD') # quita acentos + .str.encode('ascii', errors='ignore') + .str.decode('utf-8') + .str.replace(' ', '_') + .str.replace('[^0-9a-zA-Z_]', '') +) + + diff --git a/notebooks/load_and_clean_data_username.ipynb b/notebooks/load_and_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/load_and_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/sleep_health_analysis_pati.ipynb b/notebooks/sleep_health_analysis_pati.ipynb new file mode 100644 index 00000000..6956154f --- /dev/null +++ b/notebooks/sleep_health_analysis_pati.ipynb @@ -0,0 +1,1963 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c940ecfe-dfee-40dd-bae2-b9422eceda4c", + "metadata": {}, + "source": [ + "## Data Analysis" + ] + }, + { + "cell_type": "markdown", + "id": "f9021d81-cdc9-4cd5-8a6e-a3bc0d39d823", + "metadata": {}, + "source": [ + "### 1. Importing different libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "4f49280c-041d-4ccf-a54d-f97ac9c48589", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c025e8be-6225-4ab4-89ff-0487f17b6179", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "57f64b6f-7b03-46f1-94ce-d3b405f1cd4a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input_data': {'file': '../data/raw/sleep_health_and_lifestyle_dataset.csv'},\n", + " 'output_data': {'file': '../data/clean/sleep_health_project_clean.csv'}}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "config" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "9fcf9fe3-c5ad-4582-be59-c0be0af2ef76", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
24Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
36Male28Software Engineer5.94308Obese140/90853000Insomnia14090
47Male29Teacher6.36407Obese140/90823500Insomnia14090
\n", + "
" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 4 Male 28 Sales Representative 5.9 \n", + "3 6 Male 28 Software Engineer 5.9 \n", + "4 7 Male 29 Teacher 6.3 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 4 30 8 Obese \n", + "3 4 30 8 Obese \n", + "4 6 40 7 Obese \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic diastolic \n", + "0 126/83 77 4200 No Disorder 126 83 \n", + "1 125/80 75 10000 No Disorder 125 80 \n", + "2 140/90 85 3000 Sleep Apnea 140 90 \n", + "3 140/90 85 3000 Insomnia 140 90 \n", + "4 140/90 82 3500 Insomnia 140 90 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean = pd.read_csv(config['output_data']['file'], encoding='ISO-8859-1')\n", + "sleep_df_clean.head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "bdfb0a13-97a2-4277-84e2-ceb32eb2c401", + "metadata": {}, + "source": [ + "#### 1.1 Basic casting of dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "60130bbb-f1e2-4a11-a66b-e8eb4432b190", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(132, 15)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "ddee0066-0d4b-402a-bff2-28eee8a7ff31", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "person_id int64\n", + "gender object\n", + "age int64\n", + "occupation object\n", + "sleep_duration float64\n", + "quality_of_sleep int64\n", + "physical_activity_level int64\n", + "stress_level int64\n", + "bmi_category object\n", + "blood_pressure object\n", + "heart_rate int64\n", + "daily_steps int64\n", + "sleep_disorder object\n", + "systolic int64\n", + "diastolic int64\n", + "dtype: object" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.dtypes" + ] + }, + { + "cell_type": "markdown", + "id": "9003bdda-862e-49fa-8c8b-c74e224466fb", + "metadata": {}, + "source": [ + "### 2. Exploratory Data Analysis (EDA)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "b0fea3d9-e79a-48ea-8645-613fa26258c9", + "metadata": {}, + "outputs": [], + "source": [ + "import statsmodels.api as sm\n", + "\n", + "from scipy.stats import chi2_contingency, ttest_ind, mannwhitneyu, shapiro\n", + "from statsmodels.stats.outliers_influence import variance_inflation_factor\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import classification_report, roc_auc_score" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "af85090d-815a-4615-876f-ec649b5616f6", + "metadata": {}, + "outputs": [], + "source": [ + "my_palette1 = sns.color_palette(\"Greens\")\n", + "my_palette2 = sns.color_palette(\"Oranges\")\n", + "my_palette3 = sns.color_palette(\"Blues\")" + ] + }, + { + "cell_type": "markdown", + "id": "bb26f207-1b89-4416-b3c3-3db9e26143b9", + "metadata": {}, + "source": [ + "Work on a copy of the original DataFrame." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "125b1d83-4639-4fc7-b1e4-5c0266b0d005", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df_clean = sleep_df_clean.copy()" + ] + }, + { + "cell_type": "markdown", + "id": "3e27459b-4195-47f1-9427-c0b6b665c8ba", + "metadata": {}, + "source": [ + "Numeric distribution." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "cb58356c-381b-4ad4-8c77-207372c6a39e", + "metadata": {}, + "outputs": [], + "source": [ + "numeric_cols = ['age',\n", + " 'sleep_duration',\n", + " 'quality_of_sleep',\n", + " 'physical_activity_level',\n", + " 'stress_level',\n", + " 'heart_rate',\n", + " 'daily_steps',\n", + " 'systolic',\n", + " 'diastolic']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9ce47194-d63b-4394-890f-c1cad764554f", + "metadata": {}, + "outputs": [], + "source": [ + "categorical_cols = ['gender',\n", + " 'occupation',\n", + " 'bmi_category',\n", + " 'sleep_disorder']" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b02130f0-d650-4c2d-a96b-2a42b206c715", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "gender\n", + "Female 45.830769\n", + "Male 36.567164\n", + "Name: age, dtype: float64" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.groupby(\"gender\")[\"age\"].mean()" + ] + }, + { + "cell_type": "markdown", + "id": "63176313-3018-41d3-a184-34d1c61e05b4", + "metadata": {}, + "source": [ + "#### 2.1 Age Distribution by Gender" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "2c370cd1-f6bd-481f-9cc0-b3070d04e94a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.6, 1.0, 'Age Distribution by Gender')" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "palette = [my_palette3[2], my_palette2[3]]\n", + "# palette = ['#9c9678', '#524e3a', '#a99467']\n", + "\n", + "sns.displot(\n", + " x=\"age\",\n", + " data=sleep_df_clean,\n", + " hue=\"gender\",\n", + " palette=palette,\n", + " kind=\"kde\",\n", + " fill=True)\n", + "plt.title(\"Age Distribution by Gender\", x=0.6)" + ] + }, + { + "cell_type": "markdown", + "id": "28e3185f-8e1e-45d4-b573-b422da0f9275", + "metadata": {}, + "source": [ + "#### 2.2 Age Distribution based on Sleep Disorder" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "34184819-9873-48ff-bfb7-145fe8a8e550", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.6, 1.0, 'Age Distribution based on Sleep Disorder')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + "\n", + "sns.displot(\n", + " x=\"age\",\n", + " data=sleep_df_clean,\n", + " hue=\"sleep_disorder\",\n", + " palette=palette,\n", + " kind=\"kde\",\n", + " fill=True)\n", + "\n", + "plt.title(\"Age Distribution based on Sleep Disorder\",x=0.6)" + ] + }, + { + "cell_type": "markdown", + "id": "7bc4f01b-3e31-4d5e-b027-cf69b6385339", + "metadata": {}, + "source": [ + "#### 2.3 Distribution of Sleep Disorders by Gender" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "5ed01874-0d40-42b2-b0e5-9e4f4f585122", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 0, 'sleep_disorder')" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.countplot(\n", + " x= sleep_df_clean[\"sleep_disorder\"], \n", + " data= sleep_df_clean, \n", + " hue= sleep_df_clean[\"gender\"], \n", + " palette=[my_palette3[2], my_palette2[2]]\n", + ")\n", + "ax.set_xlabel(\"sleep_disorder\", labelpad=20)" + ] + }, + { + "cell_type": "markdown", + "id": "81d9d4f4-43ce-4c20-8465-94193b52d864", + "metadata": {}, + "source": [ + "#### 2.4 Distribution of BMI Categories by Sleep Disorder" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "46e161a5-bb5d-4413-b9bc-0484aeb2d389", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Distribution of BMI Categories by Sleep Disorder')" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.countplot(\n", + " x = sleep_df_clean[\"bmi_category\"],\n", + " hue = sleep_df_clean[\"sleep_disorder\"],\n", + " data = sleep_df_clean,\n", + " palette = ['#9c9678', '#524e3a', '#a99467']\n", + " # palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + ")\n", + "ax.set_title(\"Distribution of BMI Categories by Sleep Disorder\", pad=20)" + ] + }, + { + "cell_type": "markdown", + "id": "512642fb-ebec-4752-a272-332b048c57c9", + "metadata": {}, + "source": [ + "#### 2.5 Distribution of Sleep Quality by Sleep Disorder" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "ce7b537f-8d6f-4571-9792-c92a1f89f012", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Distribution of Sleep Quality by Sleep Disorder')" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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Scjoov59fUVlYWMDX1xdr165FZmYmrl27hlOnTmHUqFGF7uPdc1imTBmYmZmpnEMvLy/Y2dkpjyE4OBjJycn5TjG9TUdHBx06dMC8efNw+PBhxMbGwt3dHfv27cPBgwfz3O7JkyfYu3dvjtdD9nU6b792nj9/jrJly+ZoGxcXV+jXDfD+7wPZf2zk9963cuVKTJ48GaGhoWjdujVMTU3RvXt33LlzR6WGvP4fZ2Vl5Zgqerdtdh95/XzfVtjznNe+PnW8Nfsjtn//fmRmZhZ4O3WLFi3QokULZGZm4vLly8rbZS0sLNCnT59C7asofznHxcXluSz7P7iuri4AIC0tTaXd+34eh5mZGR4/fpxjefZFmuXLl3+v/gGgXLly0NLSKvX9ZOvduzcCAgJw/fr1PNtk72/Hjh2wtbUtsN3UqVPh7e2da5t3bx3P6+dZrVq1PPejra2NNm3a4ODBg3j48GGu1808fPgQERERKrf36+rq5nhNADlfF6GhoUhOTsbOnTtVjrekPycm25gxY7Bx40bs3r0bhw4dgomJSY6/xvMTFxeHihUrKp9nZGQgISFB5ReelpYWRo4ciWnTpmHp0qVYvXo12rZtm+et/AUxMzPD2LFjERYWhuvXr6NTp065titfvjzq1KmDefPm5bo+OzCUL18eZmZmymvs3qVQKFSeF+Z9oDiEENi7dy8MDAzg6uqaZzsDAwPMnj0bs2fPxpMnT5SjNF27dsXff/+trCGv/8daWlooV66cyvJ33wez+8jr5/u2wp7nvPb1qePIzEcqJiYGEyZMgLGxcaEveNTW1kbjxo2Vf/llD/UWZjSiKG7cuIE///xTZdnmzZuhUChQv359AFDesXLt2jWVdnv27MnRn1wuL3Rtbdu2xfHjx3PcYbJhwwbo6+ujSZMmhT2MPBkYGKBx48bYuXOnSl1ZWVn45ZdfUKlSJTg4OBS539zeVIE3n7ERGxub71+hHTp0QJkyZXDv3j24urrm+gDeBJXq1avjzz//zLPdu7+UNm3apPL87NmzePDgQYEhesqUKRBCYMSIETkuqM7MzMSXX36JzMxMjBkzRrnczs4O8fHxyhEk4M0dNIcPH1bZPvuNPvu1C7z5Jff2VFBRFPR/oEGDBmjatCkWLlyITZs2wc/PDwYGBoXu/91zuH37dmRkZOQ4h0OHDkXZsmXRr18/3Lp1q1CjP+np6XmOdERGRgLIfwSjS5cuuH79OqpWrZrr6yF72y5duiAhIQGZmZm5tns3dBXmfaA4Zs+ejZs3b2LMmDHKP4oKYmFhAT8/P/Tt2xe3bt1CSkoKHB0dUbFiRWzevFll2io5ORm//fab8g6n/GT//PL6+b6tsOeZcseRmY/A9evXlfOr8fHxOHXqFIKCgqCtrY1du3Ypb63OzZo1a3D8+HF07twZlStXRmpqKtavXw8Ayg/bUygUsLW1xe7du9G2bVuYmpqifPny+d5GnB9ra2t069YN/v7+sLKywi+//IKjR49i4cKFyjeHhg0bwtHRERMmTEBGRgbKlSuHXbt25XoHgbOzM3bu3InAwEA0aNAAWlpaef5FNmvWLOXc9MyZM2FqaopNmzZh//79WLRoEYyNjYt1TO8KCAhAu3bt0Lp1a0yYMAFly5bF6tWrcf36dWzZsqVYf1XNmzcPZ86cga+vL1xcXKCnp4eoqCisWrUKCQkJWLx4cZ7b2tnZYc6cOZg+fTru37+Pjh07oly5cnjy5AkuXryo/CsVANauXQtPT0906NABfn5+qFixIp4+fYrIyEj88ccf+PXXX1X6vnz5MoYOHQofHx/ExsZi+vTpqFixonJaKi/NmjXDihUrMGbMGDRv3hyjRo1C5cqVlR+ad+7cOfj7+6Ndu3bKbXx9fTFz5kz06dMHEydORGpqKlauXJkjDLVr1w5ly5ZF3759MWnSJKSmpiIwMDDHtEBhVa1aFXp6eti0aROcnJxgaGgIa2trlV8wY8aMga+vL2QyWYHH/q6dO3eiTJkyaNeuHW7cuIEZM2agbt266N27t0o7ExMTDBgwAIGBgbC1tUXXrl0L7DsxMRF2dnbw8fGBh4cHbGxs8PLlS4SFheG7776Dk5NTnqNwwJtbzI8ePYqmTZti9OjRcHR0RGpqKqKjo3HgwAGsWbMGlSpVQp8+fbBp0yZ06tQJY8aMQaNGjaCjo4OHDx/ixIkT8PLyQo8ePZT9FuZ9ID/Pnz/H+fPnAbwJGNkfmnfq1Cn07t1b+XrOS+PGjdGlSxfUqVMH5cqVQ2RkJDZu3KgSUhYtWoR+/fqhS5cuGD58ONLS0rB48WI8f/4cCxYsKLBGJycnfP7551ixYgV0dHTg4eGB69evY8mSJSofyliU80x5UNulx/Tesu8myX6ULVtWmJubi1atWon58+eL+Pj4HNu8e9fHuXPnRI8ePYStra2Qy+XCzMxMtGrVSuzZs0dlu2PHjol69eoJuVyuchV+fh/6ldfdTJ07dxY7duwQtWrVEmXLlhV2dnZi2bJlOba/ffu2aN++vTAyMhIVKlQQX331ldi/f3+Ou5mePn0qevXqJUxMTIRMJlPZJ3K5C+uvv/4SXbt2FcbGxqJs2bKibt26Oe5Syb6b6ddff1VZnn0nQWE+PO3UqVOiTZs2wsDAQOjp6YkmTZqIvXv35tpfYe5mOn/+vBg5cqSoW7euMDU1Fdra2qJChQqiY8eO4sCBAypt87q7JzQ0VLRu3VoYGRkJuVwubG1tRa9evcSxY8dU2v3555+id+/ewtzcXOjo6AhLS0vRpk0bsWbNGmWb7NffkSNHRP/+/YWJiYnQ09MTnTp1Enfu3CnweLKdPXtW9OzZU1hYWCjv1NLV1RX79+/Ptf2BAweEi4uL0NPTE1WqVBGrVq3K9Xj37t0r6tatK3R1dUXFihXFxIkTxcGDB3O8fgpzN5MQb+7WqVGjhtDR0cn1dZWWlibkcrno2LFjoY89u+6IiAjRtWtXYWhoKBQKhejbt6/K3VFvCwsLEwDEggULCrWPtLQ0sWTJEuHp6SkqV64s5HK50NXVFU5OTmLSpEkiISFBpX1ux/bvv/+K0aNHC3t7e6GjoyNMTU1FgwYNxPTp08XLly+V7dLT08WSJUuU593Q0FDUqFFDDB8+XOU1UZT3gdzY2toq3/dkMpkwNDQUjo6Oon///uLw4cO5bvPucU2ZMkW4urqKcuXKCblcLqpUqSLGjRsn/vvvP5XtQkNDRePGjYWurq4wMDAQbdu2FWfOnFFpk9/7YFpamvj666+Fubm50NXVFU2aNBHnzp3L9TVWmPNclPeMT4lMiCJ84AAR0f8XHByMQYMG4dKlS/lem1BUGzZswMCBAzFp0iQsXLiwxPotbXv37kW3bt2wf//+PK8/KQlff/01AgMDERsb+17XlqiTnZ0dateujX379qm7FPpIcJqJiDTKgAED8PjxY0yZMgUGBgaYOXOmukvK182bN/HgwQN8/fXXcHFxUd5KW9LOnz+P27dvY/Xq1Rg+fLhkgwxRaWCYISKNM3nyZEyePFndZRTKiBEjcObMGdSvXx8hISGldpdJ9rUcXbp0wdy5c0tlH0RSxWkmIiIikjTemk1ERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSVkbdBZS2rKwsPHr0CAqFAjKZTN3lEBERUSEIIfDixQtYW1tDSyv/sZePPsw8evQINjY26i6DiIiIiiE2NhaVKlXKt81HH2YUCgWANyfDyMhIzdUQERFRYSQlJcHGxkb5ezw/H32YyZ5aMjIyYpghIiKSmMJcIsILgImIiEjSGGaIiIhI0hhmiIiISNI++mtmCiszMxPp6enqLoM0iI6ODrS1tdVdBhERFeCTDzNCCMTFxeH58+fqLoU0kImJCSwtLfkZRUREGuyTDzPZQcbc3Bz6+vr8pUUA3oTclJQUxMfHAwCsrKzUXBEREeXlkw4zmZmZyiBjZmam7nJIw+jp6QEA4uPjYW5uziknIiIN9UlfAJx9jYy+vr6aKyFNlf3a4PVURESa65MOM9k4tUR54WuDiEjzMcwQERGRpDHMfCB+fn7o3r27ussokJ2dHVasWKF8LpPJEBoa+sHrUNd+iYhIej7pC4CpYI8fP0a5cuXUXQYREVGeODJD+bK0tIRcLi+VvkvzotrXr1+XWt9ERKRZGGZK2I4dO+Ds7Aw9PT2YmZnBw8MDycnJOdoJIbBo0SJUqVIFenp6qFu3Lnbs2KHS5ubNm+jUqRMMDQ1hYWGB/v3747///lOud3d3x6hRozBq1CiYmJjAzMwM33zzDYQQhao1Pj4eXbt2hZ6eHuzt7bFp06Ycbd6e7nn9+jVGjRoFKysr6Orqws7ODgEBAcq2MTEx8PLygqGhIYyMjNC7d288efJEud7f3x8uLi5Yv349qlSpArlcDiEE7ty5g5YtW0JXVxc1a9bE0aNHc9Txzz//wNfXF+XKlYOZmRm8vLwQHR2tXJ89jRcQEABra2s4ODgU6hwQEZH0McyUoMePH6Nv374YPHgwIiMjERYWBm9v71zDxTfffIOgoCAEBgbixo0bGDduHD7//HOEh4cr+2rVqhVcXFxw+fJlHDp0CE+ePEHv3r1V+gkJCUGZMmVw4cIFrFy5EsuXL8dPP/1UqHr9/PwQHR2N48ePY8eOHVi9erXyQ+Jys3LlSuzZswfbt2/HrVu38Msvv8DOzg7Am3DWvXt3PH36FOHh4Th69Cju3bsHX19flT7u3r2L7du347fffsPVq1eRlZUFb29vaGtr4/z581izZg0mT56ssk1KSgpat24NQ0NDnDx5EqdPn4ahoSE6duyoMgLz+++/IzIyEkePHsW+ffsKdQ6IiEj6eM1MCXr8+DEyMjLg7e0NW1tbAICzs3OOdsnJyVi2bBmOHz8ONzc3AECVKlVw+vRprF27Fq1atUJgYCDq16+P+fPnK7dbv349bGxscPv2beXIg42NDZYvXw6ZTAZHR0f89ddfWL58OYYNG5Zvrbdv38bBgwdx/vx5NG7cGADw888/w8nJKc9tYmJiUL16dTRv3hwymUx5jABw7NgxXLt2DVFRUbCxsQEAbNy4EbVq1cKlS5fQsGFDAG9GdzZu3IgKFSoAAI4cOYLIyEhER0ejUqVKAID58+fD09NT2ffWrVuhpaWFn376SXmrdFBQEExMTBAWFob27dsDAAwMDPDTTz+hbNmy+R47EX0aNqwcWyr9Dhi9olT6peLjyEwJqlu3Ltq2bQtnZ2f4+Phg3bp1ePbsWY52N2/eRGpqKtq1awdDQ0PlY8OGDbh37x4AICIiAidOnFBZX6NGDQBQtgGAJk2aqHwWipubG+7cuYPMzMx8a42MjESZMmXg6uqqXFajRg2YmJjkuY2fnx+uXr0KR0dHjB49GkeOHFHpz8bGRhlkAKBmzZowMTFBZGSkcpmtra0yyGRvV7lyZWWQyT6Gt0VERODu3btQKBTKc2FqaorU1FSVc+Hs7MwgQ0T0CeLITAnS1tbG0aNHcfbsWRw5cgTff/89pk+fjgsXLqi0y8rKAgDs378fFStWVFmXfbFtVlYWunbtioULF+bYT0l8T1D21FdRPhSufv36iIqKwsGDB3Hs2DH07t0bHh4e2LFjB4QQufb17nIDA4Nc63jbu/1kZWWhQYMGuV7T83YwerdvIiL6NDDMlDCZTIZmzZqhWbNmmDlzJmxtbbFr1y6VNjVr1oRcLkdMTAxatWqVaz/169fHb7/9Bjs7O5Qpk/eP6fz58zmeV69evcDvEXJyckJGRgYuX76MRo0aAQBu3bpV4LeHGxkZwdfXF76+vujVqxc6duyIp0+fombNmoiJiUFsbKxydObmzZtITEzMd+oqe7tHjx7B2toaAHDu3DmVNvXr18e2bdtgbm4OIyOjfOsjIqJPD6eZStCFCxcwf/58XL58GTExMdi5cyf+/fffHL/MFQoFJkyYgHHjxiEkJAT37t3DlStX8MMPPyAkJAQAMHLkSDx9+hR9+/bFxYsXcf/+fRw5cgSDBw9WmUKKjY3F+PHjcevWLWzZsgXff/89xowZU2Ctjo6O6NixI4YNG4YLFy4gIiICQ4cOVX65Ym6WL1+OrVu34u+//8bt27fx66+/wtLSEiYmJvDw8ECdOnXQr18//PHHH7h48SIGDBiAVq1aqUxlvcvDwwOOjo4YMGAA/vzzT5w6dQrTp09XadOvXz+UL18eXl5eOHXqFKKiohAeHo4xY8bg4cOHBR4rERF93BhmSpCRkRFOnjyJTp06wcHBAd988w2WLl2qcjFrtm+//RYzZ85EQEAAnJyc0KFDB+zduxf29vYAAGtra5w5cwaZmZno0KEDateujTFjxsDY2BhaWv/3YxswYABevXqFRo0aYeTIkfjqq6/wxRdfFKreoKAg2NjYoFWrVvD29sYXX3wBc3PzPNsbGhpi4cKFcHV1RcOGDREdHY0DBw5AS0tLeQt3uXLl0LJlS3h4eKBKlSrYtm1bvjVoaWlh165dSEtLQ6NGjTB06FDMmzdPpY2+vj5OnjyJypUrw9vbG05OThg8eDBevXrFkRoiIoJMFPZDSSQqKSkJxsbGSExMzPGLLzU1FVFRUbC3t4eurq6aKiw+d3d3uLi4qHz9AJUsqb9GiD5lvJtJ2vL7/f0ujswQERGRpDHMfKROnTqlclv3uw8iIqKPBe9mkrCwsLA817m6uuLq1asfrBYiIiJ1YZj5SOnp6aFatWrqLoOIiKjUcZqJiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYeYjlf31AkRERB873pqdh7WrZn6wfQ0fNadI7ePj4zFjxgwcPHgQT548Qbly5VC3bl34+/vDzc2tlKp8P5s3b0b//v0xbNgwrFmzRt3lEBHRR4QjMxLUs2dP/PnnnwgJCcHt27exZ88euLu74+nTp+ouLU/r16/HpEmTsHXrVqSkpKi7HCIi+ogwzEjM8+fPcfr0aSxcuBCtW7eGra0tGjVqhKlTp6Jz5855bvfPP//A19cX5cqVg5mZGby8vBAdHa3SJigoCE5OTtDV1UWNGjWwevVq5bro6GjIZDJs3boVTZs2ha6uLmrVqpXvpxC/ve3Zs2cxZcoU1KhRAzt27FBZHxwcDBMTE4SGhsLBwQG6urpo164dYmNjlW38/f3h4uKCjRs3ws7ODsbGxujTpw9evHihbCOEwKJFi1ClShXo6emhbt26KvvKzMzEkCFDYG9vDz09PTg6OuK7774rsH4iItJsDDMSk/3dSqGhoUhLSyvUNikpKWjdujUMDQ1x8uRJnD59GoaGhujYsSNev34NAFi3bh2mT5+OefPmITIyEvPnz8eMGTMQEhKi0tfEiRPx9ddf48qVK2jatCm6deuGhISEfPe/fv16dO7cGcbGxvj888/x888/51rjvHnzEBISgjNnziApKQl9+vRRaXPv3j2EhoZi37592LdvH8LDw7FgwQLl+m+++QZBQUEIDAzEjRs3MG7cOHz++ecIDw8HAGRlZaFSpUrYvn07bt68iZkzZ2LatGnYvn17oc4jERFpJoYZiSlTpgyCg4MREhICExMTNGvWDNOmTcO1a9fy3Gbr1q3Q0tLCTz/9BGdnZzg5OSEoKAgxMTHKkZVvv/0WS5cuhbe3N+zt7eHt7Y1x48Zh7dq1Kn2NGjUKPXv2hJOTEwIDA2FsbJxrOMmWlZWF4OBgfP755wCAPn364Ny5c7h7965Ku/T0dKxatQpubm5o0KABQkJCcPbsWVy8eDFHX7Vr10aLFi3Qv39//P777wCA5ORkLFu2DOvXr0eHDh1QpUoV+Pn54fPPP1ceg46ODmbPno2GDRvC3t4e/fr1g5+fH8MMEZHEMcxIUM+ePfHo0SPs2bMHHTp0QFhYGOrXr4/g4OBc20dERODu3btQKBTKkR1TU1Okpqbi3r17+PfffxEbG4shQ4aofLP23Llzce/ePZW+3r7AuEyZMnB1dUVkZGSetR45cgTJycnw9PQEAJQvXx7t27fH+vXrVdpl95WtRo0aMDExUenbzs4OCoVC+dzKygrx8fEAgJs3byI1NRXt2rVTOYYNGzaoHMOaNWvg6uqKChUqwNDQEOvWrUNMTEye9RMRkebj3UwSlX1dSbt27TBz5kwMHToUs2bNgp+fX462WVlZaNCgATZt2pRjXYUKFZCamgrgzVRT48aNVdZra2sXWItMJstz3fr16/H06VPo6+ur1HPlyhV8++23Kv3n1s/by3R0dHKsy8rKUvYJAPv370fFihVV2snlcgDA9u3bMW7cOCxduhRubm5QKBRYvHgxLly4UOAxEhGR5mKY+UjUrFkzz8+VqV+/PrZt2wZzc3MYGRnlWG9sbIyKFSvi/v376NevX777OX/+PFq2bAkAyMjIQEREBEaNGpVr24SEBOzevRtbt25FrVq1lMuzsrLQokULHDx4EF26dFH2dfnyZTRq1AgAcOvWLTx//hw1atQo8NiBN8cvl8sRExODVq1a5drm1KlTaNq0KUaMGKFc9u7IExERSQ/DjMQkJCTAx8cHgwcPRp06daBQKHD58mUsWrQIXl5euW7Tr18/LF68GF5eXpgzZw4qVaqEmJgY7Ny5ExMnTkSlSpXg7++P0aNHw8jICJ6enkhLS8Ply5fx7NkzjB8/XtnXDz/8gOrVq8PJyQnLly/Hs2fPMHjw4Fz3u3HjRpiZmcHHxwdaWqozml26dMHPP/+sDDM6Ojr46quvsHLlSujo6GDUqFFo0qSJMtwURKFQYMKECRg3bhyysrLQvHlzJCUl4ezZszA0NMTAgQNRrVo1bNiwAYcPH4a9vT02btyIS5cuwd7evlD7ICIizcQwIzGGhoZo3Lgxli9fjnv37iE9PR02NjYYNmwYpk2blus2+vr6OHnyJCZPngxvb2+8ePECFStWRNu2bZUjNUOHDoW+vj4WL16MSZMmwcDAAM7Ozhg7dqxKXwsWLMDChQtx5coVVK1aFbt370b58uVz3e/69evRo0ePHEEGeHPdj6+vL548eaKscfLkyfjss8/w8OFDNG/ePMd1NQX59ttvYW5ujoCAANy/fx8mJiaoX7++8rz873//w9WrV+Hr6wuZTIa+fftixIgROHjwYJH2Q0REmkUmhBDqLqI0JSUlwdjYGImJiTmmWFJTUxEVFQV7e3vo6uqqqUJpiI6Ohr29Pa5cuQIXF5cS7Ts4OBhjx47F8+fPS7TfksDXCJF0bVg5tlT6HTB6Ran0S6ry+/39Lt7NRERERJLGMENERESSxjBDhWJnZwchRIlPMQGAn5+fRk4xERGRNDDMEBERkaQxzBAREZGkMcwQERGRpKk1zAQEBKBhw4ZQKBQwNzdH9+7dcevWLZU2fn5+kMlkKo8mTZqoqWIiIiLSNGoNM+Hh4Rg5ciTOnz+Po0ePIiMjA+3bt0dycrJKu44dO+Lx48fKx4EDB9RUMREREWkatX4C8KFDh1SeBwUFwdzcHBEREcrv/wHefFGgpaVlofpMS0tDWlqa8nlSUlLJFEtEREQaSaOumUlMTAQAmJqaqiwPCwuDubk5HBwcMGzYMMTHx+fZR0BAAIyNjZUPGxubUq2Zii86OhoymQxXr15VdylERCRhGvPdTEIIjB8/Hs2bN0ft2rWVyz09PeHj4wNbW1tERUVhxowZaNOmDSIiIiCXy3P0M3XqVJUvRkxKSipWoOnetWXBjUpI6N6TRd4m+7NZ8vqmbCmwsbHB48eP8/xuJyIiosLQmDAzatQoXLt2DadPn1ZZ7uvrq/x37dq14erqCltbW+zfvx/e3t45+pHL5bmGHNI82trahZ4+JCIiyotGTDN99dVX2LNnD06cOIFKlSrl29bKygq2tra4c+fOB6pO87m7u2P06NGYNGkSTE1NYWlpCX9/f5U2/v7+qFy5MuRyOaytrTF69GjlumfPnmHAgAEoV64c9PX14enpqXJ+g4ODYWJign379sHR0RH6+vro1asXkpOTERISAjs7O5QrVw5fffUVMjMzldvZ2dlh/vz5GDx4MBQKBSpXrowff/xRuf7daabMzEwMGTIE9vb20NPTg6OjI7777rvSOWlERPTRUGuYEUJg1KhR2LlzJ44fPw57e/sCt0lISEBsbCysrKw+QIXSERISAgMDA1y4cAGLFi3CnDlzcPToUQDAjh07sHz5cqxduxZ37txBaGgonJ2dldv6+fnh8uXL2LNnD86dOwchBDp16oT09HRlm5SUFKxcuRJbt27FoUOHEBYWBm9vbxw4cAAHDhzAxo0b8eOPP2LHjh0qdS1duhSurq64cuUKRowYgS+//BJ///13rseQlZWFSpUqYfv27bh58yZmzpyJadOmYfv27aVwxoiI6GOh1mmmkSNHYvPmzdi9ezcUCgXi4uIAAMbGxtDT08PLly/h7++Pnj17wsrKCtHR0Zg2bRrKly+PHj16qLN0jVOnTh3MmjULAFC9enWsWrUKv//+O9q1a4eYmBhYWlrCw8MDOjo6qFy5Mho1agQAuHPnDvbs2YMzZ86gadOmAIBNmzbBxsYGoaGh8PHxAQCkp6cjMDAQVatWBQD06tULGzduxJMnT2BoaIiaNWuidevWOHHihMrUYKdOnTBixAgAwOTJk7F8+XKEhYWhRo0aOY5BR0cHs2fPVj63t7fH2bNnsX37dvTu3bsUzhoREX0M1DoyExgYiMTERLi7u8PKykr52LZtG4A311T89ddf8PLygoODAwYOHAgHBwecO3cOCoVCnaVrnDp16qg8t7KyUt715ePjg1evXqFKlSoYNmwYdu3ahYyMDABAZGQkypQpg8aNGyu3NTMzg6OjIyIjI5XL9PX1lUEGACwsLGBnZwdDQ0OVZe/eafZ2XTKZDJaWlvnejbZmzRq4urqiQoUKMDQ0xLp16xATE1OUU0FERJ8YtY7MCCHyXa+np4fDhw9/oGqkTUdHR+W5TCZDVlYWgDd3Dd26dQtHjx7FsWPHMGLECCxevBjh4eF5/gyEEJDJZPn2n98+C1PXu7Zv345x48Zh6dKlcHNzg0KhwOLFi3HhwoV8jpyIiD51GnM3E5UuPT09dOvWDd26dcPIkSNRo0YN/PXXX6hZsyYyMjJw4cIF5TRTQkICbt++DScnpw9a46lTp9C0aVPltBQA3Lt374PWQERE0sMw8wkIDg5GZmYmGjduDH19fWzcuBF6enqwtbWFmZkZvLy8MGzYMKxduxYKhQJTpkxBxYoV4eXl9UHrrFatGjZs2IDDhw/D3t4eGzduxKVLlwp1YTgREX26NOLWbCpdJiYmWLduHZo1a4Y6derg999/x969e2FmZgbgzddINGjQAF26dIGbmxuEEDhw4ECOKaLS9r///Q/e3t7w9fVF48aNkZCQoDJKQ0RElBuZKOjCFYlLSkqCsbExEhMTYWRkpLIuNTUVUVFRsLe3h66urpoqJE3G1wiRdG1YObZU+h0wekWp9Euq8vv9/S6OzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzFCxubu7Y+zYsZ/MfomISDPxiybzUFofg52bon40tp+fH0JCQhAQEIApU6Yol4eGhqJHjx54n2+oCA4OxqBBgwAAWlpaMDIygoODAzp37owxY8bA2NhY2Xbnzp0f/PubiIiI3sWRGYnS1dXFwoUL8ezZsxLv28jICI8fP8bDhw9x9uxZfPHFF9iwYQNcXFzw6NEjZTtTU1MoFIoS3z8ACCGQkZFRKn1nZmYiKyurVPomIqIPj2FGojw8PGBpaYmAgIB82/3222+oVasW5HI57OzssHTp0gL7lslksLS0hJWVFZycnDBkyBCcPXsWL1++xKRJk5Tt3p3uWb16NapXrw5dXV1YWFigV69eynVpaWkYPXo0zM3Noauri+bNm+PSpUvK9WFhYZDJZDh8+DBcXV0hl8tx6tQpJCcnY8CAATA0NISVlVWu9b9+/RqTJk1CxYoVYWBggMaNGyMsLEy5Pjg4GCYmJti3bx9q1qwJuVyOBw8eFHgeiIhIGhhmJEpbWxvz58/H999/j4cPH+baJiIiAr1790afPn3w119/wd/fHzNmzEBwcHCR92dubo5+/fphz549yMzMzLH+8uXLGD16NObMmYNbt27h0KFDaNmypXL9pEmT8NtvvyEkJAR//PEHqlWrhg4dOuDp06cq/UyaNAkBAQGIjIxEnTp1MHHiRJw4cQK7du3CkSNHEBYWhoiICJVtBg0ahDNnzmDr1q24du0afHx80LFjR9y5c0fZJiUlBQEBAfjpp59w48YNmJubF/kcEBGRZuI1MxLWo0cPuLi4YNasWfj5559zrF+2bBnatm2LGTNmAAAcHBxw8+ZNLF68GH5+fkXeX40aNfDixQskJCTkCAMxMTEwMDBAly5doFAoYGtri3r16gEAkpOTERgYiODgYHh6egIA1q1bh6NHj+Lnn3/GxIkTlf3MmTMH7dq1AwC8fPkSP//8MzZs2KBcFhISgkqVKinb37t3D1u2bMHDhw9hbW0NAJgwYQIOHTqEoKAgzJ8/HwCQnp6O1atXo27dukU+biIi0mwcmZG4hQsXIiQkBDdv3syxLjIyEs2aNVNZ1qxZM9y5cyfX0ZWCZF9YLJPJcqxr164dbG1tUaVKFfTv3x+bNm1CSkoKgDeBIz09XaUWHR0dNGrUCJGRkSr9uLq6Kv997949vH79Gm5ubsplpqamcHR0VD7/448/IISAg4MDDA0NlY/w8HDcu3dP2a5s2bKoU6dOkY+ZiIg0H0dmJK5ly5bo0KEDpk2blmO0RQiRI3i8z51OkZGRMDIygpmZWY51CoUCf/zxB8LCwnDkyBHMnDkT/v7+uHTpUp4hKLf