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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1 - Model Loading and Initial Analysis"
]
},
{
"cell_type": "code",
"execution_count": 183,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n"
]
},
{
"cell_type": "code",
"execution_count": 184,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 10000 entries, 0 to 9999\n",
"Data columns (total 19 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 ID 10000 non-null int64 \n",
" 1 AGE 10000 non-null object \n",
" 2 GENDER 10000 non-null object \n",
" 3 RACE 10000 non-null object \n",
" 4 DRIVING_EXPERIENCE 10000 non-null object \n",
" 5 EDUCATION 10000 non-null object \n",
" 6 INCOME 10000 non-null object \n",
" 7 CREDIT_SCORE 9018 non-null float64\n",
" 8 VEHICLE_OWNERSHIP 10000 non-null float64\n",
" 9 VEHICLE_YEAR 10000 non-null object \n",
" 10 MARRIED 10000 non-null float64\n",
" 11 CHILDREN 10000 non-null float64\n",
" 12 POSTAL_CODE 10000 non-null int64 \n",
" 13 ANNUAL_MILEAGE 9043 non-null float64\n",
" 14 VEHICLE_TYPE 10000 non-null object \n",
" 15 SPEEDING_VIOLATIONS 10000 non-null int64 \n",
" 16 DUIS 10000 non-null int64 \n",
" 17 PAST_ACCIDENTS 10000 non-null int64 \n",
" 18 OUTCOME 10000 non-null float64\n",
"dtypes: float64(6), int64(5), object(8)\n",
"memory usage: 1.4+ MB\n"
]
}
],
"source": [
"#read data\n",
"df = pd.read_csv(\"Car_Insurance_Claim.csv\") \n",
"#show info about dataset\n",
"df.info()\n"
]
},
{
"cell_type": "code",
"execution_count": 185,
"metadata": {},
"outputs": [
{
"data": {
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" <th>OUTCOME</th>\n",
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" <td>0.0</td>\n",
" <td>10238</td>\n",
" <td>16000.0</td>\n",
" <td>sedan</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>199901</td>\n",
" <td>16-25</td>\n",
" <td>female</td>\n",
" <td>majority</td>\n",
" <td>0-9y</td>\n",
" <td>high school</td>\n",
" <td>working class</td>\n",
" <td>0.493146</td>\n",
" <td>1.0</td>\n",
" <td>before 2015</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10238</td>\n",
" <td>11000.0</td>\n",
" <td>sedan</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0-9y</td>\n",
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" <td>0.206013</td>\n",
" <td>1.0</td>\n",
" <td>before 2015</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>32765</td>\n",
" <td>11000.0</td>\n",
" <td>sedan</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>731664</td>\n",
" <td>26-39</td>\n",
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" <td>10-19y</td>\n",
" <td>none</td>\n",
" <td>working class</td>\n",
" <td>0.388366</td>\n",
" <td>1.0</td>\n",
" <td>before 2015</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>32765</td>\n",
" <td>12000.0</td>\n",
" <td>sedan</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
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"</table>\n",
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"text/plain": [
" ID AGE GENDER RACE DRIVING_EXPERIENCE EDUCATION \\\n",
"0 569520 65+ female majority 0-9y high school \n",
"1 750365 16-25 male majority 0-9y none \n",
"2 199901 16-25 female majority 0-9y high school \n",
"3 478866 16-25 male majority 0-9y university \n",
"4 731664 26-39 male majority 10-19y none \n",
"\n",
" INCOME CREDIT_SCORE VEHICLE_OWNERSHIP VEHICLE_YEAR MARRIED \\\n",
"0 upper class 0.629027 1.0 after 2015 0.0 \n",
"1 poverty 0.357757 0.0 before 2015 0.0 \n",
"2 working class 0.493146 1.0 before 2015 0.0 \n",
"3 working class 0.206013 1.0 before 2015 0.0 \n",
"4 working class 0.388366 1.0 before 2015 0.0 \n",
"\n",
" CHILDREN POSTAL_CODE ANNUAL_MILEAGE VEHICLE_TYPE SPEEDING_VIOLATIONS \\\n",
"0 1.0 10238 12000.0 sedan 0 \n",
"1 0.0 10238 16000.0 sedan 0 \n",
"2 0.0 10238 11000.0 sedan 0 \n",
"3 1.0 32765 11000.0 sedan 0 \n",
"4 0.0 32765 12000.0 sedan 2 \n",
"\n",
" DUIS PAST_ACCIDENTS OUTCOME \n",
"0 0 0 0.0 \n",
"1 0 0 1.0 \n",
"2 0 0 0.0 \n",
"3 0 0 0.0 \n",
"4 0 1 1.0 "
]
},
"execution_count": 185,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#dataset showcase\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The goal of my machine learning algorithm is to predict if a car insurance will be claimed or not. For that inputs like ID, AGE, GENDER, RACE, DRIVING_EXPERIENCE, EDUCATION, INCOME, CREDIT_SCORE, VEHICLE_OWENERSHIP, VEICLE_YEAR, MARRIED, CHILDREN, POSTAL_CODE, ANNUAL_MILEAGE, VEHICLE TYPE, SPEEDING_VIOLATIONS, DUIS and PAST_ACCIDENTS will be accounted in order to calculate the output, OUTCOME."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can render this problem as being a classification problem because we are looking to categorize the data into two possible outcomes(discrete values): insurance claim or not, 0 or 1. "
]
},
{
"cell_type": "code",
"execution_count": 186,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"ID 10000\n",
"AGE 4\n",
"GENDER 2\n",
"RACE 2\n",
"DRIVING_EXPERIENCE 4\n",
"EDUCATION 3\n",
"INCOME 4\n",
"CREDIT_SCORE 9018\n",
"VEHICLE_OWNERSHIP 2\n",
"VEHICLE_YEAR 2\n",
"MARRIED 2\n",
"CHILDREN 2\n",
"POSTAL_CODE 4\n",
"ANNUAL_MILEAGE 21\n",
"VEHICLE_TYPE 2\n",
"SPEEDING_VIOLATIONS 21\n",
"DUIS 7\n",
"PAST_ACCIDENTS 15\n",
"OUTCOME 2\n",
"dtype: int64"
]
},
"execution_count": 186,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#check for unique values\n",
