From 039600ffc7fe78c0a969e26eb8c1f07529ba0b85 Mon Sep 17 00:00:00 2001 From: nebiyuu Date: Sun, 20 Jul 2025 18:10:48 -0700 Subject: [PATCH 1/6] intialized ci,created necessary folders,loaded all datas --- .github/workflows/py.yml | 0 .gitignore | 4 ++++ notebooks/EDA.ipynb | 0 3 files changed, 4 insertions(+) create mode 100644 .github/workflows/py.yml create mode 100644 .gitignore create mode 100644 notebooks/EDA.ipynb diff --git a/.github/workflows/py.yml b/.github/workflows/py.yml new file mode 100644 index 0000000..e69de29 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..838f985 --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ +/data +/venv +/__pycache__/ +*.pyc \ No newline at end of file diff --git a/notebooks/EDA.ipynb b/notebooks/EDA.ipynb new file mode 100644 index 0000000..e69de29 From 77432137ffff12c123a4581f51f4f8eef14eebc4 Mon Sep 17 00:00:00 2001 From: nebiyuu Date: Sun, 20 Jul 2025 19:00:51 -0700 Subject: [PATCH 2/6] created requremnt.txt and more eda on fraud data --- notebooks/EDA.ipynb | 555 ++++++++++++++++++++++++++++++++++++++++++++ requirements.txt | 4 + 2 files changed, 559 insertions(+) create mode 100644 requirements.txt diff --git a/notebooks/EDA.ipynb b/notebooks/EDA.ipynb index e69de29..1161c2a 100644 --- a/notebooks/EDA.ipynb +++ b/notebooks/EDA.ipynb @@ -0,0 +1,555 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "814f5f5a", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "da48fc77", + "metadata": {}, + "outputs": [], + "source": [ + "#import csv files\n", + "df_fraud = pd.read_csv('../data/raw/Fraud_Data.csv')\n", + "df_transactions = pd.read_csv('../data/raw/creditcard.csv') \n", + "df_ip = pd.read_csv('../data/raw/IpAddress_to_Country.csv')" + ] + }, + { + "cell_type": "markdown", + "id": "16cfc8a8", + "metadata": {}, + "source": [ + "EDA on fraud_data" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "e3309413", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 151112 entries, 0 to 151111\n", + "Data columns (total 11 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 user_id 151112 non-null int64 \n", + " 1 signup_time 151112 non-null object \n", + " 2 purchase_time 151112 non-null object \n", + " 3 purchase_value 151112 non-null int64 \n", + " 4 device_id 151112 non-null object \n", + " 5 source 151112 non-null object \n", + " 6 browser 151112 non-null object \n", + " 7 sex 151112 non-null object \n", + " 8 age 151112 non-null int64 \n", + " 9 ip_address 151112 non-null float64\n", + " 10 class 151112 non-null int64 \n", + "dtypes: float64(1), int64(4), object(6)\n", + "memory usage: 12.7+ MB\n", + "None\n", + "number of rows and columns (151112, 11)\n" + ] + } + ], + "source": [ + "print(df_fraud.info())\n", + "# number of rows and columns on fraud_data\n", + "print(\"number of rows and columns\",df_fraud.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e1aada6c", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\nebiy\\AppData\\Local\\Temp\\ipykernel_15620\\332268304.py:6: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " sns.countplot(x='class', data=df_fraud, palette='Set1')\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Count and plot class 0 vs 1.\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "plt.figure(figsize=(10, 6))\n", + "sns.countplot(x='class', data=df_fraud, palette='Set1')\n", + "plt.title('Class Distribution in Fraud Data')\n", + "plt.xlabel('class (0: No Fraud, 1: Fraud)')\n", + "plt.ylabel('Count')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0c26ae2a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fraud Ratio (class 1): 0.09364577267192546\n" + ] + } + ], + "source": [ + "#Calculate fraud ratio (class == 1) to know just how skewed it is.\n", + "fraud_ratio = df_fraud['class'].value_counts(normalize=True)\n", + "print(\"Fraud Ratio (class 1):\", fraud_ratio[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "df65d6bc", + "metadata": {}, + "outputs": [], + "source": [ + "#Convert signup_time and purchase_time to datetime.\n", + "\n", + "df_fraud['signup_time'] = pd.to_datetime(df_fraud['signup_time'], errors='coerce')\n", + "df_fraud['purchase_time'] = pd.to_datetime(df_fraud['purchase_time'], errors='coerce')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "04ae1d30", + "metadata": {}, + "outputs": [], + "source": [ + "# how long does it take to make a purchase after signup?\n", + "df_fraud['time_to_purchase'] = (df_fraud['purchase_time'] - df_fraud['signup_time']).dt.total_seconds() / 3600 # convert to hours" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "c03e0b1a", + "metadata": {}, + "outputs": [], + "source": [ + "# Hour of day, day of week, weekday/weekend, etc.\n", + "df_fraud['purchase_hour'] = df_fraud['purchase_time'].dt.hour\n", + "df_fraud['purchase_dayofweek'] = df_fraud['purchase_time'].dt.dayofweek\n", + "df_fraud['is_weekend'] = df_fraud['purchase_dayofweek'].isin([5, 6])\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "6d30b14c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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user_idsignup_timepurchase_timepurchase_valuedevice_idsourcebrowsersexageip_addressclasstime_to_purchasepurchase_hourpurchase_dayofweekis_weekend
0220582015-02-24 22:55:492015-04-18 02:47:1134QVPSPJUOCKZARSEOChromeM397.327584e+0801251.85611125True
13333202015-06-07 20:39:502015-06-08 01:38:5416EOGFQPIZPYXFZAdsChromeF533.503114e+0804.98444410False
213592015-01-01 18:52:442015-01-01 18:52:4515YSSKYOSJHPPLJSEOOperaM532.621474e+0910.000278183False
31500842015-04-28 21:13:252015-05-04 13:54:5044ATGTXKYKUDUQNSEOSafariM413.840542e+090136.690278130False
42213652015-07-21 07:09:522015-09-09 18:40:5339NAUITBZFJKHWWAdsSafariM454.155831e+0801211.516944182False
