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..f684bdd6 100644
--- a/README.md
+++ b/README.md
@@ -1,77 +1,47 @@
-# 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
-```
-
-If you're a MacOS/Linux user type (if you're using a csh/tcsh shell):
-
-```bash
-source ./venv/bin/activate.csh
-```
-
-If you're a Windows user type:
-
-```bash
-.\venv\Scripts\activate
-```
-
-4. **Install dependencies**:
-
-```bash
-uv pip install -r requirements.txt
-```
-
-# Questions
-...
-
-# Dataset
-...
-
-## Main dataset issues
-
-- ...
-- ...
-- ...
-
-## Solutions for the dataset issues
-...
-
-# Conclussions
-...
-
-# Next steps
-...
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
+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
+66,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
+67,Male,32,Accountant,7.2,8,50,6,Normal Weight,118/76,68,7000,None
+68,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,Insomnia
+69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
+70,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
+71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+72,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+73,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+74,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+75,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+76,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+77,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+78,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+79,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+80,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
+82,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
+83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
+84,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
+85,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
+86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
+88,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
+89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+90,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+91,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+92,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+93,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
+94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
+95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia
+96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+98,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
+100,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
+101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+102,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+103,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea
+105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea
+106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia
+107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,None
+108,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
+109,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
+110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+112,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+113,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+114,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+115,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+116,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+117,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+118,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+119,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+120,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+121,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+122,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+123,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+124,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+125,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+126,Female,37,Nurse,7.5,8,60,4,Normal Weight,120/80,70,8000,None
+127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+129,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+130,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+131,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+132,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+133,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+134,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+135,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+136,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+137,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+139,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+140,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+141,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+142,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+143,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+144,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea
+146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
+147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia
+148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia
+149,Female,39,Lawyer,6.9,7,50,6,Normal Weight,128/85,75,5500,None
+150,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
+151,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
+152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+153,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+154,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+155,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+156,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+157,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+158,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+159,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+160,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+161,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+162,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
+163,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
+164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
+165,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
+166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia
+167,Male,41,Engineer,7.3,8,70,6,Normal Weight,121/79,72,6200,None
+168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
+169,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
+170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+171,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+172,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+173,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+174,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+176,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+177,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+180,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+181,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+182,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+183,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+184,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
+186,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
+187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+189,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+191,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+193,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+194,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+195,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+196,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+197,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+198,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+199,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+200,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+201,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
+203,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
+204,Male,43,Engineer,6.9,6,47,7,Normal Weight,117/76,69,6800,None
+205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,None
+206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+207,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+208,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+209,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+211,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+212,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+213,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+214,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+215,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+216,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+217,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+218,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea
+220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea
+221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+224,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+225,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+226,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+227,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+228,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+229,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+230,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+231,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+232,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+233,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+234,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+235,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+236,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+237,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+239,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+240,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+241,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+242,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+243,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+244,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+245,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+246,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+247,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia
+249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,None
+250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,None
+251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