"df.nunique()\n"
]
},
{
"cell_type": "code",
"execution_count": 187,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"ID 0\n",
"AGE 0\n",
"GENDER 0\n",
"RACE 0\n",
"DRIVING_EXPERIENCE 0\n",
"EDUCATION 0\n",
"INCOME 0\n",
"CREDIT_SCORE 982\n",
"VEHICLE_OWNERSHIP 0\n",
"VEHICLE_YEAR 0\n",
"MARRIED 0\n",
"CHILDREN 0\n",
"POSTAL_CODE 0\n",
"ANNUAL_MILEAGE 957\n",
"VEHICLE_TYPE 0\n",
"SPEEDING_VIOLATIONS 0\n",
"DUIS 0\n",
"PAST_ACCIDENTS 0\n",
"OUTCOME 0\n",
"dtype: int64"
]
},
"execution_count": 187,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#check for null values\n",
"df.isnull().sum() \n"
]
},
{
"cell_type": "code",
"execution_count": 188,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 188,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#check for duplicates\n",
"df.duplicated().sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2 - Data Cleaning and Shaping"
]
},
{
"cell_type": "code",
"execution_count": 189,
"metadata": {},
"outputs": [
{
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" <td>high school</td>\n",
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" <td>0.493146</td>\n",
" <td>1.0</td>\n",
" <td>before 2015</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
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" <td>478866</td>\n",
" <td>16-25</td>\n",
" <td>male</td>\n",
" <td>majority</td>\n",
" <td>0-9y</td>\n",
" <td>university</td>\n",
" <td>working class</td>\n",
" <td>0.206013</td>\n",
" <td>1.0</td>\n",
" <td>before 2015</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>32765</td>\n",
" <td>11000.0</td>\n",
" <td>sedan</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>731664</td>\n",
" <td>26-39</td>\n",
" <td>male</td>\n",
" <td>majority</td>\n",
" <td>10-19y</td>\n",
" <td>none</td>\n",
" <td>working class</td>\n",
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" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
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"text/plain": [
" ID AGE GENDER RACE DRIVING_EXPERIENCE EDUCATION \\\n",
"0 569520 65+ female majority 0-9y high school \n",
"1 750365 16-25 male majority 0-9y none \n",
"2 199901 16-25 female majority 0-9y high school \n",
"3 478866 16-25 male majority 0-9y university \n",
"4 731664 26-39 male majority 10-19y none \n",
"\n",
" INCOME CREDIT_SCORE VEHICLE_OWNERSHIP VEHICLE_YEAR MARRIED \\\n",
"0 upper class 0.629027 1.0 after 2015 0.0 \n",
"1 poverty 0.357757 0.0 before 2015 0.0 \n",
"2 working class 0.493146 1.0 before 2015 0.0 \n",
"3 working class 0.206013 1.0 before 2015 0.0 \n",
"4 working class 0.388366 1.0 before 2015 0.0 \n",
"\n",
" CHILDREN POSTAL_CODE ANNUAL_MILEAGE VEHICLE_TYPE SPEEDING_VIOLATIONS \\\n",
"0 1.0 10238 12000.0 sedan 0 \n",
"1 0.0 10238 16000.0 sedan 0 \n",
"2 0.0 10238 11000.0 sedan 0 \n",
"3 1.0 32765 11000.0 sedan 0 \n",
"4 0.0 32765 12000.0 sedan 2 \n",
"\n",
" DUIS PAST_ACCIDENTS OUTCOME \n",
"0 0 0 0.0 \n",
"1 0 0 1.0 \n",
"2 0 0 0.0 \n",
"3 0 0 0.0 \n",
"4 0 1 1.0 "
]
},
"execution_count": 189,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 190,
"metadata": {},
"outputs": [],
"source": [
"#drop rows with null values\n",
"df1 = df.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 191,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"ID 0\n",
"AGE 0\n",
"GENDER 0\n",
"RACE 0\n",
"DRIVING_EXPERIENCE 0\n",
"EDUCATION 0\n",
"INCOME 0\n",
"CREDIT_SCORE 0\n",
"VEHICLE_OWNERSHIP 0\n",
"VEHICLE_YEAR 0\n",
"MARRIED 0\n",
"CHILDREN 0\n",
"POSTAL_CODE 0\n",
"ANNUAL_MILEAGE 0\n",
"VEHICLE_TYPE 0\n",
"SPEEDING_VIOLATIONS 0\n",
"DUIS 0\n",
"PAST_ACCIDENTS 0\n",
"OUTCOME 0\n",
"dtype: int64"
]
},
"execution_count": 191,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df1.isnull().sum() "
]
},
{
"cell_type": "code",
"execution_count": 192,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\ricar\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:1773: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._setitem_single_column(ilocs[0], value, pi)\n"
]
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" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>569520</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0.629027</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>10238</td>\n",
" <td>12000.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>750365</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.357757</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10238</td>\n",
" <td>16000.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>199901</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0.493146</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10238</td>\n",
" <td>11000.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>478866</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>0.206013</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>32765</td>\n",
" <td>11000.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>731664</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0.388366</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>32765</td>\n",
" <td>12000.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" ID AGE GENDER RACE DRIVING_EXPERIENCE EDUCATION INCOME \\\n",
"0 569520 3 0 0 0 0 2 \n",
"1 750365 0 1 0 0 1 1 \n",
"2 199901 0 0 0 0 0 3 \n",