6DAwMilRrVlYWtLW1ERERAW1tbZV1hoaGyn/r6enlGsKIiEj6ODLzEViwYAH27t2Ls2fPqiyvWbMmTp8+rbLs7NmzcHBwyPGLvyDx8fHYvHkzunfvDi2t3F82ZcqUgYeHBxYtWoRr164hOjoax48fR7Vq1VC2bFmVWtLT03H58mU4OTnluc9q1apBR0cH58+fVy579uwZbt++rXxer149ZGZmIj4+HtWqVVN5WFpaFukYiYhImjgy8xFwdnZGv3798P3336ss//rrr9GwYUN8++238PX1xblz57Bq1SqsXr063/6EEIiLi4MQAs+fP8e5c+cwf/58GBsbY8GCBblus2/fPty/fx8tW7ZEuXLlcODAAWRlZcHR0REGBgb48ssvMXHiRJiamqJy5cpYtGgRUlJSMGTIkDzrMDQ0xJAhQzBx4kSYmZnBwsIC06dPVwlTDg4O6NevHwYMGIClS5eiXr16+O+//3D8+HE4OzujU6dORTiTREQkRQwzeSjqB9mp27fffovt27erLKtfvz62b9+OmTNn4ttvv4WVlRXmzJlT4MW/SUlJsLKygkwmg5GRERwdHTFw4ECMGTMGRkZGuW5jYmKCnTt3wt/fH6mpqahevTq2bNmCWrVqAXgzepSVlYX+/fvjxYsXcHV1xeHDh1GuXLl8a1m8eDFevnyJbt26QaFQ4Ouvv0ZiYqJKm6CgIMydOxdff/01/vnnH5iZmcHNzY1BhojoEyET73MRhQQkJSXB2NgYiYmJOX4Rp6amIioqCvb29tDV1VVThaTJ+Bohkq7S+iR3qf2xK1X5/f5+F6+ZISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmMH7fZAcfdz42iAi0nyfdJjR0dEBAOXH7hO9K/u1kf1aISIizfNJf86MtrY2TExMEB8fDwDQ19fnR94TgDcjMikpKYiPj4eJiUmRPzGZiIg+nE86zABQfuR9dqAhepuJiQm/FoGISMN98mFGJpPBysoK5ubmSE9PV3c5pEF0dHQ4IkNEJAGffJjJpq2tzV9cREREEvRJXwBMRERE0scwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREksYwQ0RERJLGMENERESSxjBDREREkqbWMBMQEICGDRtCoVDA3Nwc3bt3x61bt1TaCCHg7+8Pa2tr6Onpwd3dHTdu3FBTxURERKRp1BpmwsPDMXLkSJw/fx5Hjx5FRkYG2rdvj+TkZGWbRYsWYdmyZVi1ahUuXboES0tLtGvXDi9evFBj5URERKQpyqhz54cOHVJ5HhQUBHNzc0RERKBly5YQQmDFihWYPn06vL29AQAhISGwsLDA5s2bMXz4cHWUTURERBpEo66ZSUxMBACYmpoCAKKiohAXF4f27dsr28jlcrRq1Qpnz57NtY+0tDQkJSWpPIiIiOjjpTFhRgiB8ePHo3nz5qhduzYAIC4uDgBgYWGh0tbCwkK57l0BAQEwNjZWPmxsbEq3cCIiIlIrjQkzo0aNwrVr17Bly5Yc62QymcpzIUSOZdmmTp2KxMRE5SM2NrZU6iUiIiLNoNZrZrJ99dVX2LNnD06ePIlKlSopl1taWgJ4M0JjZWWlXB4fH59jtCabXC6HXC4v3YKJiIhIY6h1ZEYIgVGjRmHnzp04fvw47O3tVdbb29vD0tISR48eVS57/fo1wsPD0bRp0w9dLhEREWkgtY7MjBw5Eps3b8bu3buhUCiU18EYGxtDT08PMpkMY8eOxfz581G9enVUr14d8+fPh76+Pj777DN1lk5EREQaQq1hJjAwEADg7u6usjwoKAh+fn4AgEmTJuHVq1cYMWIEnj17hsaNG+PIkSNQKBQfuFoiIiLSRGoNM0KIAtvIZDL4+/vD39+/9AsiIiIiydGYu5mIiIiIioNhhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJK1McTZq06YNdu7cCRMTE5XlSUlJ6N69O44fP14StRGRhGxYObZU+h0wekWp9KupeB6Jiq5YIzNhYWF4/fp1juWpqak4derUexdFREREVFhFGpm5du2a8t83b95EXFyc8nlmZiYOHTqEihUrllx1RERERAUoUphxcXGBTCaDTCZDmzZtcqzX09PD999/X2LFERERERWkSGEmKioKQghUqVIFFy9eRIUKFZTrypYtC3Nzc2hra5d4kURERER5KVKYsbW1BQBkZWWVSjFERERERVWsu5kA4Pbt2wgLC0N8fHyOcDNz5sz3LoyIiIioMIoVZtatW4cvv/wS5cuXh6WlJWQymXKdTCZjmCEiIqIPplhhZu7cuZg3bx4mT55c0vUQERERFUmxPmfm2bNn8PHxee+dnzx5El27doW1tTVkMhlCQ0NV1vv5+Snvnsp+NGnS5L33S0RERB+PYoUZHx8fHDly5L13npycjLp162LVqlV5tunYsSMeP36sfBw4cOC990tEREQfj2JNM1WrVg0zZszA+fPn4ezsDB0dHZX1o0ePLlQ/np6e8PT0zLeNXC6HpaVlccokIiKiT0CxwsyPP/4IQ0NDhIeHIzw8XGWdTCYrdJgpjLCwMJibm8PExAStWrXCvHnzYG5unmf7tLQ0pKWlKZ8nJSWVWC1ERESkeYoVZqKiokq6jlx5enrCx8cHtra2iIqKwowZM9CmTRtERERALpfnuk1AQABmz579QeojIiIi9Sv258x8CL6+vsp/165dG66urrC1tcX+/fvh7e2d6zZTp07F+PHjlc+TkpJgY2NT6rUSERGRehQrzAwePDjf9evXry9WMQWxsrKCra0t7ty5k2cbuVye56gNERERfXyKFWaePXum8jw9PR3Xr1/H8+fPc/0CypKSkJCA2NhYWFlZldo+iIiISFqKFWZ27dqVY1lWVhZGjBiBKlWqFLqfly9f4u7du8rnUVFRuHr1KkxNTWFqagp/f3/07NkTVlZWiI6OxrRp01C+fHn06NGjOGUTERHRR6hYnzOTa0daWhg3bhyWL19e6G0uX76MevXqoV69egCA8ePHo169epg5cya0tbXx119/wcvLCw4ODhg4cCAcHBxw7tw5KBSKkiqbiIiIJK5ELwC+d+8eMjIyCt3e3d0dQog81x8+fLgkyiIiIqKPWLHCzNt3CwGAEAKPHz/G/v37MXDgwBIpjIiIiKgwihVmrly5ovJcS0sLFSpUwNKlSwu804mIiIioJBUrzJw4caKk6yAiIiIqlve6Zubff//FrVu3IJPJ4ODggAoVKpRUXURERESFUqy7mZKTkzF48GBYWVmhZcuWaNGiBaytrTFkyBCkpKSUdI1EREREeSpWmBk/fjzCw8Oxd+9ePH/+HM+fP8fu3bsRHh6Or7/+uqRrJCIiIspTsaaZfvvtN+zYsQPu7u7KZZ06dYKenh569+6NwMDAkqqPiIiIKF/FGplJSUmBhYVFjuXm5uacZiIiIqIPqlhhxs3NDbNmzUJqaqpy2atXrzB79my4ubmVWHFEREREBSnWNNOKFSvg6emJSpUqoW7dupDJZLh69SrkcjmOHDlS0jUSERER5alYYcbZ2Rl37tzBL7/8gr///htCCPTp0wf9+vWDnp5eSddIRERElKdihZmAgABYWFhg2LBhKsvXr1+Pf//9F5MnTy6R4oiIiIgKUqxrZtauXYsaNWrkWF6rVi2sWbPmvYsiIiIiKqxihZm4uDhYWVnlWF6hQgU8fvz4vYsiIiIiKqxihRkbGxucOXMmx/IzZ87A2tr6vYsiIiIiKqxiXTMzdOhQjB07Funp6WjTpg0A4Pfff8ekSZP4CcBERET0QRUrzEyaNAlPnz7FiBEj8Pr1awCArq4uJk+ejKlTp5ZogURERET5KVaYkclkWLhwIWbMmIHIyEjo6emhevXqkMvlJV0fERERUb6KFWayGRoaomHDhiVVCxEREWmgDSvHlkq/A0avKJF+inUBMBEREZGmYJghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkkro+4CiCh3a1fNLJV+h4+aUyr9EhGpC0dmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjS1BpmTp48ia5du8La2hoymQyhoaEq64UQ8Pf3h7W1NfT09ODu7o4bN26op1giIiLSSGoNM8nJyahbty5WrVqV6/pFixZh2bJlWLVqFS5dugRLS0u0a9cOL168+MCVEhERkaZS69cZeHp6wtPTM9d1QgisWLEC06dPh7e3NwAgJCQEFhYW2Lx5M4YPH/4hSyUiIiINpbHXzERFRSEuLg7t27dXLpPL5WjVqhXOnj2b53ZpaWlISkpSeRAREdHHS2O/aDIuLg4AYGFhobLcwsICDx48yHO7gIAAzJ49u1RrIyLq3rVlqfTr3a5+qfRL9DHT2JGZbDKZTOW5ECLHsrdNnToViYmJykdsbGxpl0hERERqpLEjM5aWlgDejNBYWVkpl8fHx+cYrXmbXC6HXC4v9fqIiIhIM2jsyIy9vT0sLS1x9OhR5bLXr18jPDwcTZs2VWNlREREpEnUOjLz8uVL3L17V/k8KioKV69ehampKSpXroyxY8di/vz5qF69OqpXr4758+dDX18fn332mRqrJiIiIk2i1jBz+fJltG7dWvl8/PjxAICBAwciODgYkyZNwqtXrzBixAg8e/YMjRs3xpEjR6BQKNRVMhEREWkYtYYZd3d3CCHyXC+TyeDv7w9/f/8PVxQRERFJisZeM0NERERUGAwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGka+wnARFQ6+J1CRPSx4cgMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGr9okoiI6ANbu2pmqfQ7fNScUulX03FkhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJE2jw4y/vz9kMpnKw9LSUt1lERERkQYpo+4CClKrVi0cO3ZM+VxbW1uN1RAREZGm0fgwU6ZMGY7GEBERUZ40epoJAO7cuQNra2vY29ujT58+uH//fr7t09LSkJSUpPIgIiKij5dGh5nGjRtjw4YNOHz4MNatW4e4uDg0bdoUCQkJeW4TEBAAY2Nj5cPGxuYDVkxEREQfmkaHGU9PT/Ts2RPOzs7w8PDA/v37AQAhISF5bjN16lQkJiYqH7GxsR+qXCIiIlIDjb9m5m0GBgZwdnbGnTt38mwjl8shl8s/YFVERESkTho9MvOutLQ0REZGwsrKSt2lEBERkYbQ6DAzYcIEhIeHIyoqChcuXECvXr2QlJSEgQMHqrs0IiIi0hAaPc308OFD9O3bF//99x8qVKiAJk2a4Pz587C1tVV3aURERKQhNDrMbN26Vd0lEBERkYbT6GkmIiIiooIwzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkafTdTETZundtWSr9hu49WSr9ElHhldb/b+929UulX9I8HJkhIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJ4xdNUolau2qmuksgUsHXZMnhuSRNxZEZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0fjcTSu/7RoaPmlMq/RIREdH/4cgMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGr9oshR179qyVPoN3XuyVPolIiJpK63fO97t6pdKvyWFIzNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGmSCDOrV6+Gvb09dHV10aBBA5w6dUrdJREREZGG0Pgws23bNowdOxbTp0/HlStX0KJFC3h6eiImJkbdpREREZEG0Pgws2zZMgwZMgRDhw6Fk5MTVqxYARsbGwQGBqq7NCIiItIAGv3dTK9fv0ZERASmTJmisrx9+/Y4e/ZsrtukpaUhLS1N+TwxMREAkJSUlOd+Xr1Ky3Pd+0hPzyiVfvM7FnXjuSw5UjuXr1JLp973/RnxPL5REq91nss3eC5LTn7nMnudEKLgjoQG++effwQAcebMGZXl8+bNEw4ODrluM2vWLAGADz744IMPPvj4CB6xsbEF5gWNHpnJJpPJVJ4LIXIsyzZ16lSMHz9e+TwrKwtPnz6FmZlZntuoW1JSEmxsbBAbGwsjIyN1lyNpPJclh+eyZPA8lhyey5IjhXMphMCLFy9gbW1dYFuNDjPly5eHtrY24uLiVJbHx8fDwsIi123kcjnkcrnKMhMTk9IqsUQZGRlp7ItKanguSw7PZcngeSw5PJclR9PPpbGxcaHaafQFwGXLlkWDBg1w9OhRleVHjx5F06ZN1VQVERERaRKNHpkBgPHjx6N///5wdXWFm5sbfvzxR8TExOB///ufuksjIiIiDaDxYcbX1xcJCQmYM2cOHj9+jNq1a+PAgQOwtbVVd2klRi6XY9asWTmmx6joeC5LDs9lyeB5LDk8lyXnYzuXMiEKc88TERERkWbS6GtmiIiIiArCMENERESSxjBDREREksYwQ0RERJLGMKNBAgICIJPJMHbsWHWXIjn+/v6QyWQqD0tLS3WXJUn//PMPPv/8c5iZmUFfXx8uLi6IiIhQd1mSY2dnl+M1KZPJMHLkSHWXJjkZGRn45ptvYG9vDz09PVSpUgVz5sxBVlaWukuTnBcvXmDs2LGwtbWFnp4emjZtikuXLqm7rPem8bdmfyouXbqEH3/8EXXq1FF3KZJVq1YtHDt2TPlcW1tbjdVI07Nnz9CsWTO0bt0aBw8ehLm5Oe7duyeZT9HWJJcuXUJmZqby+fXr19GuXTv4+PiosSppWrhwIdasWYOQkBDUqlULly9fxqBBg2BsbIwxY8aouzxJGTp0KK5fv46NGzfC2toav/zyCzw8PHDz5k1UrFhR3eUVG8OMBnj58iX69euHdevWYe7cueouR7LKlCnD0Zj3tHDhQtjY2CAoKEi5zM7OTn0FSViFChVUni9YsABVq1ZFq1at1FSRdJ07dw5eXl7o3LkzgDevyS1btuDy5ctqrkxaXr16hd9++w27d+9Gy5YtAbwZ1Q4NDUVgYKCkf/9wmkkDjBw5Ep07d4aHh4e6S5G0O3fuwNraGvb29ujTpw/u37+v7pIkZ8+ePXB1dYWPjw/Mzc1Rr149rFu3Tt1lSd7r16/xyy+/YPDgwRr7hbearHnz5vj9999x+/ZtAMCff/6J06dPo1OnTmquTFoyMjKQmZkJXV1dleV6eno4ffq0mqoqGRyZUbOtW7fijz/++CjmLNWpcePG2LBhAxwcHPDkyRPMnTsXTZs2xY0bN2BmZqbu8iTj/v37CAwMxPjx4zFt2jRcvHgRo0ePhlwux4ABA9RdnmSFhobi+fPn8PPzU3cpkjR58mQkJiaiRo0a0NbWRmZmJubNm4e+ffuquzRJUSgUcHNzw7fffgsnJydYWFhgy5YtuHDhAqpXr67u8t6PILWJiYkR5ubm4urVq8plrVq1EmPGjFFfUR+Jly9fCgsLC7F06VJ1lyIpOjo6ws3NTWXZV199JZo0aaKmij4O7du3F126dFF3GZK1ZcsWUalSJbFlyxZx7do1sWHDBmFqaiqCg4PVXZrk3L17V7Rs2VIAENra2qJhw4aiX79+wsnJSd2lvReOzKhRREQE4uPj0aBBA+WyzMxMnDx5EqtWrUJaWhovYi0mAwMDODs7486dO+ouRVKsrKxQs2ZNlWVOTk747bff1FSR9D148ADHjh3Dzp071V2KZE2cOBFTpkxBnz59AADOzs548OABAgICMHDgQDVXJy1Vq1ZFeHg4kpOTkZSUBCsrK/j6+sLe3l7dpb0Xhhk1atu2Lf766y+VZYMGDUKNGjUwefJkBpn3kJaWhsjISLRo0ULdpUhKs2bNcOvWLZVlt2/f/qi+2PVDCwoKgrm5ufLiVSq6lJQUaGmpXuKpra3NW7Pfg4GBAQwMDPDs2TMcPnwYixYtUndJ74VhRo0UCgVq166tsszAwABmZmY5llP+JkyYgK5du6Jy5cqIj4/H3LlzkZSUxL/aimjcuHFo2rQp5s+fj969e+PixYv48ccf8eOPP6q7NEnKyspCUFAQBg4ciDJl+HZbXF27dsW8efNQuXJl1KpVC1euXMGyZcswePBgdZcmOYcPH4YQAo6Ojrh79y4mTpwIR0dHDBo0SN2lvRf+76KPwsOHD9G3b1/8999/qFChApo0aYLz589zRKGIGjZsiF27dmHq1KmYM2cO7O3tsWLFCvTr10/dpUnSsWPHEBMTw1+67+n777/HjBkzMGLECMTHx8Pa2hrDhw/HzJkz1V2a5CQmJmLq1Kl4+PAhTE1N0bNnT8ybNw86OjrqLu29yIQQQt1FEBERERUXP2eGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaISoy/vz9cXFyUz/38/NC9e3e11ZPtxx9/hI2NDbS0tLBixYpi9xMcHAwTE5MSq4uISga/zoCISs13332Htz9k3N3dHS4uLu8VKIoqKSkJo0aNwrJly9CzZ08YGxt/sH0T0YfBMENEpUYTgkNMTAzS09PRuXNnWFlZqbscIioFnGYi+kQkJydjwIABMDQ0hJWVFZYuXQp3d3eMHTsWACCTyRAaGqqyjYmJCYKDg5XPJ0+eDAcHB+jr66NKlSqYMWMG0tPT89zn29NMfn5+CA8Px3fffQeZTAaZTIaoqChUq1YNS5YsUdnu+vXr0NLSwr179wo8rpiYGHh5ecHQ0BBGRkbo3bs3njx5AuDNtJCzszMAoEqVKpDJZIiOjs63vz///BOtW7eGQqGAkZERGjRogMuXL+fZfu/evWjQoAF0dXVRpUoVzJ49GxkZGcr1iYmJ+OKLL2Bubg4jIyO0adMGf/75p3J99tTc2rVrYWNjA319ffj4+OD58+cFHjsRvcEwQ/SJmDhxIk6cOIFdu3bhyJEjCAsLQ0RERJH6UCgUCA4Oxs2bN/Hdd99h3bp1WL58eaG2/e677+Dm5oZhw4bh8ePHePz4MSpXrozBgwcjKChIpe369evRokULVK1aNd8+hRDo3r07nj59ivDwcBw9ehT37t2Dr68vAMDX1xfHjh0DAFy8eBGPHz+GjY1Nvn3269cPlSpVwqVLlxAREYEpU6bk+Y3Chw8fxueff47Ro0fj5s2bWLt2LYKDgzFv3jxlfZ07d0ZcXBwOHDiAiIgI1K9fH23btsXTp0+V/dy9exfbt2/H3r17cejQIVy9ehUjR47M/4QS0f8RRPTRe/HihShbtqzYunWrcllCQoLQ09MTY8aMEUIIAUDs2rVLZTtjY2MRFBSUZ7+LFi0SDRo0UD6fNWuWqFu3rvL5wIEDhZeXl/J5q1atlPvL9ujRI6GtrS0uXLgghBDi9evXokKFCiI4OLjA4zpy5IjQ1tYWMTExymU3btwQAMTFixeFEEJcuXJFABBRUVEF9ieEEAqFIs99BwUFCWNjY+XzFi1aiPnz56u02bhxo7CyshJCCPH7778LIyMjkZqaqtKmatWqYu3atUKIN+dMW1tbxMbGKtcfPHhQaGlpicePHxeqZqJPHa+ZIfoE3Lt3D69fv4abm5tymampKRwdHYvUz44dO7BixQrcvXsXL1++REZGBoyMjN6rNisrK3Tu3Bnr169Ho0aNsG/fPqSmpsLHx6fAbSMjI2FjY6My2lKzZk2YmJggMjISDRs2LHI948ePx9ChQ7Fx40Z4eHjAx8cnzxGiiIgIXLp0STkSAwCZmZlITU1FSkoKIiIi8PLlS5iZmals9+rVK5UptMqVK6NSpUrK525ubsjKysKtW7dgaWlZ5GMg+tRwmonoEyDeuqMoLzKZLEe7t6+HOX/+PPr06QNPT0/s27cPV65cwfTp0/H69ev3rm/o0KHYunUrXr16haCgIPj6+kJfX7/A7YQQkMlkhV5eGP7+/rhx4wY6d+6M48ePo2bNmti1a1eubbOysjB79mxcvXpV+fjrr79w584d6OrqIisrC1ZWVirrr169ilu3bmHixIl51pBde3GPgehTw5EZok9AtWrVoKOjg/Pnz6Ny5coAgGfPnuH27dto1aoVAKBChQp4/Pixcps7d+4gJSVF+fzMmTOwtbXF9OnTlcsePHhQpDrKli2LzMzMHMs7deoEAwMDBAYG4uDBgzh58mSh+qtZsyZiYmIQGxurHJ25efMmEhMT4eTkVKTa3ubg4AAHBweMGzcOffv2RVBQEHr06JGjXf369XHr1i1Uq1Yt137q16+PuLg4lClTBnZ2dnnuLyYmBo8ePYK1tTUA4Ny5c9DS0oKDg0Oxj4HoU8IwQ/QJMDQ0xJAhQzBx4kSYmZnBwsIC06dPh5bW/w3OtmnTBqtWrUKTJk2QlZWFyZMnq1z4Wq1aNcTExGDr1q1o2LAh9u/fn+eIRV7s7Oxw4cIFREdHw9DQEKamptDS0oK2tjb8/PwwdepUVKtWTWU6LD8eHh6oU6cO+vXrhxUrViAjIwMjRoxAq1at4OrqWqTagDfTPxMnTkSvXr1gb2+Phw8f4tKlS+jZs2eu7WfOnIkuXbrAxsYGPj4+0NLSwrVr1/DXX39h7ty58PDwgJubG7p3746FCxfC0dERjx49woEDB9C9e3dljbq6uhg4cCCWLFmCpKQkjB49Gr179+YUE1EhcZqJ6BOxePFitGzZEt26dYOHhweaN2+OBg0aKNcvXboUNjY2aNmyJT777DNMmDBBZarHy8sL48aNw6hRo+Di4oKzZ89ixowZRaphwoQJ0NbWRs2aNVGhQgXExMQo1w0ZMgSvX7/G4MGDC91f9u3k5cqVQ8uWLeHh4YEqVapg27ZtRaorm7a2NhISEjBgwAA4ODigd+/e8PT0xOzZs3Nt36FDB+zbtw9Hjx5Fw4YN0aRJEyxbtgy2trbK+g4cOICWLVti8ODBcHBwQJ8+fRAdHQ0LCwtlP9WqVYO3tzc6deqE9u3bo3bt2li9enWxjoHoUyQThZlMJ6KPkjo+kTcvZ86cgbu7Ox4+fKjyi/5j5+/vj9DQUFy9elXdpRBJFqeZiEit0tLSEBsbixkzZqB3796fVJAhopLBaSYiUqstW7bA0dERiYmJWLRokcq6TZs2wdDQMNdHrVq1irW/WrVq5dnnpk2bSuKQiOgD4zQTEWmsFy9eKL+a4F06OjrKa1OK4sGDB3l+BYOFhQUUCkWR+yQi9WKYISIiIknjNBMRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJ2v8DuWG7p2B6n7IAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.countplot(\n", + " x = sleep_df_clean[\"quality_of_sleep\"],\n", + " hue = sleep_df_clean[\"sleep_disorder\"],\n", + " data = sleep_df_clean,\n", + " palette = ['#9c9678', '#524e3a', '#a99467']\n", + " # palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + ")\n", + "ax.set_title(\"Distribution of Sleep Quality by Sleep Disorder\", pad=20)" + ] + }, + { + "cell_type": "markdown", + "id": "817afb8c-5309-4a77-9810-8a5fb12cf182", + "metadata": {}, + "source": [ + "#### 2.6 Distribution of Sleep Duration by Sleep Disorder" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "id": "3cab0bef-ae68-4994-9c45-29a4cf3b18a8", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/lr/d46q9z0s2zndy_5npx2_zwq00000gn/T/ipykernel_3819/1466858378.py:1: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.boxplot(\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Distribution of Sleep Duration by Disorder')" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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Fz7R4GTdu3ICdnZ2ivaCgoETAfuedd9CoUSPMmzev1HpfDGrV/VpRbzJuuSGVpKWlISgoCCYmJhg1alSF5tHW1kaLFi3w008/AYBiF1Fl/kVZEefPn8eff/6p1BYREQEjIyM0a9YMABRnvvz1119K/Xbt2lVieXK5vMK1derUCX/88YciZBRbv3499PX11XIqq4GBAVq0aIHt27cr1VVUVISNGzfC3t4e9erVq/RyS/sDADw7+yU9Pb3cf0H7+fmhRo0auHLlCry9vUt9AM+Ci6urK/78888y+xkZGSktu3irQLHjx4/j2rVrlbom0ovKGr9OTk64ePGiUhC5c+cOjh8/XuFly2Qy1KxZU+kP140bN0qcLQVUfGy5ubnBzs4OERERSrtrcnNzERkZqTgTSF0ePHhQ4rsQEREBLS0ttG/fXql9/Pjx+OuvvzBs2DBoa2uXeuBsZc2ePRsXLlzA+PHjFf8QeZlatWph+PDhGDx4MJKTk/Ho0SO1vG/F4+zFcbhlyxalM6AAoEePHjh37hzq1KlT6th+la2EVDncckMvde7cOcW+46ysLBw5cgTh4eHQ1tbGjh07FKdylyYsLAx//PEHunfvjtq1a+PJkydYs2YNACgunmZkZARHR0f8+uuv6NSpE8zNzfHOO++Ue9pyeWxtbdGrVy/MmjULNjY22LhxI6KjoxESEqL4IXv33Xfh5uaGoKAgFBQUwMzMDDt27Cj17ImGDRti+/btWLFiBby8vKClpVXmvyZnzpyp2O8+Y8YMmJub4+eff8bevXuxcOFCmJiYqPSaXhQcHAxfX1907NgRQUFBqFmzJpYvX45z585h06ZNKv2LcN68eTh27BgGDRqEJk2aQE9PD6mpqfjxxx9x584dhIaGljmvk5MT5syZg2+++QYpKSl4//33YWZmhps3b+LUqVOKf2EDwL///W907doVfn5+GD58OOzs7HD37l0kJSXhzJkz2Lp1q9Ky4+Pj8emnn2LAgAFIT0/HN998Azs7O8VurJepzPj9+OOP8e9//xtDhgxBQEAA7ty5g4ULF8LY2LjC72OPHj2wfft2jB49Gv3790d6ejrmzp0LGxubEmcWNWzYEDExMdi9ezdsbGxgZGRU6kUWtbS0sHDhQvj7+6NHjx4YNWoU8vLyEBoaiuzsbCxYsKDC9VWEhYUFvvjiC6SlpaFevXrYt28fVq1ahS+++AK1a9dW6uvr6wsPDw8cOnQIQ4YMKfNSAqXJzs7GiRMnADwLHMUX8Tty5AgGDhyoGDNladGiBXr06IFGjRrBzMwMSUlJ2LBhg1JoedX3zd3dHUOGDMGSJUugo6ODzp0749y5c1i0aFGJcTFnzhxER0ejdevWGDduHNzc3PDkyRNcvXoV+/btQ1hYmMavzfXW0ODBzFTNFZ9tUvyoWbOmsLKyEj4+PmL+/PkiKyurxDwvnkUTFxcnPvjgA+Ho6CjkcrmwsLAQPj4+YteuXUrzHTx4UDRt2lTI5XKlMxCKl3fr1q2XrkuI/52BsW3bNuHp6Slq1qwpnJycxA8//FBi/osXL4ouXboIY2NjYWlpKcaOHSv27t1b4mypu3fviv79+wtTU1Mhk8mU1olSzvL673//K3r27ClMTExEzZo1RePGjUV4eLhSn+KzYbZu3arUXnwWxYv9S3PkyBHx3nvvCQMDA6Gnpydatmwpdu/eXeryKnK21IkTJ8SYMWNE48aNhbm5udDW1haWlpbi/fffF/v27VPqW9p7L4QQO3fuFB07dhTGxsZCLpcLR0dH0b9/f3Hw4EGlfn/++acYOHCgsLKyEjo6OsLa2lq89957IiwsTNGnePxFRUWJjz/+WJiamgo9PT3RrVs3cenSpZe+HlXGrxBCrFu3Tri7uwtdXV3h4eEhNm/eXObZUmW9rwsWLBBOTk5CLpcLd3d3sWrVqlLfs8TERNGmTRuhr68vACjO1CrtrL3i97dFixZCV1dXGBgYiE6dOoljx44p9SnrO1PWGYIv8vHxEZ6eniImJkZ4e3sLuVwubGxsxLRp00qc4VZs1qxZAoA4ceJEuct+nqOjo+KzkclkwtDQULi5uYmPP/5YHDhwoNR5Xvy+ff3118Lb21uYmZkJuVwuXFxcRGBgoLh9+7bSfK/yvgkhRF5enpg4caKwsrISurq6omXLliIuLk44OjqWONvt1q1bYty4ccLZ2Vno6OgIc3Nz4eXlJb755hvx8OFDIUTlvpekGpkQr3i6ABFRFVi7di0++eQTnD59utzjLkjzvL29IZPJcPr0aU2XQgSAu6WIiEgFOTk5OHfuHPbs2YOEhIRyLxBJ9Lox3BARUaWdOXMGHTt2hIWFBWbOnFni5p9EmsTdUkRERCQpPBWciIiIJIXhhoiIiCSF4YaIiIgk5a08oLioqAjXr1+HkZERL39NRET0hhBC4MGDB7C1tVW6GeqL3spwc/369RJ3bSYiIqI3Q3p6erlXe34rw03xvWvS09MrdVl1IiIi0pycnBw4ODiUuAfdi97KcFO8K8rY2JjhhoiI6A3zskNKeEAxERERSQrDDREREUkKww0RERFJCsMNERERSQrDDREREUkKww0RERFJCsMNERERSQrDDREREUkKww0RERFJCsMNERERSYpGw01BQQGmT58OZ2dn6OnpwcXFBXPmzEFRUVGZ88TExEAmk5V4/P3336+xciIiIqquNHpvqZCQEISFhWHdunXw9PREfHw8PvnkE5iYmGD8+PHlzpucnKx0XyhLS8uqLpeIiIjeABoNN3Fxcejduze6d+8OAHBycsKmTZsQHx//0nmtrKxgampaxRUSERHRm0aj4aZt27YICwvDxYsXUa9ePfz55584evQolixZ8tJ5mzZtiidPnsDDwwPTp09Hx44dy+ybl5eHvLw8xfOcnBx1lK9Rjx8/RmpqqqbLqDaKd20SERFpNNxMmTIF9+/fR/369aGtrY3CwkLMmzcPgwcPLnMeGxsbrFy5El5eXsjLy8OGDRvQqVMnxMTEoH379qXOExwcjNmzZ1fVy9CI1NRUDBgwQNNlVBtbt26Fh4eHpssgIqJqQCaEEJpa+S+//IJJkyYhNDQUnp6eSExMxFdffYUffvgBw4YNq/ByevbsCZlMhl27dpU6vbQtNw4ODrh//77ScTtvkuqw5SYlJQVTpkxBSEgIXFxcNFoLt9wQEUlfTk4OTExMXvr3W6NbbiZNmoSvv/4aH374IQCgYcOGuHbtGoKDgysVblq2bImNGzeWOV0ul0Mul79yvdWJnp5etdlS4eLiUm1qISIi0uip4I8ePYKWlnIJ2tra5Z4KXpqzZ8/CxsZGnaURERHRG0qjW2569uyJefPmoXbt2vD09MTZs2fxww8/YMSIEYo+U6dORUZGBtavXw8AWLJkCZycnODp6Yn8/Hxs3LgRkZGRiIyM1NTLICIiompEo+Fm2bJl+PbbbzF69GhkZWXB1tYWo0aNwowZMxR9MjMzkZaWpnien5+PoKAgZGRkQE9PD56enti7dy+6deumiZdARERE1YxGDyjWlIoekETlu3DhAgYMGMAzlYiI6LWo6N9v3luKiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJKWGpgsgIiKSqsLCQiQkJODWrVuwtLSEl5cXtLW1NV2W5DHcEBERVYHo6GiEhoYiIyND0WZnZ4dJkybB19dXg5VJH3dLERERqVl0dDQCAwPh6uqKiIgInDp1ChEREXB1dUVgYCCio6M1XaKkMdwQERGpUWFhIUJDQ+Hj44Nly5ahcePGMDAwQOPGjbFs2TL4+Phg0aJFKCws1HSpksVwQ0REpEYJCQnIyMjAZ599Bi0t5T+zWlpaCAgIwD///IOEhAQNVSh9DDdERERqdOvWLQBA3bp1S53u6uqq1I/Uj+GGiIhIjSwtLQEAly9fLnX6pUuXlPqR+jHcEBERqZGXlxfs7OywcuVKFBUVKU0rKirCqlWrYG9vDy8vLw1VKH0MN0RERGqkra2NSZMmITY2FmPHjkViYiJyc3ORmJiIsWPHIjY2FkFBQbzeTRXidW6IiIjUzNfXF4sXL0ZoaCj8/f0V7fb29li8eDGvc1PFGG6IiIiqgK+vL9577z1eoVgDGG6IiIiqiLa2Npo3b67pMt46POaGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIUHFBORWjx+/BipqamaLqNacXZ2hp6enqbLIHrrMNwQkVqkpqZiwIABmi6jWtm6dSs8PDw0XQbRW4fhhojUwtnZGVu3btV0GUhJScGUKVMQEhICFxcXjdbi7Oys0fUTva0YbohILfT09KrVVgoXF5dqVQ8RvT48oJiIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCRFo+GmoKAA06dPh7OzM/T09ODi4oI5c+agqKio3PliY2Ph5eUFXV1duLi4ICws7DVVTERERNVdDU2uPCQkBGFhYVi3bh08PT0RHx+PTz75BCYmJhg/fnyp86SmpqJbt24ICAjAxo0bcezYMYwePRqWlpbo16/fa34FREREVN1oNNzExcWhd+/e6N69OwDAyckJmzZtQnx8fJnzhIWFoXbt2liyZAkAwN3dHfHx8Vi0aBHDDREREWl2t1Tbtm3x+++/4+LFiwCAP//8E0ePHkW3bt3KnCcuLg5dunRRavPz80N8fDyePn1a6jx5eXnIyclRehAREZE0aXTLzZQpU3D//n3Ur18f2traKCwsxLx58zB48OAy57lx4wZq1aql1FarVi0UFBTg9u3bsLGxKTFPcHAwZs+erfb6iYiIqPrR6JabzZs3Y+PGjYiIiMCZM2ewbt06LFq0COvWrSt3PplMpvRcCFFqe7GpU6fi/v37ikd6erp6XgARERFVOxrdcjNp0iR8/fXX+PDDDwEADRs2xLVr1xAcHIxhw4aVOo+1tTVu3Lih1JaVlYUaNWrAwsKi1Hnkcjnkcrl6iyciIqJqSaNbbh49egQtLeUStLW1yz0VvFWrVoiOjlZqi4qKgre3N3R0dKqkTiIiInpzaDTc9OzZE/PmzcPevXtx9epV7NixAz/88AM++OADRZ+pU6di6NChiueff/45rl27hgkTJiApKQlr1qzB6tWrERQUpImXQERERNWMRndLLVu2DN9++y1Gjx6NrKws2NraYtSoUZgxY4aiT2ZmJtLS0hTPnZ2dsW/fPgQGBuKnn36Cra0tli5dytPA6a13/fp1ZGdna7oMjUtJSVH679vM1NQUtra2mi6D6LWTieKjcd8iOTk5MDExwf3792FsbKzpct5YFy5cwIABA7B161Z4eHhoupy32vXr19GjRw/k5eVpuhSqRuRyOfbs2cOAQ5JR0b/fGt1yQ0TqkZ2djby8PNSyNETNmtqaLoeqgfz8Qty89RDZ2dkMN/TWYbghkpCaNbWhK+fXmojebrwrOBEREUkKww0RERFJCsMNERERSQrDDREREUkKww0RERFJCsMNERERSQrDDREREUkKww0RERFJCsMNERERSQrDDREREUkKww0RERFJCm9CQ0REVEUKCwuRkJCAW7duwdLSEl5eXtDW5s1tqxrDDRERURWIjo5GaGgoMjIyFG12dnaYNGkSfH19NViZ9HG3FBERkZpFR0cjMDAQrq6uiIiIwKlTpxAREQFXV1cEBgYiOjpa0yVKGsMNERGRGhUWFiI0NBQ+Pj5YtmwZGjduDAMDAzRu3BjLli2Dj48PFi1ahMLCQk2XKlncLaWi69evIzs7W9NlaFRKSorSf99mpqamsLW11XQZRFQNJCQkICMjA6GhodDSUt6GoKWlhYCAAPj7+yMhIQHNmzfXUJXSxnCjguvXr6Nnjx54kpen6VKqhSlTpmi6BI3Tlcuxe88eBhwiwq1btwAAdevWLXW6q6urUj9SP4YbFWRnZ+NJXh66dHoX5mZGmi6HNOzuvQeI+v00srOzGW6ICJaWlgCAy5cvo3HjxiWmX7p0SakfqR/DzSswNzOClaWZpssgIqJqxMvLC3Z2dli5ciWWLVumtGuqqKgIq1atgr29Pby8vDRYpbTxgGIiIiI10tbWxqRJkxAbG4uxY8ciMTERubm5SExMxNixYxEbG4ugoCBe76YKccsNERGRmvn6+mLx4sUIDQ2Fv7+/ot3e3h6LFy/mdW6qGMMNERFRFfD19cV7773HKxRrAMMNERFRFdHW1ubp3hrAY26IiIhIUhhuiIiISFIYboiIiEhSGG6IiIhIUhhuiIiISFIYboiIiEhSGG6IiIhIUhhuiIiISFIYboiIiEhSGG6IiIhIUhhuiIiISFIYboiIiEhSGG6IiIhIUnhXcCIioipSWFiIhIQE3Lp1C5aWlvDy8oK2tramy5I8hhsiIqIqEB0djdDQUGRkZCja7OzsMGnSJPj6+mqwMunjbikiIiI1i46ORmBgIFxdXREREYFTp04hIiICrq6uCAwMRHR0tKZLlDSGGyIiIjUqLCxEaGgofHx8sGzZMjRu3BgGBgZo3Lgxli1bBh8fHyxatAiFhYWaLlWyGG6IiIjUKCEhARkZGfjss8+gpaX8Z1ZLSwsBAQH4559/kJCQoKEKpY/hhoiISI1u3boFAKhbt26p011dXZX6kfox3BAREamRpaUlAODy5culTr906ZJSP1I/hhsiIiI18vLygp2dHVauXImioiKlaUVFRVi1ahXs7e3h5eWloQqlj+GGiIhIjbS1tTFp0iTExsZi7NixSExMRG5uLhITEzF27FjExsYiKCiI17upQrzODRERkZr5+vpi8eLFCA0Nhb+/v6Ld3t4eixcv5nVuqhjDDRERURXw9fXFe++9xysUawDDDRERURXR1tZG8+bNNV3GW0flcJOdnY1Tp04hKyurxAFTQ4cOfeXCiIiIiFShUrjZvXs3/P39kZubCyMjI8hkMsU0mUxW4XDj5OSEa9eulWgfPXo0fvrppxLtMTEx6NixY4n2pKQk1K9fvxKvgIiIiKRKpXAzceJEjBgxAvPnz4e+vr7KKz99+rTS5afPnTsHX19fDBgwoNz5kpOTYWxsrHjOawUQERFRMZXCTUZGBsaNG/dKwQYoGUoWLFiAOnXqwMfHp9z5rKysYGpq+krrJiIiImlS6To3fn5+iI+PV2sh+fn52LhxI0aMGKG0m6s0TZs2hY2NDTp16oRDhw69dNl5eXnIyclRehAREZE0qbTlpnv37pg0aRIuXLiAhg0bQkdHR2l6r169Kr3MnTt3Ijs7G8OHDy+zj42NDVauXAkvLy/k5eVhw4YN6NSpE2JiYtC+ffsy5wsODsbs2bMrXRMRERG9eVQKNwEBAQCAOXPmlJgmk8lUuo376tWr0bVrV9ja2pbZx83NDW5ubornrVq1Qnp6OhYtWlRuuJk6dSomTJigeJ6TkwMHB4dK10hERETVn0rh5sVTv1/VtWvXcPDgQWzfvr3S87Zs2RIbN24st49cLodcLle1PCIiInqDVIt7S4WHh8PKygrdu3ev9Lxnz56FjY1NFVRFREREbyKVL+IXGxuLRYsWISkpCTKZDO7u7pg0aRLatWtXqeUUFRUhPDwcw4YNQ40ayuVMnToVGRkZWL9+PQBgyZIlcHJygqenp+IA5MjISERGRqr6MoiIiEhiVNpys3HjRnTu3Bn6+voYN24cvvzyS+jp6aFTp06IiIio1LIOHjyItLQ0jBgxosS0zMxMpKWlKZ7n5+cjKCgIjRo1Qrt27XD06FHs3bsXffv2VeVlEBERkQSptOVm3rx5WLhwIQIDAxVt48ePxw8//IC5c+fio48+qvCyunTpAiFEqdPWrl2r9Hzy5MmYPHmyKiUTERHRW0KlLTcpKSno2bNnifZevXohNTX1lYsiIiIiUpVK4cbBwQG///57ifbff/+dp1gTERGRRql8b6lx48YhMTERrVu3hkwmw9GjR7F27Vr861//UneNRERERBWmUrj54osvYG1tje+//x5btmwBALi7u2Pz5s3o3bu3WgskIiIiqgyVTwX/4IMP8MEHH6izFiIiIqJXVi0u4kdERESkLhXecmNubo6LFy/inXfegZmZWbl37r57965aiiMiIiKqrAqHm8WLF8PIyEjx/+WFGyIiIiJNqXC4GTZsmOL/hw8fXhW1EBEREb0ylY650dbWRlZWVon2O3fuQFtb+5WLIiIiIlKVSuGmrNsl5OXloWbNmq9UEBEREdGrqNSp4EuXLgUAyGQy/Oc//4GhoaFiWmFhIQ4fPoz69eurt0IiIiKiSqhUuFm8eDGAZ1tuwsLClHZB1axZE05OTggLC1NvhURERESVUKlwU3xTzI4dO2L79u0wMzOrkqKIiIiIVKXSFYoPHTqk7jqIiIiI1ELl2y/8888/2LVrF9LS0pCfn6807YcffnjlwoiIiIhUoVK4+f3339GrVy84OzsjOTkZDRo0wNWrVyGEQLNmzdRdIxEREVGFqRRupk6diokTJ2LOnDkwMjJCZGQkrKys4O/vj/fff1/dNVZbd+890HQJVA1wHBBVX48fP1YcL0qAs7Mz9PT0NF1GlVMp3CQlJWHTpk3PFlCjBh4/fgxDQ0PMmTMHvXv3xhdffKHWIqurqN9Pa7oEIiIqR2pqKgYMGKDpMqqNrVu3wsPDQ9NlVDmVwo2BgQHy8vIAALa2trhy5Qo8PT0BALdv31ZfddVcl07vwtzMSNNlkIbdvfeAQZeomnJ2dsbWrVs1WkNKSgqmTJmCkJAQuLi4aLQWZ2dnja7/dVEp3LRs2RLHjh2Dh4cHunfvjokTJ+K///0vtm/fjpYtW6q7xmrL3MwIVpY8HZ6IqLrS09OrNlsqXFxcqk0tUqdSuPnhhx/w8OFDAMCsWbPw8OFDbN68GXXr1lVc6I+IiIhIEyodbgoLC5Geno5GjRoBAPT19bF8+XK1F0ZERESkikrfOFNbWxt+fn7Izs6ugnKIiIiIXo1KdwVv2LAhUlJS1F0LERER0StTKdzMmzcPQUFB2LNnDzIzM5GTk6P0ICIiItIUlQ4oLr5QX69evSCTyRTtQgjIZDIUFhaqpzoiIiKiSuKNM4mIiEhSVAo3Pj4+6q6DiIiISC1UCjeHDx8ud3r79u1VKoaIiIjoVakUbjp06FCi7fljb3jMDREREWmKSmdL3bt3T+mRlZWF3377De+++y6ioqLUXSMRERFRham05cbExKREm6+vL+RyOQIDA5GQkPDKhRERERGpQqUtN2WxtLREcnKyOhdJREREVCkqbbn566+/lJ4LIZCZmYkFCxagcePGaimMiIiISBUqhZsmTZpAJpNBCKHU3rJlS6xZs0YthRERERGpQqVwk5qaqvRcS0sLlpaW0NXVVUtRRERERKpSKdw4Ojqquw4iIiIitahwuFm6dGmFFzpu3DiViiEiIiJ6VRUON4sXL1Z6fuvWLTx69AimpqYAgOzsbOjr68PKyorhhoiIiDSmwqeCp6amKh7z5s1DkyZNkJSUhLt37+Lu3btISkpCs2bNMHfu3Kqsl4iIiKhcKl3n5ttvv8WyZcvg5uamaHNzc8PixYsxffp0tRVHREREVFkqhZvMzEw8ffq0RHthYSFu3rz5ykURERERqUqlcNOpUycEBAQgPj5eca2b+Ph4jBo1Cp07d1ZrgURERESVoVK4WbNmDezs7NC8eXPo6upCLpejRYsWsLGxwX/+8x9110hERERUYSpd58bS0hL79u3DpUuXkJSUBCEE3N3dUa9ePXXXR0RERFQpKoWbYq6urnB1dS1zurGxMRITE+Hi4vIqqyEiIiKqMLXeFfxFL957ioiIiKiqVWm4ISIiInrdGG6IiIhIUhhuiIiISFKqNNzIZLJypzs5OUEmk5V4jBkzpsx5YmNj4eXlBV1dXbi4uCAsLEzdZRMREdEbTKMHFJ8+fRqZmZmKR3R0NABgwIABpfZPTU1Ft27d0K5dO5w9exbTpk3DuHHjEBkZqfbaiYiI6M30SqeCA/8LMKVtpdm/fz/s7OzKnNfS0lLp+YIFC1CnTh34+PiU2j8sLAy1a9fGkiVLAADu7u6Ij4/HokWL0K9fPxVfAREREUmJyltuVq9ejQYNGkBXVxe6urpo0KBBiasTt23bFnK5vELLy8/Px8aNGzFixIgyd2fFxcWhS5cuSm1+fn6Ij48v9V5XxfLy8pCTk6P0ICIiImlS+a7g48ePR8+ePbF161Zs3boVPXv2RGBgoMp3Bd+5cyeys7MxfPjwMvvcuHEDtWrVUmqrVasWCgoKcPv27TLnCw4OhomJieLh4OCgUo1ERERU/am0W2rFihVYtWoVBg8erGjr1asXGjVqhLFjx+K7776r9DJXr16Nrl27wtbWttx+L27VKW+3WLGpU6diwoQJiuc5OTkMOERERBKlUrgpLCyEt7d3iXYvLy8UFBRUennXrl3DwYMHsX379nL7WVtb48aNG0ptWVlZqFGjBiwsLMqcTy6XV3j3GBEREb3ZVNotNWTIEKxYsaJE+8qVK+Hv71/p5YWHh8PKygrdu3cvt1+rVq0UZ1QVi4qKgre3N3R0dCq9XiIiIpIelc+WWr16NaKiotCyZUsAwIkTJ5Ceno6hQ4cq7QL64Ycfyl1OUVERwsPDMWzYMNSooVzO1KlTkZGRgfXr1wMAPv/8c/z444+YMGECAgICEBcXh9WrV2PTpk2qvgwiIiKSGJXCzblz59CsWTMAwJUrVwA8O63b0tIS586dU/R72UX8AODgwYNIS0vDiBEjSkzLzMxEWlqa4rmzszP27duHwMBA/PTTT7C1tcXSpUt5GjgREREpqBRuDh06pLYCunTpUubF/tauXVuizcfHB2fOnFHb+omIiEhaXukKxZcvX8aBAwfw+PFjAC+/IjERERFRVVMp3Ny5cwedOnVCvXr10K1bN2RmZgIAPv30U0ycOFGtBRIRERFVhkrhJjAwEDo6OkhLS4O+vr6ifdCgQfjtt9/UVhwRERFRZal0zE1UVBQOHDgAe3t7pXZXV1dcu3ZNLYURERERqUKlLTe5ublKW2yK3b59mxfLIyIiIo1SactN+/btsX79esydOxfAs1O+i4qKEBoaio4dO6q1wOrs7r0Hmi6BqgGOAyKi6kWlcBMaGooOHTogPj4e+fn5mDx5Ms6fP4+7d+/i2LFj6q6x2jE1NYWuXI6o309ruhSqJnTlcpiammq6DCIigorhxsPDA3/99ReWL18ObW1t5Obmom/fvhgzZgxsbGzUXWO1Y2tri9179iA7O1vTpWhUSkoKpkyZgpCQELi4uGi6HI0yNTV96U1fiYjo9VD59gvW1taYM2eOOmt5o9ja2vKP2f9zcXGBh4eHpssgIiIC8AoX8Tty5AiGDBmC1q1bIyMjAwCwYcMGHD16VG3FEREREVWWSuEmMjISfn5+0NPTw5kzZ5CXlwcAePDgAebPn6/WAomIiIgqQ6Vw89133yEsLAyrVq2Cjo6Oor1169a87xMRERFplErhJjk5Ge3bty/Rbmxs/NYfZEtERESapVK4sbGxweXLl0u0Hz169K0/a4aIiIg0S6VwM2rUKIwfPx4nT56ETCbD9evX8fPPPyMoKAijR49Wd41EREREFabSqeCTJ0/G/fv30bFjRzx58gTt27eHXC5HUFAQvvzyS3XXSERERFRhKl/nZt68efjmm29w4cIFFBUVwcPDA4aGhuqsjYiIiKjSVA43AKCvrw9vb2911UJERBJz/fr1t/5Ek5SUFKX/vs1e19XcKxxu+vbtW+GFbt++XaViiIhIOq5fv46ePXrgyf9fC+1tN2XKFE2XoHG6cjl279lT5QGnwuHGxMSkKusgIiKJyc7OxpO8PPR4rwEsTA00XQ5p2J3sXOz54xyys7OrT7gJDw9X/P/jx49RVFQEA4Nng/Xq1avYuXMn3N3d4efnp/4qiYjojWVhagBrS2NNl0FvEZVOBe/duzc2bNgA4Fkyb9myJb7//nv06dMHK1asUGuBRERERJWhUrg5c+YM2rVrBwDYtm0batWqhWvXrmH9+vVYunSpWgskIiIiqgyVws2jR49gZGQEAIiKikLfvn2hpaWFli1b4tq1a2otkIiIiKgyVAo3devWxc6dO5Geno4DBw6gS5cuAICsrCwYG3O/KhEREWmOSuFmxowZCAoKgpOTE1q0aIFWrVoBeLYVp2nTpmotkIiIiKgyVLqIX//+/dG2bVtkZmaicePGivZOnTrhgw8+UFtxRERERJWl8hWKra2tYW1trdTWvHnzVy6IiIiI6FWotFuKiIiIqLpiuCEiIiJJeaUbZxJR9ZKfX6jpEqia4FigtxnDDZGE3Lz1UNMlEBFpHMMNkYTUsjREzZrami6DqoH8/EKGXXprMdwQSUjNmtrQlfNrTURvNx5QTERERJLCcENERESSwnBDREREksJwQ0RERJLCcENERESSwnBDREREksJwQ0RERJLCcENERESSwnBDREREksJwQ0RERJLCcENERESSwnBDREREksJwQ0RERJLCcENERESSwnBDREREksJwQ0RERJLCcENERESSwnBDREREkqLxcJORkYEhQ4bAwsIC+vr6aNKkCRISEsrsHxMTA5lMVuLx999/v8aqiYiIqLqqocmV37t3D23atEHHjh2xf/9+WFlZ4cqVKzA1NX3pvMnJyTA2NlY8t7S0rMJKiYiI6E2h0XATEhICBwcHhIeHK9qcnJwqNK+VlVWFQhARERG9XTQabnbt2gU/Pz8MGDAAsbGxsLOzw+jRoxEQEPDSeZs2bYonT57Aw8MD06dPR8eOHcvsm5eXh7y8PMXznJwctdRPREQvd+derqZLoGrgdY4DjYablJQUrFixAhMmTMC0adNw6tQpjBs3DnK5HEOHDi11HhsbG6xcuRJeXl7Iy8vDhg0b0KlTJ8TExKB9+/alzhMcHIzZs2dX5UshIqIy7Dl0TtMl0FtGo+GmqKgI3t7emD9/PoBnW2POnz+PFStWlBlu3Nzc4ObmpnjeqlUrpKenY9GiRWWGm6lTp2LChAmK5zk5OXBwcFDjKyEiorL06NgAFmYGmi6DNOzOvdzXFnQ1Gm5sbGzg4eGh1Obu7o7IyMhKLadly5bYuHFjmdPlcjnkcrlKNRIR0auxMDOAtaXxyzsSqYlGTwVv06YNkpOTldouXrwIR0fHSi3n7NmzsLGxUWdpRERE9IbS6JabwMBAtG7dGvPnz8fAgQNx6tQprFy5EitXrlT0mTp1KjIyMrB+/XoAwJIlS+Dk5ARPT0/k5+dj48aNiIyMrPTWHiIiIpImjYabd999Fzt27MDUqVMxZ84cODs7Y8mSJfD391f0yczMRFpamuJ5fn4+goKCkJGRAT09PXh6emLv3r3o1q2bJl4CERERVTMaDTcA0KNHD/To0aPM6WvXrlV6PnnyZEyePLmKqyIiIqI3lcZvv0BERESkTgw3REREJCkMN0RERCQpDDdEREQkKRo/oJiIiKTtTjbvLUWvdxww3BARUZUwNTWFrlyOPX/w3lL0jK5cDlNT0ypfD8MNERFVCVtbW+zeswfZ2dmaLkWjUlJSMGXKFISEhMDFxUXT5WiUqakpbG1tq3w9DDdERFRlbG1tX8sfszeBi4tLifspUtXgAcVEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpNTRdABGpT35+oaZLoGqCY4HeZgw3RBJgamoKuVyOm7cearoUqkbkcjlMTU01XQbRa8dwQyQBtra22LNnD7KzszVdisalpKRgypQpCAkJgYuLi6bL0ShTU1PY2tpqugyi147hhkgibG1t+YfsOS4uLvDw8NB0GUSkATygmIiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJEXj4SYjIwNDhgyBhYUF9PX10aRJEyQkJJQ7T2xsLLy8vKCrqwsXFxeEhYW9pmqJiIioutPodW7u3buHNm3aoGPHjti/fz+srKxw5cqVcq+omZqaim7duiEgIAAbN27EsWPHMHr0aFhaWqJfv36vr3giIiKqljQabkJCQuDg4IDw8HBFm5OTU7nzhIWFoXbt2liyZAkAwN3dHfHx8Vi0aBHDDREREWk23OzatQt+fn4YMGAAYmNjYWdnh9GjRyMgIKDMeeLi4tClSxelNj8/P6xevRpPnz6Fjo5OiXny8vKQl5eneJ6Tk6O+F6Ehjx8/RmpqqkZrSElJUfqvJjk7O0NPT0/TZRARUTWg0XCTkpKCFStWYMKECZg2bRpOnTqFcePGQS6XY+jQoaXOc+PGDdSqVUuprVatWigoKMDt27dhY2NTYp7g4GDMnj27Sl6DpqSmpmLAgAGaLgMAMGXKFE2XgK1bt/JS+0REBEDD4aaoqAje3t6YP38+AKBp06Y4f/48VqxYUWa4AQCZTKb0XAhRanuxqVOnYsKECYrnOTk5cHBweNXyNcrZ2Rlbt27VdBnVhrOzs6ZLICKiakKj4cbGxqbEv7bd3d0RGRlZ5jzW1ta4ceOGUltWVhZq1KgBCwuLUueRy+WQy+WvXnA1oqenxy0VREREpdDoqeBt2rRBcnKyUtvFixfh6OhY5jytWrVCdHS0UltUVBS8vb1LPd6GiIiI3i4aDTeBgYE4ceIE5s+fj8uXLyMiIgIrV67EmDFjFH2mTp2qtIvq888/x7Vr1zBhwgQkJSVhzZo1WL16NYKCgjTxEoiIiKia0Wi4effdd7Fjxw5s2rQJDRo0wNy5c7FkyRL4+/sr+mRmZiItLU3x3NnZGfv27UNMTAyaNGmCuXPnYunSpTwNnIiIiABo+JgbAOjRowd69OhR5vS1a9eWaPPx8cGZM2eqsCoiIiJ6U2n89gtERERE6sRwQ0RERJLCcENERESSwnBDREREkqLxA4qJiIiqCu/Dp+xtuQ8fww0REUkW78On7G25Dx/DDRERSRbvw6fsbbkPH8MNERFJFu/D93biAcVEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpDDdEREQkKQw3REREJCkMN0RERCQpvEIxEalFdbhBIcCbFBIRww0RqUl1ukEhwJsUEr3NGG6ISC14g8KS3pabFBJVNww3RKQWvEEhEVUXPKCYiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJIXhhoiIiCSF4YaIiIgkheGGiIiIJOWtvCu4EAIAkJOTo+FKiIiIqKKK/24X/x0vy1sZbh48eAAAcHBw0HAlREREVFkPHjyAiYlJmdNl4mXxR4KKiopw/fp1GBkZQSaTabqcN1ZOTg4cHByQnp4OY2NjTZdDBIDjkqofjkn1EULgwYMHsLW1hZZW2UfWvJVbbrS0tGBvb6/pMiTD2NiYX1iqdjguqbrhmFSP8rbYFOMBxURERCQpDDdEREQkKQw3pDK5XI6ZM2dCLpdruhQiBY5Lqm44Jl+/t/KAYiIiIpIubrkhIiIiSWG4ISIiIklhuCEiIiJJYbihCunQoQO++uqrt2a9pBqZTIadO3dqugwiSbt69SpkMhkSExM1XUq1xXBTzQ0fPhwymQwLFixQat+5c+crX1157dq1kMlkkMlk0NbWhpmZGVq0aIE5c+bg/v37Sn23b9+OuXPnvtL66M2WlZWFUaNGoXbt2pDL5bC2toafnx/i4uI0XVqZIiIioK2tjc8//1zTpVA1MXz4cPTp00fTZbwSBwcHZGZmokGDBpoupdpiuHkD6OrqIiQkBPfu3VP7so2NjZGZmYl//vkHx48fx2effYb169ejSZMmuH79uqKfubk5jIyM1L5+4NnltAsKCqpk2YWFhSgqKqqSZb9t+vXrhz///BPr1q3DxYsXsWvXLnTo0AF3797VdGllWrNmDSZPnoxffvkFjx490nQ5RGqhra0Na2tr1KjxVt5koEIYbt4AnTt3hrW1NYKDg8vtFxkZCU9PT8jlcjg5OeH7779/6bJlMhmsra1hY2MDd3d3jBw5EsePH8fDhw8xefJkRb8Xdw8tX74crq6u0NXVRa1atdC/f3/FtLy8PIwbNw5WVlbQ1dVF27Ztcfr0acX0mJgYyGQyHDhwAN7e3pDL5Thy5Ahyc3MxdOhQGBoawsbGptT68/PzMXnyZNjZ2cHAwAAtWrRATEyMYvratWthamqKPXv2wMPDA3K5HNeuXXvp+0Dly87OxtGjRxESEoKOHTvC0dERzZs3x9SpU9G9e/cy58vIyMCgQYNgZmYGCwsL9O7dG1evXlXqEx4eDnd3d+jq6qJ+/fpYvny5Ylrx5vdffvkFrVu3hq6uLjw9PZU+87JcvXoVx48fx9dff4369etj27ZtStOLx8rOnTtRr1496OrqwtfXF+np6Yo+s2bNQpMmTbBhwwY4OTnBxMQEH374oeLmu8CzcL5w4UK4uLhAT08PjRs3VlpXYWEhRo4cCWdnZ+jp6cHNzQ3/+te/Xlo/Vb0OHTpg3LhxmDx5MszNzWFtbY1Zs2Yp9Zk1a5Zia6WtrS3GjRunmHbv3j0MHToUZmZm0NfXR9euXXHp0iXF9Od/j9zc3KCvr4/+/fsjNzcX69atg5OTE8zMzDB27FgUFhYq5nNycsL8+fMxYsQIGBkZoXbt2li5cqVi+ou7pTjGSiGoWhs2bJjo3bu32L59u9DV1RXp6elCCCF27Nghnv/44uPjhZaWlpgzZ45ITk4W4eHhQk9PT4SHh5e57PDwcGFiYlLqtPHjxwsjIyNRUFAghBDCx8dHjB8/XgghxOnTp4W2traIiIgQV69eFWfOnBH/+te/FPOOGzdO2Nrain379onz58+LYcOGCTMzM3Hnzh0hhBCHDh0SAESjRo1EVFSUuHz5srh9+7b44osvhL29vYiKihJ//fWX6NGjhzA0NFSsVwghPvroI9G6dWtx+PBhcfnyZREaGirkcrm4ePGi4jXp6OiI1q1bi2PHjom///5bPHz4sLJvO73g6dOnwtDQUHz11VfiyZMnZfYDIHbs2CGEECI3N1e4urqKESNGiL/++ktcuHBBfPTRR8LNzU3k5eUJIYRYuXKlsLGxEZGRkSIlJUVERkYKc3NzsXbtWiGEEKmpqQKAsLe3F9u2bRMXLlwQn376qTAyMhK3b98ut+Zvv/1W9O/fXwghxLJly0T79u2VphePFW9vb3H8+HERHx8vmjdvLlq3bq3oM3PmTGFoaCj69u0r/vvf/4rDhw8La2trMW3aNEWfadOmifr164vffvtNXLlyRYSHhwu5XC5iYmKEEELk5+eLGTNmiFOnTomUlBSxceNGoa+vLzZv3lzBd5/Uqfg3VYhnv2vGxsZi1qxZ4uLFi2LdunVCJpOJqKgoIYQQW7duFcbGxmLfvn3i2rVr4uTJk2LlypWKZfXq1Uu4u7uLw4cPi8TEROHn5yfq1q0r8vPzhRD/G2O+vr7izJkzIjY2VlhYWIguXbqIgQMHivPnz4vdu3eLmjVril9++UWxXEdHR2Fubi5++ukncenSJREcHCy0tLREUlKSEOJ/34uzZ88KITjGSsNwU809/0Vs2bKlGDFihBCiZLj56KOPhK+vr9K8kyZNEh4eHmUuu7xws2LFCgFA3Lx5UwihHG4iIyOFsbGxyMnJKTHfw4cPhY6Ojvj5558Vbfn5+cLW1lYsXLhQCPG/cLNz505FnwcPHpT4gt+5c0fo6ekp1nv58mUhk8lERkaG0jo7deokpk6dqnhNAERiYmKZr5tUs23bNmFmZiZ0dXVF69atxdSpU8Wff/6p1Of5cLN69Wrh5uYmioqKFNPz8vKEnp6eOHDggBBCCAcHBxEREaG0jLlz54pWrVoJIf73I75gwQLF9KdPnwp7e3sREhJSZq2FhYXCwcFBMcZu3boldHR0xKVLlxR9isfKiRMnFG1JSUkCgDh58qQQ4lm40dfXVxrrkyZNEi1atBBCPBvvurq64vjx40rrHzlypBg8eHCZ9Y0ePVr069evzOlUdV4MN23btlWa/u6774opU6YIIYT4/vvvRb169RRh5XkXL14UAMSxY8cUbbdv3xZ6enpiy5YtQoj/jbHLly8r+owaNUro6+uLBw8eKNr8/PzEqFGjFM8dHR3FkCFDFM+LioqElZWVWLFihRCiZLgpzds+xrhb6g0SEhKCdevW4cKFCyWmJSUloU2bNkptbdq0waVLl5Q2d1aU+P8LV5d20LKvry8cHR3h4uKCjz/+GD///LPieIYrV67g6dOnSrXo6OigefPmSEpKUlqOt7e34v+vXLmC/Px8tGrVStFmbm4ONzc3xfMzZ85ACIF69erB0NBQ8YiNjcWVK1cU/WrWrIlGjRpV+jVT+fr164fr169j165d8PPzQ0xMDJo1a4a1a9eW2j8hIQGXL1+GkZGR4rMyNzfHkydPcOXKFdy6dQvp6ekYOXKk0uf53XffKX2eAJTGRY0aNeDt7V1iPD0vKioKubm56Nq1KwDgnXfeQZcuXbBmzRqlfsXLKla/fn2YmpoqLdvJyUnpeDMbGxtkZWUBAC5cuIAnT57A19dX6TWsX79e6TWEhYXB29sblpaWMDQ0xKpVq5CWllZm/fT6vPhb8fznO2DAADx+/BguLi4ICAjAjh07FMcHJiUloUaNGmjRooViXgsLC7i5uSmNH319fdSpU0fxvFatWnBycoKhoaFSW/E6S6ur+PCBF/s8j2NMGY9GeoO0b98efn5+mDZtGoYPH640TQhRIoiIV7izRlJSEoyNjWFhYVFimpGREc6cOYOYmBhERUVhxowZmDVrFk6fPl1mKCqtPgMDg0rVWlRUBG1tbSQkJEBbW1tp2vM/FHp6eq98JhmVrvi4FF9fX8yYMQOffvopZs6cWWI8As8+Ly8vL/z8888lpllaWuLJkycAgFWrVin9gQBQ4vMtTXmf8Zo1a3D37l3o6+sr1XP27FnMnTtXafmlLef5Nh0dnRLTig9SL/7v3r17YWdnp9Sv+D5CW7ZsQWBgIL7//nu0atUKRkZGCA0NxcmTJ1/6Gqnqlff5Ojg4IDk5GdHR0Th48CBGjx6N0NBQxMbGlvmb9eJvXWnLL2+dFanrRRxjJTHcvGEWLFiAJk2aoF69ekrtHh4eOHr0qFLb8ePHUa9evQr9oXheVlYWIiIi0KdPH2hplb5xr0aNGujcuTM6d+6MmTNnwtTUFH/88Qf8/PxQs2ZNHD16FB999BEA4OnTp4iPjy/3ejV169aFjo4OTpw4gdq1awN4drDexYsX4ePjAwBo2rQpCgsLkZWVhXbt2lXqNVHV8PDwKPO6Ns2aNcPmzZthZWUFY2PjEtNNTExgZ2eHlJQU+Pv7l7ueEydOoH379gCAgoICJCQk4Msvvyy17507d/Drr7/il19+gaenp6K9qKgI7dq1w/79+9GjRw/FsuLj49G8eXMAQHJyMrKzs1G/fv2XvnYAioPW09LSFOP0RUeOHEHr1q0xevRoRduLW6ao+tLT00OvXr3Qq1cvjBkzBvXr18d///tfeHh4oKCgACdPnkTr1q0BPBt7Fy9ehLu7+2utkWOsJIabN0zDhg3h7++PZcuWKbVPnDgR7777LubOnYtBgwYhLi4OP/74o9KZJ6URQuDGjRsQQiA7OxtxcXGYP38+TExMSlxbp9iePXuQkpKC9u3bw8zMDPv27UNRURHc3NxgYGCAL774ApMmTYK5uTlq166NhQsX4tGjRxg5cmSZdRgaGmLkyJGYNGkSLCwsUKtWLXzzzTdK4apevXrw9/fH0KFD8f3336Np06a4ffs2/vjjDzRs2BDdunWrxDtJlXHnzh0MGDAAI0aMQKNGjWBkZIT4+HgsXLgQvXv3LnUef39/hIaGonfv3pgzZw7s7e2RlpaG7du3Y9KkSbC3t8esWbMwbtw4GBsbo2vXrsjLy0N8fDzu3buHCRMmKJb1008/wdXVFe7u7li8eDHu3buHESNGlLreDRs2wMLCAgMGDCgRznv06IHVq1crwo2Ojg7Gjh2LpUuXQkdHB19++SVatmypCDsvY2RkhKCgIAQGBqKoqAht27ZFTk4Ojh8/DkNDQwwbNgx169bF+vXrceDAATg7O2PDhg04ffo0nJ2dK7QO0py1a9eisLAQLVq0gL6+PjZs2AA9PT04Ojoqzv4LCAjAv//9bxgZGeHrr7+GnZ1dmd+JqsIxVhLDzRto7ty52LJli1Jbs2bNsGXLFsyYMQNz586FjY0N5syZU+rugufl5OTAxsYGMpkMxsbGcHNzw7BhwzB+/PhS/7UNAKampti+fTtmzZqFJ0+ewNXVFZs2bVL8K3nBggUoKirCxx9/jAcPHsDb2xsHDhyAmZlZubWEhobi4cOH6NWrF4yMjDBx4sQSFxMMDw/Hd999h4kTJyIjIwMWFhZo1aoVg00VMzQ0RIsWLbB48WLFcVUODg4ICAjAtGnTSp1HX18fhw8fxpQpU9C3b188ePAAdnZ26NSpk2Jsffrpp9DX10doaCgmT54MAwMDNGzYsMRWvgULFiAkJARnz55FnTp18Ouvv+Kdd94pdb1r1qzBBx98UOpWx379+mHQoEG4efOmosYpU6bgo48+wj///IO2bduWOC7nZebOnQsrKysEBwcjJSUFpqamaNasmeJ9+fzzz5GYmIhBgwZBJpNh8ODBGD16NPbv31+p9dDrZ2pqigULFmDChAkoLCxEw4YNsXv3bsXu+vDwcIwfPx49evRAfn4+2rdvj3379pXYpVTVOMZKkolXOTCDiKgKXb16Fc7Ozjh79iyaNGmi1mWvXbsWX331FbKzs9W6XCLSPJ4tRURERJLCcENERESSwt1SREREJCncckNERESSwnBDREREksJwQ0RERJLCcENERESSwnBDRBUyfPhw9OnTR9NlvJSTkxOWLFmieC6Tycq8RURV0tR6iYhXKCYiicvMzHzp1bGJSFq45YaIJM3a2lpxh251e/r0aZUsFwDy8/OrbNlEUsdwQ0RKtm3bhoYNG0JPTw8WFhbo3LkzcnNzS/QTQmDhwoVwcXGBnp4eGjdujG3btin1uXDhArp16wZDQ0PUqlULH3/8MW7fvq2Y3qFDB3z55Zf48ssvYWpqCgsLC0yfPh0VvfxWVlYWevbsCT09PTg7O+Pnn38u0ef53UP5+fn48ssvYWNjA11dXTg5OSE4OFjRNy0tDb1794ahoSGMjY0xcOBAxX2oAGDWrFlo0qQJ1qxZAxcXF8jlcgghcOnSJbRv3x66urrw8PBAdHR0iToyMjIwaNAgmJmZKW66ePXqVcX04t1+wcHBsLW1Rb169Sr0HhBRSQw3RKSQmZmJwYMHY8SIEUhKSkJMTAz69u1batiYPn06wsPDsWLFCpw/fx6BgYEYMmQIYmNjFcvy8fFBkyZNEB8fj99++w03b97EwIEDlZazbt061KhRAydPnsTSpUuxePFi/Oc//6lQvcOHD8fVq1fxxx9/YNu2bVi+fDmysrLK7L906VLs2rULW7ZsQXJyMjZu3AgnJycAz8Janz59cPfuXcTGxiI6OhpXrlzBoEGDlJZx+fJlbNmyBZGRkUhMTERRURH69u0LbW1tnDhxAmFhYZgyZYrSPI8ePULHjh1haGiIw4cP4+jRozA0NMT777+vtIXm999/R1JSEqKjo7Fnz54KvQdEVApBRPT/EhISBABx9erVEtOGDRsmevfuLYQQ4uHDh0JXV1ccP35cqc/IkSPF4MGDhRBCfPvtt6JLly5K09PT0wUAkZycLIQQwsfHR7i7u4uioiJFnylTpgh3d/eX1pqcnCwAiBMnTijakpKSBACxePFiRRsAsWPHDiGEEGPHjhXvvfee0vqKRUVFCW1tbZGWlqZoO3/+vAAgTp06JYQQYubMmUJHR0dkZWUp+hw4cEBoa2uL9PR0Rdv+/fuV1rt69Wrh5uamtN68vDyhp6cnDhw4IIR49v7WqlVL5OXlvfS1E1H5uOWGiBQaN26MTp06oWHDhhgwYABWrVqFe/fuleh34cIFPHnyBL6+vjA0NFQ81q9fjytXrgAAEhIScOjQIaXp9evXBwBFHwBo2bIlZDKZ4nmrVq1w6dIlFBYWlltrUlISatSoAW9vb0Vb/fr1YWpqWuY8w4cPR2JiItzc3DBu3DhERUUpLc/BwQEODg6KNg8PD5iamiIpKUnR5ujoCEtLS6X5ateuDXt7e6XX8LyEhARcvnwZRkZGivfC3NwcT548UXovGjZsiJo1a5b7uono5Xi2FBEpaGtrIzo6GsePH0dUVBSWLVuGb775BidPnlTqV1RUBADYu3cv7OzslKYVH7xbVFSEnj17IiQkpMR6bGxsXrlW8f+7yp4PRi/TrFkzpKamYv/+/Th48CAGDhyIzp07Y9u2bRBClLqsF9sNDAxKreN5Ly6nqKgIXl5epR4T9HxQenHZRKQahhsiUiKTydCmTRu0adMGM2bMgKOjI3bs2KHUx8PDA3K5HGlpafDx8Sl1Oc2aNUNkZCScnJxQo0bZPzUnTpwo8dzV1RXa2trl1unu7o6CggLEx8ejefPmAIDk5GRkZ2eXO5+xsTEGDRqEQYMGoX///nj//fdx9+5deHh4IC0tDenp6YqtNxcuXMD9+/fh7u5e5vKK57t+/TpsbW0BAHFxcUp9mjVrhs2bN8PKygrGxsbl1kdEr467pYhI4eTJk5g/fz7i4+ORlpaG7du349atWyX+uBsZGSEoKAiBgYFYt24drly5grNnz+Knn37CunXrAABjxozB3bt3MXjwYJw6dQopKSmIiorCiBEjlHY5paenY8KECUhOTsamTZuwbNkyjB8//qW1urm54f3330dAQABOnjyJhIQEfPrpp9DT0ytznsWLF+OXX37B33//jYsXL2Lr1q2wtraGqakpOnfujEaNGsHf3x9nzpzBqVOnMHToUPj4+Cjt+npR586d4ebmhqFDh+LPP//EkSNH8M033yj18ff3xzvvvIPevXvjyJEjSE1NRWxsLMaPH49//vnnpa+ViCqH4YaIFIyNjXH48GF069YN9erVw/Tp0/H999+ja9euJfrOnTsXM2bMQHBwMNzd3eHn54fdu3fD2dkZAGBra4tjx46hsLAQfn5+aNCgAcaPHw8TExNoaf3vp2fo0KF4/PgxmjdvjjFjxmDs2LH47LPPKlRveHg4HBwc4OPjg759++Kzzz6DlZVVmf0NDQ0REhICb29vvPvuu7h69Sr27dsHLS0txSnjZmZmaN++PTp37gwXFxds3ry53Bq0tLSwY8cO5OXloXnz5vj0008xb948pT76+vo4fPgwateujb59+8Ld3R0jRozA48ePuSWHqArIRGk7jImIXoMOHTqgSZMmSrdLICJ6VdxyQ0RERJLCcENE1dKRI0eUTiN/8UFEVBbuliKiaunx48fIyMgoc3rdunVfYzVE9CZhuCEiIiJJ4W4pIiIikhSGGyIiIpIUhhsiIiKSFIYbIiIikhSGGyIiIpIUhhsiIiKSFIYbIiIikhSGGyIiIpKU/wO/LNYVQbAaBgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.boxplot(\n", + " x = sleep_df_clean[\"sleep_disorder\"],\n", + " y = sleep_df_clean[\"sleep_duration\"],\n", + " palette = ['#9c9678', '#524e3a', '#a99467']\n", + " # palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + ")\n", + "ax.set_title(\"Distribution of Sleep Duration by Disorder\")" + ] + }, + { + "cell_type": "markdown", + "id": "acef8dad-d886-4eb0-9cd7-5325b215eb52", + "metadata": {}, + "source": [ + "### 4. Univariate Analysis\n", + "Analysis of one variable at a time to understand its distribution, central tendency, and spread." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "5ecd1e9e-d029-4035-a456-1115de20b071", + "metadata": {}, + "outputs": [], + "source": [ + "def univariate_analysis(df, numeric_columns, categorical_columns):\n", + "\n", + " \"\"\"\n", + " Performs univariate analysis: distributions, statistics, and plots.\n", + " Args:\n", + " df (pd.DataFrame): Dataset.\n", + " numeric_columns (list): List of numeric column names.\n", + " categorical_columns (list): List of categorical column names.\n", + " \"\"\"\n", + " \n", + " for col in numeric_columns:\n", + " print(f\"\\n===== {col} =====\")\n", + " print(df[col].describe())\n", + " sns.histplot(df[col], kde=True, bins=15)\n", + " plt.title(f'Distribution of {col}')\n", + " plt.show()\n", + " \n", + " for col in categorical_columns:\n", + " print(f\"\\n===== {col} =====\")\n", + " print(df[col].value_counts())\n", + " sns.countplot(y=col, data=df)\n", + " plt.title(f'Counts of {col}')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "a115bbf7-1faf-4079-a502-1e64175d6c16", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== age =====\n", + "count 132.000000\n", + "mean 41.128788\n", + "std 8.813942\n", + "min 27.000000\n", + "25% 33.750000\n", + "50% 41.000000\n", + "75% 49.000000\n", + "max 59.000000\n", + "Name: age, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== sleep_duration =====\n", + "count 132.000000\n", + "mean 7.082576\n", + "std 0.775335\n", + "min 5.800000\n", + "25% 6.400000\n", + "50% 7.150000\n", + "75% 7.725000\n", + "max 8.500000\n", + "Name: sleep_duration, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== quality_of_sleep =====\n", + "count 132.000000\n", + "mean 7.151515\n", + "std 1.269037\n", + "min 4.000000\n", + "25% 6.000000\n", + "50% 7.000000\n", + "75% 8.000000\n", + "max 9.000000\n", + "Name: quality_of_sleep, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== physical_activity_level =====\n", + "count 132.000000\n", + "mean 58.393939\n", + "std 20.468840\n", + "min 30.000000\n", + "25% 44.250000\n", + "50% 60.000000\n", + "75% 75.000000\n", + "max 90.000000\n", + "Name: physical_activity_level, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== stress_level =====\n", + "count 132.000000\n", + "mean 5.537879\n", + "std 1.740428\n", + "min 3.000000\n", + "25% 4.000000\n", + "50% 6.000000\n", + "75% 7.000000\n", + "max 8.000000\n", + "Name: stress_level, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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j4eHhcq7Kz/3pHD582IwbN84kJiYab29vExYWZi677DIzefJkk5uba4wxZt68eaZPnz4mKirK+Pj4mNjYWHPLLbeYLVu2OLfz+OOPmy5dupjQ0FBjt9tN06ZNzcMPP2wyMjLOeXynnpNTz3FycrK5++67TaNGjYy3t7dp2LCh6dmzp5k2bVqFbWRlZRk/Pz8jycyZM6fax2wMdzPhwrAZc47bMwAAAOow7mYCAACWxpgZALAgY4wcDsdZ1/H09KzWeCLAauiZAQALWr16dYXnupw6nfoZWUB9xZgZALCgnJyccz75ODExscKDCoH6iDADAAAsjctMAADA0tw6AHj69OlatGiRduzYIT8/P/Xs2VMzZsxweSDTqFGjKlz37datm/OD0M6ltLRUBw4cUFBQEAPhAACwCGOMcnJyFBsbKw+Ps/e9uDXMrF69WmPGjFHXrl1VUlKiyZMna8CAAfrll18UEBDgXG/gwIEun9p6rsdvn+zAgQMVPtEXAABYQ2pq6jmfIO3WMLNs2TKX+blz5yoyMlKbNm3SVVdd5Wy32+2n/WTgyih/7HhqaqqCg4OrXywAAKg12dnZaty48Vk/PqRcnXrOTFZWliQpLCzMpX3VqlWKjIxUgwYN1KtXLz377LOKjIw87TaKiopcPhk4JydHkhQcHEyYAQDAYiozRKTO3M1kjNH111+vo0eP6ptvvnG2//Of/1RgYKDi4+OVnJysp556SiUlJdq0aZPzE21PlpSUpKlTp1Zoz8rKIswAAGAR2dnZCgkJqdTv7zoTZsaMGaPPPvtM33777VmvjR08eFDx8fFauHChhg8fXmH5qT0z5d1UhBkAAKyjKmGmTlxmGjt2rJYsWaI1a9acc5BPTEyM4uPjtWvXrtMut9vtp+2xAQAA9ZNbw4wxRmPHjtXixYu1atUqJSYmnvM9R44cUWpqqmJiYmqhQgAAUNe59aF5Y8aM0QcffKD58+crKChIaWlpSktLU0FBgSQpNzdXjzzyiNatW6eUlBStWrVKQ4cOVUREhG644QZ3lg4AAOoIt46ZOdMI5blz52rUqFEqKCjQsGHD9MMPP+jYsWOKiYlRnz599Le//a3Sz46pyjU3AABQN1hmzMy5cpSfn5+WL19eS9UAAAAr4rOZAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApdWJz2YCAADnZ+/evcrIyKj1/UZERKhJkya1vt+TEWYAALC4vXv3qlXr1irIz6/1ffv5+2vH9u1uDTSEGQAALC4jI0MF+fm6Y+ILimrSrNb2e2jv7/pwxqPKyMggzAAAgPMX1aSZ4pq3dXcZtY4BwAAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNK83F2A1e3du1cZGRm1vt+IiAg1adKk1vfrLpxnAFXFz42LB2HmPOzdu1etWrdWQX5+re/bz99fO7Zvvyi+YTjPAKqKnxsXF8LMecjIyFBBfr7umPiCopo0q7X9Htr7uz6c8agyMjIuim8WzjOAquLnxsWFMFMDopo0U1zztu4uo97jPAOoKn5uXBwYAAwAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNMAMAACyNz2YC4LR3715lZGTU+n4jIiIuqg/l4zwDNYswA0BS2S/YVq1bqyA/v9b37efvrx3bt18Uv2g5z0DNI8wAkCRlZGSoID9fd0x8QVFNmtXafg/t/V0fznhUGRkZF8UvWc4zUPMIMwBcRDVpprjmbd1dRr3HeQZqDgOAAQCApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApbk1zEyfPl1du3ZVUFCQIiMjNWzYMO3cudNlHWOMkpKSFBsbKz8/P/Xu3Vvbtm1zU8UAAKCucWuYWb16tcaMGaP169drxYoVKikp0YABA5SXl+dc5/nnn9fMmTP1+uuva8OGDYqOjlb//v2Vk5PjxsoBAEBd4dYnAC9btsxlfu7cuYqMjNSmTZt01VVXyRijWbNmafLkyRo+fLgkad68eYqKitL8+fM1evRod5QNAADqkDo1ZiYrK0uSFBYWJklKTk5WWlqaBgwY4FzHbrerV69eWrt27Wm3UVRUpOzsbJcJAADUX3UmzBhjNGHCBF1xxRVq166dJCktLU2SFBUV5bJuVFSUc9mppk+frpCQEOfUuHHjC1s4AABwqzoTZh588EFt2bJFCxYsqLDMZrO5zBtjKrSVmzRpkrKyspxTamrqBakXAADUDXXiU7PHjh2rJUuWaM2aNYqLi3O2R0dHSyrroYmJiXG2p6enV+itKWe322W32y9swQAAoM5wa8+MMUYPPvigFi1apK+++kqJiYkuyxMTExUdHa0VK1Y424qLi7V69Wr17NmztssFAAB1kFt7ZsaMGaP58+frk08+UVBQkHMcTEhIiPz8/GSz2TR+/Hg999xzat68uZo3b67nnntO/v7+uv32291ZOgAAqCPcGmZmz54tSerdu7dL+9y5czVq1ChJ0mOPPaaCggI98MADOnr0qLp166YvvvhCQUFBtVwtAACoi9waZowx51zHZrMpKSlJSUlJF74gAABgOXXmbiYAAIDqIMwAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLc2uYWbNmjYYOHarY2FjZbDZ9/PHHLstHjRolm83mMnXv3t09xQIAgDrJrWEmLy9PHTt21Ouvv37GdQYOHKiDBw86p6VLl9ZihQAAoK7zcufOBw0apEGDBp11Hbvdrujo6FqqCAAAWE2dHzOzatUqRUZGqkWLFrrvvvuUnp7u7pIAAEAd4taemXMZNGiQbr75ZsXHxys5OVlPPfWUrr76am3atEl2u/207ykqKlJRUZFzPjs7u7bKBQAAblCnw8ytt97qfN2uXTt16dJF8fHx+uyzzzR8+PDTvmf69OmaOnVqbZUIAADcrM5fZjpZTEyM4uPjtWvXrjOuM2nSJGVlZTmn1NTUWqwQAADUtjrdM3OqI0eOKDU1VTExMWdcx263n/ESFAAAqH/cGmZyc3P122+/OeeTk5P1448/KiwsTGFhYUpKStKNN96omJgYpaSk6IknnlBERIRuuOEGN1YNAADqEreGmY0bN6pPnz7O+QkTJkiSRo4cqdmzZ+vnn3/W+++/r2PHjikmJkZ9+vTRP//5TwUFBbmrZAAAUMe4Ncz07t1bxpgzLl++fHktVgMAAKzIUgOAAQAATkWYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAllatMNO0aVMdOXKkQvuxY8fUtGnT8y4KAACgsqoVZlJSUuRwOCq0FxUVaf/+/eddFAAAQGVV6VOzlyxZ4ny9fPlyhYSEOOcdDoe+/PJLJSQk1FhxAAAA51KlMDNs2DBJks1m08iRI12WeXt7KyEhQS+99FKNFQcAAHAuVQozpaWlkqTExERt2LBBERERF6QoAACAyqpSmCmXnJxc03UAAABUS7XCjCR9+eWX+vLLL5Wenu7ssSn37rvvnndhAAAAlVGtMDN16lQ988wz6tKli2JiYmSz2Wq6LgAAgEqpVph566239N577+nOO++s6XoAAACqpFrPmSkuLlbPnj1ruhYAAIAqq1aYuffeezV//vyargUAAKDKqnWZqbCwUO+8845WrlypDh06yNvb22X5zJkza6Q4AACAc6lWmNmyZYs6deokSdq6davLMgYDAwCA2lStMPP111/XdB0AAADVUq0xMwAAAHVFtXpm+vTpc9bLSV999VW1CwIAAKiKaoWZ8vEy5Y4fP64ff/xRW7durfABlAAAABdStcLMyy+/fNr2pKQk5ebmnldBAAAAVVGjY2b+/Oc/87lMAACgVtVomFm3bp18fX1rcpMAAABnVa3LTMOHD3eZN8bo4MGD2rhxo5566qkaKQwAAKAyqhVmQkJCXOY9PDzUsmVLPfPMMxowYECNFAYAAFAZ1Qozc+fOrek6AAAAqqVaYabcpk2btH37dtlsNrVp00aXXnppTdUFAABQKdUKM+np6RoxYoRWrVqlBg0ayBijrKws9enTRwsXLlTDhg1ruk4AAIDTqtbdTGPHjlV2dra2bdumzMxMHT16VFu3blV2drbGjRtX0zUCAACcUbV6ZpYtW6aVK1eqdevWzrY2bdrojTfeYAAwAACoVdXqmSktLZW3t3eFdm9vb5WWlp53UQAAAJVVrTBz9dVX66GHHtKBAwecbfv379fDDz+svn371lhxAAAA51KtMPP6668rJydHCQkJatasmS655BIlJiYqJydHr732Wk3XCAAAcEbVGjPTuHFjbd68WStWrNCOHTtkjFGbNm3Ur1+/mq4PAADgrKrUM/PVV1+pTZs2ys7OliT1799fY8eO1bhx49S1a1e1bdtW33zzzQUpFAAA4HSqFGZmzZql++67T8HBwRWWhYSEaPTo0Zo5c2aNFQcAAHAuVQozP/30kwYOHHjG5QMGDNCmTZvOuygAAIDKqlKYOXTo0GlvyS7n5eWlw4cPn3dRAAAAlVWlMNOoUSP9/PPPZ1y+ZcsWxcTEnHdRAAAAlVWlMDN48GA9/fTTKiwsrLCsoKBAU6ZM0ZAhQ2qsOAAAgHOp0q3ZTz75pBYtWqQWLVrowQcfVMuWLWWz2bR9+3a98cYbcjgcmjx58oWqFQAAoIIqhZmoqCitXbtW999/vyZNmiRjjCTJZrPpmmuu0ZtvvqmoqKgLUigAAMDpVPmhefHx8Vq6dKmOHj2q3377TcYYNW/eXKGhoReiPgAAgLOq1hOAJSk0NFRdu3atyVoAAACqrFqfzQQAAFBXEGYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAIClEWYAAICluTXMrFmzRkOHDlVsbKxsNps+/vhjl+XGGCUlJSk2NlZ+fn7q3bu3tm3b5p5iAQBAneTWMJOXl6eOHTvq9ddfP+3y559/XjNnztTrr7+uDRs2KDo6Wv3791dOTk4tVwoAAOqqan9qdk0YNGiQBg0adNplxhjNmjVLkydP1vDhwyVJ8+bNU1RUlObPn6/Ro0fXZqkAAKCOqrNjZpKTk5WWlqYBAwY42+x2u3r16qW1a9ee8X1FRUXKzs52mQAAQP1VZ8NMWlqaJCkqKsqlPSoqyrnsdKZPn66QkBDn1Lhx4wtaJwAAcK86G2bK2Ww2l3ljTIW2k02aNElZWVnOKTU19UKXCAAA3MitY2bOJjo6WlJZD01MTIyzPT09vUJvzcnsdrvsdvsFrw8AANQNdbZnJjExUdHR0VqxYoWzrbi4WKtXr1bPnj3dWBkAAKhL3Nozk5ubq99++805n5ycrB9//FFhYWFq0qSJxo8fr+eee07NmzdX8+bN9dxzz8nf31+33367G6sGAAB1iVvDzMaNG9WnTx/n/IQJEyRJI0eO1HvvvafHHntMBQUFeuCBB3T06FF169ZNX3zxhYKCgtxVMgAAqGPcGmZ69+4tY8wZl9tsNiUlJSkpKan2igIAAJZSZ8fMAAAAVAZhBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWBphBgAAWJqXuwsAAKC6jDEqKilVblGJcgtLlFtUopzCEm05UCj/VlcqJddDmfuOyVFqVHJicpQaORxGJaWlf8yXGhlJpcZIRiqVkTEqm068liQPm00eNsnDw/bHa5vtxLxUmOOpBn3u1r+25Whz3m4F2r0UYPdSoN1LwX7eigj0UXigXQE+nrLZbG49d/UJYQYAUOtKHKXKK3Iop+i48oocyi06rpwTYSTvRCA5OaA4p9PMl5Sa0+6j4fUTtSlTUubhWjwyT4X8abgWbsuVtm0/41p2Lw9FBNoVHuij8AAfRYf4Ki7UX43D/BUX6qfGof6KCPQh8FQSYQYXVPlfTTmFJSo87lBRiUOFx0udX8va/vjqKDUqNUalpUYOI5WWGu3dl6vgbjdpR5aH9icfkU022WySTZLNZjvx9Y/XOrGs7K8mmzw8JE8PmzxttrKvJ/6iKn9d3u5xyrw5/c9H4KJ13FGqvKLywOFwBo8/2kqUV+yoGDpOep1TWLZewXFHjddX1gviqUC7l2yOYm39YZPiW7ZTYFCQPD1s8vLwkJeHTZ6eNnmdmC9rL/v+t9kkj/KfLzZV+FkjlfXclE1lP5+cr0/83MrMOKT1X3yim2+7U37BDZzHnldcomP5x5WZV6z84rKfd/uPFWj/sYIzHo+ft6fiQv3UtGGAWkQFqXlUkFpEBappRKB8vBglcjLCDCqttNToaH6xMnKLdTinSIdzC5WRU6wjecXKLjyu7ILjyi4sUVbBceUUHD/RVqJiR+l57zu09yhty5KUlXn+B1JpPmry/y3SnxenyX/pCtm9POXj5SG7czpp3vvEvGf5a48Tyzyd6/uUv/b2qLAtl3W9PWT39JTd20M+nh7y8OAvM1SeMUYOY1TiKJuOl5aqxGF0pMgm3/iO2nigUAe8Dqig2KHC4w7lFztOhJETX4tPDigO5+ucohIVl5z/9/KpfLw8FGT3UqCvlwJ8yr465+0nXp+YDzzldZDvH5dwAny8XL5XNm/erMsmPqE73likuOaxNV73mew7flDLVs3VX196UJ07X3radfKLS3Qkt+xn55HcImXkFunAsUKlHs3XvswCpR7NV1p2oQqOO7QrPVe70nO1fNsh5/u9PW1qFR2sDnEhJ6YGcpyhd+piQZiBU0GxQ/uP5Sv1aIH2Hy3QvqNlfzXsO5qvA8cKlJFbfF7fML4nfon7envI17vsF/fJX308Pf7oOTmph+TY0Ux9umSJ2vW4WoEhoZIkoxPXso354/VprnGXmhPXw098LS2Vy3z569KTrpmfzOblo/zjRvnHi6t93OfL29N2Sig6EXxOE5p8TgpaVVrX20O7jx6XV3ic8kqk3KKSEz1YJ/Vw2USXdyUYY3TcYVTsKFVxSdlUVOI48bVUO48Uy964vdIKbCo+nOscy3Hy/0eX+VOm8nEeJQ6j447y16U6Xj4GxFHx/3EZb0WNeFbPfXtU0tHzOkYfTw8F2D2dQeLkcSHl7UHO0OF94qtn2euTQkiA3VN2L8/zqsWK/H285B/mpcZh/mdcp6jEoQPHCrU3M1+/pedq16Ec7TyUo12HcpVbVKKf92fp5/1Z+vC7svX9vGyKvClJO7M95JlVoMggX3leRH8IEWYuMsYYHckr1m/pufr9cO6Jr3n6PT33rN2dJwv191bDIHvZFGhXeKBdIX7eCvb1UpCvt4JPvA72++P1qX81VcXmzZv13v2v6LIhvRTXPKpa26isUmfoMUr9fYfenjxaH3/6XzVr0cr5y6ioxKGi46Uqdpzy+sTlsyLnL7A/5otKSk9a74+24pKTX/+x/smXuI47jI47SpRbdEEPXZLU6N63tOyApAPJp11eHmg8zzEI8uRLfCeHofJLfOVd+LJJBdmeCh88Xq9/f0wNd29xXjL8YzsnLiGeNF+2DZuMTgzWNOXh9eRQ+0f3f1ng/SPgnrpueUg47igLBuVhobzNUeoaHM62vDKBP/r26fq/w5IOH6zRf79T2WySt4eHvDxtspWW6OjBPWrbsrnCGwTJ19tTfiemAGcYOfn1KW0+f7RxiePCs3t5KjEiQIkRAerVoqGz3RijfUcLtGVflrbsP6YtqWWhJreoRH7NumjrMWnrxn3y9rQpLtRfCeH+SggPULCft/sOphYQZuqx8v/0W08k+J/3Z2nbgWxl5p25lyHI7qVGoX6KC/VTXKi/GjUoex3bwE9Rwb4KD/SRt2f9/UHmYbPJw9MmeUq+npIj57Big7zUOia41mo4+S/78uBzcjg6bag6fkpwOnXdCkHq5O2UbT+3oFCHM4/Jxz9IpcZ22r/uS090gznO8Ld/9XgqsH0/fZVSIKWk1uB26wYvD5uzJ8zHy0NylGjf3hRFRDeSn5//H2O3PFzHcXmdrv3E+A4vTw95n/jq5WGTt2dZYHF97eHyl/m+Xds089kH9d9Nm9S5c2c3nhGcD5vNpsZhZQOFr+0QI6ksjH/89fe6a+Jzajf0XmWWeKnweKmSM/KUnJEn6bDCAnyUGBGgFpGBahhkr3e9rISZeiS/uESb9xzTd8lH9GPqMW3dn6Wj+ccrrGezSXGhfrqkYaCaNQzUJZGBahZZ9joswMcNleNkNptNPl42+Xh5KNBee9+imzdv1mWXDdaENxYprnlb54BG5+BGU3aZ7uQBkOUDto2R83LdqQMiT/d+Z0+JpGOH07Rm8fsaO+4hxcTGuvSolBrXHpVSZ4+LkaNUJ3prXHtuygd/n9zDY1N5D095m+2P96qsR8n7RAAoDwWnBobygODtWRYqTg4N5cu9y9f18DjjmKey8zxII95YpLjmjWvt3xf1l6eHTYmh3srZtEQ97h6lRpe0UEZusVKO5CklI08HswuVmVeszLxibdpzVCF+3rokMlDNIwMVWU+CDWHGwvKPl+rrnen6bnemvk8+oi37sircoujtaVOLqCC1bxSido1C1L5RiFpGl3UxA2fj7KW6wPYVHdB/v1+k4a0nq3PnSy74/oD6zmazOYcCdE0IU+Fxh/Ycyddvh3OVkpGnrILj2rTnqDbtOarwAB+1iQlWy+ggBdTiH081zbqVX4SMMTqcW6QdWR6KuuN5/c/Hh1RqDrmsExviq25Nw3VZfKg6xJUFl4txgB0AoIyvt6daRgepZXSQjjvKLj/tSs9VckaejuQV65vfMvR/v2coITxA7RqFKCHc33K9NYSZOq6ktFSpmQX6/USizit2SPKSb1wblRqpcZifuiWGq1timLo3DVdcqJ/l/hMCAGqHt6eHWkQFqUVUkIqOO7TzUI5+OZitQ9lF2p2Rp90ZeQrx81bHuBC1iQ22zB/DhJk6qMRRqj0nbsfbfTjP5TktXh42NbQ7tHXxm/r3a1M18Mo/ubFSAIBV2b091SGugTrENdCR3CJtO5itXw5kK6vguNbsytC63UfUJiZYnZuE1vm7oQgzdYQxRgeOFWp7WrZ2pee6PJwqwMdTzSID1TQiQI1C/ZT2+3at/2mZIgOedWPFAID6IjzQrquaN1SPpuHafjBbP6VmKTO/WD/ty9KW/VlqFRWkLglhdfYmEcKMm2UXHNe2A9nakZat7MISZ3ug3UvNI8vuNIoJ8eXSEQDggvP29FCHuAZq3yhEezPztXnvMe3NzNf2tBxtT8tR88hAdU0IU8Mgu7tLdUGYcYNSY7TnSL627DumlCP5znYfTw9dEhmo1jFBatSAsS8AAPew2WyKDw9QfHiA0rILtSE5U7tPDBzelZ6rllFB6tEs3N1lOhFmalHhcYfz4XU5J/XCNA71U9vYEDVtGFCvH0gHALCe6GBfDe0Yq4zcIn2fnKld6bllH62QnqOEAE95+Ddwd4mEmdpwLL9YP6Ye07YD2c7nwPh6eahNbLDaNQpRqH/dvAYJAEC5iEC7BrePUXpOodb+dkR7MvO1O9dTjUbP0cc7cuXOB0sTZi6g9OxCbUg5qt8P5zof/h4R6KNLm4SqRWSgvOiFAQBYTGSQr4Zd2kipmflatS1VmfKr0Q84qQ7CzAWQllWo71MyT3wmRpn4cH91bhKqxjwHBgBQDzQO81fvqBK9NWuGBg9/w621EGZqUFpWodYnH9GeE4N6bZJaRAepS3yoIgLr1shvAADOl80mFfz2nexe7v0jnTBTA7KPS//dckC/Hy7ribHZpFbRQeqaEMZ4GAAALjDCzHk4ku9Q2MCxWnHQW1KebJJaxwSra0KoGhBiAACoFYSZapqzZrdeWJ6uoI7XSJKaRgSoZ7NwhXM5CQCAWkWYqaZgPy8VO6TC1G0a2KWFOraLdXdJAABclLg3uJpu7Bynp68K06H5ExVud/dNaQAAXLwIM9Xk5emhTtFcUgIAwN0IMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNLqdJhJSkqSzWZzmaKjo91dFgAAqEPq/BOA27Ztq5UrVzrnPT093VgNAACoa+p8mPHy8qI3BgAAnFGdvswkSbt27VJsbKwSExM1YsQI7d69+6zrFxUVKTs722UCAAD1V50OM926ddP777+v5cuXa86cOUpLS1PPnj115MiRM75n+vTpCgkJcU6NGzeuxYoBAEBtq9NhZtCgQbrxxhvVvn179evXT5999pkkad68eWd8z6RJk5SVleWcUlNTa6tcAADgBnV+zMzJAgIC1L59e+3ateuM69jtdtntfAAkAAAXizrdM3OqoqIibd++XTExMe4uBQAA1BF1Osw88sgjWr16tZKTk/Xdd9/ppptuUnZ2tkaOHOnu0gAAQB1Rpy8z7du3T7fddpsyMjLUsGFDde/eXevXr1d8fLy7SwMAAHVEnQ4zCxcudHcJAACgjqvTl5kAAADOhTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAszRJh5s0331RiYqJ8fX112WWX6ZtvvnF3SQAAoI6o82Hmn//8p8aPH6/Jkyfrhx9+0JVXXqlBgwZp79697i4NAADUAXU+zMycOVP33HOP7r33XrVu3VqzZs1S48aNNXv2bHeXBgAA6oA6HWaKi4u1adMmDRgwwKV9wIABWrt2rZuqAgAAdYmXuws4m4yMDDkcDkVFRbm0R0VFKS0t7bTvKSoqUlFRkXM+KytLkpSdnV3j9eXm5kqS9u3apqKC/Brf/pkc3pcsSdq0aZOzhtri4eGh0tLSWt3nzp07JXGeLzTOc+3gPNeOi+08u/t4c3Nza/z3bPn2jDHnXtnUYfv37zeSzNq1a13ap02bZlq2bHna90yZMsVIYmJiYmJiYqoHU2pq6jnzQp3umYmIiJCnp2eFXpj09PQKvTXlJk2apAkTJjjnS0tLlZmZqfDwcNlsthqtLzs7W40bN1ZqaqqCg4NrdNv4A+e5dnCeawfnuXZwnmvHhTzPxhjl5OQoNjb2nOvW6TDj4+Ojyy67TCtWrNANN9zgbF+xYoWuv/76077HbrfLbre7tDVo0OBClqng4GC+WWoB57l2cJ5rB+e5dnCea8eFOs8hISGVWq9OhxlJmjBhgu6880516dJFPXr00DvvvKO9e/fqr3/9q7tLAwAAdUCdDzO33nqrjhw5omeeeUYHDx5Uu3bttHTpUsXHx7u7NAAAUAfU+TAjSQ888IAeeOABd5dRgd1u15QpUypc1kLN4jzXDs5z7eA81w7Oc+2oK+fZZkxl7nkCAACom+r0Q/MAAADOhTADAAAsjTADAAAsjTADAAAsjTBTRbNnz1aHDh2cDwjq0aOHPv/8c3eXVe9Nnz5dNptN48ePd3cp9U5SUpJsNpvLFB0d7e6y6qX9+/frz3/+s8LDw+Xv769OnTpp06ZN7i6rXklISKjw/9lms2nMmDHuLq1eKSkp0ZNPPqnExET5+fmpadOmeuaZZ2r9M7jKWeLW7LokLi5Of//733XJJZdIkubNm6frr79eP/zwg9q2bevm6uqnDRs26J133lGHDh3cXUq91bZtW61cudI57+np6cZq6qejR4/q8ssvV58+ffT5558rMjJSv//++wV/QvnFZsOGDXI4HM75rVu3qn///rr55pvdWFX9M2PGDL311luaN2+e2rZtq40bN+quu+5SSEiIHnrooVqvhzBTRUOHDnWZf/bZZzV79mytX7+eMHMB5Obm6o477tCcOXM0bdo0d5dTb3l5edEbc4HNmDFDjRs31ty5c51tCQkJ7iuonmrYsKHL/N///nc1a9ZMvXr1clNF9dO6det0/fXX69prr5VU9n95wYIF2rhxo1vq4TLTeXA4HFq4cKHy8vLUo0cPd5dTL40ZM0bXXnut+vXr5+5S6rVdu3YpNjZWiYmJGjFihHbv3u3ukuqdJUuWqEuXLrr55psVGRmpSy+9VHPmzHF3WfVacXGxPvjgA9199901/kHDF7srrrhCX375pX799VdJ0k8//aRvv/1WgwcPdks99MxUw88//6wePXqosLBQgYGBWrx4sdq0aePusuqdhQsXavPmzdqwYYO7S6nXunXrpvfff18tWrTQoUOHNG3aNPXs2VPbtm1TeHi4u8urN3bv3q3Zs2drwoQJeuKJJ/T9999r3Lhxstvt+p//+R93l1cvffzxxzp27JhGjRrl7lLqnYkTJyorK0utWrWSp6enHA6Hnn32Wd12223uKcigyoqKisyuXbvMhg0bzOOPP24iIiLMtm3b3F1WvbJ3714TGRlpfvzxR2dbr169zEMPPeS+oi4Subm5Jioqyrz00kvuLqVe8fb2Nj169HBpGzt2rOnevbubKqr/BgwYYIYMGeLuMuqlBQsWmLi4OLNgwQKzZcsW8/7775uwsDDz3nvvuaUeemaqwcfHxzkAuEuXLtqwYYNeeeUVvf32226urP7YtGmT0tPTddlllznbHA6H1qxZo9dff11FRUUMUr1AAgIC1L59e+3atcvdpdQrMTExFXpwW7durf/85z9uqqh+27Nnj1auXKlFixa5u5R66dFHH9Xjjz+uESNGSJLat2+vPXv2aPr06Ro5cmSt10OYqQHGGBUVFbm7jHqlb9+++vnnn13a7rrrLrVq1UoTJ04kyFxARUVF2r59u6688kp3l1KvXH755dq5c6dL26+//qr4+Hg3VVS/zZ07V5GRkc4BqqhZ+fn58vBwHXbr6enJrdlW8cQTT2jQoEFq3LixcnJytHDhQq1atUrLli1zd2n1SlBQkNq1a+fSFhAQoPDw8ArtOD+PPPKIhg4dqiZNmig9PV3Tpk1Tdna2W/66qs8efvhh9ezZU88995xuueUWff/993rnnXf0zjvvuLu0eqe0tFRz587VyJEj5eXFr7kLYejQoXr22WfVpEkTtW3bVj/88INmzpypu+++2y318K9cRYcOHdKdd96pgwcPKiQkRB06dNCyZcvUv39/d5cGVMu+fft02223KSMjQw0bNlT37t21fv16egxqWNeuXbV48WJNmjRJzzzzjBITEzVr1izdcccd7i6t3lm5cqX27t3rtl+sF4PXXntNTz31lB544AGlp6crNjZWo0eP1tNPP+2WemzGGOOWPQMAANQAnjMDAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADAAAsjTADoF5LSEjQrFmzanWfvXv31vjx42t1n8DFjDADoNpGjRqlYcOGubsMABc5wgyAC+748ePuLgFAPUaYAXBOH330kdq3by8/Pz+Fh4erX79+evTRRzVv3jx98sknstlsstlsWrVqlVJSUmSz2fSvf/1LvXv3lq+vrz744ANJZZ9k3Lp1a/n6+qpVq1Z68803nfsoLi7Wgw8+qJiYGPn6+iohIUHTp093Lk9KSlKTJk1kt9sVGxurcePGVetYsrKy9Je//EWRkZEKDg7W1VdfrZ9++kmStHPnTtlsNu3YscPlPTNnzlRCQoLKP/3ll19+0eDBgxUYGKioqCjdeeedysjIqFY9AM4fYQbAWR08eFC33Xab7r77bm3fvl2rVq3S8OHDNWXKFN1yyy0aOHCgDh48qIMHD6pnz57O902cOFHjxo3T9u3bdc0112jOnDmaPHmynn32WW3fvl3PPfecnnrqKc2bN0+S9Oqrr2rJkiX617/+pZ07d+qDDz5QQkKCpLIw9fLLL+vtt9/Wrl279PHHH6t9+/ZVPhZjjK699lqlpaVp6dKl2rRpkzp37qy+ffsqMzNTLVu21GWXXaYPP/zQ5X3z58/X7bffLpvNpoMHD6pXr17q1KmTNm7cqGXLlunQoUO65ZZbqn+SAZwfAwBnsWnTJiPJpKSkVFg2cuRIc/3117u0JScnG0lm1qxZLu2NGzc28+fPd2n729/+Znr06GGMMWbs2LHm6quvNqWlpRX289JLL5kWLVqY4uLiKtcfHx9vXn75ZWOMMV9++aUJDg42hYWFLus0a9bMvP3228YYY2bOnGmaNm3qXLZz504jyWzbts0YY8xTTz1lBgwY4PL+1NRUI8ns3LnTGGNMr169zEMPPVTlWgFUDz0zAM6qY8eO6tu3r9q3b6+bb75Zc+bM0dGjR8/5vi5dujhfHz58WKmpqbrnnnsUGBjonKZNm6bff/9dUtlg4h9//FEtW7bUuHHj9MUXXzjff/PNN6ugoEBNmzbVfffdp8WLF6ukpKTKx7Jp0ybl5uYqPDzcpY7k5GRnHSNGjNCePXu0fv16SdKHH36oTp06qU2bNs5tfP311y7vb9WqlSQ5twGgdnm5uwAAdZunp6dWrFihtWvX6osvvtBrr72myZMn67vvvjvr+wICApyvS0tLJUlz5sxRt27dKmxfkjp37qzk5GR9/vnnWrlypW655Rb169dPH330kRo3bqydO3dqxYoVWrlypR544AG98MILWr16tby9vSt9LKWlpYqJidGqVasqLGvQoIEkKSYmRn369NH8+fPVvXt3LViwQKNHj3bZxtChQzVjxowK24iJial0LQBqDmEGwDnZbDZdfvnluvzyy/X0008rPj5eixcvlo+PjxwOxznfHxUVpUaNGmn37t264447zrhecHCwbr31Vt1666266aabNHDgQGVmZiosLEx+fn667rrrdN1112nMmDFq1aqVfv75Z3Xu3LnSx9G5c2elpaXJy8vLOR7ndO644w5NnDhRt912m37//XeNGDHCZRv/+c9/lJCQIC8vfoQCdQHfiQDO6rvvvtOXX36pAQMGKDIyUt99950OHz6s1q1bq7CwUMuXL9fOnTsVHh6ukJCQM24nKSlJ48aNU3BwsAYNGqSioiJt3LhRR48e1YQJE/Tyyy8rJiZGnTp1koeHh/79738rOjpaDRo00HvvvSeHw6Fu3brJ399f//jHP+Tn56f4+PgqHUu/fv3Uo0cPDRs2TDNmzFDLli114MABLV26VMOGDXNeGhs+fLjuv/9+3X///erTp48aNWrk3MaYMWM0Z84c3XbbbXr00UcVERGh3377TQsXLtScOXOcPU0Aag9hBsBZBQcHa82aNZo1a5ays7MVHx+vl156SYMGDVKXLl20atUqdenSRbm5ufr666/P2ONx7733yt/fXy+88IIee+wxBQQEqH379s4n5QYGBmrGjBnatWuXPD091bVrVy1dulQeHh5q0KCB/v73v2vChAlyOBxq3769Pv30U4WHh1fpWGw2m5YuXarJkyfr7rvv1uHDhxUdHa2rrrpKUVFRLsc8dOhQ/fvf/9a7777rso3Y2Fj93//9nyZOnKhrrrlGRUVFio+P18CBA+XhwTBEwB1sxpx4cAIAAIAF8WcEAACwNMIMAMv65ptvXG6RPnUCcHHgMhMAyyooKND+/fvPuPySSy6pxWoAuAthBgAAWBqXmQAAgKURZgAAgKURZgAAgKURZgAAgKURZgAAgKURZgAAgKURZgAAgKURZgAAgKX9/4vlJttO615FAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== heart_rate =====\n", + "count 132.000000\n", + "mean 71.204545\n", + "std 4.867306\n", + "min 65.000000\n", + "25% 68.000000\n", + "50% 70.000000\n", + "75% 74.000000\n", + "max 86.000000\n", + "Name: heart_rate, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== daily_steps =====\n", + "count 132.000000\n", + "mean 6637.878788\n", + "std 1766.288657\n", + "min 3000.000000\n", + "25% 5000.000000\n", + "50% 7000.000000\n", + "75% 8000.000000\n", + "max 10000.000000\n", + "Name: daily_steps, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== systolic =====\n", + "count 132.000000\n", + "mean 128.363636\n", + "std 7.825650\n", + "min 115.000000\n", + "25% 120.750000\n", + "50% 130.000000\n", + "75% 135.000000\n", + "max 142.000000\n", + "Name: systolic, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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dABGRoajVamg0mkbfr1KphEqlavT9EjVVDDNE1Cyp1Wq0CQxEQX5+o+9bbmWF61FRDDRE9YRhhoiaJY1Gg4L8fDz/1sdwVfk22n5T1DHYsmIhNBoNwwxRPWGYIaJmzVXlC0+/IEOXQUSPgB2AiYiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIMGmbWrVuHDh06wM7ODnZ2dujduzd+++03/XJRFBESEgIPDw/I5XIMHDgQV69eNWDFREREZGwMGmY8PT3x0Ucf4cKFC7hw4QIGDx6MJ554Qh9YVq5ciVWrVmHNmjU4f/483NzcMGzYMOTk5BiybCIiIjIiBg0zwcHBGD16NPz9/eHv748PP/wQNjY2OHPmDERRxOrVq/Huu+9i/PjxaNeuHTZt2oT8/Hxs3brVkGUTERGRETGaPjOlpaXYvn078vLy0Lt3b8TGxiI5ORnDhw/XryOTyTBgwACcOnWq2u3odDpotdoKExERETVdBg8zV65cgY2NDWQyGV555RXs3LkTbdu2RXJyMgDA1dW1wvqurq76ZVVZvnw5FAqFfvLy8mrQ+omIiMiwDB5mAgICEBERgTNnzmDmzJmYMmUKrl27pl8uCEKF9UVRrDTv7xYtWoTs7Gz9FB8f32C1ExERkeEZ/HEGFhYWaN26NQCgW7duOH/+PD777DO89dZbAIDk5GS4u7vr109NTa10tubvZDIZZDJZwxZNRERERsPgZ2buJ4oidDodWrZsCTc3Nxw4cEC/rKioCMeOHUOfPn0MWCEREREZE4OemXnnnXcwatQoeHl5IScnB9u3b8fRo0exb98+CIKAefPmYdmyZfDz84Ofnx+WLVsGKysrTJo0yZBlExERkRExaJhJSUnB5MmTkZSUBIVCgQ4dOmDfvn0YNmwYAODNN99EQUEBZs2ahczMTPTs2RO///47bG1tDVk2ERERGRGDhplvv/32gcsFQUBISAhCQkIapyAiIiKSHKPrM0NERERUGwwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQwzREREJGkMM0RERCRpDDNEREQkaQYNM8uXL0f37t1ha2sLFxcXPPnkk7hx40aFdaZOnQpBECpMvXr1MlDFREREZGwMGmaOHTuG2bNn48yZMzhw4ABKSkowfPhw5OXlVVhv5MiRSEpK0k979+41UMVERERkbMwMufN9+/ZVeL1hwwa4uLggLCwMjz32mH6+TCaDm5tbY5dHREREEmDQMHO/7OxsAICjo2OF+UePHoWLiwvs7e0xYMAAfPjhh3BxcalyGzqdDjqdTv9aq9U2XMFERET3UavV0Gg0jb5fpVIJlUrV6Ps1BkYTZkRRxPz589GvXz+0a9dOP3/UqFF45pln4O3tjdjYWPzrX//C4MGDERYWBplMVmk7y5cvx5IlSxqzdCIiIgD3gkybwEAU5Oc3+r7lVla4HhXVLAON0YSZOXPm4PLlyzh58mSF+RMmTND/vV27dujWrRu8vb2xZ88ejB8/vtJ2Fi1ahPnz5+tfa7VaeHl5NVzhREREf9JoNCjIz8fzb30MV5Vvo+03RR2DLSsWQqPRMMwYyty5c7F7924cP34cnp6eD1zX3d0d3t7euHXrVpXLZTJZlWdsiIiIGouryheefkGGLqPZMGiYEUURc+fOxc6dO3H06FG0bNnyoe9JT09HfHw83N3dG6FCIiIiMnYGvTV79uzZ2Lx5M7Zu3QpbW1skJycjOTkZBQUFAIDc3FwsWLAAp0+fRlxcHI4ePYrg4GAolUqMGzfOkKUTERGRkTDomZl169YBAAYOHFhh/oYNGzB16lSYmpriypUr+O6775CVlQV3d3cMGjQI33//PWxtbQ1QMRERERkbg19mehC5XI79+/c3UjVEREQkRXw2ExEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUkawwwRERFJGsMMERERSRrDDBEREUmamaELIKLK1Go1NBpNo+9XqVRCpVI1+n6JiB4FwwyRkVGr1WgTGIiC/PxG37fcygrXo6IYaIhIUhhmiIyMRqNBQX4+nn/rY7iqfBttvynqGGxZsRAajYZhhogkhWGGyEi5qnzh6Rdk6DKIiIweOwATERGRpDHMEBERkaQxzBAREZGkMcwQERGRpBk0zCxfvhzdu3eHra0tXFxc8OSTT+LGjRsV1hFFESEhIfDw8IBcLsfAgQNx9epVA1VMRERExsagYebYsWOYPXs2zpw5gwMHDqCkpATDhw9HXl6efp2VK1di1apVWLNmDc6fPw83NzcMGzYMOTk5BqyciIiIjIVBb83et29fhdcbNmyAi4sLwsLC8Nhjj0EURaxevRrvvvsuxo8fDwDYtGkTXF1dsXXrVsyYMcMQZRMREZERMao+M9nZ2QAAR0dHAEBsbCySk5MxfPhw/ToymQwDBgzAqVOnDFIjERERGRejGTRPFEXMnz8f/fr1Q7t27QAAycnJAABXV9cK67q6uuLOnTtVbken00Gn0+lfa7XaBqqYiIiIjIHRnJmZM2cOLl++jG3btlVaJghChdeiKFaaV2758uVQKBT6ycvLq0HqJSIiIuNgFGFm7ty52L17N44cOQJPT0/9fDc3NwB/naEpl5qaWulsTblFixYhOztbP8XHxzdc4URERGRwBg0zoihizpw52LFjBw4fPoyWLVtWWN6yZUu4ubnhwIED+nlFRUU4duwY+vTpU+U2ZTIZ7OzsKkxERETUdBm0z8zs2bOxdetW/PLLL7C1tdWfgVEoFJDL5RAEAfPmzcOyZcvg5+cHPz8/LFu2DFZWVpg0aZIhSyciIiIjYdAws27dOgDAwIEDK8zfsGEDpk6dCgB48803UVBQgFmzZiEzMxM9e/bE77//Dltb20auloiIiIyRQcOMKIoPXUcQBISEhCAkJKThCyIiIiLJMYoOwERERER1xTBDREREksYwQ0RERJLGMENERESSZjSPMyBpUKvV0Gg0jb5fpVIJlUrV6PslIiLjxzBDNaZWq9EmMBAF+fmNvm+5lRWuR0Ux0BARUSUMM1RjGo0GBfn5eP6tj+Gq8m20/aaoY7BlxUJoNBqGGSIiqoRhhmrNVeULT78gQ5dBREQEgB2AiYiISOIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNLqFGZatWqF9PT0SvOzsrLQqlWrRy6KiIiIqKbqFGbi4uJQWlpaab5Op8Pdu3cfuSgiIiKimqrVgyZ3796t//v+/fuhUCj0r0tLS3Ho0CH4+PjUW3FERERED1OrMPPkk08CAARBwJQpUyosMzc3h4+PDz755JN6K46IiIjoYWoVZsrKygAALVu2xPnz56FUKhukKCIiIqKaqlWYKRcbG1vfdRARERHVSZ3CDAAcOnQIhw4dQmpqqv6MTbn169c/cmFERERENVGnMLNkyRJ88MEH6NatG9zd3SEIQn3XRURERFQjdQozX375JTZu3IjJkyfXdz1EREREtVKncWaKiorQp0+f+q6FiIiIqNbqFGamTZuGrVu31nctRERERLVWp8tMhYWF+Prrr3Hw4EF06NAB5ubmFZavWrWqXoojIiIiepg6hZnLly+jU6dOAIDIyMgKy9gZmIiIiBpTncLMkSNH6rsOIiIiojqpU58ZIiIiImNRpzMzgwYNeuDlpMOHD9e5ICIiIqLaqFOYKe8vU664uBgRERGIjIys9ABKIiIiooZUpzDz6aefVjk/JCQEubm5j1QQERERUW3Ua5+ZF154gc9lIiIiokZVr2Hm9OnTsLS0rM9NEhERET1QnS4zjR8/vsJrURSRlJSECxcu4F//+le9FEZERERUE3UKMwqFosJrExMTBAQE4IMPPsDw4cPrpTAiIiKimqhTmNmwYUN910FERERUJ3UKM+XCwsIQFRUFQRDQtm1bdO7cub7qIiIiIqqROoWZ1NRUTJw4EUePHoW9vT1EUUR2djYGDRqE7du3w9nZub7rJCIiIqpSne5mmjt3LrRaLa5evYqMjAxkZmYiMjISWq0Wr776an3XSERERFStOp2Z2bdvHw4ePIjAwED9vLZt22Lt2rXsAExERESNqk5nZsrKymBubl5pvrm5OcrKyh65KCIiIqKaqlOYGTx4MF577TUkJibq5929exevv/46hgwZUuPtHD9+HMHBwfDw8IAgCNi1a1eF5VOnToUgCBWmXr161aVkIiIiaqLqFGbWrFmDnJwc+Pj4wNfXF61bt0bLli2Rk5ODL774osbbycvLQ8eOHbFmzZpq1xk5ciSSkpL00969e+tSMhERETVRdeoz4+XlhfDwcBw4cADXr1+HKIpo27Ythg4dWqvtjBo1CqNGjXrgOjKZDG5ubnUpk4iIiJqBWp2ZOXz4MNq2bQutVgsAGDZsGObOnYtXX30V3bt3R1BQEE6cOFGvBR49ehQuLi7w9/fH9OnTkZqa+sD1dTodtFpthYmIiIiarlqFmdWrV2P69Omws7OrtEyhUGDGjBlYtWpVvRU3atQobNmyBYcPH8Ynn3yC8+fPY/DgwdDpdNW+Z/ny5VAoFPrJy8ur3uohIiIi41OrMHPp0iWMHDmy2uXDhw9HWFjYIxdVbsKECRgzZgzatWuH4OBg/Pbbb7h58yb27NlT7XsWLVqE7Oxs/RQfH19v9RAREZHxqVWfmZSUlCpvydZvzMwMaWlpj1xUddzd3eHt7Y1bt25Vu45MJoNMJmuwGoiIiMi41OrMTIsWLXDlypVql1++fBnu7u6PXFR10tPTER8f36D7ICIiImmpVZgZPXo03n//fRQWFlZaVlBQgMWLF+Pxxx+v8fZyc3MRERGBiIgIAEBsbCwiIiKgVquRm5uLBQsW4PTp04iLi8PRo0cRHBwMpVKJcePG1aZsIiIiasJqdZnpvffew44dO+Dv7485c+YgICAAgiAgKioKa9euRWlpKd59990ab+/ChQsYNGiQ/vX8+fMBAFOmTMG6detw5coVfPfdd8jKyoK7uzsGDRqE77//Hra2trUpm4iIiJqwWoUZV1dXnDp1CjNnzsSiRYsgiiIAQBAEjBgxAqGhoXB1da3x9gYOHKjfRlX2799fm/KIiIioGar1oHne3t7Yu3cvMjMzER0dDVEU4efnBwcHh4aoj4iIiOiB6jQCMAA4ODige/fu9VkLERERUa3V6dlMRERERMaCYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCTNzNAFEBE9qsLiUqgz8nE3qwA5hSXIKSxGbmEJcnUlKBNFyMxMITMzgYWZCeTmpnC3l0OrLYFgZmHo0omoHjDMEJFkFJWU4UZyDi4lZOFKQjZua3JxJz0fqTm6Om1P9cYO7EkQ4aRNgLvCEu4KS7gpLGFlwV+NRFLCn1giMloFRaU4H5eBP6I1OBObgagkLYpKyqpc11ZmhhYOcthbmcPW0hy2lmawlZnBxESArqQMuuIy6EpKkacrQVJ2IeI0uSgsEVFYJuBuVgHuZhXot6WQm8PHyQqtXWzgYS+HiSA01kcmojpgmCEioxKdmosD11Jw4lYaLsRloqi0YnhRyM3RwVOBDp4KBLjZwdvRCipHK9hbmUOoRegICwtDj34DMWX5f2Hi0AJJ2YVIyi5ERl4RsguKcSkhG5cSsiE3N4WvszX8XG3h5SCv1T6IqHEwzBCRQYmiiMi7Wuy7moT9V1MQnZpbYbm7whL9WivRt7USnVX2UDla1UugEAQBZYW5cLAQ4emhQJCHAgCgKy7F3awCRKfl4nZaHgqKSxGZqEVkohb2Vubo6GmPQHdbyMxMH7kGIqofDDNEZBAxabn45eJd7IpIhDojXz/f3FRAb18lhrRxQT8/JVoprRv1bIjM3BStnG3QytkGpWUiEjLzEZ2ai5spucjKL8axm2k4FaNBoJsdOqvsYW/FTsREhsYwQ0SNJjOvCLsi7mLnxbu4nJCtny83N8WgNs4YEeSGQW1cYGdpbsAq/2JqIsDbyRreTtbo7+eMqGQtLsdnIyO/CJfvZiMyMRtt3e3Qo6UjbI2kZqLmiGGGiBqUKIo4G5uBbefU+C0yWd+B19REwGN+SjzZuQWGtXU1+juILMxM0NHTHh1aKJCQWYAwdSbupOcjMlGLqKQctPdUoJu3A6xlxv05iJoi/tQRUYNIz9Xh5/AEbD8Xj9uaPP38tu52eKabJ4I7ekBpIzNghXUjCAK8HK3g5WiFu1kFOB2TjrtZBYiIz8LVxGz0bOmETl72MDVhR2GixsIwQ0T1RhRFXLiTiU2n4rD/ajKKS0UAgLWFKcZ28sBzPVRo30LRZO4IamEvx1NdWiA+swCnYjRI0epwMlqDqCQtBgW4oIWD3NAlEjULDDNE9MgKi0ux+1IiNp2Kw9VErX5+R08FnuuhwuMdPWDTRC+/CIIAlaMVvBy8cC1Jiz+i05GeV4SfwhPQxs0W/f2URn8JjUjq+BNGRHWWmFWAzWfuYNs5NTLziwEAMjMTPNmpBSb39ka7FgoDV9h4BEFAkIcCvs42+CNGg8i7WlxPzsGd9HwMbuOC1i42hi6RqMlimCGiWhFFEediM7DxVBx+v5aC0rJ7l5Ja2Msxubc3JnTzgoN1871d2dLcFEPauCLIXYFD11OgyS3CnitJCHS3xQB/Z0OXR9QkGfSp2cePH0dwcDA8PDwgCAJ27dpVYbkoiggJCYGHhwfkcjkGDhyIq1evGqZYomausLgUP1yIx+jPT2LC12fwW2QySstE9GrliC9f6IpjCwfilQG+zTrI/J2bwhITunuhm7cDBABRSTnYclaN1MKm0V+IyJgY9MxMXl4eOnbsiBdffBFPPfVUpeUrV67EqlWrsHHjRvj7+2Pp0qUYNmwYbty4AVtbWwNUTNT8pOYUYvMZNbacuYP0vCIAgKW5CcZ1boEpfXzQxs3OwBUaLzMTE/RtrURLpTV+v5aC7IJinCg0g6L/C/ozWkT06AwaZkaNGoVRo0ZVuUwURaxevRrvvvsuxo8fDwDYtGkTXF1dsXXrVsyYMaMxSyVqdiLvZmP9yVj873Ki/q4kd4UlpvTxwcTuXhz5thY87OWY1EOFE7fS7j0Woc9ELDmegfUBhXCxtTR0eUSSZ7R9ZmJjY5GcnIzhw4fr58lkMgwYMACnTp2qNszodDrodDr9a61WW+V69UWtVkOj0TToPqqiVCqhUqkafb/UxAkmOJ1QgI/Onca5uAz97K7eDnixrw9GBLnB3NSgV6cly8LMBEMCXSHXZeBsUjEiU4Exn5/E5xM7o7evk6HLI5I0ow0zycnJAABXV9cK811dXXHnzp1q37d8+XIsWbKkQWsrp1ar0SYwEAX5+Q9fuZ7JraxwPSqKgYbqha64FDe1Jmgx4xt8fCoLAGBmImBMB3e82LclOnnZG7S+pkRlXYZdm15Hrzf+g3itDs//5wwWjmiDVwa0ajLj7xA1NqMNM+Xu/+EWRfGBP/CLFi3C/Pnz9a+1Wi28vLwapDaNRoOC/Hw8/9bHcFX5Nsg+qpKijsGWFQuh0WgYZuiRZOYXISI+C1FJWhSXmsFM4QpbCwFT+vrihV7ecFPwEkhDKMlIwMqhSvwUZ4afwxOwYt91RCVpseKpDpBb8GncRLVltGHGzc0NwL0zNO7u7vr5qamplc7W/J1MJoNM1rhDpLuqfOHpF9So+ySqK1EUEZ9ZgIvqTMSl/3VW0c68DLG712DbN8vQu0eAAStsHmRmAj55tiO6eNtj8S9XsftSIm5rcvH15G7wsOfIwUS1YbQXv1u2bAk3NzccOHBAP6+oqAjHjh1Dnz59DFgZkTTpSkpxKT4Lm8+qsfPiXX2Qaam0xrjOLTDUrQS5l3+HzIyXOhrT8z29sWVaTzhaWyDyrhZj15zEhb/1VyKihzPomZnc3FxER0frX8fGxiIiIgKOjo5QqVSYN28eli1bBj8/P/j5+WHZsmWwsrLCpEmTDFg1kbRocnW4nJCN68la/V1J5qYC2rrboaOXPRz+vCspId2QVTZvPVs5Yfecvpj+XRiikrR47psz+Gh8BzzV1dPQpRFJgkHDzIULFzBo0CD96/K+LlOmTMHGjRvx5ptvoqCgALNmzUJmZiZ69uyJ33//nWPMED1EaZmI6NRcXE7IQmJ2oX6+g5U5OnjaI9DdFjIz9s0wJp4OVvh5Zm8s/PEy9lxJwhs/XoI6Ix/zhvqxYzDRQxg0zAwcOBCiWP3AUYIgICQkBCEhIY1XFJGEaQuKEZmYjci7WhQUlwIABAHwdbZBhxYKeDrI+cVoxKwszPDFc53h7WSF0KMx+OzQLcRn5OOjpzrAwsxoewUQGZzRdgAmopopKSvD7bQ8XE3UQp3xV4dea5kp2nko0K6Fosk+sbopMjER8ObINlA5WuHdXZHYcfEuErML8NUL3aCwMjd0eURGib/hiCRKk6vD1UQtridrUVhcpp/v6SBHB08FWiltYGrCszBSNbGHCh72cszaEo4ztzMwft0f2DC1B1ROVoYujcjoMMwQSUhBcSlupeTgWpIWKdq/Rrq2kZkh0N0Wbd3t+JiBJuQxf2f8NLM3XtpwHjFpeRgX+gf+M6UbOqscDF0akVFhmCEyciWlZbitycON5BzEpeeh/PmEJsK926qDPBTwdrKCCfvCNElt3Oywc3ZfvLTxPK4majHx6zP4/LnOGBHkZujSiIwGwwyRMRJMkFoo4Nq1ZMSk5qGo9K/LSM42MrRxs0Ubd1tYWfBHuDlwtbPEDzN6Y+62izh8PRWvbA7DkrFB+EdvH0OXViN8hh01NP4mJDISxaVlOB2Tjv9eyIbn7E04kWoOIAcAYGtphgBXW7Rxs4WTTeOOcE3GwVpmhq8nd8W/frmKbefUeP+Xq7ibVYC3RrSBiRH3jeIz7KgxMMwQGVBhcSlO3tLgt8hkHIxKQXZBMQDA1NoB5iYiAtwVaONqBw97S95STTAzNcGyce3g6SDHx/tv4Ktjt5GUVYiPn+lgtOMG8Rl21BgYZogaWXJ2IY7eSMWRG6k4eUuDvKJS/TKljQW6uJjhv8vn45UF70PlX/1zyKh5EgQBswe1hrvCEm/+dBm7LyUiNacQX03uBoXceG/d5jPsqCExzBA1sOLSMoTfycSRG2k4eiMV15NzKix3V1hiRJAbRrZzQ3cfR1yKuIhv4iJgxFcOyAiM7+IJF1tLvLI5DGduZ+CZL09hw4s90IIPqaRmiGGGqJ6Vlom4lqjF6dsanLmdgfOxGcjRleiXCwLQycsegwJcMDDAGe08FEbd54GMVz8/JX6Y0RsvbjyHmym5GB96byyath52hi6NqFExzBA9oqKSMkQlaXE+LgOnY9Jx7r7wAgCO1hZ4zE+JQW1c0N/PGY7WHAuG6kdbDzvsnNUXUzfcCzTPfnUa617ogv5+zoYujajRMMwQ1YIoikjILMDF+CxEqLMQEZ+JyEQtikrKKqxna2mGni0d0auVE3q1ckKgux1H46UG42Evx4+v9MGM/17AmdsZeHHDeax4ik/dpuaDYYaoGmVlIuLS83AtSYuoJC2uJWpx5W42NLlFlda1tzJHF5UDev8ZXtp6MLxQ41LIzbHppR5Y+OO9TsFv/HgJSdkFmD2oNe+EoyaPYYaaPVEUkaLVITo1FzFpubj55+MCbiTnIP9vdxqVMzMR0NbDDp297NFJZY9OXg7wcbLiFwYZnMzMFKsndIKHvRxfHovB//1+E3ezCvDvJ9rBzJRP3aami2GGmo2S0jKoM/IRnZqL6LTcP8NLHm6n5lbq41JOZmaCNu52aOtuh7butmjroUCQhx0szY1zTA8iExMBb49qAw97S4Tsvopt5+KRnF2INZO6wJpPT6cmikc2NTn5RSW4nZaHmD8DS/kUl56H4lKxyveYmgjwdrRCK2cbtHaxQVuPe+HFx8ma/6MlSfpHbx+42Vni1e0XceRGGp775gy+ndIdzrYcQZqaHoYZkqz0XJ3+7Er52ZaY1FzczSqo9j1yc1O0crZGaxcbtP4zuPi62MDbycpoR1AlqqvhQW7YOr0Xpm26gMsJ2Ri/7g9sfLEHfJ1tDF0aUb1imCGjV1wGyDyDsOdWHn6Ivazv25KZX1ztexytLdDa+V5Q8S0PLy428FDIOaYLNStdVA74eWYfTN1wDnfS8zE+9BRCn++Cvq2Vhi6NqN4wzJBRydWVIEVbiLQcHdJydNDk6qAttIDb8yvw7UUtAK1+XUEAWtjL9WdZfP8MLL7ONhzHhehvWiqt8fPMPpj+3QVcVGfhH+vPYXFwW0zu5c2O69QkMMyQwRSXliE1R4fk7EIkawuRnF2I3Go64pZkp6JXoBd6BXjBz/VeaGmltIHcgpeGiGpCaSPDtum98M6OK9hx8S7e/+UqrifnYMnYIJizXxhJHMMMNZqikjIkZhcgIaMA8Zn5SMvVQbyvP64AwMnGAs62MjjbyOBsK0NRSizWrHgJ74SFoUuXAIPUTtQUWJqb4pNnO8LfzRYr9l3H1rNqxKTmIvT5LnCyYcdgki6GGWowJWVlSM4uRPyf4SVFW4iy+8KLlYUp3BWWcLOzhJvCEi62lrAwq/i/xARNIxZN1MQJgoBXBvjCz8UGr22PwNnYDAR/cRJrn++CzioHQ5dHVCcMM1Sv8otKEKfJx21NLtQZ+ZVuhba1NIOXgxW8HOXwsJfDVmbGa/ZEBjAk0BU7Z/XBjP+G4bYmD89+dRr/epz9aEiaGGbokYiiiIy8IsRq8nBbk4ek7MIKy60sTOHlYAVPRzm8HKygkJsbqFIiup+fqy1+mdMXb/18GXuvJOP9X64i7E4mlo9vDysLfj2QdPBopTrJyi/CjZQc3EjOqXSLtLOtDC2V1miltIaLrYz/yyMyYraW5lg7qQu+PRmL5b9dxy8RibiaqMVnEzshyENh6PKIaoRhhmoso6AUtt2ewOFkM2Sq7+jnmwoCPB3laKW0RkulNWwtefaFSEoEQcC0/q3QwdMec7aGIzo1F+PWnsLCEQF4uV9Ljs1ERo9hhh6osLgUe68k4aewBJyOSYfjkOnILLo3xovKwQr+brbwdbbm6LlETUCPlo747bX+eHvHFRy4loIP90bh6M1UfPJMJ7gpLA1dXpNXViaipEyEiXAvYJb/SQ/HMENVup6sxfZz8dgRngBt4V9jvxQmXEOv9v7o3s6P19SJmiAnGxm+ntwV287F49+/XsMf0ekY+dlxLBkbhLEdPfjlWkdlZSKyC4uRlV+MrPyie38WFKOwuPTPqQxFpWWV3icAkFuYwkZmBltLM9jIzGBnaa4fwoK/h+9hK5Benq4Ev15OxLZz8YiIz9LPb2Evx4TuXvC3yMSox96E79od/AEiasIEQcCknir0bOWIedsjcOVuNl7bHoGfw+/iwyfbwcvRytAlGr28EuBmSg6StYVIyS5Eao4OJfePTVEDIoD8olLkF5UiNUdXablCbg4Pe0tY60xgYtV8+zjxG4mgTs/HxlNx+OFCvH4EXjMTAcPaumJiDxX6t1bCxERAeHi4gSslosbk62yDn2f2wdfHY/D54Wgcv5mGYZ8ew/xh/nipb0s+Uf5vkrILcCo6Hb+ez0KLmeuxL9ECSEyusI6ZiQB7K3PYyy3u/WllDisLM1iam8DS3BSW5qYwNxFQJt67U7RMBEpFEflFJcgtLEGO7t6fWQXF0OTokFVQjOw/J8AMnnP+i0WHNHheF4fHO3g0q8e6MMw0U6Io4mxsBtafjMWBqBT9SLw+TlaY0F2Fp7t6wtmWI4ISNXcWZiaYM9gPo9u7452dV3DmdgaW7b2OnRcT8e7oQPTza54PrCwpLUO4OguHolJwMCoFMWl5+mVmdi4QIMLFzhKudvcGBXW1s4SDlXmdLtPZyMzgYlt5vq6kFEnZhbibWYDoxHRkFZvgRnox3v/lKj743zUMDHDB+C4tMDTQtdJgpE0Nw0wzoyspxf8uJWH9yVhcS/rroY0D/J3xYl8fPObnzDsXiKiSVs422Da9F368kIAP90YhKkmLF749iwH+zlg0ug3auNkZusQGpy0sxvGbaTgUlYojN1KR9bdhKUwEoL2nPXyti7Fuyev45xvvwyfAv0HrkZmZwsfJGj5O1vAWU/DZW9Pwr2924XwaEHlXi4N/Bi13hSVe7tcSE3uoYCNrml/7TfNTUSW5uhJsOXMH/zkZi7Q/r7tampvgqS6eeLGvD1pXFfuJiP5GEAQ8290LQ9u64vNDt7D5zB0cu5mGE7fS8HRXT7w6xA+eDk2rP018Rj4ORqXgUFQqzsamVxjVXCE3x6AAZwwJdMVj/s5QyM0RHh6OT+MiYIgTIaW5GQj2t8biiV1wKyUHOy7exU9hCUjKLsTSPVH47NAtTO7ljal9feBi27TuTmOYaeIy8oqw8Y9YbDwVp78ryc3OEv/o441JPVSwt2o+11SJqH44WlsgZGwQpvbxwcr917H3SjJ+uJCAn8PvIriDO/75mC/aekjzTE1pmYiL6kwcup6KQ1EpuJmSW2F5K2drDA10xZA2Lujq7WC0/Yb8XG3x1sg2mDfUD7su3sVXx2/jdloeQo/GYP0fsZjevxVmDPBtMmdqmsanoEqSsgvwzfFYbDunRkFxKYB7P4QzB/jiiU4tmvz1UyJqeD5Ka4Q+3xXh6kys+v0mTkZrsCsiEbsiEtHfT4np/VtBXoc7eBpbdsG9y0eHr6fi6I3UCqOam5oI6ObtcC/ABLqglbONASutPZmZKSZ0V+GZrl44EJWCdUdjEBGfhS8OR2PbuXi8Mdwfz3T1NNpQVlMMM01MQmY+1h6Jxk9hCfrToe1bKDBroC+GB7nBlP1hiKiedVE5YPO0noi8m42vjt/GnsuJOHFLgxO3NHCSm8B+wBRoi4znd09pmYioJC3+iNbgyI1UnI/LROnfQpedpRkGBrhgSKALBvg7N4kz2CYmAkYEuWF4W1fsv5qMj367jrj0fCzacQUb/4jD4rFt0cdXup25GWaaiMSsAqw9Eo0fLsTrQ0yvVo6YNbA1+vspOdAVETW4di0U+OK5znhzRAC+PRmLHeEJSC8ogaLXMziQDFzKU8PX2QYqRyu42Mlg0ki/l0pKy3AjJQdhdzJxKjodp2+n/3k781/8XGwwONAFgwOM+/LRoxIEASPbuWNwG1dsPnMHnx++hRspOZj0zVlM7O6FRaMDJflAYIYZiUvOLkTo0WhsPxevHz2yX2sl5g31QzcfRwNXR0TNkZejFULGBuHtUW3w7W9nsGTTPlj79URqjg6pOTqcvp0OmZkJvBys4Okgh9JWBqW1BWTmj/5YlOLSMmTlFyM+zwT2g17Ce4fTEbvzd/3l9nI2MjP0bOmIfn5KDGnjCpVT0+q4/DAWZiZ4qV9LPNXFEx//fh2bz6ix/Xw8Dl1Pxb+fCMLIdu6GLrFWGGYkysTaHt9ezMaBHUdQVHIvxPRq5YjXh/qjZysnA1dHRARYmpuit6ccaTuW4tnPdyDfxhN3MvIQn1kAXUkZotNyEZ32VwdbG5kZnGwsYGtpBitzM8gtTCE3N4Xszz5+IgARIiACupIyFBSVIr+4FAVFpcjVlSAzvwg5+sevmEHRYzyuaYoAALYyM3T0skdvXyf09nVChxaKJnv2pTYUVuZY+mR7jO3YAm//fBm3NXl4ZXM4RrVzw4fj2ktm4D2GGYnRlZTiapYpWvzzP9hzKx8A0N3HAa8P85f09U4iatpkpoCvpwLtPRUoKxORklMIdUY+krMLocktQq6uRD89KkszE1iblCDu7D4s+udzeLJ/R7RS2nAMrQfo0dIRe1/rjzWHo/HlsRj8FpmMsDuZ+HRCJ/RtbfzfLQwzElFSVobIu1qci81AQbEpTCxM4edojvfHdUa/1uwTQ0TSYWIiwF0hh7tCrp+nKy5Fel4R0vOKkKcrQcGfZ1wKikqhKy1D+W+48l91MrN7Z23kFvcmawtT2FtZwNHKAnILUyTcuopVv4di8PKXOY5WDVmam2LBiACMbOeG17ZfRExaHl749ixmPOaL+cP8jfouWIYZIyeKIm6k5OB0TLp+nBgbMxG3f1yGn7d+ga5+zgaukIjo0cnMTeFhL4eHvfzhK1ODatdCgV/n9scHv17DtnNqfHksBqdiNPh8Ymf4KK0NXV6VjDdmNXOiKCIuPQ9bz6mx/2oKtIUlsLYwxeA2LhjmXoyCm6d5NoaIiBqE3MIUy8e3x5cvdIFCbo7LCdkIXnMSB6+lGLq0KjHMGKEUbSF2XLyLXyISocktgoWpCfr4OmFKHx+0b6EAL/sSEVFjGNnOHfvm9Uc3bwfkFJZg2ncX8MnvNyqMy2MMeJnJiOQUFuNUTDquJ+cAAEwFAR28FOju4wh5PdyySEREVFvuCjm2Tu+FZXujsPFUHL44HI1LCdn4fGInoxlQkGHGCBSXliHsTibC7mSi5M+028bNFr1bOcFOgoMXERFR02JhZoKQsUHo6KXAoh1XcPxmGh7/4iS++Uc3BLob/jlcRn2ZKSQkBIIgVJjc3NwMXVa9EcV7Q2pvOh2Hs7EZKCkT4aGwxMTuXhgR5MYgQ0RERmVcZ0/smNkXKkcrJGQW4Kl1p7D/arKhyzL+MzNBQUE4ePCg/rWpadO43HI3swDHb6UhNUcH4N6zQPq1VqK1iw079hIRkdFq62GH3XP6YvbWcPwRnY4Z/w3DwhEBmD2otcFqMvowY2Zm1qTOxmQXFONktAbRqfdGvbQwNUH3lg7o5GnP0SiJiEgS7K0ssPHFHvhwz71+NDIDj0Fj9GHm1q1b8PDwgEwmQ8+ePbFs2TK0atWq2vV1Oh10Op3+tVarbYwyH6q4tAwX4jIRpr73dFYBQFALO/Ru5QQrC6P/ZyBqUGq1GhqNplH3GRUV1aj7I2pqzE3v9aMZEeSGXq0M+yxAo/4W7dmzJ7777jv4+/sjJSUFS5cuRZ8+fXD16lU4OVX9/KHly5djyZIljVxp9URRRHRqLk5Ea/TPDPFykOMxf2cobWQGro7I8NRqNdoEBqIgP98g+8/NzX34SkRUrd6+hn8eoFGHmVGjRun/3r59e/Tu3Ru+vr7YtGkT5s+fX+V7Fi1aVGGZVquFl5dXg9dalfRcHY7eTENCZgEAwNbSDP39lGjtzH4xROU0Gg0K8vPx/Fsfw1Xl22j7jTp3DL9t+gyFhYWNtk8iahhGHWbuZ21tjfbt2+PWrVvVriOTySCTGfaMh66kFGdvZ+BSQhbKRMDUREBXbwd083aAOfvFEFXJVeULT7+gRttfijqm0fZFRA1LUmFGp9MhKioK/fv3N3QpVbp3q3UO/ojRIL+oFADg62yN/n7OUPA2ayIiogZh1GFmwYIFCA4OhkqlQmpqKpYuXQqtVospU6YYurRKUrSFOHojDcnae6es7a3MMdDfGd5OxvlQLiIioqbCqMNMQkICnnvuOWg0Gjg7O6NXr144c+YMvL29DV2anoncDmHppohTxwMAzE0F9GzphE5e9jDlQ5SIiIganFGHme3btxu6hGqVlJZh7608ePzza8Tl3RvIL8DNFv1aK2EjM+pmJSIialL4rVtHi3ZcwY8XtTC1tIHCvAzDOqjQwl5u6LKIiIiaHd5aU0eTe3vDTmaC9P1rMcSthEGGiIjIQBhm6qiDpz2+GuOC3IjfwCFjiIiIDIeXmR6BzMywKaaxh2Pn8O9ERGSMGGYkSJuRBgB44YUXDLJ/Dv9ORETGhGFGggpy7z08c8yMdxHQoWuj7ZfDvxMRkTFimJEwJw9vDv9ORETNHjsAExERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkMcwQERGRpDHMEBERkaQxzBAREZGkcdA8IiIDMMSzzpRKJVQqVaPvl6ihMcwQETUiQz5bTW5lhetRUQw01OQwzBARNSJDPVstRR2DLSsWQqPRMMxQk8MwQ0RkAI39bDWipowdgImIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSGGaIiIhI0hhmiIiISNIYZoiIiEjSOM4MSQaHf28cjd3Ohvh3JaKmhWGGjB6Hf28chmxnAMjNzTXIfolI+hhmyOhx+PfGYah2jjp3DL9t+gyFhYWNtk8ialoYZkgyOPx742jsdk5RxzTavoioaWIHYCIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0hhkiIiKSNIYZIiIikjSGGSIiIpI0jjNDRETURDTXx74wzBAREUlcc3/sC8MMERGRxDX3x74wzBARETURzfWxL+wATERERJLGMENERESSxjBDREREksYwQ0RERJImiTATGhqKli1bwtLSEl27dsWJEycMXRIREREZCaMPM99//z3mzZuHd999FxcvXkT//v0xatQoqNVqQ5dGRERERsDow8yqVavw8ssvY9q0aQgMDMTq1avh5eWFdevWGbo0IiIiMgJGHWaKiooQFhaG4cOHV5g/fPhwnDp1ykBVERERkTEx6kHzNBoNSktL4erqWmG+q6srkpOTq3yPTqeDTqfTv87OzgYAaLXaeq8vNzcXAJBw6yp0Bfn1vv3qpKhjAADJcTcRY23F/TaQtIRYAEBYWJj+37ox3LhxAwCPK+63fjW347m5fV5DH1e5ubn1/j1bvj1RFB++smjE7t69KwIQT506VWH+0qVLxYCAgCrfs3jxYhEAJ06cOHHixKkJTPHx8Q/NC0Z9ZkapVMLU1LTSWZjU1NRKZ2vKLVq0CPPnz9e/LisrQ0ZGBpycnCAIQr3Wp9Vq4eXlhfj4eNjZ2dXrtpsbtmX9YnvWH7Zl/WJ71p+m3paiKCInJwceHh4PXdeow4yFhQW6du2KAwcOYNy4cfr5Bw4cwBNPPFHle2QyGWQyWYV59vb2DVkm7OzsmuSBZAhsy/rF9qw/bMv6xfasP025LRUKRY3WM+owAwDz58/H5MmT0a1bN/Tu3Rtff/011Go1XnnlFUOXRkREREbA6MPMhAkTkJ6ejg8++ABJSUlo164d9u7dC29vb0OXRkREREbA6MMMAMyaNQuzZs0ydBmVyGQyLF68uNJlLao9tmX9YnvWH7Zl/WJ71h+25V8EUazJPU9ERERExsmoB80jIiIiehiGGSIiIpI0hhkiIiKSNIYZIiIikjSGmfscP34cwcHB8PDwgCAI2LVrV4XlO3bswIgRI6BUKiEIAiIiIiptY+DAgRAEocI0ceLExvkARuRBbVlcXIy33noL7du3h7W1NTw8PPCPf/wDiYmJFbah0+kwd+5cKJVKWFtbY+zYsUhISGjkT2Ic6qM9eWze87Cf85CQELRp0wbW1tZwcHDA0KFDcfbs2Qrr8Nj8S320J4/Nex7Wln83Y8YMCIKA1atXV5jfHI9Nhpn75OXloWPHjlizZk21y/v27YuPPvrogduZPn06kpKS9NNXX33VEOUatQe1ZX5+PsLDw/Gvf/0L4eHh2LFjB27evImxY8dWWG/evHnYuXMntm/fjpMnTyI3NxePP/44SktLG+tjGI36aE+Axybw8J9zf39/rFmzBleuXMHJkyfh4+OD4cOHIy0tTb8Oj82/1Ed7Ajw2gYe3Zbldu3bh7NmzVQ713yyPzUd/HGTTBUDcuXNnlctiY2NFAOLFixcrLRswYID42muvNWhtUvOgtix37tw5EYB4584dURRFMSsrSzQ3Nxe3b9+uX+fu3buiiYmJuG/fvoYs1+jVpT1FkcdmVWrSltnZ2SIA8eDBg6Io8th8kLq0pyjy2KxKdW2ZkJAgtmjRQoyMjBS9vb3FTz/9VL+suR6bPDPTQLZs2QKlUomgoCAsWLAAOTk5hi7J6GVnZ0MQBP2ztMLCwlBcXIzhw4fr1/Hw8EC7du1w6tQpA1UpHfe3Zzkem7VTVFSEr7/+GgqFAh07dgTAY/NRVNWe5XhsPlxZWRkmT56MhQsXIigoqNLy5npsSmIEYKl5/vnn0bJlS7i5uSEyMhKLFi3CpUuXcODAAUOXZrQKCwvx9ttvY9KkSfoHpiUnJ8PCwgIODg4V1nV1da30JHWqqKr2BHhs1savv/6KiRMnIj8/H+7u7jhw4ACUSiUAHpt18aD2BHhs1tSKFStgZmaGV199tcrlzfXYZJhpANOnT9f/vV27dvDz80O3bt0QHh6OLl26GLAy41RcXIyJEyeirKwMoaGhD11fFEUIgtAIlUnTg9qTx2bNDRo0CBEREdBoNPjmm2/w7LPP4uzZs3Bxcan2PTw2q/ew9uSx+XBhYWH47LPPEB4eXuvjrKkfm7zM1Ai6dOkCc3Nz3Lp1y9ClGJ3i4mI8++yziI2NxYEDByqcRXBzc0NRUREyMzMrvCc1NRWurq6NXaokPKg9q8Jjs3rW1tZo3bo1evXqhW+//RZmZmb49ttvAfDYrIsHtWdVeGxWduLECaSmpkKlUsHMzAxmZma4c+cO3njjDfj4+ABovscmw0wjuHr1KoqLi+Hu7m7oUoxK+RfvrVu3cPDgQTg5OVVY3rVrV5ibm1c4zZyUlITIyEj06dOnscs1eg9rz6rw2Kw5URSh0+kA8NisD39vz6rw2Kxs8uTJuHz5MiIiIvSTh4cHFi5ciP379wNovscmLzPdJzc3F9HR0frXsbGxiIiIgKOjI1QqFTIyMqBWq/Xjd9y4cQPAvTTs5uaGmJgYbNmyBaNHj4ZSqcS1a9fwxhtvoHPnzujbt69BPpOhPKgtPTw88PTTTyM8PBy//vorSktL9ddzHR0dYWFhAYVCgZdffhlvvPEGnJyc4OjoiAULFqB9+/YYOnSooT6WwTxqe/LY/MuD2tLJyQkffvghxo4dC3d3d6SnpyM0NBQJCQl45plnAIDH5n0etT15bP7lYd9B9/8nxdzcHG5ubggICADQjI9Ng95LZYSOHDkiAqg0TZkyRRRFUdywYUOVyxcvXiyKoiiq1WrxscceEx0dHUULCwvR19dXfPXVV8X09HTDfSgDeVBblt/aXtV05MgR/TYKCgrEOXPmiI6OjqJcLhcff/xxUa1WG+5DGdCjtiePzb88qC0LCgrEcePGiR4eHqKFhYXo7u4ujh07Vjx37lyFbfDY/MujtiePzb887Dvofvffmi2KzfPYFERRFBsgIxERERE1CvaZISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCEiIiJJY5ghIiIiSWOYISIiIkljmCGiZuPo0aMQBAFZWVkAgI0bN8Le3t6gNRHRo2OYISLJuT+U1NWECRNw8+bN+imKiAyGz2YiomZLLpdDLpcbugwiekQ8M0NEDeqnn35C+/btIZfL4eTkhKFDh+LYsWMwNzfXPwyz3BtvvIHHHnsMAHDnzh0EBwfDwcEB1tbWCAoKwt69exEXF4dBgwYBABwcHCAIAqZOnQoA0Ol0ePXVV+Hi4gJLS0v069cP58+fr7a2qi4z7d69G926dYOlpSWUSiXGjx9ff41BRA2CYYaIGkxSUhKee+45vPTSS4iKisLRo0cxfvx4dO3aFa1atcJ///tf/bolJSXYvHkzXnzxRQDA7NmzodPpcPz4cVy5cgUrVqyAjY0NvLy88PPPPwO499T6pKQkfPbZZwCAN998Ez///DM2bdqE8PBwtG7dGiNGjEBGRkaN6t2zZw/Gjx+PMWPG4OLFizh06BC6detWz61CRPXO0E+6JKKmKywsTAQgxsXFVVq2YsUKMTAwUP96165doo2NjZibmyuKoii2b99eDAkJqXK75U8WzszM1M/Lzc0Vzc3NxS1btujnFRUViR4eHuLKlSurfN+GDRtEhUKhX793797i888/X9ePS0QGwjMzRNRgOnbsiCFDhqB9+/Z45pln8M033yAzMxMAMHXqVERHR+PMmTMAgPXr1+PZZ5+FtbU1AODVV1/F0qVL0bdvXyxevBiXL19+4L5iYmJQXFyMvn376ueZm5ujR48eiIqKqlG9ERERGDJkSF0+KhEZEMMMETUYU1NTHDhwAL/99hvatm2LL774AgEBAYiNjYWLiwuCg4OxYcMGpKamYu/evXjppZf07502bRpu376NyZMn48qVK+jWrRu++OKLavcliiIAQBCESvPvn1cddgYmkiaGGSJqUIIgoG/fvliyZAkuXrwICwsL7Ny5E8C9wLJ9+3Z89dVX8PX1rXBWBQC8vLzwyiuvYMeOHXjjjTfwzTffAAAsLCwAAKWlpfp1W7duDQsLC5w8eVI/r7i4GBcuXEBgYGCNau3QoQMOHTr0SJ+XiBofb80mogZz9uxZHDp0CMOHD4eLiwvOnj2LtLQ0fbgYMWIEFAoFli5dig8++KDCe+fNm4dRo0bB398fmZmZOHz4sP593t7eEAQBv/76K0aPHg25XA4bGxvMnDkTCxcuhKOjI1QqFVauXIn8/Hy8/PLLNap38eLFGDJkCHx9fTFx4kSUlJTgt99+w5tvvlm/DUNE9YpnZoiowdjZ2eH48eMYPXo0/P398d577+GTTz7BqFGjAAAmJiaYOnUqSktL8Y9//KPCe0tLSzF79mwEBgZi5MiRCAgIQGhoKACgRYsWWLJkCd5++224urpizpw5AICPPvoITz31FCZPnowuXbogOjoa+/fvh4ODQ43qHThwIH788Ufs3r0bnTp1wuDBg3H27Nl6bBEiagiCWH6hmYjIAKZPn46UlBTs3r3b0KUQkUTxMhMRGUR2djbOnz+PLVu24JdffjF0OUQkYQwzRGQQTzzxBM6dO4cZM2Zg2LBhhi6HiCSMl5mIiIhI0tgBmIiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJI1hhoiIiCSNYYaIiIgkjWGGiIiIJO3/Aaqn1hfw5FYfAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== diastolic =====\n", + "count 132.000000\n", + "mean 84.537879\n", + "std 6.049926\n", + "min 75.000000\n", + "25% 80.000000\n", + "50% 85.000000\n", + "75% 88.500000\n", + "max 95.000000\n", + "Name: diastolic, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== gender =====\n", + "gender\n", + "Male 67\n", + "Female 65\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== bmi_category =====\n", + "bmi_category\n", + "Normal 73\n", + "Overweight 52\n", + "Obese 7\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "===== sleep_disorder =====\n", + "sleep_disorder\n", + "No Disorder 73\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "univariate_analysis(sleep_df_clean, numeric_cols, categorical_cols)" + ] + }, + { + "cell_type": "markdown", + "id": "807417d1-c9d7-4b28-b31f-01113de0d771", + "metadata": {}, + "source": [ + "### 5. Bivariate Analysis \n", + "Analysis of the relationship between two variables.\n", + "\n", + "- Explore correlations or associations between variables.\n", + "- Identify whether there is a significant relationship before building predictive models." + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "a1529203-13a1-4a79-aaa5-d7298080270c", + "metadata": {}, + "outputs": [], + "source": [ + "def correlation_analysis(df, numeric_columns, target_col, categorical_columns):\n", + " \n", + " # Correlation heatmap\n", + " corr = sleep_df_clean.select_dtypes(include=['int64', 'float64']).corr()\n", + " plt.figure(figsize=(10,8))\n", + " sns.heatmap(corr, annot=True, cmap='coolwarm')\n", + " plt.title(\"Correlation Matrix\")\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "7791583f-0e92-4987-bb09-cb6fcee82243", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "target_col = 'sleep_disorder'\n", + "correlation_analysis(sleep_df_clean, numeric_cols, target_col, categorical_cols)\n", + "plt.savefig(\"Correlation Matrix.png\")" + ] + }, + { + "cell_type": "markdown", + "id": "8e6a5f0f-4479-414f-b0f6-0180a13962b9", + "metadata": {}, + "source": [ + "### 7. Hypothesis Testing" + ] + }, + { + "cell_type": "markdown", + "id": "f953a299-1f09-4203-9c9b-7e71c598a480", + "metadata": {}, + "source": [ + "#### 7.1 Setup and Configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "5d4c2b0a-58b6-4154-aee4-7b8a0f9e069c", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from scipy import stats\n", + "import statsmodels.api as sm\n", + "import os" + ] + }, + { + "cell_type": "markdown", + "id": "75ad5877-8cd6-49de-9b36-f3560cedaf46", + "metadata": {}, + "source": [ + "### Primary Hypothesis (H1)\n", + "Individuals with high stress, high BMI, low sleep duration, and poor sleep quality are significantly more likely to have a sleep disorder." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "82e663f6-ba3c-4d24-9c5f-77eecced1989", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 0.81 0.72 0.76 18\n", + " 1 0.71 0.80 0.75 15\n", + "\n", + " accuracy 0.76 33\n", + " macro avg 0.76 0.76 0.76 33\n", + "weighted avg 0.76 0.76 0.76 33\n", + "\n", + "ROC-AUC: 0.787037037037037\n" + ] + }, + { + "data": { + "text/html": [ + "
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FeatureCoefficient
6systolic0.214925
4heart_rate0.183709
1sleep_duration0.062172
5daily_steps0.000423
3physical_activity_level-0.053785
0stress_level-0.396165
2quality_of_sleep-0.597751
\n", + "
" + ], + "text/plain": [ + " Feature Coefficient\n", + "6 systolic 0.214925\n", + "4 heart_rate 0.183709\n", + "1 sleep_duration 0.062172\n", + "5 daily_steps 0.000423\n", + "3 physical_activity_level -0.053785\n", + "0 stress_level -0.396165\n", + "2 quality_of_sleep -0.597751" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean['has_disorder'] = sleep_df_clean['sleep_disorder'].apply(lambda x: 0 if x == \"No Disorder\" else 1)\n", + "\n", + "features = [\n", + " 'stress_level',\n", + " 'sleep_duration',\n", + " 'quality_of_sleep',\n", + " 'physical_activity_level',\n", + " 'heart_rate',\n", + " 'daily_steps',\n", + " 'systolic'\n", + "]\n", + "\n", + "\n", + "X = sleep_df_clean[features]\n", + "y = sleep_df_clean['has_disorder']\n", + "\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y, test_size=0.25, random_state=42, stratify=y\n", + ")\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "log_reg = LogisticRegression(max_iter=1000)\n", + "log_reg.fit(X_train, y_train)\n", + "\n", + "\n", + "from sklearn.metrics import classification_report, roc_auc_score\n", + "\n", + "y_pred = log_reg.predict(X_test)\n", + "y_pred_proba = log_reg.predict_proba(X_test)[:, 1]\n", + "\n", + "print(classification_report(y_test, y_pred))\n", + "print(\"ROC-AUC:\", roc_auc_score(y_test, y_pred_proba))\n", + "\n", + "\n", + "coeffs = pd.DataFrame({\n", + " 'Feature': features,\n", + " 'Coefficient': log_reg.coef_[0]\n", + "}).sort_values(by='Coefficient', ascending=False)\n", + "\n", + "coeffs" + ] + }, + { + "cell_type": "markdown", + "id": "5cb0440e-5e9b-44b6-a97b-c7e539d25d7b", + "metadata": {}, + "source": [ + "#### Overall Conclusions\n", + "**1.** The model validates key physiological predictors\n", + "Systolic BP and heart rate are significant positive predictors of sleep disorder risk.\n", + "\n", + "This supports hypothesis H1e.\n", + "\n", + "**2.** Sleep quality is the most meaningful negative predictor\n", + "\n", + "Higher sleep quality strongly reduces the likelihood of a disorder, supporting part of H1 (poor sleep quality → higher risk).\n", + "\n", + "**3.** Stress behaves in the opposite direction than expected\n", + "\n", + "The negative coefficient contradicts hypotheses H1 and H1b.\n", + "In this dataset, stress does not function as a valid predictor.\n", + "\n", + "**4.** Physical activity shows a protective effect\n", + "\n", + "The effect is modest but aligns with hypothesis H1d." + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "7398ac28-39e4-4356-968c-e43021e91b23", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: has_disorder R-squared: 0.394\n", + "Model: OLS Adj. R-squared: 0.360\n", + "Method: Least Squares F-statistic: 11.54\n", + "Date: Wed, 10 Dec 2025 Prob (F-statistic): 3.16e-11\n", + "Time: 13:15:56 Log-Likelihood: -61.953\n", + "No. Observations: 132 AIC: 139.9\n", + "Df Residuals: 124 BIC: 163.0\n", + "Df Model: 7 \n", + "Covariance Type: nonrobust \n", + "===========================================================================================\n", + " coef std err t P>|t| [0.025 0.975]\n", + "-------------------------------------------------------------------------------------------\n", + "const -2.6700 1.547 -1.726 0.087 -5.732 0.392\n", + "stress_level -0.0641 0.054 -1.181 0.240 -0.172 0.043\n", + "sleep_duration -0.0447 0.103 -0.434 0.665 -0.249 0.159\n", + "quality_of_sleep -0.1221 0.083 -1.478 0.142 -0.286 0.041\n", + "physical_activity_level -0.0006 0.004 -0.169 0.866 -0.008 0.007\n", + "heart_rate 0.0077 0.014 0.547 0.585 -0.020 0.035\n", + "daily_steps -4.636e-06 4.64e-05 -0.100 0.920 -9.64e-05 8.71e-05\n", + "systolic 0.0326 0.005 6.261 0.000 0.022 0.043\n", + "==============================================================================\n", + "Omnibus: 1.029 Durbin-Watson: 1.702\n", + "Prob(Omnibus): 0.598 Jarque-Bera (JB): 1.090\n", + "Skew: 0.203 Prob(JB): 0.580\n", + "Kurtosis: 2.819 Cond. No. 3.06e+05\n", + "==============================================================================\n", + "\n", + "Notes:\n", + "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", + "[2] The condition number is large, 3.06e+05. This might indicate that there are\n", + "strong multicollinearity or other numerical problems.\n" + ] + } + ], + "source": [ + "X = pd.concat(\n", + " [\n", + " sleep_df_clean[features],\n", + " ],\n", + " axis=1\n", + ")\n", + "y = sleep_df_clean['has_disorder']\n", + "\n", + "X = X.astype(float)\n", + "y = y.astype(float)\n", + "\n", + "# 6. Add intercept and fit OLS regression\n", + "X = sm.add_constant(X)\n", + "model = sm.OLS(y, X).fit()\n", + "\n", + "# 7. Inspect results\n", + "print(model.summary())" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "65ded620-2221-432c-9e1a-a36e0424a9ac", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Optimization terminated successfully.