+252,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
+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
+267,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia
+268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,None
+269,Female,49,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+271,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+272,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+273,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+275,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+276,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
+278,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
+279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia
+280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
+281,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,None
+282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+283,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+284,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+285,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+286,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+287,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+288,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+289,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+290,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+291,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+292,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+293,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+294,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+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
+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/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
+66,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
+67,Male,32,Accountant,7.2,8,50,6,Normal Weight,118/76,68,7000,None
+68,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,Insomnia
+69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
+70,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
+71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+72,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+73,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+74,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
+75,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+76,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+77,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+78,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+79,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+80,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
+81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
+82,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
+83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
+84,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
+85,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
+86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
+88,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
+89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+90,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+91,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+92,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
+93,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
+94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
+95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia
+96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+98,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
+100,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
+101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+102,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+103,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
+104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea
+105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea
+106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia
+107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,None
+108,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
+109,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
+110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+112,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+113,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+114,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
+115,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+116,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+117,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+118,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+119,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+120,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+121,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+122,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+123,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+124,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+125,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
+126,Female,37,Nurse,7.5,8,60,4,Normal Weight,120/80,70,8000,None
+127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+129,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+130,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+131,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+132,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+133,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+134,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+135,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+136,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
+137,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+139,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+140,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+141,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+142,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
+143,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+144,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
+145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea
+146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
+147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia
+148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia
+149,Female,39,Lawyer,6.9,7,50,6,Normal Weight,128/85,75,5500,None
+150,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
+151,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
+152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+153,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+154,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+155,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+156,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+157,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+158,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+159,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+160,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+161,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
+162,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
+163,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
+164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
+165,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
+166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia
+167,Male,41,Engineer,7.3,8,70,6,Normal Weight,121/79,72,6200,None
+168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
+169,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
+170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+171,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+172,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+173,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+174,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
+175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+176,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+177,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
+178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+180,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+181,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+182,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+183,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+184,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
+185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
+186,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
+187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+189,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+191,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
+192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+193,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+194,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+195,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+196,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+197,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+198,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+199,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+200,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+201,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
+202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
+203,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
+204,Male,43,Engineer,6.9,6,47,7,Normal Weight,117/76,69,6800,None
+205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,None
+206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+207,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+208,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+209,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+211,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
+212,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+213,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+214,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+215,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+216,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+217,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+218,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
+219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea
+220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea
+221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+224,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+225,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+226,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+227,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+228,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+229,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+230,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+231,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+232,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+233,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+234,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+235,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
+236,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+237,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+239,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+240,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+241,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+242,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+243,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
+244,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+245,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+246,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
+247,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
+248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia
+249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,None
+250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,None
+251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
+252,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
+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
+267,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia
+268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,None
+269,Female,49,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+271,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+272,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+273,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+275,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+276,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
+278,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
+279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia
+280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
+281,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,None
+282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+283,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+284,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+285,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+286,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+287,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+288,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+289,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+290,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+291,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+292,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+293,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+294,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
+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
+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/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_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..bfccd888
--- /dev/null
+++ b/notebooks/sleep_health_cleaning_pati.ipynb
@@ -0,0 +1,504 @@
+{
+ "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": null,
+ "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": null,
+ "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": null,
+ "id": "0ec37943-cc03-4702-b4a3-f144cf3191e9",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "e80d1833-22d2-4515-b40f-51bb11ec3409",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "af483cf4-9c49-4e56-8e92-1fc210108afa",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "0e78431f-8625-467f-bc25-936dedc8c000",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "ab3f22b9-a7da-456f-b360-4f3659299e35",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a81fbcd7-b940-4cce-89a7-05d90f985031",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "e12147fe-0b5e-4b91-92db-c52b4f111eb7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df[\"gender\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c3b0b4f8-4814-4e71-92e1-b416547506ab",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df[\"occupation\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8bff6d10-4dd5-4135-84a3-f810ca1f82ba",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "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": null,
+ "id": "c1c8d6e6-5b0b-4925-bbd3-d90dd961c780",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "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": null,
+ "id": "285f5b73-61e9-4074-a2d8-add3764bc5b7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "946e4d41-af18-4d51-8090-074d7b24e14d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# sleep_df.drop(columns=[\"blood_pressure\"], inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "d7309aae-b868-47ba-865b-dd588ed24dc6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df[\"sleep_disorder\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6bd919a5-c18b-4770-9575-fff313786213",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df[\"sleep_disorder\"].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a278d4dc-00f8-41e0-a912-194dfb6f79f3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df.fillna({\"sleep_disorder\": \"No Disorder\"}, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "60d01a0f-6c33-4052-9f57-f066025433fa",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df[\"sleep_disorder\"].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "bad136b1-b525-448b-8d01-6b357bd1894c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b1b1e5cb-5de7-4ae9-a66d-c6c7f95cd680",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "376012df-d521-4cfd-b4ca-219a4f1b32ae",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "2a01a636-2679-44af-983e-e9cd579862d6",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "3c16260a-ea21-4073-bd36-25357a3926ac",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "02b81d3a-ce03-40fa-8e64-c6646e638dd8",
+ "metadata": {},
+ "outputs": [],
+ "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": null,
+ "id": "d90fb11e-ad5f-43e5-b191-eade012048ca",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df_clean.select_dtypes(include='object').describe()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1be5620a-0e2f-4648-a0cf-4164f0abd734",
+ "metadata": {},
+ "source": [
+ "### 6. Exporting the clean DataFrame"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6da8fa73-5375-46bc-9642-a3909c186d38",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sleep_df.to_csv(\"sleep_health_project_clean.csv\", index=False, encoding='utf-8')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "98fdaa01-2254-4312-8083-3e4dd235a829",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "venv",
+ "language": "python",
+ "name": "venv"
+ },
+ "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_veronique.ipynb b/notebooks/sleep_health_cleaning_veronique.ipynb
new file mode 100644
index 00000000..c411cb32
--- /dev/null
+++ b/notebooks/sleep_health_cleaning_veronique.ipynb
@@ -0,0 +1,2067 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "1e0787d1-cc80-44f6-b8dd-289100c76861",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#!pip install pandas openpyxl"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "3285ae80-c5cc-4865-b5db-a4baea512296",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#!pip install xlrd"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "09ac5399-7b97-4b0b-8b40-3ace765b17b7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "sleep_health = os.listdir(r\"C:\\Users\\Utilisateur\\IronHack\\Week4\\first_project\") "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "879cc154-31f8-446a-b48d-3376c745715f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
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+ " Person ID | \n",
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+ " Age | \n",
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+ " Sleep Duration | \n",
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374 rows × 13 columns
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374 rows × 13 columns
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132 rows × 13 columns
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132 rows × 15 columns
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+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " | 358 | \n",
+ " 359 | \n",
+ " Female | \n",
+ " 59 | \n",
+ " Nurse | \n",
+ " 8.0 | \n",
+ " 9 | \n",
+ " 75 | \n",
+ " 3 | \n",
+ " Overweight | \n",
+ " 140/95 | \n",
+ " 68 | \n",
+ " 7000 | \n",
+ " No disorder | \n",
+ " 140 | \n",
+ " 95 | \n",
+ "
\n",
+ " \n",
+ " | 359 | \n",
+ " 360 | \n",
+ " Female | \n",
+ " 59 | \n",
+ " Nurse | \n",
+ " 8.1 | \n",
+ " 9 | \n",
+ " 75 | \n",
+ " 3 | \n",
+ " Overweight | \n",
+ " 140/95 | \n",
+ " 68 | \n",
+ " 7000 | \n",
+ " No disorder | \n",
+ " 140 | \n",
+ " 95 | \n",
+ "
\n",
+ " \n",
+ " | 360 | \n",
+ " 361 | \n",
+ " Female | \n",
+ " 59 | \n",
+ " Nurse | \n",
+ " 8.2 | \n",
+ " 9 | \n",
+ " 75 | \n",
+ " 3 | \n",
+ " Overweight | \n",
+ " 140/95 | \n",
+ " 68 | \n",
+ " 7000 | \n",
+ " Sleep Apnea | \n",
+ " 140 | \n",
+ " 95 | \n",
+ "
\n",
+ " \n",
+ " | 364 | \n",
+ " 365 | \n",
+ " Female | \n",
+ " 59 | \n",
+ " Nurse | \n",
+ " 8.0 | \n",
+ " 9 | \n",
+ " 75 | \n",
+ " 3 | \n",
+ " Overweight | \n",
+ " 140/95 | \n",
+ " 68 | \n",
+ " 7000 | \n",
+ " Sleep Apnea | \n",
+ " 140 | \n",
+ " 95 | \n",
+ "
\n",
+ " \n",
+ " | 366 | \n",
+ " 367 | \n",
+ " Female | \n",
+ " 59 | \n",
+ " Nurse | \n",
+ " 8.1 | \n",
+ " 9 | \n",
+ " 75 | \n",
+ " 3 | \n",
+ " Overweight | \n",
+ " 140/95 | \n",
+ " 68 | \n",
+ " 7000 | \n",
+ " Sleep Apnea | \n",
+ " 140 | \n",
+ " 95 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
132 rows × 15 columns
\n",
+ "