"3 478866 0 1 0 0 2 3 \n",
"4 731664 1 1 0 1 1 3 \n",
"\n",
" CREDIT_SCORE VEHICLE_OWNERSHIP VEHICLE_YEAR MARRIED CHILDREN \\\n",
"0 0.629027 1.0 0 0.0 1.0 \n",
"1 0.357757 0.0 1 0.0 0.0 \n",
"2 0.493146 1.0 1 0.0 0.0 \n",
"3 0.206013 1.0 1 0.0 1.0 \n",
"4 0.388366 1.0 1 0.0 0.0 \n",
"\n",
" POSTAL_CODE ANNUAL_MILEAGE VEHICLE_TYPE SPEEDING_VIOLATIONS DUIS \\\n",
"0 10238 12000.0 0 0 0 \n",
"1 10238 16000.0 0 0 0 \n",
"2 10238 11000.0 0 0 0 \n",
"3 32765 11000.0 0 0 0 \n",
"4 32765 12000.0 0 2 0 \n",
"\n",
" PAST_ACCIDENTS OUTCOME \n",
"0 0 0.0 \n",
"1 0 1.0 \n",
"2 0 0.0 \n",
"3 0 0.0 \n",
"4 1 1.0 "
]
},
"execution_count": 192,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.preprocessing import LabelEncoder\n",
"\n",
"#encode targeted values into a value ranging between 0 and the number of classes\n",
"le = LabelEncoder()\n",
"df1.loc[:,(\"AGE\")] = le.fit_transform(df1[\"AGE\"])\n",
"df1.loc[:,(\"GENDER\")] = le.fit_transform(df1[\"GENDER\"])\n",
"df1.loc[:,(\"RACE\")] = le.fit_transform(df1[\"RACE\"])\n",
"df1.loc[:,(\"DRIVING_EXPERIENCE\")] = le.fit_transform(df1[\"DRIVING_EXPERIENCE\"])\n",
"df1.loc[:,(\"EDUCATION\")] = le.fit_transform(df1[\"EDUCATION\"])\n",
"df1.loc[:,(\"INCOME\")] = le.fit_transform(df1[\"INCOME\"])\n",
"df1.loc[:,(\"VEHICLE_YEAR\")] = le.fit_transform(df1[\"VEHICLE_YEAR\"])\n",
"df1.loc[:,(\"VEHICLE_TYPE\")] = le.fit_transform(df1[\"VEHICLE_TYPE\"])\n",
"df1.head()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3 - Data Visualization"
]
},
{
"cell_type": "code",
"execution_count": 193,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ID count was too much memory consuming\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CREDIT_SCORE count was too much memory consuming\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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b967Pf7wvO6+qu4CjkzwE+HiSo3bSPCNqtZP6jjtI1jA4Rcrhhx++a4OVJEnqzLivkLo9yY/a8vMkdyX50bgHqaofMjjFuQK4Ocmhbb+HAre0ZluBw4a6LQFubPUlI+qjjnNOVS2vquWLFi0ad3iSJEldGiuoVdWDqmr/tuwD/CHw7p31SbKozaSRZF/gqcC3gAuB1a3ZauCCtn4hsDLJ3kmOYHDTwGXtNOntSY5LEmDVUB9JkqR5a9xr1O6hqj6R5Mx7aXYosK5dp7YHsKGqPpVkI7AhyWnA9cDJbZ9XJtkAXAXcCZzRTp0CnM6/PJ7jYryRQJIkLQDjPvD2OUNf92DwXLWdPsesqr4B/NaI+m3ACdP0WQusHVHfBOzs+jZJkqR5Z9wZtWcOrd/J4EG1J834aCRJkvQr4971+cJJD0SSJEn3NO5dn0uSfDzJLUluTvKxJEvuvackSZLuq3FfIfU+BndlPpzBw2Y/2WqSJEmakHGD2qKqel9V3dmW8wAfVCZJkjRB4wa1W5M8P8mebXk+cNskByZJkrTQjRvUXgScAnwPuAn4I8AbDCRJkiZo3MdzvAFYXVU/AEhyIPBWBgFOkiRJEzDujNq/2R7SAKrq+4x4mK0kSZJmzrhBbY8kB2z/0mbU7tPrpyRJkjSeccPW24AvJ/kog1dHncKIVz1JkiRp5oz7ZoL1STYBTwECPKeqrproyCRJkha4sU9ftmBmOJMkSdpNxr1GTZIkSbuZQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlA+tnSHHvGL9bA9BWpA2v2XVbA9BkibGGTVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOjWxoJbksCSfT3J1kiuTvLTVD0zy2STfbp8HDPU5K8mWJNckOXGofkySK9q2dybJpMYtSZLUi0nOqN0J/EVVPQo4DjgjyZHAmcAlVbUMuKR9p21bCTwaWAGcnWTPtq/3AmuAZW1ZMcFxS5IkdWFiQa2qbqqqr7X124GrgcXAScC61mwd8Oy2fhJwflXdUVXXAluAY5McCuxfVRurqoD1Q30kSZLmrd1yjVqSpcBvAV8BDqmqm2AQ5oCDW7PFwA1D3ba22uK2PrUuSZI0r008qCXZD/gY8LKq+tHOmo6o1U7qo461JsmmJJu2bdu264OVJEnqyESDWpJfYxDSPlhV/7OVb26nM2mft7T6VuCwoe5LgBtbfcmI+g6q6pyqWl5VyxctWjRzP0SSJGkWTPKuzwD/A7i6qt4+tOlCYHVbXw1cMFRfmWTvJEcwuGngsnZ69PYkx7V9rhrqI0mSNG/tNcF9PxE4FbgiyeWt9mrgTcCGJKcB1wMnA1TVlUk2AFcxuGP0jKq6q/U7HTgP2Be4uC2SJEnz2sSCWlV9kdHXlwGcME2ftcDaEfVNwFEzNzpJkqT++WYCSZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkTk0sqCU5N8ktSb45VDswyWeTfLt9HjC07awkW5Jck+TEofoxSa5o296ZJJMasyRJUk8mOaN2HrBiSu1M4JKqWgZc0r6T5EhgJfDo1ufsJHu2Pu8F1gDL2jJ1n5IkSfPSxIJaVX0B+P6U8knAura+Dnj2UP38qrqjqq4FtgDHJjkU2L+qNlZVAeuH+kiSJM1ru/satUOq6iaA9nlwqy8Gbhhqt7XVFrf1qXVJkqR5r5ebCUZdd1Y7qY/eSbImyaYkm7Zt2zZjg5MkSZoNuzuo3dxOZ9I+b2n1rcBhQ+2WADe2+pIR9ZGq6pyqWl5VyxctWjSjA5ckSdrddndQuxBY3dZXAxcM1Vcm2TvJEQxuGrisnR69Pclx7W7PVUN9JEmS5rW9JrXjJB8GjgcOSrIVeC3wJmBDktOA64GTAarqyiQbgKuAO4EzququtqvTGdxBui9wcVskSZLmvYkFtap67jSbTpim/Vpg7Yj6JuCoGRyaJEnSnNDLzQSSJEmawqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1as4EtSQrklyTZEuSM2d7PJIkSZM2J4Jakj2B9wBPB44EnpvkyNkdlSRJ0mTNiaAGHAtsqarvVNUvgPOBk2Z5TJIkSRM1V4LaYuCGoe9bW02SJGne2mu2BzCmjKjVDo2SNcCa9vXHSa6Z6Kg0XxwE3Drbg9B9k7eunu0hSNPxb8tc9tpR0WOiHjGqOFeC2lbgsKHvS4AbpzaqqnOAc3bXoDQ/JNlUVctnexyS5hf/tmgmzJVTn18FliU5IsmvAyuBC2d5TJIkSRM1J2bUqurOJH8GfBrYEzi3qq6c5WFJkiRN1JwIagBVdRFw0WyPQ/OSp8slTYJ/W3S/pWqHa/IlSZLUgblyjZokSdKCY1DTguarySTNtCTnJrklyTdneyya+wxqWrB8NZmkCTkPWDHbg9D8YFDTQuarySTNuKr6AvD92R6H5geDmhYyX00mSeqaQU0L2VivJpMkabYY1LSQjfVqMkmSZotBTQuZryaTJHXNoKYFq6ruBLa/muxqYIOvJpN0fyX5MLAR+FdJtiY5bbbHpLnLNxNIkiR1yhk1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJPUrSSXJjlxSu1lSS5K8rMklw8tq9r265IcNNT++CSfausvSPLuoW2rknwzyZVJrkry8lY/L8kfTTnu0umOOWLcH0py+tD3307yjSR7tfFdMbSPdw612yvJrUneOOLf4ZokX0/y1SRH34d/Tklz0F6zPQBJ2okPM3hjxKeHaiuBVwCHV9XR93XHSZ4OvAx4WlXdmGQf4NR76fZPYx7zz4GNST4K3Aa8G/jTqrozCcCTq+rWEf2eBlwDnJLk1XXPB10+r6o2JXkh8Bbg340xDklznDNqknr2UeAZSfaGwawW8HAG72m9v84CXl5VNwJU1c+r6m9nYL9U1c3AW4E3A/8J+EZVfXGMrs8F3gFcDxw3TZuNwOKZGKek/jmjJqlbVXVbksuAFcAFDGbTPgIU8Mgklw81f3FV/e+2/vkkd7X1/YBvjdj9UcDmXRzSzo451X8HVgPHA8unbBse37qq+m9J9gVOAP4EeAiD0LZxxH5XAJ/YxXFLmqMMapJ6t/305/ag9qJW39lpyF+dWkxyPPDyGRrLuKc+qaq7k/wNsLyqbptufEOeAXy+qn6a5GPAXyb586raHug+mOSBwJ7A4+7Hb5A0h3jqU1LvPgGckORxwL5V9bUZ2u+VwDEztK/p3N2WcTwXeGqS6xjM9D0UePLQ9ucBRwAfAt4zg2OU1DGDmqSuVdWPgUuBcxnMrs2UNwJvTvIwgCR7J3nJDO5/bEn2B57E4AaJpVW1FDiDQXj7lar6JfAa4Lgkj9rtA5W02xnUJM0FHwYeC5w/VHvklEdl7FLIqqqLGMxM/UOSKxnMYg1fDvI3Sba2Zfu1YvfrmEM+P7SP9cBzgM9V1R1DbS4AnrX9Roqhcf8MeBszdzpXUsdyz7u/JUmS1Atn1CRJkjrlXZ+SdD8k+Qqw95TyqVV1xWyMR9L84qlPSZKkTnnqU5IkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlT/x89RxLdR1tWMQAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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mrVHPUfsxVXV1kgt20uxoYEU7T20/YFVVfS7J9cCqJGcDdwNntjHXJ1kF3AJsBc5th04BzuFHP89xLV5IIEmS9gGj/uDtrwy93I/B76pN+TtmVfVl4NmT1B8AnreDPhcDF09SXwtMdX6bJEnSrDPqitpLhp5vZfBDtadP+2wkSZL0Q6Ne9fnqcU9EkiRJP27Uqz7nJ7kqyeYk9yX5VJL5O+8pSZKkx2rUW0h9mMFVmU9h8GOzn201SZIkjcmoQW1uVX24qra2bTngD5VJkiSN0ahB7f4kr0wyp22vBB4Y58QkSZL2daMGtf8CvBz4F2AT8DLACwwkSZLGaNSf5/gDYGlVfQMgyeHAuxkEOEmSJI3BqCtqz9wW0gCq6utM8mO2kiRJmj6jBrX9khy27UVbUXtMt5+SJEnSaEYNW+8B/i7JJxncOurlTHKrJ0mSJE2fUe9MsDLJWuAXgAC/UlW3jHVmkiRJ+7iRD1+2YGY4kyRJ2kNGPUdNkiRJe5hBTZIkqVMGNUmSpE75ExvT5OTzVs70FKR90ro/PGumpyBJY+OKmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUqbEFtSTHJPm/SW5Nsj7J61r98CSfT3J7ezxsqM+FSTYkuS3JC4bqJye5qe27JEnGNW9JkqRejHNFbSvwO1X174BTgXOTHA9cAKypqoXAmvaatm8JcAKwGLgsyZw21uXAMmBh2xaPcd6SJEldGFtQq6pNVfWP7flDwK3APOB0YEVrtgI4oz0/Hbiyqh6pqjuADcApSY4GDqmq66uqgJVDfSRJkmatPXKOWpIFwLOBvweOqqpNMAhzwJGt2TzgnqFuG1ttXns+sS5JkjSrjT2oJXki8Cng9VX14FRNJ6nVFPXJ3mtZkrVJ1m7ZsmXXJytJktSRsQa1JAcwCGkfq6pPt/J97XAm7XFzq28EjhnqPh+4t9XnT1LfTlVdUVWLqmrR3Llzp++DSJIkzYBxXvUZ4E+BW6vqvUO7VgNL2/OlwGeG6kuSHJjkOAYXDdzQDo8+lOTUNuZZQ30kSZJmrf3HOPZzgF8HbkpyY6u9GXgnsCrJ2cDdwJkAVbU+ySrgFgZXjJ5bVY+2fucAy4GDgWvbJkmSNKuNLahV1ReZ/PwygOftoM/FwMWT1NcCJ07f7CRJkvrnnQkkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6NbagluRDSTYnuXmodniSzye5vT0eNrTvwiQbktyW5AVD9ZOT3NT2XZIk45qzJElST8a5orYcWDyhdgGwpqoWAmvaa5IcDywBTmh9Lksyp/W5HFgGLGzbxDElSZJmpbEFtaq6Dvj6hPLpwIr2fAVwxlD9yqp6pKruADYApyQ5Gjikqq6vqgJWDvWRJEma1fb0OWpHVdUmgPZ4ZKvPA+4Zarex1ea15xPrkiRJs14vFxNMdt5ZTVGffJBkWZK1SdZu2bJl2iYnSZI0E/Z0ULuvHc6kPW5u9Y3AMUPt5gP3tvr8SeqTqqorqmpRVS2aO3futE5ckiRpT9vTQW01sLQ9Xwp8Zqi+JMmBSY5jcNHADe3w6ENJTm1Xe5411EeSJGlW239cAyf5BHAacESSjcDbgXcCq5KcDdwNnAlQVeuTrAJuAbYC51bVo22ocxhcQXowcG3bJEmSZr2xBbWqesUOdj1vB+0vBi6epL4WOHEapyZJkrRX6OViAkmSJE1gUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjq11wS1JIuT3JZkQ5ILZno+kiRJ47ZXBLUkc4BLgRcCxwOvSHL8zM5KkiRpvPaKoAacAmyoqq9V1feAK4HTZ3hOkiRJY7W3BLV5wD1Drze2miRJ0qy1/0xPYESZpFbbNUqWAcvay4eT3DbWWWm2OAK4f6Ynoccm714601OQdsTvlr3Z2yeLHmP11MmKe0tQ2wgcM/R6PnDvxEZVdQVwxZ6alGaHJGuratFMz0PS7OJ3i6bD3nLo8x+AhUmOS/I4YAmweobnJEmSNFZ7xYpaVW1N8lrgL4A5wIeqav0MT0uSJGms9oqgBlBV1wDXzPQ8NCt5uFzSOPjdot2Wqu3OyZckSVIH9pZz1CRJkvY5BjXtM3Z2G7IMXNL2fznJz8zEPCXtPZJ8KMnmJDfvYL/fK9otBjXtE0a8DdkLgYVtWwZcvkcnKWlvtBxYPMV+v1e0Wwxq2leMchuy04GVNfAl4NAkR+/piUrae1TVdcDXp2ji94p2i0FN+4pRbkPmrcokTTe/V7RbDGraV4xyG7KRblUmSbvA7xXtFoOa9hWj3IZspFuVSdIu8HtFu8Wgpn3FKLchWw2c1a7SOhX4ZlVt2tMTlTSr+L2i3bLX3JlA2h07ug1Zkt9o+/+YwZ0vfgnYAHwbePVMzVfS3iHJJ4DTgCOSbATeDhwAfq9oenhnAkmSpE556FOSJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SbNKkicnuTLJV5PckuSaJE9PcvOEdhcl+d32fHmSl7XnX0iyaELb05J8M8k/JbktyXVJXjxhrH9OcmN7z1cM7Vue5I6278Ykf9fqr0rygyTPHGp7c5IFY/nDSNor+TtqkmaNJAGuAlZU1ZJWOwk4ahqG/9uqevHQmFcn+U5VrWn731dV706yEFiX5JNV9f2277yq+uQkY24Efg/41WmYn6RZyBU1SbPJc4Hvtx8aBaCqbuTHb4q929qY7wBeO8m+2xn8sOlhIwz1OeCEJM+YzvlJmj0MapJmkxOBdTvY91NDhx9vBH5jN9/rH4F/O7GY5GeA26tq81D5D4fe+2ND9R8A7wLevJtzkTRLeehT0r7iq1V10rYXSS7azfEy4fUbkrwG+Elg8YR9Ozr0CfBx4PeSHLeb85E0C7miJmk2WQ+cvIfe69nArUOv31dVz2BwvtnKJAeNMkhVbQXeA5w//VOUtLczqEmaTf4aOLCtbAGQ5GeBp07nm7QrNd8KXDpxX1V9GlgLLN2FIZcDzwfmTsf8JM0eBjVJs0ZVFfDLwC+2n+dYD1wE3LuLQ/15ko1t+9+t9vPbfp6DQUD77aErPid6B/DGJNu+Y4fPUbsxyeMmzPt7wCXAkbs4T0mzXAbfa5IkSeqNK2qSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqf+P6tuY2cvVrUjAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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AxypJktSVic6oVdX29rkTeDdwDnBfu5xJ+9zZmm8DTh7qvgjY3uqLRtRHne+aqpqqqqkFCxYczK8iSZJ0yE0sqCV5apKn71kHfhj4OLAOWNGarQBuaOvrgGVJjkhyGoOHBja2y6MPJTm3Pe25fKiPJEnSnDXJS58nAO9uv6QxH3hnVf15kr8D1ia5GLgHuBCgqrYkWQvcDjwKXFpVu9uxLgGuBY4CbmqLJEnSnDaxoFZVnwKeO6L+AHDePvqsAlaNqG8CzjzYY5QkSeqZbyaQJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpU2MFtSTrx6lJkiTp4Jm/v51JjgSeAhyX5BggbdfRwEkTHpskSdJhbb9BDfhp4DIGoexWvhbUHgR+Z3LDkiRJ0n6DWlX9NvDbSV5dVW8+RGOSJEkSjz2jBkBVvTnJdwOnDvepqjUTGpckSdJhb6ygluTtwLOB24DdrVyAQU2SJGlCxgpqwBRwelXVJAcjSZKkrxn3d9Q+DjxrkgORJEnS1xt3Ru044PYkG4FH9hSr6iUTGZUkSZLGDmq/PMlBSJIkaW/jPvX5V5MeiCRJkr7euK+QeijJg2355yS7kzw4Zt95Sf4+yXva9rFJbk5yV/s8ZqjtFUm2JrkzyflD9bOTbG77rkySUeeSJEmaS8YKalX19Ko6ui1HAj8OvGXMc/w8cMfQ9uXA+qpaDKxv2yQ5HVgGnAEsAa5KMq/1uRpYCSxuy5Ixzy1JkjRrjfvU59epqj8FfvCx2iVZBPxr4PeHykuB1W19NXDBUP26qnqkqu4GtgLnJDkROLqqNrSfB1kz1EeSJGnOGvcHb39saPNJDH5XbZzfVPufwOuApw/VTqiqHQBVtSPJ8a2+EPjboXbbWu0rbX16fdQ4VzKYeeOUU04ZY3iSJEn9Gvepzx8dWn8U+DSDGbB9SvJiYGdV3Zrk+WOcY9R9Z7Wf+t7FqmuAawCmpqb8cV5JkjSrjfvU5ysfx7G/B3hJkh8BjgSOTvKHwH1JTmyzaScCO1v7bcDJQ/0XAdtbfdGIuiRJ0pw27lOfi5K8O8nOJPcl+eN2/9k+VdUVVbWoqk5l8JDAX1bVy4F1wIrWbAVwQ1tfByxLckSS0xg8NLCxXSZ9KMm57WnP5UN9JEmS5qxxHyZ4G4MgdRKD+8P+rNUejzcAP5TkLuCH2jZVtQVYC9wO/DlwaVXteQH8JQweSNgKfBK46XGeW5IkadYY9x61BVU1HMyuTXLZuCepqg8AH2jrDwDn7aPdKmDViPom4MxxzydJkjQXjDujdn+Sl7cfr52X5OXAA5McmCRJ0uFu3KD2KuClwGeBHcBPAI/nAQNJkiSNadxLn78GrKiqf4TBa6CANzEIcJIkSZqAcWfU/tWekAZQVZ8DnjeZIUmSJAnGD2pPmvby9GMZfzZOkiRJj8O4Yes3gQ8nuZ7BWwFeyoinMyVJknTwjPtmgjVJNjF4EXuAH6uq2yc6MkmSpMPc2JcvWzAznEmSJB0i496jJkmSpEPMoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdmlhQS3Jkko