\n", + " Current function value: 0.450264\n", + " Iterations 7\n", + " Logit Regression Results \n", + "==============================================================================\n", + "Dep. Variable: has_disorder No. Observations: 132\n", + "Model: Logit Df Residuals: 124\n", + "Method: MLE Df Model: 7\n", + "Date: Wed, 10 Dec 2025 Pseudo R-squ.: 0.3451\n", + "Time: 13:17:59 Log-Likelihood: -59.435\n", + "converged: True LL-Null: -90.752\n", + "Covariance Type: nonrobust LLR p-value: 4.489e-11\n", + "===========================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "-------------------------------------------------------------------------------------------\n", + "const -25.6230 11.470 -2.234 0.025 -48.104 -3.142\n", + "stress_level -0.1666 0.366 -0.455 0.649 -0.885 0.551\n", + "sleep_duration 0.3203 0.794 0.403 0.687 -1.236 1.877\n", + "quality_of_sleep -0.7737 0.586 -1.320 0.187 -1.922 0.375\n", + "physical_activity_level -0.0140 0.025 -0.551 0.582 -0.064 0.036\n", + "heart_rate 0.0483 0.096 0.504 0.614 -0.140 0.236\n", + "daily_steps -1.891e-05 0.000 -0.061 0.951 -0.001 0.001\n", + "systolic 0.2099 0.046 4.550 0.000 0.119 0.300\n", + "===========================================================================================\n" + ] + } + ], + "source": [ + "import statsmodels.api as sm\n", + "\n", + "# 1. Seleccionar características (features)\n", + "X = sleep_df_clean[features].astype(float) # Solo las columnas que quieres usar\n", + "\n", + "# 2. Variable dependiente (binaria)\n", + "y = sleep_df_clean['has_disorder'].astype(float)\n", + "\n", + "# 3. Agregar intercepto\n", + "X = sm.add_constant(X)\n", + "\n", + "# 4. Ajustar modelo de regresión logística\n", + "logit_model = sm.Logit(y, X).fit()\n", + "\n", + "# 5. Revisar resultados\n", + "print(logit_model.summary())" + ] + }, + { + "cell_type": "markdown", + "id": "5cbf3438-4577-4f90-8773-7a5560ff080b", + "metadata": {}, + "source": [ + "### H1a: Obesity increases likelihood of sleep apnea" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "b38f3b87-7839-4d81-a5d6-07344f3c778f", + "metadata": {}, + "outputs": [], + "source": [ + "# Sleep disorder flags\n", + "sleep_df_clean['is_insomnia'] = sleep_df_clean['sleep_disorder'].apply(lambda x: 1 if x == \"Insomnia\" else 0)\n", + "sleep_df_clean['is_apnea'] = sleep_df_clean['sleep_disorder'].apply(lambda x: 1 if x == \"Sleep Apnea\" else 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "fa753ad0-ef6d-462f-a0c8-03e2076655ae", + "metadata": {}, + "outputs": [], + "source": [ + "# BMI flag for obesity\n", + "sleep_df_clean['is_obese'] = sleep_df_clean['bmi_category'].apply(lambda x: 1 if x == \"Obese\" else 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "0a72b88c-f996-4085-817f-befb26154de0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Chi-square: 3.1307294117647064\n", + "p-value: 0.07682935807158636\n" + ] + } + ], + "source": [ + "ct = pd.crosstab(sleep_df_clean['is_obese'], sleep_df_clean['is_apnea'])\n", + "\n", + "chi2, p, dof, exp = chi2_contingency(ct)\n", + "\n", + "print(\"Chi-square:\", chi2)\n", + "print(\"p-value:\", p)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "f458b3a8-0298-4186-9e80-8b9ea4681e0f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.countplot(\n", + " x = sleep_df_clean[\"bmi_category\"],\n", + " hue = sleep_df_clean[\"sleep_disorder\"],\n", + " data = sleep_df_clean,\n", + " palette = ['#9c9678', '#524e3a', '#a99467']\n", + " # palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + ")\n", + "ax.set_title(\"Distribution of BMI Categories by Sleep Disorder\", pad=20)\n", + "plt.savefig(\"H1a: Distribution of BMI Categories by Sleep Disorder.png\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "2afd34a0-5496-488d-add2-7708221a769f", + "metadata": {}, + "source": [ + "#### Overall conclusion\n", + "The data suggest a clinically relevant relationship between obesity and sleep apnea, but it cannot be confirmed statistically at the conventional significance level because of the small number of cases." + ] + }, + { + "cell_type": "markdown", + "id": "c59b955b-ac63-40ba-adb4-a3b6ca2a5a18", + "metadata": {}, + "source": [ + "### H1b: Higher stress correlates with insomnia" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "e0d4bd09-94a2-44a8-b03a-f894cbf97428", + "metadata": {}, + "outputs": [], + "source": [ + "def boxplot_analysis(df, numeric_columns, target_col, categorical_columns=None, palette=None):\n", + " for col in numeric_columns:\n", + " plt.figure(figsize=(8, 5))\n", + " sns.boxplot(data=df, x=target_col, y=col, palette=palette)\n", + " plt.title(f'Boxplot of Stress Level by Sleep Disorder')\n", + " plt.xlabel(target_col)\n", + " plt.ylabel(col)\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "id": "ea96ee24-7d00-41b2-a23f-ac66e9bd9894", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/lr/d46q9z0s2zndy_5npx2_zwq00000gn/T/ipykernel_3819/823907634.py:4: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " sns.boxplot(data=df, x=target_col, y=col, palette=palette)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "boxplot_analysis(\n", + " sleep_df_clean,\n", + " numeric_columns=['stress_level'],\n", + " target_col='sleep_disorder',\n", + " categorical_columns=['sleep_disorder'],\n", + " palette = ['#9c9678', '#524e3a', '#a99467']\n", + " # palette=[my_palette1[1], my_palette1[3], my_palette1[5]] \n", + ")\n", + "boxplot_analysis\n", + "plt.savefig(\"boxplot_analysis.png\")" + ] + }, + { + "cell_type": "markdown", + "id": "24ec62bf-2f1c-4aa2-b8bc-cc775fba4b04", + "metadata": {}, + "source": [ + "### H1c: Sleeping <6 hours increases disorder risk" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "578decdf-d58b-423f-bbcc-60b793cc794d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "sleep_deprived \n", + "False 21.875 57.03125 21.09375\n", + "True 25.000 0.00000 75.00000\n" + ] + } + ], + "source": [ + "# Create a boolean column for sleep deprivation (<6 hours)\n", + "sleep_df_clean['sleep_deprived'] = sleep_df_clean['sleep_duration'] < 6\n", + "\n", + "# Define your custom palette\n", + "# alette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + "palette = ['#9c9678', '#524e3a', '#a99467']\n", + "\n", + "# Create the crosstab\n", + "ct = pd.crosstab(sleep_df_clean['sleep_deprived'], sleep_df_clean['sleep_disorder'])\n", + "\n", + "# Plot the bar chart\n", + "plt.figure(figsize=(10, 6))\n", + "ct.plot(kind='bar', color=palette)\n", + "plt.title('Sleep Duration <6h vs Sleep Disorder')\n", + "plt.xlabel('Sleep Deprived (<6h)')\n", + "plt.ylabel('Count')\n", + "plt.xticks(rotation=0)\n", + "plt.legend(title='Sleep Disorder')\n", + "\n", + "# Save the figure before showing\n", + "plt.savefig(\"H1c_Sleep_Deprived_vs_Sleep_Disorder.png\", bbox_inches='tight')\n", + "plt.show()\n", + "\n", + "# Print percentages\n", + "ct_percent = pd.crosstab(\n", + " sleep_df_clean['sleep_deprived'], \n", + " sleep_df_clean['sleep_disorder'], \n", + " normalize='index'\n", + ") * 100\n", + "\n", + "print(ct_percent)" + ] + }, + { + "cell_type": "markdown", + "id": "55572b53-5578-484b-a353-0d5775c8cec6", + "metadata": {}, + "source": [ + "### H1d: Low physical activity (<40 min/day) increases disorder prevalence" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "id": "e1298996-b79d-4154-9424-e14104492bc3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "low_activity \n", + "False 21.698113 54.716981 23.584906\n", + "True 23.076923 57.692308 19.230769\n" + ] + } + ], + "source": [ + "# Create a boolean column for low physical activity (<40 min)\n", + "sleep_df_clean['low_activity'] = sleep_df_clean['physical_activity_level'] < 40\n", + "\n", + "# Define your custom palette\n", + "# palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + "palette = ['#9c9678', '#524e3a', '#a99467']\n", + "\n", + "# Create the crosstab\n", + "ct = pd.crosstab(sleep_df_clean['low_activity'], sleep_df_clean['sleep_disorder'])\n", + "\n", + "# Plot the bar chart\n", + "plt.figure(figsize=(10, 6))\n", + "ct.plot(kind='bar', color=palette)\n", + "plt.title('Physical Activity <40min vs Sleep Disorder')\n", + "plt.xlabel('Low Activity (<40min)')\n", + "plt.ylabel('Count')\n", + "plt.xticks(rotation=0)\n", + "plt.legend(title='Sleep Disorder')\n", + "\n", + "# Save the figure before showing\n", + "plt.savefig(\"H1d_Physical_Activity_vs_Sleep_Disorder.png\", bbox_inches='tight')\n", + "plt.show()\n", + "\n", + "# Print percentages\n", + "ct_percent = pd.crosstab(\n", + " sleep_df_clean['low_activity'], \n", + " sleep_df_clean['sleep_disorder'], \n", + " normalize='index'\n", + ") * 100\n", + "\n", + "print(ct_percent)" + ] + }, + { + "cell_type": "markdown", + "id": "814b02d1-66dd-4b2f-b5dd-5bac6570379b", + "metadata": {}, + "source": [ + "### H1e: High heart rate / BP increases apnea risk." + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "43a66e4d-b037-4e07-a529-f02a7bd743bc", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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nz9vH/PPPPwoLC9PatWs1ceJErVixQnfddZeefvrpXL/fXn/9dX311Vd65ZVXtGrVKtWvX19ffvmlunbtKh8fHy1evFjTpk3TkiVLcs35C5JDHzlyRH379lXv3r31xRdfaOjQoYV9u4CSwQCuU7GxsYaky241atRw2KdGjRpG//797a+feeYZw2KxGNu3b3cY1759e0OS8fXXX9vbwsPDDUnGjz/+6DC2YcOGRvv27a8Yb40aNa4Yb2xsrEMMVatWNVJTUx2OM3z4cMPDw8P477//cj3P+fPnjXPnzhmDBg0yWrRo4dAnyfDz88ux7z///GNIMl566aUrXodhGMa+ffsMScaUKVOMc+fOGWfOnDG2bt1qtGzZ0qhcubKxb9++PPfNzMw0zp07Z8yfP98oXbq0QyydOnXK8TUzDMP44IMPDEnGJ5984tCemJhoSDLeeuuty8Y7ZMgQw9PT08jKyspzzNmzZ42VK1caffv2NXx8fAwXFxejY8eOxoIFC4z09PQc49PS0owuXbo4fP0iIiKMY8eOOYxzdXU1Bg8enGP/hIQEQ5KxaNGiy8ae/blbvny5Q/ujjz5qlCpVyjhw4IBhGP/7mgQGBhqnT592iLN8+fLGXXfdZW976aWXDEnG9OnTHY7ZvHlzQ5KxdOlSe9u5c+eMSpUqGd26dcsR25w5cwxJxs6dOy97DaNGjTI8PT2N48eP29t27NhhSDLeeOMNwzAM499//zUkGTNnzrzssXLz559/Go0bN7Z/HTw9PY22bdsas2bNMs6ePesw9tKfATExMUapUqWMxMREh3Eff/yxIcn44osvDMMwjB9++CHX9+zQoUOGp6enMXr0aHtbfr9meQkPDzcaNWqUZ/+qVavs3395XVfnzp2N5s2bX/Y8t912m+Hv7+/w+T5//rzRuHFjo2rVqvbvl+yftQ899JDD/ikpKYaHh4dx3333ObR///33hiQjPDzc3pbf99kw8v45BQAwr+slL7/11luNI0eOOIzNzpuSkpKMc+fOGSkpKcbChQsNT09Po1q1ag5516V+/PFHQ5KxePHiy8azfft2Y9y4cUbdunUNSUb9+vWN8ePHG3/88cdl95s2bZoh6bK5d3Yenb09/PDDxrlz5xzGFDRf3b17tyHJmD179mXjW7FihSHJWLt2rb3t/PnzRmBgoNG9e3d7W+PGjY177733ssfKzZkzZ4x7773Xfm2lS5c2WrRoYYwdO9ZITk52GNu/f3+Hz2B+c7uTJ08a5cuXN7p06eIwLjMz02jWrJlx66232tuyPysjR450GPv+++8bkoyFCxde9nqy9//nn39y7T99+rQhyejQoUOe1/XKK68Ykhzy7ks999xzuX7/DBkyxLBYLMauXbsMw/jf7xe1a9fOkVOHhobm+XvHxWWowuTQX375ZZ6xA9cbZtriujd//nwlJibm2G6//fYr7hsfH6/GjRurYcOGDu0PPvhgruOtVqtuvfVWh7amTZvm+0mwt99+e66xXjoj9syZM/ryyy913333ycvLy2GmQseOHXXmzBlt3LjRPv6jjz5Sq1at5O3tLRcXF7m6umru3LnauXNnjhjuvPNOlStXLl/xXsmzzz4rV1dXeXh4qHnz5tq2bZs+++yzHLfobNmyRffcc48qVKig0qVLy9XVVQ899JAyMzP1xx9/XPE8K1euVNmyZdWlSxeH96J58+ayWq15ruWV7fDhw6pUqdJlb5FydXVVp06dtGDBAiUnJ2vx4sUqU6aMHnvsMfn7++ujjz6yjz137pweeOABbd26VXPmzNE333yjuLg4/f3334qMjFRqaqrDsS933vysCerj42P/y3q23r17KysrK8df2rt16+awPEP2zMlvvvkmxwzUzp07O7xu0KCBLBaLOnToYG9zcXFRnTp1cv2M+/v7S9IVl3gYOHCgTp8+7TB7MzY2Vu7u7urdu7ckqXz58qpdu7amTZumGTNmaMuWLfm+vbF27dr65ZdfFB8fr/Hjx+uuu+5SYmKihg8frpYtW1523eaVK1eqcePGat68ucNnq3379g63Yq5cuVIWi0V9+/Z1GGe1WtWsWbMcn8GCfM0KysjHbKVbb71Vv/zyi4YOHao1a9Y4PD1ZuvBwsx9//FE9evRwuKWwdOnS6tevn/76668cs2W7d+/u8PqHH37QmTNn7LNksoWFheV40Ep+3+dsRflzCgBw7ZTUvPz777/X3Llz9c8//+jOO+/M9Y4rq9UqV1dXlStXTn379tVNN92k1atXO+Rdlzp8+LCk/+VMeWnYsKEmTJigXbt2afPmzbrnnnv03nvvqW7duurRo0e+ricv7du3V2Jior766iu9/PLL+uSTT9S9e/cceVZB8tX85oAdOnSQ1Wp1mH25Zs0aHT582OG291tvvVWrVq3Sc889pw0bNuR7xqy7u7s+/fRT7dixQ6+++qp69eqlf/75Ry+//LIaNGiQI5e5WH5zu4SEBP3333/q37+/w7isrCzdfffdSkxMzLHU06W50f333y8XFxf7sgKFlZ8c8JZbbrGfc8mSJbl+jb766is1bNgwx/fPgAEDZBiGvvrqK4f2e+65x2HJkJMnTyoxMTHP3zsuVtAculy5crrzzjuveJ3A9YIHkeG616BBgxwPl5IurEl16NChy+577NixXG9/CggIyHV8bk9IdXd3z3di4efnl2usucV1/vx5vfHGG3rjjTdyHZOdTC5dulT333+/evbsqWeeeUZWq1UuLi6aPXu23nvvvRz75bX2Z2GMGDFCffv2VUZGhjZu3KgXXnhBXbt21S+//GJ/rw4ePKg77rhD9erV02uvvaaaNWvKw8NDP/30k4YNG5av9+7o0aM6fvy43Nzccu2/3FIG0v8empRfp0+fVmpqqlJTU3Xu3DmVLVvWYf+5c+dq1apVSkxMtH8977jjDt1+++2qXbu2Zs6caX9ARIUKFXK9teu///6TdKFYeSW5fR6tVqsk5Th2dvulbWfPntWJEycc1uG99Nxubm7y8vLK8V65ubnlKPpJ/1u790pfw0aNGumWW25RbGysHnvsMWVmZmrhwoXq2rWrPYbsdW8nTJigqVOn6qmnnlL58uXVp08fvfzyyw4Pl8hNqVKl1Lp1a/sD8E6ePKlBgwbpww8/1HvvvZfnrVVHjx7Vn3/+mefaddmfraNHj8owjDx/NmQ/yCNbQb5mBZX9y2hgYGCeY8aMGaMyZcpo4cKFevvtt1W6dGm1bt1aU6ZMUUhIiFJSUmQYRq4/D7KPe2mcl47N7s/rM3ex/L7PeZ0LAFAylOS8PCwsTA0bNlTLli01ffp0xcTEOIxfv369/Pz85OrqqqpVq+Z6/ktlx5LfPDQrK0upqak6fvy4Tpw4IRcXF/szEwqrXLly9uts06aNateurV69emn58uX2B+cWNF/Nbw7o4uKifv366Y033tDx48dVtmxZzZs3T5UrV1b79u3t415//XVVrVpVH374oaZMmSIPDw+1b99e06ZNU3Bw8BWvsUGDBmrQoIGkC4XNmTNnatSoURo3bpyWLFmS6z75ze2yb9+/XPH8v//+U5kyZeyvL82DXFxc8nyPCyI/OWDr1q21bNkyvf7663rooYeUkZGhRo0aaezYsfY/gBw7dizHJJuLj3ulHDAlJUVZWVn5zgELkkOTA+JGQ9EWuIwKFSrkWEdHurBGljOVK1fOPuNt2LBhuY7JTmoXLlyooKAgffjhhw5/Bc/IyMh1v6J82nvVqlXtSWD2erR9+/bVSy+9pFmzZkm6sDblyZMntXTpUofZdwVZr6tixYqqUKGCfe3dS12poFexYkX9/PPPlx2Tnp6u5cuXa/HixVq7dq3c3d3VtWtXLV++XO3atXN4WMPWrVtVunRp3XTTTQ7HqFWrlipUqOCwvleTJk3022+/5Thfdlvjxo0vG5eU88Fu0v8+o5f+wpDbZzcpKUlubm55PqShsLIT+YufbpuXhx9+WEOHDtXOnTu1d+9eHTlyRA8//LDDmBo1amju3LmSpD/++ENLliyRzWbT2bNnr/jAs0uVKVNGY8aM0YcffnjZ9dYqVqwoT0/PXP/Akd2f/V+LxaJvv/0216flXtpWkK9ZQa1YsUIWi8VeoM6Ni4uLRo0apVGjRun48eNav369nn/+ebVv316HDh1SuXLlVKpUKR05ciTHvtmzgi79ul76syP7OvL6zF38y0B+3+e8zgUAuP6ZIS/PXsP1l19+ydHXrFmzfOU8F8sen50z5cYwDH3//ff68MMP9dFHHyk5OVktW7aUzWbTAw88cNk1cwsje3blxXe7FTRfLWgOOG3aNC1evFgPPPCAVqxYoaioKJUuXdo+pkyZMho/frzGjx+vo0eP2mfddunSRb///nuBrs9isWjkyJGaMGHCFXPA/OR22df4xhtv2B8+d6lLC5JJSUmqUqWK/fX58+d17NixIskBpQtrCl9O165d1bVrV/vEmpiYGPXu3Vs1a9ZUy5YtVaFChavKAcuVKyeLxZJnDnixgubQ5IC40bA8AnAZ4eHh2rZtm3bs2OHQvnjxYidFdIGXl5fatGmjLVu2qGnTpgoJCcmxZf+jb7FY5Obm5vAPXFJSkpYvX57v82X/Y1nQxfsv1adPH0VERGjOnDn2vwRnx3XxP8iGYWjOnDm5xpFbDJ07d9axY8eUmZmZ63tx6dN4L1W/fn0dO3Ysx7IFkvThhx+qW7du8vf316BBg1S6dGn7EgkLFy5Ux44dHQq20oW/QmdmZioxMdGh/Y8//tCxY8dUtWpVe9t9992n33//XT/++KO97fz581q4cKFCQ0Mv+5fybOnp6fYkLduiRYvss0svtnTpUoflANLT0/XZZ5/pjjvucEiOi8LevXtVqlSpK77/0oVbGz08PDRv3jzNmzdPVapUUbt27fIcX7duXb3wwgtq0qTJFQvuuSWdkuzLg1zuPe7cubP27NmjChUq5PrZyi48du7cWYZh6O+//851XJMmTRyOW5CvWUHExsZq1apVOR4gcjlly5ZVjx49NGzYMP3333/av3+/ypQpo9DQUC1dutThey4rK0sLFy5U1apVczxQ8FK33XabPDw89P777zu0JyQk5Lg1Nb/vMwDgxmWGvDx7UsGVljPIr+zZn3v27MnRt23bNj311FOqXr267rjjDsXHx2vEiBHat2+fvv/+ew0fPrzIC7aS7Lfo16lTx95W0Hx17969kpRjKYvcNGjQQKGhoYqNjdWiRYuUkZGR4w/3FwsICNCAAQP04IMPateuXTp16lSeY/PKAQ8fPqy0tLQr5oD5ye1atWqlsmXLaseOHbmOCwkJyXE34KW50ZIlS3T+/PkrFlsv55dfflF0dLRq1qyp+++/P1/7uLu7Kzw8XFOmTJF0Yck6SWrbtq127NiRI8eeP3++LBZLrg/Ou1iZMmV066235vl7x8UKmkMDNxpm2gKXERUVpffee08dOnTQhAkTFBAQoEWLFtn/oluqlPP+7vHaa6/p9ttv1x133KEhQ4aoZs2aSk9P159//qnPPvvMvtZQ586dtXTpUg0dOlQ9evTQoUOHNHHiRFWuXFm7d+/O17l8fHxUo0YNLV++XG3btlX58uVVsWLFQhVSpkyZotDQUE2cOFH/93//p8jISLm5uenBBx/U6NGjdebMGc2ePVspKSk59m3SpImWLl2q2bNn6+abb1apUqUUEhKiXr166f3331fHjh01YsQI3XrrrXJ1ddVff/2lr7/+Wl27drXf3pWbiIgIGYahH3/8MUehsHfv3goPD9cbb7yhHj165OsWtIcfflivvvqqunfvrhdeeEH16tXT3r17FR0drTJlyujxxx+3jx04cKDefPNN9ezZU5MnT5a/v7/eeust7dq1S+vXr8/Xe1qhQgUNGTJEBw8eVN26dfXFF19ozpw5GjJkSI7CXenSpRUZGalRo0YpKytLU6ZMUVpamsaPH5+vcxXExo0b1bx583ytPVq2bFndd999mjdvno4fP66nn37a4fvr119/1fDhw9WzZ08FBwfLzc1NX331lX799Vc999xzlz12o0aN1LZtW3Xo0EG1a9fWmTNn9OOPP2r69OkKCAjQoEGD8tw3KipKn3zyiVq3bq2RI0eqadOmysrK0sGDB7V27Vo99dRTCg0NVatWrfTYY4/p4Ycf1qZNm9S6dWuVKVNGR44c0XfffacmTZpoyJAh9uMW5GuWm9OnT9vXrT59+rT27t2rZcuWaeXKlQoPD7/izOMuXbqocePGCgkJUaVKlXTgwAHNnDlTNWrUsN9mGBMTo8jISLVp00ZPP/203Nzc9NZbb2nbtm364IMPrjjToVy5cnr66ac1adIkPfLII+rZs6cOHTokm82W49a4/L7PAIAb17XOy48fP27/t/bcuXPauXOnoqOj5e7unuedbgVVtWpV1apVSxs3btSTTz7p0PfKK6/om2++Ub9+/dSnTx81atQoX8f8559/FB8fL+l/M2FXrVqlSpUqqVKlSgoPD5ckvfPOO/r222/Vrl07VatWTSdPntS3336rN954Q2FhYeratav9mAXNVzdu3Ghfeik/Bg4cqMGDB+vw4cMKCwvL8Qf/0NBQde7cWU2bNlW5cuW0c+dOLViwQC1btpSXl1eex33sscd0/Phxde/eXY0bN1bp0qX1+++/69VXX1WpUqX07LPP5rlvfnM7b29vvfHGG+rfv7/+++8/9ejRQ/7+/vrnn3/0yy+/6J9//tHs2bMdjr106VK5uLgoMjJS27dv17hx49SsWbN8F1s3b94sPz8/nTt3TocPH9aXX36pBQsWyN/fX5999lmeS8ZJ0osvvqi//vpLbdu2VdWqVXX8+HG99tprcnV1tX82Ro4cqfnz56tTp06aMGGCatSooc8//1xvvfWWhgwZcsU/3EvSxIkTdffddysyMlJPPfWUMjMzNWXKFJUpU8ZhZnlBc2jghuOMp58B10L2U2ovfRp5tk6dOl3xKbWGYRjbtm0z7rrrLsPDw8MoX768MWjQICMuLs6QZPzyyy/2cXk90f3SJ3bmpUaNGkanTp1y7UtMTDQkGbGxsQ7t+/btMwYOHGhUqVLFcHV1NSpVqmSEhYUZkyZNchg3efJko2bNmoa7u7vRoEEDY86cOfanj15MkjFs2LBcY1i/fr3RokULw93d3ZCU4326NC5JxrRp03Lt79mzp+Hi4mL8+eefhmEYxmeffWY0a9bM8PDwMKpUqWI888wzxqpVq3I8Cfi///4zevToYZQtW9awWCwO8Z87d8545ZVX7Mfx9vY26tevbwwePNjYvXt3nrEaxoWnu9asWdMYOnRojr7Dhw9fdt+87N692+jXr5/9fa9evbrxwAMP5HjisWEYRlJSkvHQQw8Z5cuXNzw8PIzbbrvNWLduXb7Ok/2527BhgxESEmK4u7sblStXNp5//nmHJ/9mf02mTJlijB8/3qhatarh5uZmtGjRwlizZo3DMfN6Mm3//v2NMmXK5BnDxdLT0w0vL68cT4K9nLVr19qf7nvp05CPHj1qDBgwwKhfv75RpkwZw9vb22jatKnx6quvGufPn7/scd955x2jW7duRq1atQwvLy/Dzc3NqF27tvH4448bhw4dchib28+AEydOGC+88IJRr149w83NzfDz8zOaNGlijBw50khKSnIY+9577xmhoaFGmTJlDE9PT6N27drGQw89ZGzatMk+Jr9fs7xkPzk3eytTpoxRq1Yto0ePHsZHH31kZGZm5tjn0uuaPn26ERYWZlSsWNFwc3MzqlevbgwaNMjYv3+/w37ffvutceedd9qv57bbbjM+++wzhzGX+1mblZVlxMTEGNWqVTPc3NyMpk2bGp999pkRHh5uhIeHF+p9vtzPKQCAOZXEvPzif2tLly5tVK9e3ejRo4exZcsWh7F55U35NW7cOKNcuXLGmTNnHNoLm4N+/fXXDrFfvF38b+/3339vdO7c2QgMDDTc3NwMLy8vo1mzZsbEiRONkydP5jhuQfLVO+64w+jSpUu+Y05NTTU8PT0NScacOXNy9D/33HNGSEiIUa5cOcPd3d2oVauWMXLkSOPff/+97HHXrFljDBw40GjYsKHh5+dnuLi4GJUrVza6detm/PDDDw5j8/ps5Ce3MwzDiI+PNzp16mSUL1/ecHV1NapUqWJ06tTJ+Oijj+xjsj8rmzdvNrp06WJ4e3sbPj4+xoMPPmgcPXr0iu9T9v7ZW3YO2a5dO+O1114z0tLScuxz6XWtXLnS6NChg1GlShXDzc3N8Pf3Nzp27Gh8++23DvsdOHDA6N27t1GhQgXD1dXVqFevnjFt2jSHPPNKv/OtWLHCaNq0qT3XnDx5cq6/g+b3fc7r+xq4nlkMIx+PGATg4LHHHtMHH3ygY8eOXfYvmSg5pk+frpdffll///23PD09nR1Okdu/f7+CgoI0bdo0Pf3008V+vrlz52rEiBH29VHxPxEREfr3338vu44aAADIn5Kelx8+fFhBQUGaP3++HnjgAWeHc9X27Nmj4OBgrVmzRpGRkc4Ox1RsNpvGjx+vf/75p8DrHwO4MbE8AnAFEyZMUGBgoGrVqqUTJ05o5cqV+r//+z+98MILJTIxRO6GDRumWbNm6c0337wmRc3r2fnz5zVlyhSNGTOGgi0AACgy12NeHhgYqKioKL388svq2bOnU5dfKwqTJk1S27ZtKdgCQBGgaAtcgaurq6ZNm6a//vpL58+fV3BwsGbMmKERI0Y4OzQUIQ8PDy1YsMC+AD8K79ChQ+rbt6+eeuopZ4cCAACuI9drXv7CCy/Iy8tLf//9t6pVq+bscArt/Pnzql27tsaMGePsUADgusDyCAAAAAAAAABgIiX73gsAAAAAAAAAuM5QtAUAAAAAAAAAE6FoCwAAABRSzZo1ZbFYcmzDhg2TJBmGIZvNpsDAQHl6eioiIkLbt293ctQAAAAwu+v+QWRZWVk6fPiwfHx8ZLFYnB0OAAAAroJhGEpPT1dgYKApnrKemJiozMxM++tt27YpMjJSPXv2lCRNnTpVM2bM0Lx581S3bl1NmjRJkZGR2rVrl3x8fPJ9HnJaAACA60N+89nr/kFkf/31V4l+AicAAAByOnTokKpWrersMHKIiorSypUrtXv3bklSYGCgoqKi9Oyzz0qSMjIyFBAQoClTpmjw4MH5Pi45LQAAwPXlSvnsdT/TNnsGw6FDh+Tr6+vkaAAAAHA10tLSVK1atQLNUr1Wzp49q4ULF2rUqFGyWCzau3evkpKS1K5dO/sYd3d3hYeHKyEhoUBFW3JaAACA60N+89nrvmibffuYr68vCS4AAMB1woxLBCxbtkzHjx/XgAEDJElJSUmSpICAAIdxAQEBOnDgwGWPlZGRoYyMDPvr9PR0SeS0AAAA14sr5bPOXwgMAAAAuA7MnTtXHTp0UGBgoEP7pQm5YRhXTNJjYmLk5+dn31gaAQAA4MZC0RYAAAC4SgcOHND69ev1yCOP2NusVquk/824zZacnJxj9u2lxowZo9TUVPt26NChog8aAAAApkXRFgAAALhKsbGx8vf3V6dOnextQUFBslqtWrdunb3t7Nmzio+PV1hY2GWP5+7ubl8KgSURAAAAbjzX/Zq2AADAnDIzM3Xu3DlnhwGTcXV1VenSpZ0dRoFkZWUpNjZW/fv3l4vL/9Jri8WiqKgoRUdHKzg4WMHBwYqOjpaXl5d69+7txIgBAEBRIafFpYoqn6VoCwAArinDMJSUlKTjx487OxSYVNmyZWW1Wk35sLHcrF+/XgcPHtTAgQNz9I0ePVqnT5/W0KFDlZKSotDQUK1du/aKTwsGAADmRk6LyymKfNZiGIZRhDGZTlpamvz8/JSamsptZQAAmMCRI0d0/Phx+fv7y8vLq8QU5lD8DMPQqVOnlJycrLJly6py5co5xtyoud2Net0AAJgVOS1yU5T5LDNtAQDANZOZmWlPbitUqODscGBCnp6eki48rMvf37/ELZUAAACuf+S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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "High Heart Rate (>80 bpm) vs Sleep Disorder (%):\n", + " sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "high_hr \n", + "False 20.967742 58.870968 20.16129\n", + "True 37.500000 0.000000 62.50000\n", + "\n", + "High Systolic BP (>130) vs Sleep Disorder (%):\n", + " sleep_disorder Insomnia No Disorder Sleep Apnea\n", + "high_bp \n", + "False 18.279570 72.043011 9.677419\n", + "True 30.769231 15.384615 53.846154\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Create boolean columns for high heart rate and high blood pressure\n", + "sleep_df_clean['high_hr'] = sleep_df_clean['heart_rate'] > 80\n", + "sleep_df_clean['high_bp'] = sleep_df_clean['systolic'] > 130\n", + "\n", + "# Define your custom palette\n", + "# palette = [my_palette1[1], my_palette1[3], my_palette1[5]]\n", + "palette = ['#9c9678', '#524e3a', '#a99467']\n", + "\n", + "# Create crosstabs\n", + "ct_hr = pd.crosstab(sleep_df_clean['high_hr'], sleep_df_clean['sleep_disorder'])\n", + "ct_bp = pd.crosstab(sleep_df_clean['high_bp'], sleep_df_clean['sleep_disorder'])\n", + "\n", + "# Visualisation\n", + "fig, axes = plt.subplots(1, 2, figsize=(14, 6))\n", + "\n", + "# Heart Rate\n", + "ct_hr.plot(kind='bar', ax=axes[0], color=palette)\n", + "axes[0].set_title('High Heart Rate (>80 bpm) vs Sleep Disorder')\n", + "axes[0].set_xlabel('High Heart Rate (>80 bpm)')\n", + "axes[0].set_ylabel('Count')\n", + "axes[0].legend(title='Sleep Disorder')\n", + "axes[0].set_xticklabels(['No', 'Yes'], rotation=0)\n", + "\n", + "# Blood Pressure\n", + "ct_bp.plot(kind='bar', ax=axes[1], color=palette)\n", + "axes[1].set_title('High BP (>130) vs Sleep Disorder')\n", + "axes[1].set_xlabel('High Systolic BP (>130)')\n", + "axes[1].set_ylabel('Count')\n", + "axes[1].legend(title='Sleep Disorder')\n", + "axes[1].set_xticklabels(['No', 'Yes'], rotation=0)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "# Save figure before showing\n", + "plt.savefig(\"H1e_High_HR_BP_vs_Sleep_Disorder.png\", dpi=300, bbox_inches='tight')\n", + "plt.show()\n", + "\n", + "# Print row-wise percentages\n", + "ct_hr_percent = pd.crosstab(sleep_df_clean['high_hr'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "ct_bp_percent = pd.crosstab(sleep_df_clean['high_bp'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "\n", + "print(\"High Heart Rate (>80 bpm) vs Sleep Disorder (%):\\n\", ct_hr_percent)\n", + "print(\"\\nHigh Systolic BP (>130) vs Sleep Disorder (%):\\n\", ct_bp_percent)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "16c033eb-cafe-4499-8004-5dfed70986ef", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "acd48b10-52b6-4d7d-a1bc-de1ee8b74c51", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sleep_health_analysis_veronique.ipynb b/notebooks/sleep_health_analysis_veronique.ipynb new file mode 100644 index 00000000..aac24354 --- /dev/null +++ b/notebooks/sleep_health_analysis_veronique.ipynb @@ -0,0 +1,225 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "92ab6a0f-c295-4fb0-9cdd-6aa0f9c2ec7a", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0631176b-cbaf-4a1d-aacd-6aa66a2e0881", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa23d506-b5b9-4ea4-b835-21af5490c385", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df_clean = pd.read_csv(config['output_data']['file'], encoding='ISO-8859-1')\n", + "sleep_df_clean.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "129d48b9-1550-4014-b808-068e184cba56", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "proportion of obese in sleep apnea\n", + "\"\"\"\n", + "proportion_table_by_bmi = pd.crosstab(sleep_df_clean['bmi_category'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "\n", + "print(\"Proportion of obese per sleep apnea ( %) :\")\n", + "print(proportion_table_by_bmi.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "4affd665-1679-4639-a6e1-d106fa46c8d5", + "metadata": {}, + "source": [ + "# Conclusion H1a: Obesity increases likelihood of sleep apnea\n", + "The table indicates that obese people are more affected by both insomnia and sleep apnea than the rest of the population.\n", + "Furthermore, the data suggests that in this sample, no obese person is entirely free of a sleep disorder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85b7ce64-3827-4e77-a173-1a867f1d4e96", + "metadata": {}, + "outputs": [], + "source": [ + "proportion_table_stress = pd.crosstab(sleep_df_clean['stress_level'], sleep_df_clean['sleep_disorder'], normalize='index') * 100\n", + "\n", + "print(\"Proportion of stress per insomnia ( %) :\")\n", + "print(proportion_table_stress.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "2efa62ce-2918-4a5e-8a3f-baf2fc7669b2", + "metadata": {}, + "source": [ + "# Conclusion H1b: Higher stress correlates with insomnia.