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" + ], + "text/plain": [ + " user_id signup_time purchase_time purchase_value \\\n", + "0 22058 2015-02-24 22:55:49 2015-04-18 02:47:11 34 \n", + "1 333320 2015-06-07 20:39:50 2015-06-08 01:38:54 16 \n", + "2 1359 2015-01-01 18:52:44 2015-01-01 18:52:45 15 \n", + "3 150084 2015-04-28 21:13:25 2015-05-04 13:54:50 44 \n", + "4 221365 2015-07-21 07:09:52 2015-09-09 18:40:53 39 \n", + "\n", + " device_id source browser sex age ip_address class \\\n", + "0 QVPSPJUOCKZAR SEO Chrome M 39 7.327584e+08 0 \n", + "1 EOGFQPIZPYXFZ Ads Chrome F 53 3.503114e+08 0 \n", + "2 YSSKYOSJHPPLJ SEO Opera M 53 2.621474e+09 1 \n", + "3 ATGTXKYKUDUQN SEO Safari M 41 3.840542e+09 0 \n", + "4 NAUITBZFJKHWW Ads Safari M 45 4.155831e+08 0 \n", + "\n", + " time_to_purchase purchase_hour purchase_dayofweek is_weekend \n", + "0 1251.856111 2 5 True \n", + "1 4.984444 1 0 False \n", + "2 0.000278 18 3 False \n", + "3 136.690278 13 0 False \n", + "4 1211.516944 18 2 False " + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_fraud.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "619fcd8c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Group by hour and calculate fraud ratio\n", + "fraud_ratio = df_fraud.groupby('purchase_hour')['class'].mean()\n", + "\n", + "# Plot\n", + "plt.plot(fraud_ratio.index, fraud_ratio.values, marker='o')\n", + "plt.title('Fraud Rate by Purchase Hour')\n", + "plt.xlabel('Hour of Day')\n", + "plt.ylabel('Fraud Rate (Class=1)')\n", + "plt.grid(True)\n", + "plt.xticks(range(0, 24))\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "66f00926", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Group by hour and calculate fraud ratio\n", + "fraud_ratio = df_fraud.groupby('purchase_dayofweek')['class'].mean()\n", + "\n", + "# Plot\n", + "plt.plot(fraud_ratio.index, fraud_ratio.values, marker='o')\n", + "plt.title('Fraud Rate by purchase_dayofweek')\n", + "plt.xlabel('Day of week ')\n", + "plt.ylabel('Fraud Rate (Class=1)')\n", + "plt.grid(True)\n", + "plt.xticks(range(0, 7))\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "e4eb2da4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fraud percentage on weekends: 10.01%\n", + "Fraud percentage on weekdays: 9.10%\n" + ] + } + ], + "source": [ + "# Calculate and display the percentage of frauds for weekend and weekday transactions\n", + "weekend_fraud_pct = df_fraud[df_fraud['is_weekend'] & (df_fraud['class'] == 1)].shape[0] / df_fraud[df_fraud['is_weekend']].shape[0] * 100\n", + "weekday_fraud_pct = df_fraud[~df_fraud['is_weekend'] & (df_fraud['class'] == 1)].shape[0] / df_fraud[~df_fraud['is_weekend']].shape[0] * 100\n", + "print(f\"Fraud percentage on weekends: {weekend_fraud_pct:.2f}%\")\n", + "print(f\"Fraud percentage on weekdays: {weekday_fraud_pct:.2f}%\")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "a6385858", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "plt.figure(figsize=(9, 6))\n", + "sns.set_style(\"whitegrid\")\n", + "\n", + "# Draw the countplot\n", + "ax = sns.countplot(\n", + " x='is_weekend',\n", + " hue='class',\n", + " data=df_fraud,\n", + " palette={0: '#3498db', 1: '#e74c3c'}, # Blue for legit, red for fraud\n", + " dodge=True\n", + ")\n", + "\n", + "# Title and axis labels\n", + "plt.title('Weekend vs Weekday Transactions by Fraud Class', fontsize=14, fontweight='bold')\n", + "plt.xlabel('Weekend? (False = Weekday, True = Weekend)', fontsize=12)\n", + "plt.ylabel('Transaction Count', fontsize=12)\n", + "plt.legend(title='Fraud Class', labels=['Not Fraud (0)', 'Fraud (1)'])\n", + "\n", + "# Annotate fraud percentage\n", + "for i, is_weekend_val in enumerate([False, True]):\n", + " total = df_fraud[df_fraud['is_weekend'] == is_weekend_val].shape[0]\n", + " frauds = df_fraud[(df_fraud['is_weekend'] == is_weekend_val) & (df_fraud['class'] == 1)].shape[0]\n", + " pct = 100 * frauds / total if total > 0 else 0\n", + " # Fraud bar is always the second one in each group (i + 2)\n", + " bar = ax.patches[i + 2]\n", + " ax.annotate(f'{pct:.1f}% Fraud',\n", + " (bar.get_x() + bar.get_width()/2, bar.get_height() + 2),\n", + " ha='center', va='bottom',\n", + " fontsize=11, fontweight='bold',\n", + " color=\"#8f251a\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "85ce8c1b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# ASSUME df IS YOUR DATAFRAME WITH signup_time, purchase_time, AND class COLUMNS\n", + "\n", + "# 1. CONVERT signup_time AND purchase_time TO DATETIME (IF NOT ALREADY)\n", + "df_fraud['signup_time'] = pd.to_datetime(df_fraud['signup_time'])\n", + "df_fraud['purchase_time'] = pd.to_datetime(df_fraud['purchase_time'])\n", + "\n", + "# 2. CALCULATE time_to_purchase IN MINUTES\n", + "df_fraud['time_to_purchase'] = (df_fraud['purchase_time'] - df_fraud['signup_time']).dt.total_seconds() / 60\n", + "\n", + "# 3. PLOT DISTRIBUTION OF time_to_purchase FOR FRAUD AND NON-FRAUD\n", + "plt.figure(figsize=(12,6))\n", + "\n", + "# NON-FRAUD (class=0)\n", + "plt.hist(df_fraud[df_fraud['class'] == 0]['time_to_purchase'], bins=50, alpha=0.5, label='Non-Fraud')\n", + "\n", + "# FRAUD (class=1)\n", + "plt.hist(df_fraud[df_fraud['class'] == 1]['time_to_purchase'], bins=50, alpha=0.5, label='Fraud')\n", + "\n", + "plt.xlabel('Time from Signup to Purchase (minutes)')\n", + "plt.ylabel('Number of Transactions')\n", + "plt.title('Time to Purchase Distribution by Transaction Class')\n", + "plt.legend()\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "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": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..ff9b472 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,4 @@ +pandas +matplotlib +seaborn +scikit-learn \ No newline at end of file From 2f637716422b36ee7086a87fa54bb8208ca1d328 Mon Sep 17 00:00:00 2001 From: nebiyuu Date: Sun, 20 Jul 2025 19:11:26 -0700 Subject: [PATCH 3/6] finished eda on fraud data --- notebooks/EDA.ipynb | 90 ++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 89 insertions(+), 1 deletion(-) diff --git a/notebooks/EDA.ipynb b/notebooks/EDA.ipynb index 1161c2a..95f6cd3 100644 --- a/notebooks/EDA.ipynb +++ b/notebooks/EDA.ipynb @@ -486,7 +486,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "id": "85ce8c1b", "metadata": {}, "outputs": [ @@ -529,6 +529,94 @@ "plt.legend()\n", "plt.show()\n" ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "e12775bd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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P1dj9a5izpmDUHo6tXmj1tPft29eaq7HH4YVdDVNX44waphpaZb059Fj1WlNo9O5DjSPTpk1LaMi5RshoWLjep17jkepeo0a8M2Xoda3h/HoPeKFe9aXH6d2PF9y1FkYsNa6psS7eOtTnR2zPvB6Tnme9D5rTwKT3q+pGa1jo86Q2raGh9T1iF1n06P2oaUHa3/scEX0+iPccNPY+auxzCwBSGT32AOAz+rKphdp0UWDRF3X1LDVGAVcrxatnT1/AtXCU5h5rlWitBB1vMFQDgXo8tZ/m4uvLtuaXq8fbmxOs3jcNZdW8V30R19zfu+66yw1H1jb9VOhWGNYXajUUKIjobx3HG0LbEAUbLbCmUKLHEtvzrzKqfOq11/Ol4K/FydTbWN/K8CqDwrX2Uc++GgIUuGMXj9NpvPR4vHnaGt6vQKF5uZqSUNfog1hqNNBaB6JpDHrMmkagxonYhdfqClQKdhrJoOHC2k/Prx6313ChYKSwrbUaGlssr7ZXXnnFhU8FXZVFi7vpOYhdIE3hTa83BXCtZq85zLG8HmGNotDtag+714KICvFaLE+nZdPzqrCm166GxzenYSLex+EFXM2r13xx1VtL8Xp3Va8KixpNoKHyer+IRgvEM81Gr0lN09HCdWoM02tQrzm9bhT4vftSD7567jW3XXWjzwfNLffek3pPabSChp+rsUC92gq+CureqQpVh3qPqCe7rrUZVG/aR58jXg+5VovXwnV6fzeXGhg1okajHDT3Xa9vvU90nwr8ei97C//FUkjXmgl6fvUe0uPQqS/V2y7ec9DY+6ixzy0ASGUEewDwGa1erx5iBVV98VToUrjVMN3GaGi6vgRrIS59YVUYVUhVT1a89KVX96uh+AoOOobuW8Ne1cigHjwNpVVPoL5EKwworCtQ6Yu2F5TPPPNM11OrRe5UFgVuDefXl3uv17EhCkUKNgqHtR+7er7V66+5tDq+wp7KpEWz9HjVEx+7QKAoDGghMS2upYXJFBRUdh0/lhoTFJq8xcz0fGruth5PY6MeNEzYWzlcQVbPhUKwwkTtqQyxFE7VGKPHo0XK9Pxo8a/YFcY1D1jhTsOVX3zxRUuE5nAruKvRR3WildMV3jxa3E4BSz2a6g3V49V9xy68qCHgGvas14d6TjX/O5aOq8YWPb/qNdVrSGFTZdbZFpKhscfh0XtG76GmLnQYDzUUac636lYr+itM6jqFaL2+1Mse76JsahzQ+03vJw1712tOz7FeF95ngnqt9f7S60Nz7DXFwDtbg3qk9fpWqNf9a7SCbq/3gBqvvOdBPdgK9SqfTv+meq49BUbvJ42q0WtCx1ejgu430cakuqiMDzzwgGss0GtYrxf1nnun19Njrmt+veh1pM9Bvf70XtEIBjU4qtFI0yLUWNDY+yiezy0ASFWBaDyr0QAAAKQBfe3RaA+tdq7gDwBAOqDHHgAApD1N+VBPvoZ6a+g4q5wDANIJwR4AAKQ9zVXX9AktpKbh2XWdeg8AAL9iKD4AAAAAAD7G6e4AAAAAAPAxgj0AAAAAAD5GsAcAAAAAwMdYPK8OWlhH5+vVOYZ1DlMAAAAAAFqSlr9TFg2FQi6LJoJgXweFep0OBwAAAACA1tS/f38Lh8MJ7UOwr4PXOqInNBgMtnVx0IDKykrXCENdpQfqM/1Qp+mHOk0v1Gf6oU7TC/XZvuq08vdtifbWC8G+Dt7wez3RvIH8gbpKL9Rn+qFO0w91ml6oz/RDnaYX6rN91WmgCdPBWTwPAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMOfYAAAAA4INToensXVpgDf6V0YSF8eJBsAcAAACAFBaJRGzhwoVWWlra1kVBiiLYAwAAAEAK+/HHHy0UClmvXr3c+c2bsmo6UmPUxaJFi6ysrMyNvEjmmQ4I9gAAAACQwqqqqlyoz83NbeuioJm6detmxcXFtnr1atdIkywsngcAAAAA7XRuNlqXRlu0xIgLXh0AAAAAAPgYwR4AAAAAAB9jjj0AAAAA+NDS0oitKK9olfvKzw5ZQW78c8L79etn++23n1133XU1rp8yZYrdcsst9vrrr7dAKc2OOeYY+/DDD9e4vkePHvb2229ba9hll11s1KhRNnz4cGstBHsAAAAA8CGF+jdnL7SySMue2z4nHLSh/QoTCvby/PPP28EHH2zbbbedtaYTTjjBXWIlcwX6VESwBwAAAACfUqgvaeFg31S9e/e28ePH2zPPPJPUFeAbk5uba927d7f2hDn2AAAAAICkO/PMM23BggV2991313ub+fPn2xlnnGFDhgyxbbbZxq644gqLRCLVw/Y1tP6mm25y27beemu76qqr3Pngm+r88893l7/85S9uJMEPP/xg3377rZ144ok2cOBA69+/vx155JH23Xffudt/8MEHblpBXcfwPPLIIzZ06FAbNGiQ3XbbbdYWCPYAAAAAgKTTvPbRo0fbHXfcYUVFRWtsV4A/7rjjrKyszB544AG74YYb7M0337SJEydW3+bTTz+1uXPn2sMPP2yXXHKJTZ482aZNm9ascj3zzDOu0WHSpEm2zjrr2Mknn+xGF+h6hfTKykq75ppr4jrWO++8YxMmTHDHe/TRR23GjBk2b948a20EewAAAABAi1CPe9++fV34rSsUq0dfIVq94upBv/TSS12ILykpcbdRyL788stt/fXXtwMOOMA23nhjF54bMmnSJNf7HnvxeuBFvfJa4G7AgAFWXl5uhx9+uOuBV8jfbLPN7MADD3S9+PF4/PHHbf/997dhw4bZRhttZFdeeaVlZWVZa2OOPQAAAACgRWjRurFjx7rh7a+99lqNbQrb6667rnXq1Kn6Og1nr6iosP/973/u765du1qHDh2qt+t3bRcFds9WW21ld911l/tdQV0NCrF69uxZ/bt652Pn4x9xxBH29NNP25dffmnff/+9zZw507p16xbX49Nj0P15OnfubGuvvba1NoI9AAAAAKDFKKwfdNBBrtf+r3/9a/X1dfVsq4c+9mddi+55c+wVxj3Z2dnVv6uhQKME6hN7vxoZoJX7FcjVi69T9Cnc33PPPW57IBBYY381LIRCf0Tp2nP+MzMzrbUR7AEAAAAALWrMmDG211571VhIb7311nOL1y1dutQKCgrcdZ999pkLzRoW/8033zR4zIbCe7x0zvuFCxfac889Vx3W33333eqw7oX0lStXVo8c+Omnn9xIA9Hw+9ipAbrdjz/+aK2NYA+0gKWlEXde0ebIzw4lfK5QAAAAtC86x7wf7kM94gr3F198cfVQ+B122MENWz/33HPt7LPPtiVLlrj59Oo179ixo7WGgoICKy0tddMENt98c5s+fbo99NBD1SFewV2jAbQA4GGHHWYvv/yyG6rvBfujjz7aRowYYYMHD3bTAW699VY3b7+1EeyBFqBQ/+bshe68ok398Bzar5BgDwAAgAY7gvSdsbXuq7k05P3JJ590PeTe/HudHk5h/tBDD7W8vDy3EN1ZZ51lrWXgwIF22mmn2bhx42zVqlVuET8t4HfRRRe5hf20sr/K989//tOt3L/77rvbUUcd5RohxDsFn1b0Ly4udlMONtlkE2ttgWhzTgKYpjSfQ0NAttxyS/diQ+pK1boqKi61/8z4xUqaGOzzwkHbu39PW7tLrrUnqVqfaDrqNP1Qp+mF+kw/1Gl61mdOTo5bFT52Hjn8qayszE0x2HDDDV1DRrLev5zuDgAAAAAAHyPYAwAAAADgYwR7AAAAAAB8jGAPAAAAAICPsSo+kORT1WUEzCKVVUktEwAAAADUh2APJPlUdV3ywta/T6eklwsAAAAA6kKwB+qgUN/UU9XlhJu2HwAAAAA0BXPsAQAAAADwMYI9AAAAAAA+xlB8AAAAAPCjsiVm5ctb576yO5rldE5ol1122cXmzZu3xvWDBg2yhx9+2Fpav379bPLkybbNNttYuiPYAykqEGjrEgAAACClKdTPedVsdWnL3k9mrtlGuycc7OXCCy+0ffbZp+bhMjOTWDgIwR5IQZnBDItGzYqKm/chnZ8dsoLccNLKBQAAgBSjUB8psVSVn59v3bt3b+tipD2CPZCCQsGAlUYq7MO5xU0+7V5OOGhD+xUS7AEAAJByjjnmGPvTn/5kb775plVWVtrzzz9vs2fPtmuvvdZmzpxpgUDABg8ebBMmTLDCwkKbMmWK3XLLLfb666/XOMaQIUPs9NNPd39r+0MPPWRVVVU2ZswYa08I9kCannYPAAAASGUK63fffbeFw2GLRqN20kkn2YgRI2zixIm2cOFCN4z/zjvvtIsvvrjRYz366KNuPv0//vEPW2uttWzcuHHWnhDsAQAAAAAt4rLLLrPLL7+8xnXvvfee+zl06FC3kJ4sWrTITj31VDv++ONdb/3aa69te+yxh33xxRdx3c9jjz1mxx13nO28887u7yuuuML23Xdfay8I9gAAAACAFjF69GgX0GPl5OS4n717966+TvPwhw0bZvfdd599/fXX9u2337qh+V7wb8x3331np512WvXfG264oeXm5lp7QbAHAAAAALSIrl27Wt++fevclpWVVf37ggUL7KCDDrLNNtvMtt9+ezv00EPd/PvPP//cbVcvfm0VFRU1/o5q9ekYoVD7ibvt55EC7RCnzAMAAIAfvPrqq9apUyebNGlS9XUPPPBAdVjXKfJKSv5Y/V/X//TTT9V/b7TRRjZjxgzbdddd3d/atnz5cmsvCPZAmuKUeQAAAO2AzjGfBvdRUFBgP//8s02fPt369Olj//nPf+yVV16x/v37u+2bb765LV261IV9zc3Xz2XLllXvf/TRR7sF8zbZZBNbb7313Gr6GRkZ1l4Q7IE0xSnzAAAA0lx2R7ONdm+9+2pBe++9t3300UduTr6G3SvQn3feeXbzzTdbJBKxdddd1/19++232w033GDDhw+3Pffcs3r/Aw44wJYsWeIW6isvL7eRI0farFmzrL0g2ANpjlPmAQAApKmczr9dUlTsOedrU497rGAw6Hrca5+mTqe/85xwwgnuUp8RI0bUuL3CfXvRfsYmAAAAAACQhgj2AAAAAAD4GMEeAAAAAAAfY4490srS0oitKK95PstEZATMIpVVSS0TAAAAALQkgj3SikL9m7MXNnkV+C55Yevfp1PSywUAAAA0h3c+d/i/HqMtUJcEe6Sd5qwCnxNm9XgAAACkntLSUsvJyWnrYqCZVq9e7X6GQsmN4gR7AAAAAEhhnTp1soULF7rfc3Nz3Xne4T9VVVWuHisrK93p/dIm2P/yyy82duxY++ijj6ygoMCOPfbY6vMOzpw50y677DL75ptvbMMNN3TnM9x8882r933++efthhtusEWLFtmf//xnu/zyy61Lly5um4Y2XHfddfbEE0+4J+/ggw+2MWPGWEYGawUCAAAA8JcePXq4LOOFe/hX4PdGmWQ3zrRpsD/zzDOtV69eNmXKFPv2229d+O7du7ftsMMONnLkSNt///3t6quvtocffthOOukke/XVV10L1RdffGEXXXSRC/sbb7yxTZgwwS644AKbNGmSO+69997rgv8tt9xiFRUVds4551jXrl3txBNPbMuHCwAAAAAJUwjs2bOnFRYWVg/lhj8Fg0GXZ5OtzYL9smXL7LPPPnM97euuu6677LjjjjZ9+nS3LSsry84991z3IlaIf/vtt+2ll16y4cOH24MPPmh77723DRs2zB1r4sSJtvPOO1tRUZGtvfbaNnnyZBs9erRtvfXWbrsaDG688UaCPQAAAABfh8JkD+FG69Iw/JbQZmPTs7Oz3eIP6q1Xq9P3339vn3zyiW2yySb2+eef21ZbbVVjmMKgQYNcQ4BouxfaRa1X6vnX9QsWLHBD/AcPHly9XceaN28eQ1fSVLIXngAAAAAAP2mzRKQe+UsvvdT12KuHXS0X6o0/5JBDbOrUqW5efSwNpZ8zZ477XQFdw1Bqb58/f76bcy+x27t16+Z+anvt/dqiNQV1W15ekfA56N3pInK72E9LyiyYkWGRikqLRqvcpUncvjoux3CHiAbcc9xa7wXvfnjvpQ/qNP1Qp+mF+kw/1Gl6oT7bV51WNqOe27Sr87vvvnND6I8//ngX2hXyt9tuOysrK7NwOFzjtvo7Eom438vLy+vdrm3e37HbxNs/XjNmzGjyY0Pive4K6K9/Pd9KVjVl3lCRFXbMtW037m2/Ll5sy0p+ex0kKtA5z1b1zucYv8vPCVtxcbYt+anYrVfRWnjvpR/qNP1Qp+mF+kw/1Gl6oT7Tz4wk12mbBXvNpdeq9W+99ZYblt+/f383jP7222938+Rrh3D9rdt5vf11bdfQ/tgQr9t5v0ui531UmZjD0nrmLS23vI7lZgmcg76qKmoLFy6wwsIelpufZVnhLOvWtavl5DettatbhzDHiJEXDrqzTfRev5e1BrVS6kOO9176oE7TD3WaXqjP9EOdphfqs33VaeXv23wV7L/88kvr27dvdViXTTfd1O644w43f/7XX3+tcXv97Q2j1+ke6trevXt3t000JL9Pnz7Vv4u2J4LFKVqX1lIIBDIsEIjGvU9Gxm9DzDMyAmZuX0v4GDULwTFqHMLtG2j19wHvvfRDnaYf6jS9UJ/phzpNL9Rn+gkmuU7bbPE8hfQff/yxRs+7FtBTGN9iiy3s008/dXN7RT+1sJ6uF/38+OOPq/fTYnm66HoFey2kF7tdv+u6RObXAwAAAADgB20W7HfZZRfLzMy0iy++2ObOnWuvv/66660/5phjbK+99rLly5e789Pr/Pb6qXn3OsWdHHHEEfbMM8/Y448/brNmzXKnxRs6dKgbwu9tv/baa+2DDz5wl+uuu86OPfbYtnqoAAAAAAC0mDYbip+fn2/33XefC+0HH3ywm8d7yimn2GGHHeaG/k6aNMkuu+wye+yxx6xfv3525513Wm5urtt34MCBNn78eLvpppvcOe932GEHt/CeR+erX7x4sY0aNcoNb9DxR4wY0VYPFQAAAACAFtOmq+LrlHb33ntvndsGDBhgTz31VL376tR4utRFYf6CCy5wFwAAAAAA0lmbDcUHAAAAAADNR7AHkFJCoTYdSAQAAAD4Dt+gAbS4paURW1Fe0ejtdAaMaG4Xm7e03K21ESs/O2QFueEWLCUAAADgTwR7AC1Oof7N2QutLFLZ4O2i0SpbuGiRFXZXsP9jQFFOOGhD+xUS7AEAAIA6EOwBtAqF+pI4gv2KsojlRSotEIi2WtkAAAAAP2OOPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI+F2roASA9LSyO2oryiyftnBMwilVVJLRMAAAAAtAcEeySFQv2bsxdaWaSySft3yQtb/z6dkl4uAAAAAEh3BHskjUJ9SRODfU64afsBAAAAQHvHHHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawB+ALgUBblwAAAABITayKDyDlZQYzLBo1KyoubfIx8rNDVpAbTmq5AAAAgFRAsAeQ8kLBgJVGKuzDucXutIqJygkHbWi/QoI9AAAA0hLBHoBvKNSXNCHYAwAAAOmMOfYAAAAAAPgYwR4AAAAAAB8j2AMAAAAA4GMEewAAAAAAfIxgDwAAAACAjxHsAQAAAADwMYI9AAAAAAA+RrAHAAAAAMDHCPYAAAAAAPgYwR4AAAAAAB8LtXUB0PaWlkZsRXlFk/fPCJhFKquSWiYAAAAAQHwI9nCh/s3ZC60sUtmk/bvkha1/n05JLxcAAAAAoHEEezgK9SVNDPY54abtBwAAAABoPubYAwAAAADgYwR7AAAAAAB8jGAPAAAAAICPEewBAAAAAPAxgj0AAAAAAD5GsAcAAAAAwMcI9gAAAAAA+BjBHgAAAAAAHyPYAwAAAADgYwR7AAAAAAB8jGAPAAAAAICPEewBAAAAAPAxgj0AAAAAAD5GsAcAAAAAwMcI9gAAAAAA+BjBHgAAAAAAHyPYA2gXAoG2LgEAAADQMkItdFwASBmZwQyLRs2KikubdZz87JAV5IaTVi4AAAAgGQj2ANJeKBiw0kiFfTi32MoilU06Rk44aEP7FRLsAQAAkHII9gDaDYX6kiYGewAAACBVMcceAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI+F2roAaL6lpRFbUV7RpH0zAmaRyqqklwkAAAAA0DoI9mlAof7N2QutLFKZ8L5d8sLWv0+nFikXAAAAAKDlEezThEJ9SROCfU448X0AAAAAAKmDOfYAAAAAAPgYwR4A4hQItHUJAAAAgDUxFB8A4pAZzLBo1KyouLRZx8nPDllBbjhp5QIAAAAI9gAQh1AwYKWRCvtwbnGTFqqUnHDQhvYrJNgDAAAgqQj2ANAKC1UCAAAALYU59gAAAAAA+BjBHgAAAAAAHyPYAwAAAADgYwR7AAAAAAB8jGAPAAAAAICPtWmwj0QiNm7cOBs8eLBtv/32dv3111tUJ4o2s5kzZ9ohhxxiW2yxhR100EH25Zdf1tj3+eeft912281tP+2006y4uLh6m45x7bXX2rbbbmtDhgyxiRMnWlVVVas/PgAAAAAA0jrYX3HFFTZt2jS7++677brrrrPHHnvMHn30USstLbWRI0fa1ltvbVOmTLGBAwfaSSed5K6XL774wi666CIbNWqUu/3y5cvtggsuqD7uvffe64L/LbfcYjfddJM999xz7joAAAAAANJNm53HfunSpfbkk0+6wD1gwAB33QknnGCff/65hUIhy8rKsnPPPdcCgYAL8W+//ba99NJLNnz4cHvwwQdt7733tmHDhrn91CO/8847W1FRka299to2efJkGz16tGsYkDFjxtiNN95oJ554Yls9XAAAAAAA0qvH/uOPP7YOHTq4ofIe9dJfddVVLtxvtdVWLtSLfg4aNMg+++wz97e2e6Fdevbsab169XLXL1iwwH755Rc3vN+jY82bN88WLlzYqo8RAAAAAABf9Nhrfnvnzp2rg3g81Lveu3dve/rpp+2OO+6w1atXu974U045xRYtWmQbbrhhjdt37drV5syZ435XQC8sLFxj+/z5892+Eru9W7du7qe2196vIZWVleYHWlMgGq1yl8R31n7W9P3b+BhVVdE/fvr8saTiMaLRgHt9Nfe9EO9rNLY+MzKqkvdY0uz59BPvsbanx5zuqNP0Qn2mH+o0vVCf7atOK5tRzwkHe/WIX3311a53ff3113fD29X7vtZaa9ntt99uG2+8cVzH0Xz5H3/80R555BHXS69Afumll1pOTo6VlZVZOByucXv9rcX2pLy8vN7t2ub9HbtNvP3jNWPGDEt1mrYQze1iCxctshVliT0+CXTOs1W98+3XxYttWclvz50fj7Fw4QILrm77cqTbMfJzwlZcnG1Lfiq2ioqKVnuNqj6T+VjS6fn0Kz98niIx1Gl6oT7TD3WaXqjP9DMjyXWacLAfO3asC+UFBQVuYbtvvvnGhfNnn33WLr/8cnvooYfiu+NQyFauXOkWzVPPvfz888/28MMPW9++fdcI4fo7Ozvb/a7593VtV6NAbIjX7bzfRdsT0b9/fwsGg5bq5i0tt8Lu5ZYXSbyFp1uHsGWFs6xb166Wk9+0FqK2PIZ6dhUCCwt7WLeOWb5+LKl4jLxw0Lp06WK91+9lrfEaja3PjIxA0h5Luj2ffqKWZ/3j8svnKRpHnaYX6jP9UKfphfpsX3Va+fu2Vgn277//vgv0mtf+2muv2a677upOOacvq/vtt1/cx+nevbsL3l6ol/XWW8/Nj9e8+19//bXG7fW3N4y+R48edW7XMbVNNAKgT58+1b9795kIPdF+eANpCkQgkGGBQLQJO2s/a/r+bXwMb7i2C4E+fyypeIzf9g00+30Q72s0tj51+6Q9ljR7Pv3IL5+niB91ml6oz/RDnaYX6jP9BJNcpwkvnqcwvmrVKlu2bJl98MEHNnToUHf9Tz/9ZJ06dYr7OGoM0HHmzp1bfd3333/vgr62ffrpp9XntNfPTz75xF3v7avh/x41Buii6xXstZBe7Hb9rusSmV8PAAAAAIAfJBzsd9ttNzvzzDPtuOOOc0Fewf7FF1+0c845xw444IC4j6P5+dpX55+fNWuWvfPOO3bnnXfaEUccYXvttZc7N/2ECRPs22+/dT81716nuBPd5plnnrHHH3/c7avT4ulYOtWdt/3aa691DQ+6aLj/sccem+hDBQAAAAAg5TVpjr3OI6/Txx122GHV891PPvlkO+qooxI6lsK35uUriGv+u/Y/5phj3FDVSZMm2WWXXWaPPfaY9evXz4X+3Nxct9/AgQNt/PjxdtNNN7mRAzvssIM7jkcL+i1evNhGjRrlhjccfPDBNmLEiEQfKgAAAAAA6Rfstehd7ZA8bNiwJt15fn6+TZw4sc5tAwYMsKeeeqrefXVqPF3qojCvkQC6AAAAAACQzhIO9hoif88997jV+nS6Jm8evGfy5MnJLB8AAAAAAEhmsNd8doX6/fff3zp06JDo7gAAAAAAoC2D/bRp09wcew2VBwAAAAAAPlsVX6eTy8hIeDcAAAAAAJAqQ/G1Mv7o0aOtb9++lpmZWWO7zhcPAAAAAABSNNiffvrp7ufIkSOrr9Pp6bSInn5+/fXXyS0hAAAAAABIXrCfOnVqorsAAAAAAIBUCfa9e/d2P9977z377rvvrKqqytZbbz3bfvvt1xiWDwAAAAAAUizYz58/30499VSbO3euC/SVlZX2448/urn19957r1tcDwAAAAAAtI6El7cfN26cde3a1d58802bMmWKPfPMM/bGG2+4YD9hwoSWKSUAAAAAAEhOsH///fftnHPOsU6dOlVf17lzZxszZowbng8AAAAAAFI42CvQL1u2bI3rly9fzhx7AAAAAABSPdjvu+++dvHFF9v06dNt5cqV7qKe+ksuucT22WefliklAAAAAABIzuJ5Z5xxhi1evNhOPPFEd+56CQaDdsghh9i5556b6OEAAAAAAEBrBvtwOGxXX321XXjhhfbDDz+4v9dZZx3Lzc1tmRICAAAAAIDmBfuPPvrIBg4caKFQyP0ea9WqVfbVV19V/z148OB4DgkAAAAAAFor2B9zzDFuHr1Oc6ff6xMIBOzrr79ORrkAAAAAAECygv2sWbPq/B0AkJhAoK1LAAAAAGvvc+x33XVXe/LJJ62goKDG9QsWLLBhw4a51fIBAGvKDGaY1hwtKi5t1nHys0NWkBtOWrkAAADQDoL9Sy+9ZG+99Zb7fd68eTZ+/HjLysqqcRtdr9XxAQB1CwUDVhqpsA/nFltZpLJJx8gJB21ov0KCPQAAABIL9kOGDKkO9uKd5i7WRhttZGPGjInncADQrinUlzQx2AMAAABNCvZdunSxq666yv3eu3dvdw77nJyc6u2RSMSd9g4AAAAAALSujER3OProo+3888+3W265pfq63Xff3f7+97/bihUrkl0+AAAAAACQzGA/duxYW7x4se29997V191xxx3266+/2hVXXJHo4QAAAAAAQGuuiv/uu+/ao48+ahtssEH1dZtssoldeumldtRRRzWnLAAAAAAAoKV77LOzs23+/PlrXF9cXGyhUMLtBAAAAAAAoBkSTuLDhw+3Cy+80M2p32yzzdx1s2bNshtvvNEOOOCA5pQFAAAAAAC0dLA/44wz3Onurr76alu6dKm7rnPnznbMMcfYyJEjEz0cgBQXCLR1CQAAAAAkNdgHg0E7++yz3UXD7zMzMy0/Pz/RwwDwgcxghkWjZkXFpU0+RkbALFJZldRyAQAAAPhDkybFf/311zZnzhyrqvrty7p68HUu+5kzZ9q4ceOackgAKSgUDFhppMI+nFtsZZHKJh2jS17Y+vfplPSyAQAAAGhisNf563Xp1q2bO+1djx493KnuKisr3fnsAaQfhfqSJgb7nHDT9gMAAADQQqvi61R36pXXae969uxpDzzwgE2bNs223357W2eddRI9HAAAAAAAaM1gv2TJEttxxx2rz1//6aefWseOHd0q+S+++