1JPppkS5JfafVjk9yc5K72ecxQnyuSbE1yZ5Lzh+pnJ9nc9l2ZJJMatyRJUi8mOaP2CPCDVfVc4CxgSZJzgcuB9VW1GFjftklyOrAMOANYAlyVZF471tXASmBxW5ZMcNySJEldmFhQq4GH2+Y3tKWApcDqVl8NXNDWlwLXVdUjVXU3sBU4J8mJwNFVtaGqClgz1EeSJGnOmug9aknmJbkN2AncXFW3ACdU1Q6A9nl8a74QuHeo+7ZWW9jWp9clSZLmtIkGtaraXVVnAYsYzI6duZ/mo+47q/3U9z5AsjLJpiSbdu3adcDjlSRJ6skheeqzqj4PfIDBvWX3tcuZtM+drdk24OShbouA7a2+aER91HmuqaqpqppasGDBwfwKkiRJh9wkn/pckOQZbf0o4IXAJ4B1wIrWbAVwQ1tfByxLckSS0xg8NLCxXR59KMm57WnP5UN9JEmS5qz5Ezz2icDq9uTmk4C1VfWeJBuAtUkuBu4BLgSoqi1J1gK3A48Cl1bV7nasS4BrgaOAm9oiSZI0p00sqFXVx4Dnjag/AJy3jz6rgFUj6puA/d3fJkmSNOf4ZgJJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTEwtqSU5O8v4kdyTZkuTnW/3YJDcnuat9HjPU54okW5PcmeT8ofrZSTa3fVcmyaTGLUmS1ItJzqg9CvxCVX0rcC5waZLTgcuB9VW1GFjftmn7lgFnAEuAq5LMa8e6GlgJLG7LkgmOW5IkqQsTC2pVtaOqPtLWHwLuABYCS4HVrdlq4IK2vhS4rqoeqaq7ga3AOUlOBI6uqg1VVcCaoT6SJElz1iG5Ry3JqcDzgFuAE6pqBwzCHHB8a7YQuHeo27ZWW9jWp9clSZLmtIkHtSRPA/4YuKyqHtxf0xG12k991LlWJtmUZNOuXbsOfLCSJEkdmWhQS/INDELaO6rqT1r5vnY5k/a5s9W3AScPdV8EbG/1RSPqe6mqa6pqqqqmFixYcPC+iCRJ0gyY5FOfAf4AuKOqfmto1zpgRVtfAdwwVF+W5IgkpzF4aGBjuzz6UJJz2zGXD/WRJEmas+ZP8NjfA1wEbE5yW6v9EvAGYG2Si4F7gAsBqmpLkrXA7QyeGL20qna3fpcA1wJHATe1RZIkaU6bWFCrqg8x+v4ygPP20WcVsGpEfRNw5sEbnSRJUv98M4EkSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnTKoSZIkdcqgJkmS1CmDmiRJUqcMapIkSZ0yqEmSJHXKoCZJktQpg5okSVKnJhbUkrw1yc4kHx+qHZvk5iR3tc9jhvZdkWRrkjuTnD9UPzvJ5rbvyiSZ1JglSZJ6MskZtWuBJdNqlwPrq2oxsL5tk+R0YBlwRutzVZJ5rc/VwEpgcVumH1OSJGlOmlhQq6oPAp+bVl4KrG7rq4ELhurXVdUjVXU3sBU4J8mJwNFVtaGqClgz1EeSJGlOO9T3qJ1QVTsA2ufxrb4QuHeo3bZWW9jWp9clSZLmvF4eJhh131ntpz76IMnKJJuSbNq1a9dBG5wkSdJMONRB7b52OZP2ubPVtwEnD7VbBGxv9UUj6iNV1TVVNVVVUwsWLDioA5ckSTrUDnVQWwesaOsrgBuG6suSHJHkNAYPDWxsl0cfSnJue9pz+VAfSZKkOW3+pA6c5F3A84HjkmwD/gvwBmBtkouBe4ALAapqS5K1wO3Ao8ClVbW7HeoSBk+QHgXc1BZJkqQ5b2JBrapeto9d5+2j/Spg1Yj6JuDMgzg0SZKkWaGXhwkkSZI0jUFNkiSpUwY1SZKkThnUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU2SJKlTBjVJkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkTs2f6QFIkvbtnl/9tpkegnRYOuU/b57pIQDOqEmSJHXLoCZJktQpg5okSVKnDGqSJEmdMqhJkiR1yqAmSZLUKYOaJElSpwxqkiRJnZo1QS3JkiR3Jtma5PKZHo8kSdKkzYqglmQe8DvAi4DTgZclOX1mRyVJkjRZsyKoAecAW6vqU1X1ZeA6YOkMj0mSJGmiZktQWwjcO7S9rdUkSZLmrNnyUvaMqNVejZKVwMq2+XCSOyc6Ks0VxwH3z/Qg9PjkTStmegjSvvh3y2z2X0ZFj4n6plHF2RLUtgEnD20vArZPb1RV1wDXHKpBaW5IsqmqpmZ6HJLmFv9u0cEwWy59/h2wOMlpSZ4MLAPWzfCYJEmSJmpWzKhV1aNJfg54LzAPeGtVbZnhYUmSJE3UrAhqAFV1I3DjTI9Dc5KXyyVNgn+36AlL1V735EuSJKkDs+UeNUmSpMOOQU2HNV9NJulgS/LWJDuTfHymx6LZz6Cmw5avJpM0IdcCS2Z6EJobDGo6nPlqMkkHXVV9EPjcTI9Dc4NBTYczX00mSeqaQU2Hs7FeTSZJ0kwxqOlwNtarySRJmikGNR3OfDWZJKlrBjUdtqrqUWDPq8nuANb6ajJJT1SSdwEbgOck2Zbk4pkek2Yv30wgSZLUKWfUJEmSOmVQkyRJ6pRBTZIkqVMGNUmSpE4Z1CRJkjplUJMkSeqUQU1S15J8IMn502qXJbkxyZeS3Da0LG/7P53kuKH2z0/ynrb+iiRvGdq3PMnHk2xJcnuS17b6tUl+Ytp5T93XOUeM+5a2/54ku4bavzPJJUPtvjPJx5LMb+PenOSjSd6X5FlD32fz0DGufOL/ZCXNBvNnegCS9BjexeCtEe8dqi0DfhE4parOerwHTvIi4DLgh6tqe5IjgYseo9snxzlnVX1nO8crgKmq+rm2fQKwIcn1wAPAW4CfrapHkwC8oKruT/LfgF8CXtMO+YKquv8Av6KkWc4ZNUm9ux54cZIjYDCrBZzE4F2tT9QVwGurajtAVf1zVf3eQTjuPlXVfcCbgDcCPwN8rKo+NKLpB4FvmeRYJPXPGTVJXauqB5JsBJYANzCYTfsjoIBnJ7ltqPmrq+qv2/r7k+xu608DPjHi8GcCtx7gkPZ3znH9L2AF8Hxgah9tXgxsHtoe/j6rq+p/HOA5Jc1CBjVJs8Gey597gtqrWn1/lyH//6XCJM8HXnuQxjLWpc/9qaqvJvldBpdEH5i2e08g+xjw+qG6lz6lw5CXPiXNBn8KnJfk24GjquojB+m4W4CzD9KxDtRX2zLdC6rqrKpaXlWfP8RjktQZg5qk7lXVw8AHgLcymF07WH4deOPQ05VHJHnNY/SRpEPGoCZptngX8FzguqHas6f9VMYBhayquhH4HeAvkmxhcL/a8C0hv5tkW1s2HIxzPgHvHzrnmkN0TkkzLFU102OQJEnSCM6oSZIkdcqnPiXpCUpyC3DEtPJFVbV5VHtJGpeXPiVJkjrlpU9JkqROGdQkSZI6ZVCTJEnqlEFNkiSpUwY1SZKkTv0/dtN12r1n7OEAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#iterate throw all collumns, ploting the count for every class\n",
"for i in df1:\n",
" # dont plot ID and CREDIT_SCORE becouse of the number of classes \n",
" # to save time and memory efficiency\n",
" if i == \"ID\" or i == \"CREDIT_SCORE\":\n",
" print(i+\" count was too much memory consuming\")\n",
" else:\n",
" fig ,ax = plt.subplots(figsize=(10,5))\n",
" ax = sns.countplot(x=i,data=df1)\n",
" plt.title(i+' entry count') \n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 194,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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I6yVppdIwsCswtsb6zMzMzJZYtVraTikMX1s27VcdzRgRHwLfB/4OPA1cHRFPSjpM0mGFrPsAt0fE9ELa6sB9ksYAjwA3R8RtNcpqZmZmtsSq1adNVYYrjc8nIm4BbilLO7ts/ELgwrK0F4CNay3fzMzMbGlRq6UtqgxXGjczMzOzBqnV0raupBGkVrXSMHl8cPXZzMzMzGxRqhW0FR+Ge0rZtPJxMzMzM2uQDoO2iLhncRXEzMzMzKrrMGiT9HhH0yNio0VbHDMzMzOrpNbl0dmkGw4uB/4GzGh4iczMzMxsPh3ePRoRm5Be5L4iKXA7EdgA+HdEvNzw0pmZmZkZUMdrrCJiXEQcExGbklrbLgaObHjJzMzMzGyOmi+MlzSA9AqqfYC3SAHb9Q0ul5mZmZkV1LoR4R5gJeBq4GDgzTxpOUmrRMSb1eY1MzMzs0WnVkvbOqQbEb6TP8Hc11cFsG7jimZmZmZmJbWe0zZoMZXDzMzMzDpQT5+25YADSXeNBvAUcHlEzGpw2czMzMws6/DuUUmfJAVp2wOvABPz8JOSNmh04czMzMwsqdXSdjrw3Yi4o5goaWfgDGCHRhXMzMzMzOaq9Zy2AeUBG0BE3Ams0ZgimZmZmVm5WkHbMpJ6lCdK6kl9/eF2k/SMpPGSjq4wfXtJ70h6LH+G1TuvmZmZ2dKkVtB2MXCtpEGlhDx8NXBJRzNK6gacCQwFPgkckPvIlbs3IjbJn+M6Oa+ZmZnZUqHWu0dPAG4DRkqaKmkqcA9wRynA6sAWwPiIeCEi/gNcCexdZ7kWZl4zMzOzJU497x49IyIGAoOBwRGxTkScXseyBwATCuMTc1q5rSWNkXRr4Y7UeudF0qGS2iW1T5kypY5imZmZmbWeWo/8+JGkbwFExLsR8W5O/4GkI2osWxXSomz8UWCdiNiYdKfqDZ2Yl1yucyKiLSLa+vXrV6NIZmZmZq2pVkvbN6ncd+2cPK0jE4G1C+NrAZOKGSJiWkS8l4dvAbpL6lvPvGZmZmZLk1pBW+Q+ZeWJs6jcGlY0Clhf0uD8VoX9gRHFDJLWkKQ8vEUuzxv1zGtmZma2NKnnsR2rR8Tk8rRa80XEh5K+D/wd6AacHxFPSjosTz8b+BLwXUkfAjOA/SMigIrzdnLbzMzMzJYYSjFSlYnSQcDhwI9J/c8ANgNOBs6MiIsaXsJOaGtri/b29q4uhpmZmVlNkkZHRFu9+Wu1tN0NvA4cB2xIuhngSeCYiLh1QQtpZmZmZp1TK2i7ISI2JT2rzczMzMy6SK0bEWrdbGBmZmZmi0GtlrYBkk6rNjEiDl/E5TEzMzOzCmoFbTOA0YujIGZmZmZWXa2g7Y1mu0PUzMzMbGlUq0/bfA/WNTMzM7PFr1ZL2/ckbVoYD2BqREyoNoOZmZmZLXq1grZTKqStkl8tdUBEPLboi2RmZmZm5ToM2iJih0rpktqA04DtGlEoMzMzM5tXrT5tFUVEO7DiIi6LmZmZmVWxQEFbfmF89ZeWmpmZmdki1eHlUUmnM39wtgqwDfDDRhXKzMzMzOZV60aE9vx3+Zz3v4DbgR9FxOuNLJiZmZmZzVXr8ujlwAbACcA3gX2BC4CfSOre4LKZmZmZWVYraDuZ1Lo2OCI2jYj/AT4G9KHy40DmIWk3Sc9IGi/p6ArTD5T0eP48IGnjwrSXJD0h6TFJ7eXzmpmZmS1Nal0e3QMYEhFz+rVFxDRJ3wXG0UG/NkndgDOBXYCJwChJIyLiqUK2F4HPRsRbkoYC5wBbFqbvEBFTO7VFZmZmZkugWi1tUQzYCokfUfvu0S2A8RHxQkT8B7gS2LtsOQ9ExFt59CFgrfqKbWZmZrZ0qRW0PSXpoPJESV8jtbR1ZABQfN3VxJxWzbeAWwvjAdwuabSkQ2usy8zMzGyJVvPdo8B1kr4JjCYFUpuT7ibdp8a8qpBWsXVO0g6koO3TheRtI2KSpNWAOySNi4iRFeY9FDgUYODAgTWKZGZmZtaaar3G6t/AlpJ2JN1FKuDWiPhHHcueCKxdGF8LmFSeSdJGwHnA0Ih4o7DuSfnv65KuJ11unS9oi4hzSH3haGtr8wN/zczMbIlUq6UNgIi4C7irk8seBawvaTDwb2B/4KvFDJIGAtcBX4+IZwvpvYBlIuLdPLwrcFwn129mZma2xKgraFsQEfGhpO8Dfwe6AedHxJOSDsvTzwaGAasCf5YE8GFEtAGrA9fntGWByyPitkaV1czMzKzZqcLNoS2rra0t2tv9SDczMzNrfpJG58aquizQC+PNzMzMbPFy0GZmZmbWAhy0mZmZmbUAB21mZmZmLcBBm5mZmVkLcNBmZmZm1gIctJmZmZm1AAdtZmZmZi3AQZuZmZlZC3DQZmZmZtYCHLSZmZmZtQAHbWZmZmYtwEGbmZmZWQtw0GZmZmbWAhy0mZmZmbUAB21mZmZmLaChQZuk3SQ9I2m8pKMrTJek0/L0xyVtWu+8ZmZmZkuTZRu1YEndgDOBXYCJwChJIyLiqUK2ocD6+bMlcBawZZ3zLlZvz5jJs69NZ/K0WazeuwdD1uhFn+V7dlVxzObjOmrNznXUml2z19GGBW3AFsD4iHgBQNKVwN5AMfDaG7g4IgJ4SFIfSWsCg+qYd7F5e8ZMbh87hWEjxjLzg9n07L4Mx+21Ibtu2K+pvkxbermOWrNzHbVm1wp1tJGXRwcAEwrjE3NaPXnqmXexefa16XO+RICZH8xm2IixPPva9K4qktk8XEet2bmOWrNrhTrayKBNFdKizjz1zJsWIB0qqV1S+5QpUzpZxPpMnjZrzpdYMvOD2UyeNqsh6zPrLNdRa3auo9bsWqGONjJomwisXRhfC5hUZ5565gUgIs6JiLaIaOvXr99CF7qS1Xv3oGf3eXdVz+7LsHrvHg1Zn1lnuY5as3MdtWbXCnW0kUHbKGB9SYMlLQfsD4woyzMCOCjfRboV8E5EvFrnvIvNkDV6cdxeG875MkvXuYes0aurimQ2D9dRa3auo9bsWqGOKt0D0KCFS7sDfwS6AedHxImSDgOIiLMlCTgD2A14HzgkItqrzVtrfW1tbdHe3t6ITWn6O0rMXEet2bmOWrNb3HVU0uiIaKs7fyODtsWtkUGbmZmZ2aK0VAdtkqYALzd4NX2BqQ1eh9nCcB21Zuc6as1ucdXRdSKi7g75S1TQtjhIau9MVGy2uLmOWrNzHbVm16x11O8eNTMzM2sBDtrMzMzMWoCDts47p6sLYFaD66g1O9dRa3ZNWUfdp83MzMysBbilzczMzKwFOGhrAEnbS7qpq8th1hFJB0vq39XlsNYk6SVJfSukP9Dg9d4tqenu6rOuI2kvSUdXmfZelfQLJX0pDy90nZI0SNLYhVlGPRy0dUJ+3Zb3mbU8Sd2AgwEHbdZpuf5UFBHbLM6ymEXEiIg4qavLsTi0dABSHtlK+omk4Xn4bkl/lPSApLGStsjpwyVdIukuSc9J+nZh/qMkjZL0uKRjC+t4WtKfgUeZ90X2SNo8r2OMpEckrVQ2fYs8/V/578dz+gY5/2N5fetL6iXp5ryssZL2a9CusyaU69o4SRflOvFXSStI2inXnycknS+ph6Shkq4uzLu9pL/l4V0lPSjpUUnXSFoxp78kaZik+4ADgDbgslwHPy/p+sLydpF03WLeBdZgkn4q6fA8fKqku/LwTpIuzcMH5Lo2VtLvCvO+J+k4SQ8DWxfSl5d0W+lYWmrZyHXy7lyPx0m6TJLytN1z2n2STqt0ZUJSN0mn5LI8LukHFfKcJald0pOlY3ZOP0nSU3m+U3Lal/M2jZE0cpHsUGuowjHxvPzdXSZpZ0n35/N36bx+sKQz8vDgfPwbJen4wrIk6YxcL24GVquyzorHz7I860m6M9elRyV9rEK5783THpW0TU5fU9LIfMwdK+kzuZ5fmMefkHRkhzslIlr2AwwCxhbGfwIMz8N3A+fm4e1K+YDhwBhgedITjyeQWht2Jd0tIlIwe1OebxAwG9iqwvqXA14ANs/jvYFlge2Bm4ppeXhn4No8fDpwYGE5ywNfLJU5p6/c1fvYn8VenwPYNo+fD/wq19EhOe1i4Ihcz14BeuX0s4Cv5To9spD+M2BYHn4J+GlhfXcDbXlYwDigXx6/HNizq/eJP4u8jm0FXJOH7wUeAboDxwDfycfCV4B+uY7dBXwh5w/gK4VlvZTr7J3AQYX09/Lf7YF3gLXyMfVB4NNAz1ynB+d8V5SOl2Vl/S5wbeH4uUr+W6y3pbRuOX0jYBXgGebeaNcn/30CGFBM86e5P7l+fQh8Kteh0fm4KGBv4Iac72DgjDw8olQfge8V6uO+wB25rvQH3ga+VKxTHR0/y8r1MLBPHu4JrEAhHsnjPfPw+kB7Hv4x8MtCnV0J2Ay4o7DsDutmS7e01eEKgIgYCfSW1Cen3xgRMyJiKvBPYAtS0LYr8C9Si9onSDsb4OWIeKjC8j8OvBoRo/J6pkXEh2V5VgauUWoRPBXYIKc/CPxC0s9Ir7GYQTqo7Czpd5I+ExHvLOT2W+uZEBH35+FLgZ2AFyPi2Zx2EbBdrme3AXtKWhb4PHAj6aT8SeB+SY8B3wDWKSz/qkorjXS0uAT4Wv4/2Rq4dRFulzWH0cBmSlcEZpGOQ23AZ0hB3ObA3RExJdexy0g/XgE+IgVRRTcCF0TExVXW90hETIyI2cBjpBPbJ4AXIuLFnOeKKvPuDJxdOqZGxJsV8nxF0qOk4/YGpLo/DZgJnCdpX+D9nPd+4MLcIlj18q41nRcj4olch54E/pGPV0+Q6lO5bZlbpy4ppG8HXBERH0XEJNIPknK1jp/k/50BEXE9QETMjIj3y5bTHThX0hPANXmZAKOAQ5SuCH4qIt4lNfysK+l0SbuR6m9VrR60fci829CzbHr580yig3QBv42ITfJnvYj4S54+vcr6VWFZ5Y4H/hkRGwJ7lsoYEZcDewEzgL9L2jGfmDcjVcbfShpWY9m25OnMM3iuAr4C7AiMygcAkX61lerxJyPiW4V5qtVlgAtIrXUHkFpjyn+AWIuLiA9ILWSHAA+QArUdgI8BT5PqTzUzI+KjsrT7gaGly54VzCoMf0RqvetoHUUdHl8lDSZdXdkpIjYCbia1bnxI+iF+LfAF0o8bIuIwUsv12sBjklatsxzWtYp1aHZhfDapPlVSrd7UOr7WOn6W8tRyJDAZ2Jj0o2g5mNOAtB3wb+ASSQdFxFs5392klsHzOlpwqwdtk4HVJK0qqQewR9n0/QAkfRp4p9BytbeknvmfdntS9Pt34Jua2/9ngKSK17wLxgH9JW2e51kpt3oUrUz6giA14ZLzrkv6tXkaqTl3I6U7+d6PiEuBU4BN69kJtkQZKKnUX+gA0qWnQZLWy2lfB+7Jw3eT6si3mduC9hCwbSm/Up+4IVXW9S6peR6A/OtzEunEduGi2BhrSiNJwc5IUtB2GPBYbr14GPispL5KNxscwNz6Vskw4A3gz51Y/zhSy8KgPF6t7+7twGGlY6qkVcqm9yb9CHlH0urA0JxvRVLXkltIXQk2yekfi4iHI2IY6UXga2NLovuB/fPwgYX0kcD+uQ/ZmqQfK+VqHj8jYhowUdIXcp4eklYoW87KpKtws0nH7G457zrA6xFxLvAXYFOlO7CXiYhrgV9T47zf0kFb/tV4HOlAcxPpYFD0ltLt52cDxWj5EdKvsoeA4yNiUkTcTurH82Bu0vwrhRNalfX/h3TAOV3SGNL18vLWvpNJrWb3M2+T/H7A2NwE+wlSX6VPAY/ktF8CJ9TaB7bEeRr4hqTHSX1zTiW1ilyT6+VsUn0mt3rcRDpZ3ZTTppB+HFyRl/EQqX5VciFwdu4Uu3xOu4x0ifapRb9p1iTuBdYEHoyIyaRLifcCRMSrwM9J3UbGAI9GxI01lncE0FPSyfWsPHcF+V/gNqWbYiaT+r6VO4/Uv+7xfHz9atlyxpAuiz5J6udU6lawEnBTrv/3kFo9AH6fO3qPJZ3Ax9RTXms5PwS+J2kUKXgquR54jnQl6ywq/BjpxPHz68DhOc8DwBpl0/9MOo4/BAxh7hWO7UmtvP8i9WH/EzAAuDuf9y8k/f9VtcS+EUHS3cBPIqK9LH04qWPiKV1RLrNqcsvDTflSeleV4QzgX4WuAWaLnKQVI+K9fFn1TOC5iDi1q8tl1uxauqXNzBYdSaNJd99d2tVlsSXet3PLwpOk1pD/17XFMWsNS2xLm5mZmdmSxC1tZmZmZi3AQZuZmZlZC3DQZmZmZtYCHLSZ2RJJc9+BOUhSqPDuyvwOwoML4z9Resdh6d2UB+X05ZTeYfy80rsOb5S0VmG+kHRJYXxZSVOU36Wp9E7EKfmxKqVP6enoZmad4qDNzJYGrwM/lLRc+QRJhwG7AFvkx61sx9ynnv+G9NyvIRGxPnADcF3hDQDTgQ0Lz7nbhbkP0y65qvCE9U38DDwzW1AO2sxsaTAF+AfpXYLlfgH8b37SORHxTkRclJ9yfghwZOn1TRFxAek1OjsW5r+V9O5XSG8QqPYuTTOzheKgzcyWFicBP86vZwLmvPx5pYh4vkL+9YBXSsFcQTvp5eQlV5Jej9OT9Jy7h8vy71d2eXR5zMwWQLWXrZqZLVEi4kVJjzDv65A6eil5tWnzpEfE4/ltFgcAt1TIf1VEfH+BCm1mVuCWNjNbmvwG+Bn52Jdb0aZLWrdC3vHAOrk1rmhToLxf2gjgFHxp1MwayEGbmS01ImIcKeDao5D8W+BMSb0BJPWWdGhETAcuAv5QuqSa7ypdAbirbNHnA8dFxBON3gYzW3o5aDOzpc2JwFqF8bOAfwKjJI0F7gHez9N+DswEnpX0HPBlYJ8oe/9fREyMiD9VWV95n7ZtFuXGmNnSw+8eNTMzM2sBbmkzMzMzawEO2szMzMxagIM2MzMzsxbgoM3MzMysBThoMzMzM2sBDtrMzMzMWoCDNjMzM7MW4KDNzMzMrAX8f7JHclInIuWyAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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lwG51yu8DXNLC/piZmZktkVoZsA0BpheW23PaAiQtD4wFrigkBzBR0mRJ41rWSzMzM7OSa9kpUUBV0qJG2V2Av1ScDt08ImZIWg24QdIjEXH7AitJwdw4gOHDhy9qn83MzMxKp5UjbO3AsMLyUGBGjbJ7U3E6NCJm5J/PA1eRTrEuICLGR0RbRLQNGjRokTttZmZmVjZ1AzZJ2xbej6zI27NB2/cC60oaKWlZUlA2oco6Vga2Aq4ppPWXtGLHe2BH4KEG6zMzMzPrkRqNsJ1aeH9FRd5x9SpGxDzgMOB64B/AZRExVdIhkg4pFN0DmBgRbxTSBgN3SrofuAf4U0Rc16CvZmZmZj1SozlsqvG+2vICIuJa4NqKtLMqls8DzqtIewLYoFH7ZmZmZkuDRiNsUeN9tWUzMzMza4FGI2wfljSBNJrW8Z68PLJ2NTMzMzPrKo0CtuKNbk+tyKtcNjMzM7MWqBuwRcRti6sjZmZmZlZd3YBN0gP18iPiE13bHTMzMzOr1OiU6HukiwsuBv4AvNXyHpmZmZnZfOpeJRoRo0kPZV+BFLSdDKwP/Csinm5578zMzMys8aOpIuKRiPhuRGxEGmW7ADiy5T0zMzMzM6CJh79LGkJ6rNQewMukYO2qFvfLzMzMzLJGFx3cBqwIXAYcCLyUs5aVtEpEvFSrrpmZmZl1jUYjbGuRLjr4Wn4FHzySKoAPt65rZmZmZgaN78M2YjH1w8zMzMxqaGYO27LAvqSrQwN4GLg4Iua2uG9mZmZmRoOrRCV9nBSgbQ08A7Tn91Mlrd/qzpmZmZlZ4xG2nwNfj4gbiomStgfOALZpVcfMzMzMLGl0H7YhlcEaQETcCKzemi6ZmZmZWVGjgK2XpL6ViZL60dz8t7GSHpU0TdKxVfK3lvSqpCn5dXyzdc3MzMyWFo0CtguAKySN6EjI7y8DfluvoqTewJnATsDHgX3ynLhKd0TE6Pw6sZN1zczMzHq8Rs8SPQm4Drhd0ixJs4DbgBs6gqs6NgGmRcQTEfE2cCmwW5P9WpS6ZmZmZj1KM88SPSMihgMjgZERsVZE/LyJtocA0wvL7Tmt0maS7pf058KVp83WNTMzM+vxGj2a6ijg1Yg4JyJeK6R/A+gdET+tV71KWlQs3wesFRGvS9oZuBpYt8m6HX0ZB4wDGD58eJ3umJmZmS2ZGo2wHUz1uWrjc1497cCwwvJQYEaxQETMjojX8/trgT6SBjZTt9DG+Ihoi4i2QYMGNeiSmZmZ2ZKnUcAWeQ5ZZeJcqo+CFd0LrCtpZH5awt7AhGIBSatLUn6/Se7Pi83UNTMzM1taNHNrjsERMbMyrVG9iJgn6TDgeqA3cG5ETJV0SM4/C9gL+LqkecBbwN4REUDVup3cNjMzM7MeQSk+qpEp7Q8cDvwXab4ZwMbAj4AzI+L8lvewE9ra2mLSpEnd3Q0zMzOzhiRNjoi2Zso2GmG7FXgeOBEYRZr4PxX4bkT8eVE6aWZmZmbNaRSwXR0RG5HuxWZmZmZm3aDRRQeNLiwwMzMzsxZrNMI2RNLptTIj4vAu7o+ZmZmZVWgUsL0FTF4cHTEzMzOz6hoFbC+W7UpQMzMzs6VNozlsC9w018zMzMwWr0YjbP8paaPCcgCzImJ6rQpmZmZm1rUaBWynVklbJT8uap+ImNL1XTIzMzOzoroBW0RsUy1dUhtwOrBlKzplZmZmZh9oNIetqoiYBKzQxX0xMzMzsyoWKmDLD3+v/RBSMzMzM+sydU+JSvo5CwZmqwCfAr7Zqk6ZmZmZ2QcaXXQwKf9cLpf9EDAROCoinm9lx8zMzMwsaXRK9GJgfeAk4GBgT+A3wNGS+rS4b2ZmZmZG44DtR6RRtZERsVFEbAisDQyg+i0/5iNprKRHJU2TdGyV/H0lPZBff5W0QSHvKUkPSpoiaVJlXTMzM7OlRaNTop8F1ouI9+exRcRsSV8HHqHOPDZJvYEzgR2AduBeSRMi4uFCsSeBrSLiZUk7AeOBMYX8bSJiVqe2yMzMzKyHaTTCFsVgrZD4Lo2vEt0EmBYRT0TE28ClwG4V7fw1Il7Oi3cDQ5vrtpmZmdnSo1HA9rCk/SsTJX2JNMJWzxCg+Air9pxWy5eBPxeWA5goabKkcQ3WZWZmZtZjNXyWKHClpIOByaQg6pOkq0b3aFBXVdKqjspJ2oYUsG1RSN48ImZIWg24QdIjEXF7lbrjgHEAw4cPb9AlMzMzsyVPo0dT/QsYI2lb0tWiAv4cETc10XY7MKywPBSYUVlI0ieAs4GdIuLFwrpn5J/PS7qKdIp1gYAtIsaT5r7R1tbmm/mamZlZj9NohA2AiLgZuLmTbd8LrCtpJPAvYG/gi8UCkoYDVwL7RcRjhfT+QK+IeC2/3xE4sZPrNzMzM+sRmgrYFkZEzJN0GHA90Bs4NyKmSjok558FHA+sCvxCEsC8iGgDBgNX5bRlgIsj4rpW9dXMzMyszFTlItAlVltbW0ya5Fu2mZmZWflJmpwHqhpaqIe/m5mZmdni44DNzMzMrOQcsJmZmZmVnAM2MzMzs5JzwGZmZmZWcg7YzMzMzErOAZuZmZlZyTlgMzMzMys5B2xmZmZmJeeAzczMzKzkHLCZmZmZlZwDNjMzM7OSc8BmZmZmVnIO2MzMzMxKzgGbmZmZWck5YDMzMzMruZYGbJLGSnpU0jRJx1bJl6TTc/4DkjZqtq6ZmZnZ0mKZVjUsqTdwJrAD0A7cK2lCRDxcKLYTsG5+jQF+CYxpsu5i9cpbc3jsuTeYOXsug1fqy3qr92fAcv26qztmZmbWxcp8rG9ZwAZsAkyLiCcAJF0K7AYUg67dgAsiIoC7JQ2QtAYwoom6i80rb81h4kMvcPyEh5jzznv069OLE3cdxY6jBpVmR5qZmdnCK/uxvpWnRIcA0wvL7TmtmTLN1F1sHnvujfd3IMCcd97j+AkP8dhzb3RXl8zMzKwLlf1Y38qATVXSoskyzdRNDUjjJE2SNOmFF17oZBebM3P23Pd3YIc577zHzNlzW7I+MzMzW7zKfqxvZcDWDgwrLA8FZjRZppm6AETE+Ihoi4i2QYMGLXKnqxm8Ul/69Zn/o+rXpxeDV+rbkvWZmZnZ4lX2Y30rA7Z7gXUljZS0LLA3MKGizARg/3y16KbAqxHxbJN1F5v1Vu/PibuOen9HdpzXXm/1/t3VJTMzM+tCZT/Wt+yig4iYJ+kw4HqgN3BuREyVdEjOPwu4FtgZmAa8CRxUr26r+trIgOX6seOoQYwYuEkprxwxMzOzRVP2Y73SBZo9Q1tbW0yaNKm7u2FmZmbWkKTJEdHWVNmeFLBJegF4usWrGQjMavE6zMzMrPssrmP9WhHR1AT8HhWwLQ6SJjUbDZuZmdmSp4zHej9L1MzMzKzkHLCZmZmZlZwDts4b390dMDMzs5Yq3bHec9jMzMzMSs4jbGZmZmYlt1QEbJL+Q9I/JN0iaWtJn1rE9kZLukvSVEkPSPpCIW+kpL9J+qek3+UnNSDpo7nOXElHV7T3lKQHJU2R5BvJmZmZAZJGSHqok3U+mo+nf5e0dhf2ZXlJf5L0SD7+/6CQ1zcf86flGGBEIe86Sa9I+mNFe+dJejL3dYqk0fXWv1QEbMCXgUMjYhtga6BTAZukyidCvAnsHxHrA2OBn0oakPN+CJwWEesCL+d1A7wEHA6cWmM120TE6LJdRmxmZraE2R24JiI2jIjHGxXOj8dsNh46NSI+CmwIbC5pp5z+ZeDliFgHOI0UC3T4MbBfjfaOycf+0RExpd6Ke1TAJulqSZNz5Dsupx0PbAGcJely4BDgyBzNflrSIElXSLo3vzbP9U6QNF7SROCC4noi4rGI+Gd+PwN4HhgkScC2wO9z0fNJXxwi4vmIuBd4p8Ufg5mZWU+yjKTz8xmt30taHkDSxpJuy8f96yWtIWln4AjgK5JuyeWOkvRQfh2R00bkM2+/AO4Dhkk6JscBD0j6XmUnIuLNiLglv3871xuas3cjHfMhxQDb5ZiAiLgJeG1RP4QeFbABB0fExkAbcLikVSPiRGASsG9E/AdwFmkEbHRE3AH8LC9/EvgccHahvY2B3SLii7VWKGkTYFngcWBV4JWImJez24EhTfQ7gIn5SzeuMxtsZmbWw30EGB8RnwBmA4dK6gP8HNgrH/fPBU6OiGv54Di/jaSNSc8pHwNsCnxV0oaFdi+IiA3z+3WBTYDRwMaStqzVoXxWbRfgppw0BJgO6XnowKukmKCRk3OAeJqkvvUKtuzh793kcEl75PfDSB/+iw3qbA98PAfCACtJWjG/nxARb9WqKGkN4LfAARHxngqNFDRzGe7mETFD0mrADZIeiYjbm6hnZmbW002PiL/k9xeSphddB4wiHTMBegPPVqm7BXBVRLwBIOlK4NPABODpiLg7l9sxv/6el1cgxRALHIvzNKlLgNMj4omO5CrrbnT8/zbwHGnQZzzwLeDEWoV7TMAmaWtS8LVZRLwp6VagXxNVe+U68wVm+QvwRp31rQT8CTiusMNnAQMkLZMj7KHAjEYdyKdViYjnJV1FivAdsJmZmS0Y+AQpQJoaEZs1qFstkOpQPMYLOCUiftVEf8YD/4yInxbS2kkDRe05oFuZNHe9pojoCDDnSvoNcHS98j3plOjKpAl/b0r6KGnos5rXgBULyxOBwzoWGl2lkcssC1xFGkq9vCM90k3tbgH