\n", + "\n", + "This table does not show correlation between higher stress and indomnia. Furthermore, individuals with no sleep disorder have significantly higher stress levels than those with insomnia." + ] + }, + { + "cell_type": "markdown", + "id": "a4d6b24e-4c23-4efd-82d1-557b35fd39f8", + "metadata": {}, + "source": [ + "# To observe the disorder risk for slipping less yhan 6h, we considere:\n", + "bmi_category = obese\n", + "Blood Pressure (systolic/diastolic) > 140/90\n", + "100 < Heart Rate (bpm) < 60\n", + "Sleep Disorder \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bae269b5-d8c0-4478-8cb6-6dc04ad66933", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "Create a temporary column retruning True when sleep apnea then 1or 0 whyit .astype(int)\n", + "sleep_df_clean['has_hypertension'] = (sleep_df_clean['diastolic'] > 90 ).astype(int)\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c6ee18d-76ec-4635-8088-cbfeaf233f0e", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df_clean['has_disorder'] = (\n", + " (sleep_df_clean['diastolic'] > 90) | \n", + " (sleep_df_clean['bmi_category'] == 'obese') | \n", + " (sleep_df_clean['systolic'] > 140) |\n", + " (sleep_df_clean['heart_rate'] > 100) |\n", + " (sleep_df_clean['heart_rate'] < 60) |\n", + " (sleep_df_clean['sleep_disorder'] != 'No Disorder')\n", + " ).astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f70e2bb1-0fd7-46f8-9ddd-e7097efa6dd0", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_duration_sleep = pd.crosstab(sleep_df_clean['sleep_duration'] < 6, sleep_df_clean['has_disorder'] == 1, normalize='index') * 100\n", + "\n", + "print(\"Proportion of duration sleep < 6h increase disorder ( %) :\")\n", + "print(proportion_table_duration_sleep.round(1))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "89cc47fc-2dd1-48af-a10f-3b458772782c", + "metadata": {}, + "source": [ + "# Conclusion H1c: Sleeping <6 hours increases disorder risk.\n", + "There is a correllation between the less sleeping and the disorder because, when i combine all the parametter, the risks is very hi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b8e2151-cd4a-4ab3-991a-99b230b4dbd6", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_physical_activity_level = pd.crosstab(sleep_df_clean['physical_activity_level']<40, sleep_df_clean['has_disorder'] == 1, normalize='index') * 100\n", + "\n", + "print(\"Proportion of physical_activity_level per risk disorder ( %) :\")\n", + "print(proportion_table_physical_activity_level.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "92d4fb68-d70d-4bac-8299-be802cd0d5d1", + "metadata": {}, + "source": [ + "# H1d: Low physical activity (<40 min/day) increases disorder prevalence.\n", + "Their is no correllation between less than 40mi/day of activity and disorder prevalence. Furthumore, doing more does not impact the capability to have desorder. Maybe because when your have health issu, the first medical recommandation is to have sprt activity to maintain your status. This last statement must be verify by another dataset (part of the population with activity with and without desorder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4ac757a5-4476-4734-8c0e-94031e1c4629", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "proportion_table_heart_rate = pd.crosstab(sleep_df_clean['heart_rate'] > 100, sleep_df_clean['sleep_disorder'] == \"Sleep Apnea\", normalize='index') * 100\n", + "\n", + "print(\"Proportion of heart rate< 100 increase sleep apnea ( %) :\")\n", + "print(proportion_table_heart_rate.round(1))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "4c881661-dbea-4909-8300-0dbab1f7f48b", + "metadata": {}, + "source": [ + "# H1e: Hight heart rate (> 100 bpm) does not increases sleep apnea." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sleep_health_cleaning_carmelina.ipynb b/notebooks/sleep_health_cleaning_carmelina.ipynb new file mode 100644 index 00000000..67cd0201 --- /dev/null +++ b/notebooks/sleep_health_cleaning_carmelina.ipynb @@ -0,0 +1,468 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "763adffb-1acd-4d43-b5af-b7c23e427ca0", + "metadata": {}, + "source": [ + "## Importing the data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8abe45d-f572-420e-80a0-b63e5656b5f3", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import yaml\n", + "sleep_data = pd.read_csv(\"data/raw/Sleep_health_and_lifestyle_dataset.csv\")\n", + "display(sleep_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b03536e4-fbe1-4ace-8d25-ab07b1104db2", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60942063-3eb7-4b07-a47f-c976f3891c9a", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58359c05-5cda-4ef9-99df-be6d0c5dff5e", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "afdb0b88-0888-425e-9d93-a9a0d8ac93a7", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1627024-b4d5-442f-9410-927b15a06a11", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull().sum() " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25de34a0-92e7-43ce-9af4-2e44724a5e5d", + "metadata": {}, + "outputs": [], + "source": [ + "print(sleep_data.duplicated().sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e4fc39dd-4089-4f5c-ab56-6e52777830b5", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30df7442-2b3b-4651-a291-9703db05c8f2", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2fc28c0f-a0f7-4a9d-a966-716fe609d27b", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data['Sleep Disorder'].isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9198265a-a986-443e-aaf5-2f13f6795ead", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e6f1d8d9-eccd-419e-b400-1fcef40436e1", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47bf619e-2ae1-4f88-b3f7-acde94200602", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa803e24-f609-4bb0-b7ed-1a849ad15430", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(subset=sleep_data.columns.difference(['Person ID']), keep='first')\n", + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "48461239-636f-4584-b809-918d1e9fdde1", + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"deleted: {len(sleep_data) - len(sleep_data_clean)} lines\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "10c02ad3-2bed-41bf-bc13-cb8146c8cebb", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'].isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87fc2599-08dc-4731-9c0f-9fee942137db", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data.drop_duplicates(\n", + " subset=sleep_data.columns.difference(['Person ID']), \n", + " keep='first'\n", + ").copy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30bd924e-d204-4eaa-ae9f-0abb914cc5ff", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'] = sleep_data_clean['Sleep Disorder'].fillna('None')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8b2f914-1adb-4dd8-ac20-14c3b59d08ee", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e718f68-51f4-4b13-a84e-dd332c72b214", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dccc3086-cc41-45f2-8f3c-b3ffb8ad2a94", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean.duplicated(subset=sleep_data.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7f16417f-afa3-4edf-acd8-fa73d5467f29", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41b69fe5-b2c0-4113-abb2-da3465735265", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['BMI Category'] = sleep_data_clean['BMI Category'].replace('Normal Weight', 'Normal')\n", + "sleep_data_clean['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "97d849f5-f9fe-4077-84ec-3f8cea7ab19a", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Occupation'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "839b0461-de2d-44f8-ade5-e5431f8c4811", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01c14e17-b36d-4034-a1db-7899043a7235", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Age'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73901b72-4095-48c3-9630-c30f6f9c25fc", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Blood Pressure'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "50fba77f-6a07-4b4e-b4a0-0dc6b2d0b6f4", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean[['Systolic', 'Diastolic']] = sleep_data_clean['Blood Pressure'].str.split('/', expand=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a80b7b78-bfca-4e87-80bc-c8a57959ee3c", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Systolic'] = sleep_data_clean['Systolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35325679-5391-48b0-9a43-15495bf62b5f", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['Diastolic'] = sleep_data_clean['Diastolic'].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "314b66c8-f92a-417b-ade0-5033146cc1ef", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "74d1fceb-60b9-4c75-82da-167d7fba37bf", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8369f9b8-fd0e-4804-ae1d-ed47bfb9c306", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80cc3d5a-eaac-4656-8321-b961c1935729", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.rename(columns={\n", + " 'Person ID': 'person_id',\n", + " 'Gender': 'gender',\n", + " 'Age': 'age',\n", + " 'Occupation':'occupation', \n", + " 'Sleep Duration': 'sleep_duration',\n", + " 'Quality of Sleep': 'quality_of_sleep', \n", + " 'Physical Activity Level': 'physical_activity_level', \n", + " 'Stress Level': 'stress_level',\n", + " 'BMI Category': 'bmi_category', \n", + " 'Blood Pressure': 'blood_pressure', \n", + " 'Heart Rate': 'heart_rate', \n", + " 'Daily Steps': 'daily_steps',\n", + " 'Sleep Disorder': 'sleep_disorder',\n", + " 'Systolic': 'systolic',\n", + " 'Diastolic' : 'diastolic'\n", + "})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88f13764-ab6c-4e8b-a54a-e888ff32dc2f", + "metadata": {}, + "outputs": [], + "source": [ + "display(sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd45122f-5cd7-416e-b784-44024fb11a92", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.drop(columns='blood_pressure')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9aad531-06aa-4c8b-95e3-d799a0be03fa", + "metadata": {}, + "outputs": [], + "source": [ + "display (sleep_data_clean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8b908ecb-9142-43cd-b7b5-a246312a6d68", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean = sleep_data_clean.reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a12b9e28-3bd8-401b-ad01-470e849bc04f", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean['person_id'] = range(1, len(sleep_data_clean) + 1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "699948aa-6e1f-4169-8ca9-8ce8451f9fce", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c48babc0-c799-466b-952b-07119fc87acb", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_data_clean.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sleep_health_cleaning_pati.ipynb b/notebooks/sleep_health_cleaning_pati.ipynb new file mode 100644 index 00000000..13405bf8 --- /dev/null +++ b/notebooks/sleep_health_cleaning_pati.ipynb @@ -0,0 +1,2183 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "b5efb23e-690c-4763-9fef-f2545aafc6fb", + "metadata": {}, + "source": [ + "# Data Work" + ] + }, + { + "cell_type": "markdown", + "id": "9130348a-595d-4bce-9d8e-505e0c9f57d5", + "metadata": {}, + "source": [ + "### 1. Importing and exploring the DataFrame" + ] + }, + { + "cell_type": "markdown", + "id": "d614cefb-8d6f-4dec-a6a3-5c7b0cd0212d", + "metadata": {}, + "source": [ + "Importing libraries we will need to clean the Dataset - Sleep Health and Lifestyle." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "ed15ef58-7d76-4aef-bdef-6ccbb7bb318a", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import yaml" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "3ebe0481-88e2-49f1-9588-042f21b56b8d", + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " with open(\"../config.yaml\", \"r\") as file:\n", + " config = yaml.safe_load(file)\n", + "except:\n", + " print(\"Configuration file not found!\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0ec37943-cc03-4702-b4a3-f144cf3191e9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input_data': {'file': '../data/raw/sleep_health_and_lifestyle_dataset.csv'},\n", + " 'output_data': {'file': '../data/clean/sleep_health_project_clean.csv'}}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "config" + ] + }, + { + "cell_type": "markdown", + "id": "6af1d1f5-261a-436d-a7d0-2564bc45951b", + "metadata": {}, + "source": [ + "In this step, we load the Sleep Health and Lifestyle dataset into a pandas DataFrame.\n", + "\n", + "This dataset contains information about individuals' sleep habits, health indicators, lifestyle patterns, and the presence of sleep disorders." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "e80d1833-22d2-4515-b40f-51bb11ec3409", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df = pd.read_csv(config['input_data']['file'], encoding='ISO-8859-1')\n", + "sleep_df.head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "b78cea56-d492-4d29-8dc3-381dcb8f4bea", + "metadata": {}, + "source": [ + "Columns information:\n", + "\n", + "- Person ID: An identifier for each individual.\n", + "- Gender: The gender of the person (Male/Female).\n", + "- Age: The age of the person in years.\n", + "- Occupation: The occupation or profession of the person.\n", + "- Sleep Duration (hours): The number of hours the person sleeps per day.\n", + "- Quality of Sleep (scale: 1-10): A subjective rating of the quality of sleep, ranging from 1 to 10.\n", + "- Physical Activity Level (minutes/day): The number of minutes the person engages in physical activity daily.\n", + "- Stress Level (scale: 1-10): A subjective rating of the stress level experienced by the person, ranging from 1 to 10.\n", + "- BMI Category: The BMI category of the person (e.g., Underweight, Normal, Overweight).\n", + "- Blood Pressure (systolic/diastolic): The blood pressure measurement of the person, indicated as systolic pressure over diastolic pressure.\n", + "- Heart Rate (bpm): The resting heart rate of the person in beats per minute.\n", + "- Daily Steps: The number of steps the person takes per day.\n", + "- Sleep Disorder: The presence or absence of a sleep disorder in the person (None, Insomnia, Sleep Apnea)." + ] + }, + { + "cell_type": "markdown", + "id": "14413245-9908-4bd6-a5dd-a04b16ebfa20", + "metadata": {}, + "source": [ + "Checking the shape of the DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "af483cf4-9c49-4e56-8e92-1fc210108afa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(374, 13)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.shape" + ] + }, + { + "cell_type": "markdown", + "id": "6562c523-34ba-499a-8c18-c8caa11f32db", + "metadata": {}, + "source": [ + "### 2. Cleaning names of columns" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "0e78431f-8625-467f-bc25-936dedc8c000", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.columns = (\n", + " sleep_df.columns\n", + " .str.lower()\n", + " .str.normalize('NFKD') \n", + " .str.encode('ascii', errors='ignore')\n", + " .str.decode('utf-8')\n", + " .str.replace(' ', '_')\n", + " .str.replace('[^0-9a-zA-Z_]', '')\n", + ")\n", + "sleep_df.head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "f224bb0c-d127-4ba3-9691-05acaff42a4c", + "metadata": {}, + "source": [ + "### 3. Cleaning Data" + ] + }, + { + "cell_type": "markdown", + "id": "b4729006-dd91-48a9-9c46-5e65640c2b02", + "metadata": {}, + "source": [ + "Before analysis, we check:\n", + "\n", + "- Missing values\n", + "- Duplicates\n", + "- Incorrect data types\n", + "- Formatting inconsistencies (e.g., \"140/90\" for blood pressure)\n", + "- Inconsistent categories (BMI, occupation, sleep disorder)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ab3f22b9-a7da-456f-b360-4f3659299e35", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 374 entries, 0 to 373\n", + "Data columns (total 13 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 person_id 374 non-null int64 \n", + " 1 gender 374 non-null object \n", + " 2 age 374 non-null int64 \n", + " 3 occupation 374 non-null object \n", + " 4 sleep_duration 374 non-null float64\n", + " 5 quality_of_sleep 374 non-null int64 \n", + " 6 physical_activity_level 374 non-null int64 \n", + " 7 stress_level 374 non-null int64 \n", + " 8 bmi_category 374 non-null object \n", + " 9 blood_pressure 374 non-null object \n", + " 10 heart_rate 374 non-null int64 \n", + " 11 daily_steps 374 non-null int64 \n", + " 12 sleep_disorder 155 non-null object \n", + "dtypes: float64(1), int64(7), object(5)\n", + "memory usage: 38.1+ KB\n" + ] + } + ], + "source": [ + "sleep_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a81fbcd7-b940-4cce-89a7-05d90f985031", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "person_id 0\n", + "gender 0\n", + "age 0\n", + "occupation 0\n", + "sleep_duration 0\n", + "quality_of_sleep 0\n", + "physical_activity_level 0\n", + "stress_level 0\n", + "bmi_category 0\n", + "blood_pressure 0\n", + "heart_rate 0\n", + "daily_steps 0\n", + "sleep_disorder 219\n", + "dtype: int64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "28cfabf9-b058-430c-928f-dda3248231af", + "metadata": {}, + "source": [ + "Now we can check the unique values of each columns, so we can see if we need to clean them or if they are fine." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e12147fe-0b5e-4b91-92db-c52b4f111eb7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Male', 'Female'], dtype=object)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"gender\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "c3b0b4f8-4814-4e71-92e1-b416547506ab", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Software Engineer', 'Doctor', 'Sales Representative', 'Teacher',\n", + " 'Nurse', 'Engineer', 'Accountant', 'Scientist', 'Lawyer',\n", + " 'Salesperson', 'Manager'], dtype=object)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"occupation\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "8bff6d10-4dd5-4135-84a3-f810ca1f82ba", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Overweight', 'Normal', 'Obese', 'Normal Weight'], dtype=object)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"bmi_category\"].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "95758916-ba64-4c3c-9433-fd2d63dd3d40", + "metadata": {}, + "source": [ + "\"Normal\" and \"Normal Weight\" Categories are refering to the same category, so we can rename them. " + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "4002460e-4ebb-477a-bbc6-cb25c2beb868", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df.loc[sleep_df[\"bmi_category\"] == \"Normal Weight\", \"bmi_category\"] = \"Normal\"" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "c1c8d6e6-5b0b-4925-bbd3-d90dd961c780", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['126/83', '125/80', '140/90', '120/80', '132/87', '130/86',\n", + " '117/76', '118/76', '128/85', '131/86', '128/84', '115/75',\n", + " '135/88', '129/84', '130/85', '115/78', '119/77', '121/79',\n", + " '125/82', '135/90', '122/80', '142/92', '140/95', '139/91',\n", + " '118/75'], dtype=object)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"blood_pressure\"].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "e8ec181b-43f5-4981-9a84-f6222e979e23", + "metadata": {}, + "source": [ + "We can split blod presure in two:\n", + "- Systolic (upper number)\n", + " Pressure when the heart contracts\n", + "\n", + "- Diastolic (lower number)\n", + " Pressure when the heart relaxes" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "4768c669-a4aa-4120-a97e-6e82d360d6a1", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df[['systolic', 'diastolic']] = sleep_df['blood_pressure'].str.split('/', expand=True)\n", + "sleep_df['systolic'] = pd.to_numeric(sleep_df['systolic'])\n", + "sleep_df['diastolic'] = pd.to_numeric(sleep_df['diastolic'])" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "285f5b73-61e9-4074-a2d8-add3764bc5b7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200NaN12683
12Male28Doctor6.26608Normal125/807510000NaN12580
23Male28Doctor6.26608Normal125/807510000NaN12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
................................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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374 rows × 15 columns

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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 NaN 126 \n", + "1 125/80 75 10000 NaN 125 \n", + "2 125/80 75 10000 NaN 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "4 140/90 85 3000 Sleep Apnea 140 \n", + ".. ... ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea 140 \n", + "370 140/95 68 7000 Sleep Apnea 140 \n", + "371 140/95 68 7000 Sleep Apnea 140 \n", + "372 140/95 68 7000 Sleep Apnea 140 \n", + "373 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "2 80 \n", + "3 90 \n", + "4 90 \n", + ".. ... \n", + "369 95 \n", + "370 95 \n", + "371 95 \n", + "372 95 \n", + "373 95 \n", + "\n", + "[374 rows x 15 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "946e4d41-af18-4d51-8090-074d7b24e14d", + "metadata": {}, + "outputs": [], + "source": [ + "# sleep_df.drop(columns=[\"blood_pressure\"], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "d7309aae-b868-47ba-865b-dd588ed24dc6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([nan, 'Sleep Apnea', 'Insomnia'], dtype=object)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "6bd919a5-c18b-4770-9575-fff313786213", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "Sleep Apnea 78\n", + "Insomnia 77\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "a278d4dc-00f8-41e0-a912-194dfb6f79f3", + "metadata": {}, + "outputs": [], + "source": [ + "sleep_df.fillna({\"sleep_disorder\": \"No Disorder\"}, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "60d01a0f-6c33-4052-9f57-f066025433fa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "sleep_disorder\n", + "No Disorder 219\n", + "Sleep Apnea 78\n", + "Insomnia 77\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df[\"sleep_disorder\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "bad136b1-b525-448b-8d01-6b357bd1894c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
23Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