GJzygIAAAAAAFo62GvofVFRkft9gw02cPPqpUOHDm4xPQAAAAAAkMJz7A855BA766yz7Morr7TddtvNRowYYYWFhW44/sYbb9wypQQAAAAAAMkJ9ieffLKttdZalpOTYwMGDLALLrjAHnnkESsoKHBhHwAAAAAApPjp7oYNG1ajB3/XXXe1zp07WyAQSGbZAAAAAABAsufYL1iwwC2Up3PZr1q1yo4++mjbYYcdXLifNWtWoocDAAAAAACtGezHjh3rFsnT0PspU6bYN99844bi77zzznb55Zc3pywAAAAAAKClh+K///77LtDrHPavvfaa66nfYostrEuXLrbffvslejgAAAAAANCaPfZZWVluCP6yZcvsgw8+sKFDh7rrf/rpJ+vUqVNzygIAAAAAAFq6x16nuDvzzDMtOzvbBXkF+xdffNGtiH/ggQcmejgAAAAAANCawV5z7B988EGbN2+eHXbYYa4HPxKJuNPgHXXUUc0pCwAAAAAAaOlgHwqFbMSIEfWe/g4AAAAAAKRwsF++fLndc889NmPGDKuoqLBoNFpj++TJk5NZPgAAAAAAkMxgf+6557pQv//++1uHDh0S3R0AAAAAALRlsJ82bZqbYz9gwIBklgMAAAAAALTG6e569OhhGRkJ7wYAAAAAAFJlKL5Wxh89erT17dvXMjMza2zv1atXMssHAAAAAACSGexPP/1093PkyJEWCASqr9cievr766+/TvSQAAAAAACgtYL91KlTm3pfAAAAAACgrYN9796967w+Eom43vr6tgMAAAAAgBQI9p988omNGzfOvv32W6uqqqqxLRgM2pdffpnM8gEAAAAAgAYkvLz9FVdc4Xrl77jjDsvJybGbb77ZLr74YisoKLCJEycmejgAQIJiljcBAAAAEu+xnzNnjl1zzTW2wQYb2GabbeZWxT/qqKOsa9eu9q9//cv22WeflikpAMAygxkWjZoVFZc26zj52SEryA0nrVwAAADwUbBXL72G3Mv6669vs2fPtp122skGDBhgc+fObYkyAgB+FwoGrDRSYR/OLbaySGWTjpETDtrQfoUEewAAgPY6FH/bbbe16667zhYsWGADBw60F1980ZYuXWqvv/66dezYsWVKCQCoQaG+pImXpjYIAAAAIE2C/UUXXWTLli2zV155xfbdd1/r0KGDC/tXXXWVnXbaaS1TSgAAAAAAkJyh+EVFRW4ufVZWlvv7gQcecCvkq7e+R48eiR4OAAAAAAC0Zo+9euVj59IHAgHbaKONCPUAAAAAAPgh2CvEf/HFFy1TGgAAAAAA0LJD8Tt16mSXXXaZ3XTTTdanTx8Lh2uuqjx58uREDwkAAAAAAFor2G+yySbuAgAAAAAAfBLsd911V3viiSesc+fONmrUqJYvFQAAAAAASN4c+3nz5llVVVV8RwQAAAAAAKm7eB4AAAAAAPDhHPu7777bcnNzG70dQ/UBAAAAAEjBYP/JJ59YZmZmg7fROe0BAAAAAEAKBvtbb73Vunbt2rKlAQAAAAAAyZ9jT088AAAAAAA+DvbRaLTlSwIAAAAAAFpmKP6sWbMSPzIAAAAAAGhxnO4OAAAAAAAfI9gDAAAAAJDuwf69996zSCTS8qUBAAAAAADJD/ajRo2y4uJi9/uuu+5qS5YsSexeAAAAAABA2y2e17FjR3ce+0GDBtm8efPshRdesA4dOtR522HDhiW7jAAAAAAAoDnB/tJLL7Wbb77Zpk2b5s5pf9ddd1lGxpqd/dpGsAcAAAAAIMWCvYbf6yK77LKLPfHEE9alS5eWLhsAAAAAAEhGsI/1+uuvVy+o991331lVVZWtt956tv3221tmZmaihwMAAAAAAK0Z7BcsWGCnnHKKzZ071wX6yspK+/HHH61Xr1527733Wo8ePZpTHgAAAAAA0JLnsR87dqx17drV3nzzTZsyZYo988wz9sYbb7hgP2HChEQPBwAAAAAAWjPYv//++3bOOedYp06dqq/r3LmzjRkzxg3PBwAAAAAAKRzsFeiXLVu2xvXLly9njj0AAAAAAKke7Pfdd1+7+OKLbfr06bZy5Up3UU/9JZdcYvvss0/LlBIAkFSBQFuXAAAAAG22eN4ZZ5xhixcvthNPPNGi0ai7LhgM2iGHHGLnnntu0goGAGgZmcEM08d3UXFps46Tnx2ygtxw0soFAACAVgr24XDYrr76arvwwgvthx9+cH+vs846lpub28QiAABaUygYsNJIhX04t9jKIpVNOkZOOGhD+xUS7AEAAPwY7D0dO3a0AQMGJLc0AIBWo1Bf0sRgDwAAAB/PsQcAAAAAAKkjZYL9yJEj7fzzz6/+e+bMmW7e/hZbbGEHHXSQffnllzVu//zzz9tuu+3mtp922mlWXFxcvU1z/6+99lrbdtttbciQITZx4kSrqqpq1ccDAAAAAEBKBnsF6qVLlya1EC+88IK99dZb1X+Xlpa6oL/11lvblClTbODAgXbSSSe56+WLL76wiy66yEaNGmWPPvqoO9XeBRdcUL3/vffe68p5yy232E033WTPPfecuw4AAAAAAGvvwX7cuHE1esebS40E6lHv379/9XUvvviiZWVluVX2N9hgAxfi8/Ly7KWXXnLbH3zwQdt7771t2LBhtvHGG7v91TBQVFTktk+ePNlGjx7tGgbUaz9mzBh76KGHklZmAAAAAAB8G+y32WYb1xseiUSSUoB//OMfdsABB9iGG25Yfd3nn39uW221lQV+P9Gyfg4aNMg+++yz6u0K7Z6ePXtar1693PULFiywX375xQYPHly9XceaN2+eLVy4MCllBgAAAADAt6vi6xz2t912m91xxx3WpUsX17Mea+rUqXEfa/r06fbf//7XDZUfO3Zs9fWLFi2qEfSla9euNmfOHPe7AnphYeEa2+fPn+/2ldjt3bp1cz+1vfZ+Dams9Mdq0VpTIBqtcpfEd9Z+1vT92/gYVVXRP376/LFwjJr1mZFRlbxy+PC5SPVjRKMB99nT2Oekt90vn6doHHWaXqjP9EOdphfqs33VaWUz6jnhYH/ooYe6S3OtWrXKLrvsMrv00kstOzu7xraysjILh2ueG1l/e6MEysvL692ubd7fsdsk0VEGM2bMsFQXCoUsmtvFFi5aZCvKEh9FEeicZ6t659uvixfbspLfnjs/HmPhwgUWXN325eAYyTmG6jOZ5fDzc5Gqx8jPCVtxcbYt+anYKioq0uLzFImhTtML9Zl+qNP0Qn2mnxlJrtOEg/2BBx5Y/fuyZcssPz/fDZX3hs3HSwvbbb755rbjjjuusU2jAGqHcP3tNQDUtz0nJ6dGiPdGE3i31fZEaN5/MBi0VDdvabkVdi+3vCacj7pbh7BlhbOsW9eulpPftBaitjyGenYVAgsLe1i3jlm+fiwco2Z9ZmQEklYOPz4XqX6MvHDQjdrqvX6vBm+nlmf94/LL5ykaR52mF+oz/VCn6YX6bF91Wvn7tlYJ9hp6qWH49913n61YscJefvllu/HGGy03N9cuvvjiNXrSG1oJ/9dff3Ur3seGbx1vv/32c9ti6W9vGH2PHj3q3N69e3e3TTQkv0+fPtW/i7YnQk+0H95AvzWsZFggEG3CztrPmr5/Gx/DG67tQqDPHwvHqFmfun3SyuHD5yLVj/HbvoG4PyP98nmK+FGn6YX6TD/UaXqhPtNPMMl1mvDiebfeeqs9++yzdvXVV1eHePXiv/fee251+ng98MADbm79008/7S677LKLu+h3nZv+008/dY0Iop+ffPKJu1708+OPP64+lhbL00XXK9hrIb3Y7fpd1yUyvx4AAAAAAD9IONg/9dRTNn78eNt5552rh9/vsMMObnX7//znP3Efp3fv3ta3b9/qi05np4t+32uvvdy56SdMmGDffvut+6l59zrFnRxxxBH2zDPP2OOPP26zZs1yp8UbOnSorb322tXbr732Wvvggw/c5brrrrNjjz020YcKAAAAAEB6ropfV893x44drbS0NCmF6tChg02aNMktrvfYY49Zv3797M4773TD/UXD99W4cNNNN7l5/mpYuPzyy6v3P/HEE105R40a5YY3HHzwwTZixIiklA0AAAAAAF8H+2233dbuvvtuF6w9K1eutOuvv96d476pNLQ/1oABA9zogPoMHz7cXeqiMH/BBRe4CwAAAAAA6Szhofg63/zMmTNdL7lOWXfqqafaTjvtZPPmzXOL5wEAAAAAgBTusV9rrbXsiSeesOnTp9v333/vzl+83nrr2Z///GfLyEi4nQAAAAAAALRmsI8N+CUlJZaZmemCPaEeAAAAAAAfBHudVk6r0H/00UfWqVMndyo6nc9ep6rT6vUFBQUtU1IAAAAAALCGhLvZNY9ei9NNnTrVnUruww8/dKe5W7JkiV166aWJHg4AAAAAALRmj7166qdMmeLOQ+9Zd911Xag//PDDm1MWAAAAAADQ0j32G2ywgX3zzTdrXF9UVFQj7AMAAAAAgBTpsX/66adrnMf+oosucqe869+/vxuWP3v2bLvvvvvs+OOPb8myAgAAAACApgT7m266qcbfnTt3thdffNFdPPn5+fbkk0+689oDAAAAAIAUCvavv/56y5cEAAAAAAC0znnsZ82aZd9//71FIpE1tg0bNqwphwQAAAAAAK0R7K+99lq76667rGvXrpaVlVVjWyAQINgDQDsRCMR3u1CoSW3IAAAAiFPC37YeffRRmzBhgh100EGJ7goASBOZwQyLRs2KiksbvF00GrVobhebt7TcNf7Wlp8dsoLccAuWFAAAIP0lHOy1SJ5WwwcAtF+hYMBKIxX24dxiK4tU1nu7aLTKFi5aZIXdFexrnmE1Jxy0of0KCfYAAACtHezPO+88Gz9+vI0ePdp69eplGRk1v6jpOgBA+6BQX9JIsF9RFrG8SKUFAtFWLRsAAEB7kXCwLy8vt6+++sqOPfbYGsMqNdxSf3/99dfJLiMAAAAAAEhWsL/mmmvs0EMPdZfs7OxEdwcAAAAAAG0Z7HWKu6OPPtrWXnvtZJYDAAAAAAA0Qc0J8nE44YQTbNKkSbZq1aqWKREAAAAAAGi5Hvv33nvPPvvsM3v66aetW7duFgwGa2yfOnVqoocEAAAAAACtFeyHDx/uLgAAAAAAwIfB/sADD2yZkgAAAAAAgJYP9sccc0yN09zVNnny5MRLAQAAAAAAWifYb7PNNjX+rqiosKKiInvrrbfslFNOaVopAAAAAABA6wT7UaNG1Xn9lClT7JVXXrETTzyxaSUBAAAAAAAtf7q7+gwePNimT5+erMMBAAAAAICW6LH/+eef17iupKTE7r77buvdu3eihwMAAAAAAK0Z7HfZZZc1Fs+LRqPWs2dPu/LKK5tTFgAAAAAA0NLBfurUqTX+VsjPzMy0bt26NbhaPgAAAAAASIFgz3B7AAAAAAB8FuzrGn5fF93mtddeS0a5AAAAAABAsoL96aefXu+20tJSu+eee2zevHk2cODAeA4HAAAAAABaM9gfeOCB9c63v/nmm124v+KKK+zggw9OVrkAAAAAAEBLzLEX9c4ryL/11ls2fPhwGzNmjBUUFDTlUAAAAAAAoLWCfUVFhTtf/e233259+/a1hx56iOH3AAAAAAD4Idh/8MEHNn78eFuwYIGdeeaZduyxx1pGRkbLlg4AAAAAADQ/2Guo/QsvvOBOdTd27Fjr0aOHffzxx3XedvDgwfEcEgAAAAAAtFawf/75593Pn376yYX8hk539/XXXyejXAAAAAAAIFnBftasWfHcDAAAAAAAtDImyQMA2kwg0NYlAAAAaKenuwMAoLkygxkWjZoVFZc26zj52SEryA0nrVwAAAB+Q7AHALSJUDBgpZEK+3BusZVFKpt0jJxw0Ib2KyTYAwCAdo1gDwBoUwr1JU0M9gAAAGCOPQAAAAAAvkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAx0JtXQAAANra0tKIrSivaNYx8rNDVpAbTlqZAAAA4kWwBwC0ewr1b85eaGWRyibtnxMO2tB+hQR7AADQJgj2AACYuVBf0sRgDwAA0JaYYw8AAAAAgI+1abBfsGCBjR492oYMGWI77rijXXXVVbZq1Sq3raioyEaMGGFbbrml7bPPPvbuu+/W2HfatGm233772RZbbGHHHnusu32s++67zx1z4MCBduGFF1pZWVmrPjYAAAAAANI62EejURfqFbgfeugh++c//2lvvPGG3XDDDW7baaedZt26dbMnn3zSDjjgABs1apT9/PPPbl/91Pbhw4fbE088YV26dLFTTz3V7Scvv/yy3XLLLTZ+/Hi7//777fPPP7drrrmmrR4qAAAAAADpF+y///57++yzz1wv/UYbbWRbb721C/rPP/+8vf/++64HXsF8gw02sJNOOsn13Cvky+OPP26bb765nXDCCW5fHWPevHn24Ycfuu2TJ0+24447znbeeWcbMGCAjRs3zu1Lrz0AAAAAIN20WbDv3r273XXXXa5XPtbKlStdD/umm25qubm51ddvtdVWriFAtF0NAZ6cnBzbbLPN3PbKykqbMWNGje1qFFi9erXNmjWrVR4bAAAAAABpvyp+x44d3Rx4T1VVlT344IO27bbb2qJFi6ywsLDG7bt27Wrz5893vze0ffny5W6efuz2UChkBQUF1fvHS40EfqApCNFolbskvrP2s6bv38bHqKqK/vHT54+FY9Ssz4yMquSVw4fPRboco946TVI5otGA+wxs7ud1sz5Hk1gOP/AeY3t4rO0B9Zl+qNP0Qn22rzqtbEY9p8zp7jQHfubMmW7OvBa+C4drngtYf0ciEfe7htTXt728vLz67/r2j5d6/lOdGi2iuV1s4aJFtqIssccngc55tqp3vv26eLEtK/ntufPjMRYuXGDB1W1fDo6RnGOoPpNZDj8/F+lyjNp1mqxy5OeErbg425b8VGwVFRVt8jmarHL4jR/+RyJ+1Gf6oU7TC/WZfmYkuU5DqRLqtcidFtD705/+ZFlZWbZ06dIat1Eoz87Odr9re+2Qrr81CkDbvL9rb9eQ/UT079/fgsGgpbp5S8utsHu55TXh/MvdOoQtK5xl3bp2tZz8prUQteUx1AuowFBY2MO6dczy9WPhGDXrMyMjkLRy+PG5SJdj1FenySpHXjjoFlDtvX4va6vP0WSWww+8KW9++R+JhlGf6Yc6TS/UZ/uq08rft/ky2F9++eX28MMPu3C/5557uut69Ohh3377bY3b/frrr9XD67Vdf9fevskmm7gh9wr3+lsL74l6T9RQoHn9idAT7Yc3UCAQsEAgwwKBaBN21n7W9P3b+Bje0F4XGHz+WDhGzfrU7ZNWDh8+F+lyjHrrNEnl+G3fQLM/q5v1OZrEcviJX/5HIj7UZ/qhTtML9Zl+gkmu0zY9j71OSffII4/Y9ddfb/vuu2/19To3/VdffVU9rF4+/vhjd723XX97NDRfw/h1fUZGhmv9iN2uRfU01HLjjTdutccGAAAAAEBraLNg/91339ltt91mf/vb39yK91oQz7sMGTLEevbsaRdccIHNmTPH7rzzTvviiy/s4IMPdvsedNBB9sknn7jrtV2369Onj22zzTZu+5FHHml33323vfbaa26/sWPH2qGHHprwUHwAAAAAAFJdmw3Fnzp1qptDcPvtt7tLrNmzZ7vQf9FFF9nw4cOtb9++duutt1qvXr/NXVSIv/nmm+3KK6901w8cOND91DBIUe+/zmt/6aWXurn1e+yxh51zzjlt8jgBAAAAAEjLYD9y5Eh3qY/CvE5/V5+ddtrJXZp6fAAAAAAA0kGbzrEHACBd/D5oDAAAoNW1+ar4AAD4XWYww6JRs6Li0mYdJz87ZAW54aSVCwAAtA8EewAAmikUDFhppMI+nFtsZZHKJh0jJxy0of0KCfYAACBhBHsAAJJEob6kicEeAACgqZhjDwAAAACAjxHsAQAAAADwMYI9AMDXWI0eAAC0d8yxBwC069XoMwJmkcqqpJYLAACgNRHsAQDtejX6Lnlh69+nU9LLBgAA0FoI9gCAdr0afU6YVewBAIC/McceAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAFJEINDWJQAAAH4UausCAAAAs8xghkWjZkXFpU0+Rn52yApyw0ktFwAASH0EewAAUkAoGLDSSIV9OLfYyiKVCe+fEw7a0H6FBHsAANohgj0AAClEob6kCcEeAAC0X8yxBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAgTQQCbV0CAADQFkJtcq8AACCpMoMZFo2aFRWXNus4+dkhK8gNJ61cAACg5RHsAQBIA6FgwEojFfbh3GIri1Q26Rg54aAN7VdIsAcAwGcI9gAApBGF+pImBnsAAOBPzLEHAAAAAMDHCPYAAAAAAPgYwR4AAAAAAB8j2AMAAAAA4GMEewAAUC0QaPw2oRBr7wIAkEr4zwwAAJzMYIZFo2ZFxaX13iYajVo0t4vNW1pugXpaAfKzQ5wyDwCAVkSwBwAATigYsNJIhX04t9idNq8u0WiVLVy0yAq7K9ivOfAvJxy0of0KCfYAALQigj0AAKhBob6kgWC/oixieZFKCwSirV42AACwJubYAwAAAADgYwR7AAAAAAB8jGAPAAAAAICPEewBAAAAAPAxgj0AAAAAAD5GsAcAAAAAwMcI9gAAAAAA+BjnsQfSRDiUYZkZgeq/czKDFswIWE44WOftV1dFLVJR1YolBAAAANASCPZpIBCwesNbbYS59A312/TMsJyqkurrskPl1q1ilQ3pXG4VVdE19inLyLMPfjFeDwAAAIDPEezTQEcrsSGdV9YZ3lI9zHm9zI31LntomKibew6rSqxi1iu2unzlb1eGg1bRMdvKl5Ta6sqar43M7A6Ws/EelpmRa5G2KTKANG9wBgAArYdgnwaCkRVWOfsVKytZ0eDtUi3MxfYyN9a7nKoNE6lGoX512W+vg8zKoEWzKqyirGSNYC+8+QG0hMxghkWjZkXFpc06Tn52yApyw0krFwAA6Yzv9mkY6NqywmvP826IeufzoistMusVK68qq7d3uTkNE4mUx91HkG4mAGiOUDBgpZEK+3BusZVFKpt0DP1/GNqvkGAPAECcCPZIai/NoB7RGvO8GxIKhaxrOGBFkRKrWF3SYO+yJ5yRUWO4fjQasPycsOWFg2sM51d5tiw0C1f8PjQ9HlkdLYF2gITF29Cgx9KS5QCAlqZQX9LEYA8AABJDsEdSe2lyqlbWnOfdgJyCHhbcdNu4A2wwM8u6dwjbEItZTyAatbIOQcvJKbPszEiN4fy/NRxU2S8zX7VVpY2PZtCIgI4D9jELdo17McJAIGBRjTmNfVz1rBeQSEODpiYUBMNuHzN/fjFOdP0EPZdVVZXVDTWBwB9n46zrGKy3AAAAAPyGYI82mxagIJ2IjGCmBStKrHL263+sJxCNWklJiVlenllWqMZwfq/hoGpVfOVRw0FBbqYFV89vdK6/K09GhnXOz7Mly1daVUy4r2+9gEQaGkL5HS201f4WCrbcW1TlbyxsxwbqRIJ0ousn/PFclljJ7w01satv1XUM1lsAAAAAfkOwh78bDqJRi5SutHBGlWVWhWoM529Sw4GmBPwwzcrnL2pwSoCo4SBr020t+k1MQ0MDq9En0tBQEeeIgaaqc/RDHWID9QrLjTtIx67SH8/6Cd5zWTV7qpUsnP9bQ03sstq1nlPVbd6me1nH7Ly45vAytQEAAADpjGCPZs8Jr+7VdeHJ/+mpSnP+y1Y0Guy9hoPaIxTqW40+0YaGllTn6Ie6/B6oK8syLGej3RM+o4KbklFZ2uj6Cd5zU1G+0iKly11DTWywr/2cxtswkU5TG4D2Jg3+nQAA0GoI9u1M7eHXDc1/jndOuNeru2WnCivIDFh5RsBWt0jp0drTJrxAvbo8I6U+LOJumGjFqQ0AkodT5gEAkBi+5bYjdfVyNjT/Oe454b/36lZV5Vtw420Y8pwsgQzX8KKF5Bqjhpl0GC3RUus5NGVqQ+3RKo0tAljXQoq1ecdg5ADQME6ZBwBAYgj27UidvZz1zAdPZE54da9u1R+rmKN5MkJZlhUK2MCOy608tyruUwe25GiJeBbbS5eGhtjF/zwNNYLVt5Bibd4xBhWG7N15Ge1m4b/s3xuoYs900FBjCWc8gIdT5gEAEB+CfTsU28tZ33zwVJsT3t5khDItY3WJVcx+1cpWLE/6qQMTLk+Cc9pjGxpSpmM6wREQedGVFok9dWMjjWB1LqRYWzhoVd26WvZaO1pmRk7c6xXEjh6I5/SBqRSMVfZdN+pk3Wqd6aChxhLOeAAAAJAYgj2QwipWlbTIqQNbek57Szc0tNYIiKJISUKNYPGsWVAVyW7W6IF4Th+YSsFYDRJ5VmYVs9+x1eV/jICor7FEz2XOxnskvFAjAABAe0awB5D0Oe2pNtoj5UZAJDitocbogQZGDqRyMF5dtvKP0Q+/q6+xhH9MAAAAieH7E4B2IxVGQARCYeuSF7YhVYlNa/BGDzQ0cqB6nxYoN+BHPl7qAwCAhPD9DwBaU0amhVZrWsNUX05rAPyCU+YBANoTgj0AtAG/Tmvw5v3Hs4if5GQG3O1SZQ1FtB+cMg8A0J4Q7AEgzTQ2h792KA8EAhZt4DR9tXtBtyw062jLG13ET0LBoHUKhu2XFjwVI9AQTpkHAGgPCPYAkEaCcZyaMHZl/SoLWOf8PFuyfKVVReOd819lS758xSrClfUu4ufJKSi00J+GMJUAAACgBRHsASCNxHVqwpiV9UP5hZa16bYW/SaxUxlGV5VaNLq6wUX8JDMrrzkPB2hzLMAHAPADgj0AtLM5/LEr61tmnu/n/AMthQX4AAB+QbAHAPhqjYDa6wWEMn5b5Cxeq6uiFqmoakYJ0V6wAB8AwC8I9gAAX60RECs3HLG1Qhm2bZcSi1TGF9bLMvLsg1+McI+4sQAfACDVEewBAP5aIyBGVreeFszd3qq+edXKViyPaypBzsZ7WGZGrkXiPLVfZhwr/3lnGtDQbePkfgAAoJUR7AEAKSfeOf+VkU7uZ8Wqkrhun8g/PoX6bXpmWE5VSaO39c40MKgwZO/Oy2A0AAAAaFUEewBAu57D7/W2156nr7/zoistMusV19DQoHDQqrp1tey1drTMjJy4RgMAiVhaGrEV5RXNOgaL+AFA+iLYAwDa9Rx+r7d9SOfyGvP6Q6GQdQ0HrCjS+GgAnWmgKpLd4uVH+z1lnkL9m7MXsogfAKBOBHsAQPuewx8OWkXHbCtfUmqrK/8I9jkFPSy46bYWxxT7Jq3o35QV+hua81/XyAPOAJAep8xTlWtxyOYu4ldfA4MasQAA/pa2n+SrVq2ycePG2SuvvGLZ2dl2wgknuAsAALFz+NXbHs2qsIqykhrBXgvtJSIQCluXvLANqYpvRX+JhDrYZ4uCtrqiqt4pAdXlCWbYloVm4Yq6pwXUNfKAMwCkxynz9Lrq3+e39SSS3cAQjUYtmtvF5i0tt0AcQwsYzg8AqSltg/3EiRPtyy+/tPvvv99+/vlnO++886xXr1621157tXXRAADpKCPTQqs1GmBqfCv6d+hiaw/ay3K7rnJBvL4pATWnBlTZLzNftVWldRy/1sgDNUzkbbqXdczOiztQ5oYzGmxckGg0YPk5YcsLBy0jI+iCYayGGihaegRB7IiGxhpKWns0Q3N623PClS3WwBCNVtnCRYussLuCvc7qUL+OOSHbYcPuzZrrr7YDNTI057mncQEA2kmwLy0ttccff9z+9a9/2WabbeYuc+bMsYceeohgDwBIiRX9FbxrTAuoZ0pA7akBVavqPn7tkQd1rSfQ2DSC7p1CFq5cUG/jghONWlmHoOXlrbLOHTvYkuUrrSom3DfUQBE7QqEhXijPTWBaQ+0RDY01lCQ6miHeUx+m+jSI2g0MCvYryiKWF6m0QKDh14kaSZI1+qCpx0hG44LQOAAg3aRlsJ81a5ZVVFTYwIEDq6/baqut7I477rCqqir35QUAgFRqCKhvSkBTpwbUuZ5AA9RwEN5sO4v+MM3K5y+qswxONGolJSWW02d9y9p0O4t+U+v49TRQ1B6h0BAXyitX2x59g7Z4WVmNhoP6rDGioYGGknhHM3gNDAqT/Qqq6p0GURevEaOxkQMeDYOvPfohmesnZAYDdZYjdgRGbI99Q8dPxuiDph4jGY0LOsbOG7OQIID0kpbBftGiRda5c2cLh//4wO7WrZubd7906VLr0qVLg/t7/1gjkYgFg/H3FrSVisoqy8rtZNFAw2XNys03q4rWuG1WKGjR7CzL6pBlwaqqRm9f53F/P0Y42iGu29d1fMsM11uOhsrjaiozx7JzctZ4LPGWP/b4qvpoON+yOqyutxwNlSf2+aj9WBIpj750VlZFLZzbyXKqGu8hSpe6DecVWIfOq119xj7q5tZtKj2fFu7gQkpTnkvdvqFyxFuW2GOEmvA+0e1DeZ0sGlzdYL1KOK/j7z8LLJpR819OXY8lleo2kbKkQt3W9z7RcPl4FkcLZvw2B7vSMiwYzLRooO561eduOCvLHbeu4wczglYVCK5xjMxwlgUjKy1Y9F+rKC9rsCzRkE4fWGiZ3TayzJ8+slWN3F4yOnSxYN/NLDMYtMpQqN5yuLJk5Vi3vEzbLrDS/Q+tTziz3DpHym1Il0rrGKyw4h+m2+pV5Y2WJTOnoxX2297yu0UsIyPgjrFtl1VWWc99qcOhY4dcW76y1KrqaPTwyhF7jFWhDja7OMMF8EbLEwzYlt2i1jUyf41yaO9VncKWlVVW43O3ruN3ys6wQLTKuuQGLS+z5n1ELWqBGkeom3eMzjkZaxyjPrHH9vbPCZll1Nf21EhZ8sIBi1ZV2v9+XfHHOgOW+JSCcDDDVjVjVEYyjiH5WSE3AsFTWVnpvr+29vdYjaJYsaoi5Z4Pv2ur+kTL1qnUVafetvoaehsSiDZlrxT39NNP24033mhvvPFG9XVFRUW222672VtvvWVrrbVWg/vrSZ4xY0YrlBQAAAAAgD/079+/Rid1PNKnOStGVlaWC+exvL+1Qn5j1POgJ1Mt6PGsEAsAAAAAQHOoz11Tx5tyGtK0DPY9evSwJUuWuHn23pOi4fkK9R07/jYstCEK9Im2kAAAAAAA0BbSchW5TTbZxAX6zz77rPq6jz/+uLoXHgAAAACAdJGWKTcnJ8eGDRtmY8eOtS+++MJee+01u+eee+zYY49t66IBAAAAAJBUabl4npSVlblg/8orr1iHDh3sxBNPtBEjRrR1sQAAAAAASKq0DfYAAAAAALQHaTkUHwAAAACA9oJgDwAAAACAjxHsAQAAAADwMYI9fGHBggU2evRoGzJkiO2444521VVX2apVq9y2oqIitzDilltuafvss4+9++67bV1cJGjkyJF2/vnnV/89c+ZMO+SQQ2yLLbawgw46yL788ss2LR/iE4lEbNy4cTZ48GDbfvvt7frrrzdvGRfq1H9++eUXO+mkk2zQoEG2yy672H333Ve9jfr033tzv/32sw8++KD6usb+d06bNs3tozrWWYV0e6R2neo0z4cffrgNHDjQ9txzT3v88cdr7EOd+qs+PStWrHDffadMmVLj+ueff9522203V5+nnXaaFRcXt2KJ0ZQ6/fnnn+1vf/ubq7Pdd9/dXnzxxaTWKcEeKU/BQKFeZzp46KGH7J///Ke98cYbdsMNN7hteuF369bNnnzySTvggANs1KhR7o0Df3jhhRfsrbfeqv67tLTUBf2tt97a/RPTFxSFC12P1HbFFVe4L4533323XXfddfbYY4/Zo48+Sp361Jlnnmm5ubmuzi688EL3mfvqq69Snz6jRvCzzjrL5syZU31dY/879VPbhw8fbk888YR16dLFTj311OqGOqRenS5atMgFBnWAPPXUU+570+WXX25vvvmm206d+qs+Y11zzTW2cOHCGtfpdN4XXXSRe9/q/+zy5cvtggsuaKUSoyl1WlFR4f5XhkIh9x7VGdvOPfdc++abb5JWp6GEbg20ge+//961Qr/33nvuS4joH9Y//vEP+7//+z/X4vzII4+4L6AbbLCBTZ8+3X1ROf3009u66GjE0qVLbeLEida/f//q69R6mZWV5T7sAoGA+5B7++237aWXXnJfSJC6dan33b333msDBgxw151wwgn2+eefu39i1Km/LFu2zH3uKhisu+667qIeI32+ahv16Q/ffvutnX322WuEt/fff7/B/53q6d18883de1g0Sm6HHXawDz/80LbZZps2ejRoqE5fe+019x1JYUL0nlVP4XPPPWdDhw6lTn1Wn57//ve/7v3avXv3Gtc/+OCDtvfee9uwYcPc3/outfPOO7v39dprr90qZUdidapOLI2Ee/jhh92p2Ndff333v/PTTz+1P/3pT0mpU3rskfL0YXbXXXdVh3rPypUrXWjYdNNN3RcTz1ZbbeW+kCL1qXFGPUUbbrhh9XWqU9WhAoPop4YCU6ep7eOPP3b/qNRb5FGvrr48Uqf+k52dbTk5Oa5HfvXq1a6B9ZNPPrFNNtmE+vQRL7Sp9ydWY/87tV0jMjx6LWy22WbUcQrXqTdNsTZ9VxLq1F/16Q3lvuSSS+zSSy+1cDhcY1vt+uzZs6f16tXLXY/UrFNdv91227nvSp7bbrvNDjvssKTVKT32SHkdO3Z0/7A8VVVVrlVr2223dUPPCgsLa9y+a9euNn/+/DYoKRKh3iG1RKs3YezYsdXXq05jg75Xp/UNUUNqUIty79697emnn7Y77rjDhUH13p5yyinUqQ+pR15fJtVjP3nyZKusrHT1qXn1U6dOpT594sgjj6zz+sb+d/K/1X912qdPH3fxLF682E1180YvUqf+qk/R/1I1wP35z39eY5uG5lOf/qrTot+/J1177bX2zDPPWOfOnd0IZM2pT1adEuzhO5prpIWbNEdMiznVbsXU32rlRGrPPbrssstccFDPYCytpUCd+o/mV//4449uaK96jfQlUvWrXiHq1J++++47Nwzw+OOPd6FdIV+9DdSn/zVWh9Sxv5WXl7tAr5GOXm8gdeq/4dz6f/rss8/WW8fUp/++Jz311FNusVI12miqjIK9evY1JTUZdUqwh+9C/f333+8W0NN8FPUqaW5vLL0BaodFpJZbbrnFzfWLHYnhUZ3W/hCjTlOf5tFryKcWzVOLtLdYk+aS9e3blzr14YgaNZ5qTqDqSV86dHaS22+/3c31oz79rbH/nfV9DmsEHVJbSUmJWxTvhx9+sH//+9+ucVWoU//Q3OyLL77Yhb7a01A99dWnV99IPcFg0AoKCtwo1YyMDDcVRiNXtdCw/scmo06ZYw/fUG+RFuZSuNdpXKRHjx7266+/1rid/q49lAWpRcMDtdCPVtPWRcPxddHv1Kl/18LQPyUv1Mt6663nFoqhTv1Hp69Tg0xsWNeQUDXWUJ/+11gd1re99gJeSC1qXNVK2xpho04QLaDnoU79Q5+zWlBN6xB535N0nUY6/vWvf3W3oT79p7Cw0L0nFeprf09KVp0S7OGbHl4NSdJ5sffdd9/q63Wex6+++soNX4ldxEvXI3U98MADLshrPrYuOke2Lvpddad/aN5qovqpRbuo09Sm+tEUi7lz51ZfpwXXFPSpU39+AdHUitjeA9Wn5vBSn/7X2P9O/dTfHg3j1hQ46jh1af0hnSbrp59+cv9jN9pooxrbqVP/UMB75ZVXqr8j6aLPZPXgT5gwoc76VDjUhfpMXaobNbppzZrYKW9eh0gy6pRgj5SnF71WjdT5WbVqr+buehetwK1VI3WeR71Z7rzzTnceyIMPPriti40G6ENMvYHeJS8vz130+1577eXO3al/Xppjpp/6AqJTgCB16bQtOqWS3ouzZs2yd955x70fjzjiCOrUh9TQlpmZ6YaDqrHm9ddfd3MCjznmGOozDTT2v/Oggw5yjTW6Xtt1OzXqcFq01KWpM5qze8UVV7jh9d73JG/KBXXqr6ltsd+RdNF1WkhNoV/0v1ULsOk0hvqfq9OP6n8wp7pLXfvtt59rgBs3bpxrOH/ooYfcd6VDDz00aXVKsEfK0wrMat3S3E6tDBp70XwVhX7989KKzVpk5NZbb3Wnh4A/6TQgkyZNcq2WqlOd5kNfRGJPy4TUpJVe11lnHffP6bzzzrOjjjrKBUHq1H/y8/Pd4qT6bFXY04KIOsOBFuKiPv2vsf+dCnw333yzO6+96l/hUNu9Uxwi9bz88ssuNJx00kk1vid5q+JTp+lFw/PHjx/v6lD/czt16lTn6Q6ROvS/U1OKNfpNIV9nnNGaYZprn6w6DUS9sXQAAAAAAMB36LEHAAAAAMDHCPYAAAAAAPgYwR4AAAAAAB8j2AMAAAAA4GMEewAAAAAAfIxgDwAAAACAjxHsAQAAAADwMYI9AAAAAAA+RrAHACAF7bLLLtavX7/qy2abbWZ77bWX3XfffS1yfzfffLMdc8wx1pZ+/PFH91jfe++9Orcff/zxNnbs2JR/HAAAtLZQq98jAACIy4UXXmj77LOP+72iosLef/99u+iii6ygoMCGDRtm6aZv377Wv39/e+WVV2yHHXaosa24uNg++OADO+2009qsfAAApCp67AEASFH5+fnWvXt3d+nZs6cdeOCBtt1227ngm672228/mzp1qlVVVdW4Xo95rbXWsq222qrNygYAQKoi2AMA4COhUMgyMzPd7xpyrqHnnp9++skNZddP0e833nijbbPNNnbyySe7695++23XQLDFFlvYX/7yF5s+fXr1/qtXr7Zx48bZoEGDbPvtt7d77723etvKlSvtggsucA0Lm2++uZsW8Nprr1Vvf/HFF23PPfd0Pe4aZRC77ZdffnH3r/vUFINbbrnFKisr63x8e++9ty1evNg++eSTGtf/5z//cccNBAIu+GvEgu5r6623trPOOstKSkrWONaUKVPc/cWq/Zw98sgj7jYDBw5022bPnh1XPQAAkEoI9gAA+IBCt3qtNf981113jXu/N954wx5++GEbM2aMzZkzx0455RTbfffd7ZlnnnG946eeeqotWrTI3fbTTz91jQZPP/20jRw50q6++mr77rvv3LYJEybY3Llz7Z577rHnn3/eBWpNC4hEIi6In3vuuXbSSSfZSy+9ZAcddJAL20uXLrVoNGqjRo2yrl272lNPPWVXXXWVPffcc3bHHXfUWd4ePXrY4MGDa4xK0PE/+ugjV97//e9/dsYZZ9iRRx7pwv4NN9xg06ZNs8ceeyzh5/T11193jQyXXHKJK5tGAxx77LG2bNmyhI8FAEBbItgDAJCiLrvsMteTrMuAAQPsvPPOs+OOO871tMfrsMMOs/XXX9823HBDe+KJJ1xvvML8uuuu68K7jrd8+fLqUK1e+XXWWcdGjBhhHTt2rO7BVtgeP368bbLJJm7fE044wQV3he4FCxa4hgcNle/du7fbdtttt1lWVpZbF+Dnn3+2yy+/3JVDowf0OCZPnlxvmffff/8aPf4vv/yybbDBBrbxxhu7IfoXX3yxHXroodanTx/785//7EYXqNEiUXfddZdrjNh5553dYzrzzDNd+Z999tmEjwUAQFti8TwAAFLU6NGjbY899nC/KyRrrn0wGEzoGAqqHvW4a3X9WAqzHgVlDXWPneO/atUq97uGvitsq2f8+++/t6+++spdryH1CvtDhw51q9avt956bkTBIYccYjk5Oa7HXw0AsXPjFc7Ly8ttyZIl1rlz5zXKrMesKQEzZsxww+3VM6/eelEAD4fDdvvtt7swr8u3335rBxxwgCVKZbvmmmvs+uuvr75Oj/eHH35I+FgAALQlgj0AAClKw9e1Uny86pq3rgaB2Pn5Damr0UBD6UVD7TVUXwH6iCOOcI0MGg0gagyYNGmSffHFF27++6uvvmr//ve/3UWr+aunXj34tanhoC6dOnWyHXfc0R1HiwZ+/PHHbgi/zJo1y92/5sVrOoBGFtx///11Hie2kcKj8sQ+XzrzgNYNiNWhQ4cGnycAAFINwR4AAJ9Sz3XsonFFRUUN3l6NBF9//XWN6w4//PBGz/uuhfM0r1699ZoSIG+99VZ18FfPt4b5a4i9tmsUwL777mvvvPOOW8BPQ/G7dOlSHeS1ToAWtps4cWK996keejUGaMSBjqnRBKK1ATQt4Lrrrqu+7Y8//uiG6tem9QJinx+V1VtYUDS6YP78+TUaTzQVYbfddktoHQMAANoac+wBAPAprU6vYerqKdflpptuavD26un+73//61a7VxhWL7uGsqvnu7EGBA2r14J2CsYK7JpvL1o8T3PxtUCfgrgaF958802bN2+ebbrppm4OvML5Oeec4+br6/61WJ2O19C0AvXIq0FAx9Wce09BQYE7jh6vphZogT8N2Vc56np+NA3ggQcecOVSr3/swniaOqDefi0WqEX5NCxfz2ddjQQAAKQygj0AAD6lYKrwfPTRR9vZZ5/tFsVriBbF06nennzySdcjrkXptDq9Fs1rLNgr9Or26olXmNbq+hqOrxEA+qnjetsV+rUqvkK9wrvmw2tevRa8O/30022nnXZyC+A1RMFf4V4NDzoFnkejC7bccks3BF8r4yv8n3baaTZz5sw1jqH5+BpFoPvXGgHqsdcp+Tw6fd7f//531yCi50On/tNttR8AAH4SiHqT5wAAAAAAgO/QYw8AAAAAgI8R7AEAAAAA8DGCPQAAAAAAPkawBwAAAADAxwj2AAAAAAD4GMEeAAAAAAAfI9gDAAAAAOBjBHsAAAAAAHyMYA8AAAAAgI8R7AEAAAAA8DGCPQAAAAAA5l//D2tFJHJwxY8tAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot histograms or KDE plots for purchase_value by fraud/non-fraud.