................................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
\n", + "

374 rows × 15 columns

\n", + "
" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 No Disorder 126 \n", + "1 125/80 75 10000 No Disorder 125 \n", + "2 125/80 75 10000 No Disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "4 140/90 85 3000 Sleep Apnea 140 \n", + ".. ... ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea 140 \n", + "370 140/95 68 7000 Sleep Apnea 140 \n", + "371 140/95 68 7000 Sleep Apnea 140 \n", + "372 140/95 68 7000 Sleep Apnea 140 \n", + "373 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "2 80 \n", + "3 90 \n", + "4 90 \n", + ".. ... \n", + "369 95 \n", + "370 95 \n", + "371 95 \n", + "372 95 \n", + "373 95 \n", + "\n", + "[374 rows x 15 columns]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "b1b1e5cb-5de7-4ae9-a66d-c6c7f95cd680", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 374 entries, 0 to 373\n", + "Data columns (total 15 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 person_id 374 non-null int64 \n", + " 1 gender 374 non-null object \n", + " 2 age 374 non-null int64 \n", + " 3 occupation 374 non-null object \n", + " 4 sleep_duration 374 non-null float64\n", + " 5 quality_of_sleep 374 non-null int64 \n", + " 6 physical_activity_level 374 non-null int64 \n", + " 7 stress_level 374 non-null int64 \n", + " 8 bmi_category 374 non-null object \n", + " 9 blood_pressure 374 non-null object \n", + " 10 heart_rate 374 non-null int64 \n", + " 11 daily_steps 374 non-null int64 \n", + " 12 sleep_disorder 374 non-null object \n", + " 13 systolic 374 non-null int64 \n", + " 14 diastolic 374 non-null int64 \n", + "dtypes: float64(1), int64(9), object(5)\n", + "memory usage: 44.0+ KB\n" + ] + } + ], + "source": [ + "sleep_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "376012df-d521-4cfd-b4ca-219a4f1b32ae", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(0)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.duplicated().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "e1ccabe6-0748-49a1-b00f-9c47aa493eb1", + "metadata": {}, + "source": [ + "### 4. Checking and deleting duplicated values" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "2a01a636-2679-44af-983e-e9cd579862d6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(242)" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df.duplicated(subset= sleep_df.columns.difference(['person_id'])).sum()" + ] + }, + { + "cell_type": "markdown", + "id": "e8fa5e9d-b636-4db6-af76-894a3ae450a2", + "metadata": {}, + "source": [ + "We see that we have 242 duplicated rows, so we can drop them." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "3c16260a-ea21-4073-bd36-25357a3926ac", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idgenderageoccupationsleep_durationquality_of_sleepphysical_activity_levelstress_levelbmi_categoryblood_pressureheart_ratedaily_stepssleep_disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No Disorder12683
12Male28Doctor6.26608Normal125/807510000No Disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000No Disorder14095
359360Female59Nurse8.19753Overweight140/95687000No Disorder14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
\n", + "

132 rows × 15 columns

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" + ], + "text/plain": [ + " person_id gender age occupation sleep_duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " quality_of_sleep physical_activity_level stress_level bmi_category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " blood_pressure heart_rate daily_steps sleep_disorder systolic \\\n", + "0 126/83 77 4200 No Disorder 126 \n", + "1 125/80 75 10000 No Disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 No Disorder 140 \n", + "359 140/95 68 7000 No Disorder 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean = sleep_df.drop_duplicates(subset=sleep_df.columns.difference(['person_id']), keep='first')\n", + "\n", + "sleep_df_clean" + ] + }, + { + "cell_type": "markdown", + "id": "2e51f62a-7496-4031-ab63-3336b55e5f29", + "metadata": {}, + "source": [ + "### 5. Looking at Statistical summary" + ] + }, + { + "cell_type": "markdown", + "id": "f100248b-9abb-4dd7-8460-c066471c1961", + "metadata": {}, + "source": [ + "#### 5.1 Statistical summary of numerical columns" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "02b81d3a-ce03-40fa-8e64-c6646e638dd8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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person_idagesleep_durationquality_of_sleepphysical_activity_levelstress_levelheart_ratedaily_stepssystolicdiastolic
count132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000132.000000
mean171.72727341.1287887.0825767.15151558.3939395.53787971.2045456637.878788128.36363684.537879
std110.4187798.8139420.7753351.26903720.4688401.7404284.8673061766.2886577.8256506.049926
min1.00000027.0000005.8000004.00000030.0000003.00000065.0000003000.000000115.00000075.000000
25%79.50000033.7500006.4000006.00000044.2500004.00000068.0000005000.000000120.75000080.000000
50%166.50000041.0000007.1500007.00000060.0000006.00000070.0000007000.000000130.00000085.000000
75%268.25000049.0000007.7250008.00000075.0000007.00000074.0000008000.000000135.00000088.500000
max367.00000059.0000008.5000009.00000090.0000008.00000086.00000010000.000000142.00000095.000000
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" + ], + "text/plain": [ + " person_id age sleep_duration quality_of_sleep \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 171.727273 41.128788 7.082576 7.151515 \n", + "std 110.418779 8.813942 0.775335 1.269037 \n", + "min 1.000000 27.000000 5.800000 4.000000 \n", + "25% 79.500000 33.750000 6.400000 6.000000 \n", + "50% 166.500000 41.000000 7.150000 7.000000 \n", + "75% 268.250000 49.000000 7.725000 8.000000 \n", + "max 367.000000 59.000000 8.500000 9.000000 \n", + "\n", + " physical_activity_level stress_level heart_rate daily_steps \\\n", + "count 132.000000 132.000000 132.000000 132.000000 \n", + "mean 58.393939 5.537879 71.204545 6637.878788 \n", + "std 20.468840 1.740428 4.867306 1766.288657 \n", + "min 30.000000 3.000000 65.000000 3000.000000 \n", + "25% 44.250000 4.000000 68.000000 5000.000000 \n", + "50% 60.000000 6.000000 70.000000 7000.000000 \n", + "75% 75.000000 7.000000 74.000000 8000.000000 \n", + "max 90.000000 8.000000 86.000000 10000.000000 \n", + "\n", + " systolic diastolic \n", + "count 132.000000 132.000000 \n", + "mean 128.363636 84.537879 \n", + "std 7.825650 6.049926 \n", + "min 115.000000 75.000000 \n", + "25% 120.750000 80.000000 \n", + "50% 130.000000 85.000000 \n", + "75% 135.000000 88.500000 \n", + "max 142.000000 95.000000 " + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sleep_df_clean.describe()" + ] + }, + { + "cell_type": "markdown", + "id": "1d80eb87-18cd-4a94-9160-21149f1a18f4", + "metadata": {}, + "source": [ + "#### 5.2 Statistical summary of categorical columns" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "d90fb11e-ad5f-43e5-b191-eade012048ca", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
23Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 NaN \n", + "1 125/80 75 10000 NaN \n", + "2 125/80 75 10000 NaN \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Utilisez le chemin complet et le nom du fichier comme une chaîne de caractères\n", + "#titanic_df = pd.read_csv(url)\n", + "file_path = r'C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\\data\\raw\\Sleep_health_and_lifestyle_dataset.csv'\n", + "df = pd.read_csv(file_path)\n", + "\n", + "# Affiche les 5 premières lignes du DataFrame pour vérifier la lecture\n", + "display(df.head())" + ] + }, + { + "attachments": { + "4479a41c-eee1-47c2-a355-6db4f461c513.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "1b591188-bf4a-481c-85f8-7b44874b49a1", + "metadata": {}, + "source": [ + "![image.png](attachment:4479a41c-eee1-47c2-a355-6db4f461c513.png)" + ] + }, + { + "cell_type": "markdown", + "id": "10a76d48-a40f-4494-b2cb-7aa7a7fd55a2", + "metadata": {}, + "source": [ + "# Checking for Null Values (S2D2 - ch 1.1.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "420a3cdd-ac3a-41bd-af27-8ceedad96511", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Person ID', 'Gender', 'Age', 'Occupation', 'Sleep Duration',\n", + " 'Quality of Sleep', 'Physical Activity Level', 'Stress Level',\n", + " 'BMI Category', 'Blood Pressure', 'Heart Rate', 'Daily Steps',\n", + " 'Sleep Disorder'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Column list\n", + "\"\"\"\n", + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b267aa4d-84e8-4a8d-b139-6ad253405def", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Person ID False\n", + "Gender False\n", + "Age False\n", + "Occupation False\n", + "Sleep Duration False\n", + "Quality of Sleep False\n", + "Physical Activity Level False\n", + "Stress Level False\n", + "BMI Category False\n", + "Blood Pressure False\n", + "Heart Rate False\n", + "Daily Steps False\n", + "Sleep Disorder True\n", + "dtype: bool" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "check null value True = null in each column\n", + "\"\"\"\n", + "df.isnull().any()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "035cf346-c415-41fc-ab1a-65e5348981d2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Person ID 0\n", + "Gender 0\n", + "Age 0\n", + "Occupation 0\n", + "Sleep Duration 0\n", + "Quality of Sleep 0\n", + "Physical Activity Level 0\n", + "Stress Level 0\n", + "BMI Category 0\n", + "Blood Pressure 0\n", + "Heart Rate 0\n", + "Daily Steps 0\n", + "Sleep Disorder 219\n", + "dtype: int64" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Count null value True each column\n", + "\"\"\"\n", + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0c21c752-6388-4704-b514-7a1533d585e6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
0FalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrue
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..........................................
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374 rows × 13 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration Quality of Sleep \\\n", + "0 False False False False False False \n", + "1 False False False False False False \n", + "2 False False False False False False \n", + "3 False False False False False False \n", + "4 False False False False False False \n", + ".. ... ... ... ... ... ... \n", + "369 False False False False False False \n", + "370 False False False False False False \n", + "371 False False False False False False \n", + "372 False False False False False False \n", + "373 False False False False False False \n", + "\n", + " Physical Activity Level Stress Level BMI Category Blood Pressure \\\n", + "0 False False False False \n", + "1 False False False False \n", + "2 False False False False \n", + "3 False False False False \n", + "4 False False False False \n", + ".. ... ... ... ... \n", + "369 False False False False \n", + "370 False False False False \n", + "371 False False False False \n", + "372 False False False False \n", + "373 False False False False \n", + "\n", + " Heart Rate Daily Steps Sleep Disorder \n", + "0 False False True \n", + "1 False False True \n", + "2 False False True \n", + "3 False False False \n", + "4 False False False \n", + ".. ... ... ... \n", + "369 False False False \n", + "370 False False False \n", + "371 False False False \n", + "372 False False False \n", + "373 False False False \n", + "\n", + "[374 rows x 13 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Give null value True in each column + total number of rows. So 219 cells null for 374 rows\n", + "\"\"\"\n", + "df.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "f9df8f13-09ef-4422-a6b3-06493b34e00e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200None
12Male28Doctor6.26608Normal125/807510000None
23Male28Doctor6.26608Normal125/807510000None
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
45Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
..........................................
369370Female59Nurse8.19753Overweight140/95687000Sleep Apnea
370371Female59Nurse8.09753Overweight140/95687000Sleep Apnea
371372Female59Nurse8.19753Overweight140/95687000Sleep Apnea
372373Female59Nurse8.19753Overweight140/95687000Sleep Apnea
373374Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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374 rows × 13 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "2 3 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "4 5 Male 28 Sales Representative 5.9 \n", + ".. ... ... ... ... ... \n", + "369 370 Female 59 Nurse 8.1 \n", + "370 371 Female 59 Nurse 8.0 \n", + "371 372 Female 59 Nurse 8.1 \n", + "372 373 Female 59 Nurse 8.1 \n", + "373 374 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "2 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "4 4 30 8 Obese \n", + ".. ... ... ... ... \n", + "369 9 75 3 Overweight \n", + "370 9 75 3 Overweight \n", + "371 9 75 3 Overweight \n", + "372 9 75 3 Overweight \n", + "373 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder \n", + "0 126/83 77 4200 None \n", + "1 125/80 75 10000 None \n", + "2 125/80 75 10000 None \n", + "3 140/90 85 3000 Sleep Apnea \n", + "4 140/90 85 3000 Sleep Apnea \n", + ".. ... ... ... ... \n", + "369 140/95 68 7000 Sleep Apnea \n", + "370 140/95 68 7000 Sleep Apnea \n", + "371 140/95 68 7000 Sleep Apnea \n", + "372 140/95 68 7000 Sleep Apnea \n", + "373 140/95 68 7000 Sleep Apnea \n", + "\n", + "[374 rows x 13 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.fillna(\"None\")" + ] + }, + { + "cell_type": "markdown", + "id": "4cfe1793-3b12-4ae3-8586-7da0dcc83f1a", + "metadata": {}, + "source": [ + "# Check duplicate (S2D2 - ch 1.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "f578862f-e607-4359-bc75-40cff188cf0f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(0)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "duplicated() method, which returns a boolean Series indicating\n", + "\"\"\"\n", + "df.duplicated().sum() # no duplicate because python include nID" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "94fb9ac3-4943-4f33-bee1-8d6e51833ae4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.int64(242)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "duplicated() method, without the id column obviusly \n", + "\"\"\"\n", + "\n", + "df.duplicated(subset=df.columns.difference(['Person ID'])).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "e60642c7-5105-4e85-a513-cab43436350c", + "metadata": {}, + "outputs": [], + "source": [ + "#df.duplicated((subset==df.columns.difference(['Person ID']))).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "d553496b-b0f6-4bd9-97a3-c21cc728d701", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "drop_duplicates() method, remove all duplicate, remain 1 or not? : remain 1\n", + "\"\"\"\n", + "df.drop_duplicates(subset=df.columns.difference(['Person ID']), inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "6ec51d5b-91f3-487b-8fef-65c34974f8c2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(132, 13)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "79f35f8e-ae56-40a4-a149-3f53be4a0e50", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disorder
01Male27Software Engineer6.16426Overweight126/83774200NaN
12Male28Doctor6.26608Normal125/807510000NaN
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea
56Male28Software Engineer5.94308Obese140/90853000Insomnia
67Male29Teacher6.36407Obese140/90823500Insomnia
..........................................
358359Female59Nurse8.09753Overweight140/95687000NaN
359360Female59Nurse8.19753Overweight140/95687000NaN
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea
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366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200NaN12683
12Male28Doctor6.26608Normal125/807510000NaN12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000NaN14095
359360Female59Nurse8.19753Overweight140/95687000NaN14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder systolic \\\n", + "0 126/83 77 4200 NaN 126 \n", + "1 125/80 75 10000 NaN 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 NaN 140 \n", + "359 140/95 68 7000 NaN 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "Name.apply(fonction) create 2 new column with specific blood condition : systolic and the diastolic\n", + "df['systolic'] = df.Name.apply(len)\n", + "\"\"\"\n", + "\n", + "df[['systolic', 'diastolic']] = df['Blood Pressure'].str.split('/', expand=True).astype(int)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "bc6d270b-4f99-4fdf-8343-12734ac8011a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "BMI Category\n", + "Normal 57\n", + "Overweight 52\n", + "Normal Weight 16\n", + "Obese 7\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['BMI Category'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "be50dcb8-9dcd-4f38-87b7-8103227c3b7e", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "2 categories of \"normal\" to merge in Normal : \n", + "\"\"\"\n", + "df['BMI Category'] = df['BMI Category'].replace('Normal Weight', 'Normal')" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "fa3f7313-47ed-4340-9879-bd53eade9884", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Occupation\n", + "Nurse 29\n", + "Doctor 24\n", + "Engineer 22\n", + "Teacher 15\n", + "Lawyer 15\n", + "Accountant 11\n", + "Salesperson 9\n", + "Software Engineer 3\n", + "Scientist 2\n", + "Sales Representative 1\n", + "Manager 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "df['Occupation'].value_counts()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "3b495677-aacd-4314-84b1-790f10bcb39c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sleep Disorder\n", + "Sleep Apnea 30\n", + "Insomnia 29\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Sleep Disorder'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "2eb0658b-f7a2-426d-bc25-c0420909b44b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sleep Disorder\n", + "True 73\n", + "False 59\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Sleep Disorder'].isnull().value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "6ff5dd06-295a-4204-bf9b-720ef36b5f9c", + "metadata": {}, + "outputs": [], + "source": [ + "df['Sleep Disorder'] = df['Sleep Disorder'].fillna('No disorder')" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "a9e0ba8e-2a93-4481-8f6e-759afd4f0a98", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Person IDGenderAgeOccupationSleep DurationQuality of SleepPhysical Activity LevelStress LevelBMI CategoryBlood PressureHeart RateDaily StepsSleep Disordersystolicdiastolic
01Male27Software Engineer6.16426Overweight126/83774200No disorder12683
12Male28Doctor6.26608Normal125/807510000No disorder12580
34Male28Sales Representative5.94308Obese140/90853000Sleep Apnea14090
56Male28Software Engineer5.94308Obese140/90853000Insomnia14090
67Male29Teacher6.36407Obese140/90823500Insomnia14090
................................................
358359Female59Nurse8.09753Overweight140/95687000No disorder14095
359360Female59Nurse8.19753Overweight140/95687000No disorder14095
360361Female59Nurse8.29753Overweight140/95687000Sleep Apnea14095
364365Female59Nurse8.09753Overweight140/95687000Sleep Apnea14095
366367Female59Nurse8.19753Overweight140/95687000Sleep Apnea14095
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132 rows × 15 columns

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" + ], + "text/plain": [ + " Person ID Gender Age Occupation Sleep Duration \\\n", + "0 1 Male 27 Software Engineer 6.1 \n", + "1 2 Male 28 Doctor 6.2 \n", + "3 4 Male 28 Sales Representative 5.9 \n", + "5 6 Male 28 Software Engineer 5.9 \n", + "6 7 Male 29 Teacher 6.3 \n", + ".. ... ... ... ... ... \n", + "358 359 Female 59 Nurse 8.0 \n", + "359 360 Female 59 Nurse 8.1 \n", + "360 361 Female 59 Nurse 8.2 \n", + "364 365 Female 59 Nurse 8.0 \n", + "366 367 Female 59 Nurse 8.1 \n", + "\n", + " Quality of Sleep Physical Activity Level Stress Level BMI Category \\\n", + "0 6 42 6 Overweight \n", + "1 6 60 8 Normal \n", + "3 4 30 8 Obese \n", + "5 4 30 8 Obese \n", + "6 6 40 7 Obese \n", + ".. ... ... ... ... \n", + "358 9 75 3 Overweight \n", + "359 9 75 3 Overweight \n", + "360 9 75 3 Overweight \n", + "364 9 75 3 Overweight \n", + "366 9 75 3 Overweight \n", + "\n", + " Blood Pressure Heart Rate Daily Steps Sleep Disorder systolic \\\n", + "0 126/83 77 4200 No disorder 126 \n", + "1 125/80 75 10000 No disorder 125 \n", + "3 140/90 85 3000 Sleep Apnea 140 \n", + "5 140/90 85 3000 Insomnia 140 \n", + "6 140/90 82 3500 Insomnia 140 \n", + ".. ... ... ... ... ... \n", + "358 140/95 68 7000 No disorder 140 \n", + "359 140/95 68 7000 No disorder 140 \n", + "360 140/95 68 7000 Sleep Apnea 140 \n", + "364 140/95 68 7000 Sleep Apnea 140 \n", + "366 140/95 68 7000 Sleep Apnea 140 \n", + "\n", + " diastolic \n", + "0 83 \n", + "1 80 \n", + "3 90 \n", + "5 90 \n", + "6 90 \n", + ".. ... \n", + "358 95 \n", + "359 95 \n", + "360 95 \n", + "364 95 \n", + "366 95 \n", + "\n", + "[132 rows x 15 columns]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "c5ccd008-6098-43cc-a757-3bd9f5694b2e", + "metadata": {}, + "outputs": [], + "source": [ + "df.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b327a050-4dec-4f69-9aa0-741cd30b07d1", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd22573f-b04f-47bc-acff-fb4cc492cf71", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/slides/Sleep Health & Lifestyle.pdf b/slides/Sleep Health & Lifestyle.pdf new file mode 100644 index 00000000..bec0a0c5 Binary files /dev/null and b/slides/Sleep Health & Lifestyle.pdf differ diff --git a/slides/project_presentation.pptx b/slides/project_presentation.pptx deleted file mode 100644 index e69de29b..00000000