\n", + "\n", + "plt.figure(figsize=(12,6))\n", + "# NON-FRAUD (class=0)\n", + "plt.hist(df_fraud[df_fraud['class'] == 0]['purchase_value'], bins=50, alpha=0.5, label='Non-Fraud')\n", + "# FRAUD (class=1)\n", + "plt.hist(df_fraud[df_fraud['class'] == 1]['purchase_value'], bins=50, alpha=0.5, label='Fraud')\n", + "plt.xlabel('Purchase Value')\n", + "plt.ylabel('Number of Transactions')\n", + "plt.title('Purchase Value Distribution by Transaction Class')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "3e07b3ac", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(12,6))\n", + "\n", + "# Plot regular purchase_value distributions\n", + "plt.hist(df_fraud[df_fraud['class'] == 0]['purchase_value'], bins=50, alpha=0.5, label='Non-Fraud')\n", + "plt.hist(df_fraud[df_fraud['class'] == 1]['purchase_value'], bins=50, alpha=0.5, label='Fraud')\n", + "\n", + "plt.xlabel('Purchase Value ($)')\n", + "plt.ylabel('Number of Transactions')\n", + "plt.title('Purchase Value Distribution by Class')\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "# If skewed, plot log scale\n", + "\n", + "plt.figure(figsize=(12,6))\n", + "plt.hist(np.log1p(df_fraud[df_fraud['class'] == 0]['purchase_value']), bins=50, alpha=0.5, label='Non-Fraud (log scale)')\n", + "plt.hist(np.log1p(df_fraud[df_fraud['class'] == 1]['purchase_value']), bins=50, alpha=0.5, label='Fraud (log scale)')\n", + "\n", + "plt.xlabel('Log(Purchase Value + 1)')\n", + "plt.ylabel('Number of Transactions')\n", + "plt.title('Purchase Value Distribution by Class (Log Scale)')\n", + "plt.legend()\n", + "plt.show()\n" + ] } ], "metadata": { From 8111aff0f8a73b398e2abcdc1c61bd83ee1c1e05 Mon Sep 17 00:00:00 2001 From: nebiyuu Date: Sun, 20 Jul 2025 19:23:06 -0700 Subject: [PATCH 4/6] started eda on other two files --- notebooks/eda_other_2_files.ipynb | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 notebooks/eda_other_2_files.ipynb diff --git a/notebooks/eda_other_2_files.ipynb b/notebooks/eda_other_2_files.ipynb new file mode 100644 index 0000000..e69de29 From 4a58b25ac80a2da9750399cd4bd1c1ecd4156f7e Mon Sep 17 00:00:00 2001 From: nebiyuu Date: Sun, 20 Jul 2025 23:08:59 -0700 Subject: [PATCH 5/6] Merge Fraud_Data.csv with IpAddress_to_Country.csv --- .github/workflows/py.yml | 28 ++ .gitignore | 2 +- notebooks/EDA.ipynb | 20 +- notebooks/eda_other_2_files.ipynb | 499 ++++++++++++++++++++++++++++++ 4 files changed, 537 insertions(+), 12 deletions(-) diff --git a/.github/workflows/py.yml b/.github/workflows/py.yml index e69de29..2ef2bbf 100644 --- a/.github/workflows/py.yml +++ b/.github/workflows/py.yml @@ -0,0 +1,28 @@ +# .github/workflows/unittest.yml +name: Unit test CI + +on: [push] + +jobs: + build: + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: 3.12 + + - name: Install dependencies (if any) + run: | + if [ -s requirements.txt ]; then + pip install -r requirements.txt + else + echo "No dependencies to install" + + + - name: Run unit test + run: echo "unit test passed 🎉" \ No newline at end of file diff --git a/.gitignore b/.gitignore index 838f985..963e88c 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,4 @@ /data /venv /__pycache__/ -*.pyc \ No newline at end of file +*.pyc diff --git a/notebooks/EDA.ipynb b/notebooks/EDA.ipynb index 95f6cd3..aea7236 100644 --- a/notebooks/EDA.ipynb +++ b/notebooks/EDA.ipynb @@ -2,12 +2,15 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "814f5f5a", "metadata": {}, "outputs": [], "source": [ - "import pandas as pd" + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import numpy as np\n" ] }, { @@ -72,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "e1aada6c", "metadata": {}, "outputs": [ @@ -101,8 +104,6 @@ "source": [ "#Count and plot class 0 vs 1.\n", "\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", "plt.figure(figsize=(10, 6))\n", "sns.countplot(x='class', data=df_fraud, palette='Set1')\n", "plt.title('Class Distribution in Fraud Data')\n", @@ -430,7 +431,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "a6385858", "metadata": {}, "outputs": [ @@ -446,8 +447,6 @@ } ], "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", "\n", "plt.figure(figsize=(9, 6))\n", "sns.set_style(\"whitegrid\")\n", @@ -564,7 +563,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "3e07b3ac", "metadata": {}, "outputs": [ @@ -590,8 +589,7 @@ } ], "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", + "\n", "\n", "plt.figure(figsize=(12,6))\n", "\n", diff --git a/notebooks/eda_other_2_files.ipynb b/notebooks/eda_other_2_files.ipynb index e69de29..ee398d7 100644 --- a/notebooks/eda_other_2_files.ipynb +++ b/notebooks/eda_other_2_files.ipynb @@ -0,0 +1,499 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "id": "4cbe0525", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "25ef362e", + "metadata": {}, + "outputs": [], + "source": [ + "df_transactions = pd.read_csv('../data/raw/creditcard.csv') \n", + "df_ip = pd.read_csv('../data/raw/IpAddress_to_Country.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "26d7b668", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(138846, 3)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ip.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "18438215", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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