2ykkHANc0aKt/x4iepP6kCL9TV8SYmZn1YMMldQRm+wB3Ao+S5o5vBiCpj6T1q9S9Hdg9X+HZH9gDuKNKueuBgyWtkNsbks96zUfSSaR444iKrAmkYz6kGODmaHCj23yWjnx2bncaHPt7UsB2HWli4gPA/wJ31yj3B2CPjosOSEOrbfkc8sOkixIa+TywJXBglctxvwUcJWka6fz1OQCSVpfUDhwFHCepPY/SDQbulHQ/cA/wp4i4rvObb2Zm1iP9AzggH99XAX6ZJ/3vBfwwHz+nUOUOEBFxH3Ae6fj6N+DsiPh7lXITgYuBuyQ9SLpwoDi4g6ShwP8AHwfuy8f+r+Tsc4BV87H/KODYQr07gMtJFyK0S/pMzroor+tBYCBwUr0PwU86MDMzMyu5njTCZmZmZtYjOWAzMzMzKzkHbGZmZmYl54DNzMzMrOQcsJmZmZmVnAM2MzMzs5JzwGZmpSLp1sJ9ijrSjpB0raS3Cvc+nCJp/5z/lKSBhfJbS/pjfn+gpDMKefvnh0BPlfSwpKNz+nmS9qpY74ha66zS74slfb2wPCbf33GZ3L8HC22cXii3jKRZkk6p8jk8Kun+/EDq0QvxcZpZD9FjHk1lZj3GJcDepDuPd9gbOAYYHhGjF7ZhSTuR7lC+Y35+bz9gvwbVHm9ynUeSbrr5e9IzjM8ADo2IeflRd9tExKwq9XYk3bX985L+u+Lu6PtGxCRJBwE/BnZooh9m1gN5hM3Myub3wGcl9YU0ygWsSXpW36L6NnB04fm9cyLi113QLhExEzgV+BHpiSkPRMSdTVTdB/gZ8Ay1H6l3FzCkK/ppZksmj7CZWalExIuS7gHGkp7FuzfwO9IDn9eWNKVQ/BsR0fFcwFskvZvfrwA8UqX5UcDkTnap3jornUV6nuDWQFtFXrF/50fEaZKWA7YDvgYMIAVvd1VpdyxwdSf7bWY9iAM2MyujjtOiHQHbwTm93unJ9085StoaOLqL+tLsKVEi4j1JvwLaIuLFWv0r+CxwS0S8KekK4DuSjoyIjsDuovzA6t7ARouwDWa2hPMpUTMro6tJD0reCFguP8C5K0wFNu6itmp5L7+asQ+wvaSnSCN/qwLbFPL3BUaSHkp9Zhf20cyWMA7YzKx0IuJ14FbgXNJoW1c5BfiRpNUBJPWVdHgXtt80SSsBW5AupBgRESOA/yQFce+LiHeA44BNJX1ssXfUzErBAZuZldUlwAbApYW0tStusdGpYCsiriWNVN0oaSppVKs4NeRXktrzq2Mu2SKts+CWQhsXAHsCN0fE3EKZa4BdOy64KPT7LeAndN1pXjNbwmj+K8jNzMzMrGw8wmZmZmZWcr5K1MyskyT9DehbkbxfRDzYHf0xs57Pp0TNzMzMSs6nRM3MzMxKzgGbmZmZWck5YDMzMzMrOQdsZmZmZiXngM3MzMys5P4fTBog/fbcVXgAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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LHAH8qFA2QtLenc+BY4BFdV7PzMzMbJdXb+TswsLz6yvqzutuxYjYApwJ3Ab8FrguIhZLOkPSGYWmJwK3R8SGQtlo4G5JC4HfAP8bEbfWidXMzMxsl1dvzplqPK+23EVE3AzcXFF2WcXyVcBVFWXLgMn1tm9mZmY20NQbOYsaz6stm5mZmdlOqjdy9mJJc0ijZJ3PycsTaq9mZmZmZjuiXnJWvGjshRV1lctmZmZmtpO6Tc4i4s6+CsTMzMzM6iRnku7vrj4iXtW74ZiZmZkNbvUOa24lTfy/GrgJ2Nj0iMzMzMwGsW7P1oyIKaQbku9FStC+ArwSeCwiHml6dGZmZmaDTN3bN0XE7yLi8xFxKGn0bBZwdtMjMzMzMxuE6t74XNIY0q2XTgSeJCVmP2xyXGZmZmaDUr0TAu4E9gauAz4ArMtVu0vaLyLW1VrXzMzMzHqu3sjZwaQTAv4hP4K/3LYpgBc3LzQzMzOzwafedc5a+ygOMzMzM6OxOWe7A6eSztIM4EHg6ojY3OTYzMzMzAadbs/WlPQKUjJ2JPAo0JGfL5b0ymYHZ2ZmZjbY1Bs5uxj4SETcUSyU9BbgEuCoZgVmZmZmNhjVu87ZmMrEDCAifgIc0JyQzMzMzAavesnZEEl7VBZKGk5j89WmS/q9pKWSzq1Sf6SkP0lakB/nN7qumZmZ2UBULzmbBVwvqbWzID+/Dvh+dytKGgpcChwLvAI4Jc9hq/TLiJiSHzN7uK6ZmZnZgFLv3ppfBm4F7pK0VtJa4E7gjs5EqhtTgaURsSwingVmAyc0GNfOrGtmZma2y2rk3pqXRMR4YAIwISIOjoiLG9j2GGB5Ybkjl1V6raSFkm4pnAHa6LpIOl1Su6T2NWvWNBCWmZmZWXnVu5TGOZI+BBART0fE07n8Y5I+XmfbqlIWFcv3AQdHxGTSmaE39mBdclyXR0RbRLS1tLTUCcnMzMys3OqNnH2Q6nPLLs913ekAxhWWxwIrig0iYn1EPJOf3wwMkzSqkXXNzMzMBqJ6yVnkOV+VhZupPrpVNA+YKGlCvsvAycCcYgNJB0hSfj41x/NEI+uamZmZDUSNXA5jdESsqiyrt15EbJF0JnAbMBS4MiIWSzoj118GvAv4iKQtwEbg5IgIoOq6PXxvZmZmZrscpVyoRqU0AzgL+ARpfhjAYcAFwKUR8Z9Nj7AH2traor29vb/DMDMzM6tL0vyIaKssrzdy9gtgNTATmESalL8Y+HxE3NLbQZqZmZkNdvWSsxsj4lDStc7MzMzMrMnqnRBQb9K/mZmZmfWieiNnYyRdVKsyIs7q5XjMzMzMBrV6ydlGYH5fBGJmZmZm9ZOzJ8p2RqaZmZnZQFZvzlmXC9CamZmZWfPUGzn7qKRDC8sBrI2I5bVWMDMzM7MdVy85u7BK2X75lkqnRMSC3g/JzMzMbPDqNjmLiKOqlUtqAy4C3tiMoMzMzMwGq3pzzqqKiHZgr16OxczMzGzQ26HkLN/4vPZNOc3MzMxsh3R7WFPSxXRNwvYDXgf8U7OCMjMzMxus6p0Q0J7/3TO3fSFwO3BORKxuZmBmZmZmg1G9w5pXA68Evgx8EDgJ+B7wSUnDmhybmZmZ2aBTLzm7gDRaNiEiDo2IVwMvAUZS/TIb25E0XdLvJS2VdG6V+lMl3Z8f90iaXKh7WNIDkhZIaq9c18zMzGwgqndY82+BQyJi27yziFgv6SPA7+hm3pmkocClwNFABzBP0pyIeLDQ7CHgiIh4UtKxwOXAtEL9URGxtkfvyMzMzGwXVm/kLIqJWaHweeqfrTkVWBoRyyLiWWA2cELFdu6JiCfz4lxgbGNhm5mZmQ1M9ZKzByXNqCyU9PekkbPujAGKt3nqyGW1fAi4pbAcwO2S5ks6vc5rmZmZmQ0Ide+tCdwg6YPAfFLC9BrS2Zsn1llXVcqqjrZJOoqUnL2hUPz6iFgh6UXAHZJ+FxF3VVn3dOB0gPHjx9cJyczMzKzc6t2+6TFgmqQ3kc7aFHBLRPy0gW13AOMKy2OBFZWNJL0KuAI4NiKeKLz2ivzvakk/JB0m7ZKcRcTlpLlqtLW1+cK4ZmZmtkurN3IGQET8DPhZD7c9D5goaQLwGHAy8N5iA0njgRuA90XEkkL5CGBIRDydnx8DzOzh65uZmZntchpKznZERGyRdCZwGzAUuDIiFks6I9dfBpwP7A98RxLAlohoA0YDP8xluwFXR8StzYrVzMzMrCxU5WTMXVZbW1u0t/uSaGZmZlZ+kubnQant7NCNz83MzMysOZycmZmZmZWIkzMzMzOzEnFyZmZmZlYiTs7MzMzMSsTJmZmZmVmJODkzMzMzKxEnZ2ZmZmYl4uTMzMzMrEScnJmZmZmViJMzMzMzsxJxcmZmZmZWIk7OzMzMzErEyZmZmZlZiTg5MzMzMysRJ2dmZmZmJdLU5EzSdEm/l7RU0rlV6iXpolx/v6RDG13XzMzMbCDarVkbljQUuBQ4GugA5kmaExEPFpodC0zMj2nAd4FpDa7bp57auIklKzewav1mRu+zB4ccMIKRew7vr3DMzMysl5VlX9+05AyYCiyNiGUAkmYDJwDFBOsEYFZEBDBX0khJBwKtDazbZ57auInbF63h/DmL2PTcVoYPG8LM4ydxzKQWJ2hmZmYDQJn29c08rDkGWF5Y7shljbRpZN0+s2Tlhm2dBbDpua2cP2cRS1Zu6K+QzMzMrBeVaV/fzORMVcqiwTaNrJs2IJ0uqV1S+5o1a3oYYmNWrd+8rbM6bXpuK6vWb27K65mZmVnfKtO+vpnJWQcwrrA8FljRYJtG1gUgIi6PiLaIaGtpadnpoKsZvc8eDB+2/Uc1fNgQRu+zR1Nez8zMzPpWmfb1zUzO5gETJU2QtDtwMjCnos0cYEY+a/Nw4E8R8XiD6/aZQw4YwczjJ23rtM7j0IccMKK/QjIzM7NeVKZ9fdNOCIiILZLOBG4DhgJXRsRiSWfk+suAm4HjgKXAn4HTulu3WbHWM3LP4RwzqYXWUVP7/QwOMzMz631l2tcrnSg5MLS1tUV7e3t/h2FmZmZWl6T5EdHWpXwgJWeS1gCPNPllRgFrm/wa1jPuk3Jyv5SP+6Sc3C/l01d9cnBEdJkwP6CSs74gqb1almv9x31STu6X8nGflJP7pXz6u098b00zMzOzEnFyZmZmZlYiTs567vL+DsC6cJ+Uk/ulfNwn5eR+KZ9+7RPPOTMzMzMrEY+cmZmZmZWIk7MaJE2X9HtJSyWdW6Veki7K9fdLOrQ/4hxMGuiTU3Nf3C/pHkmT+yPOwaRenxTavUbS85Le1ZfxDVaN9IukIyUtkLRY0p19HeNg08Dfr30l3SRpYe6T0/ojzsFE0pWSVktaVKO+3/bzTs6qkDQUuBQ4FngFcIqkV1Q0OxaYmB+nA9/t0yAHmQb75CHgiIh4FfAlPI+jqRrsk852/0q644c1WSP9Imkk8B3g+Ih4JfB3fR3nYNLgb+WjwIMRMRk4EvhGvn2hNc9VwPRu6vttP+/krLqpwNKIWBYRzwKzgRMq2pwAzIpkLjBS0oF9HeggUrdPIuKeiHgyL84FxvZxjINNI78TgI8B1wOr+zK4QayRfnkvcENEPAoQEe6b5mqkTwLYW5KAvYB1wJa+DXNwiYi7SJ9zLf22n3dyVt0YYHlhuSOX9bSN9Z6eft4fAm5pakRWt08kjQFOBC7rw7gGu0Z+K4cAL5T0C0nzJc3os+gGp0b65BLg5cAK4AHgnyJia9+EZzX0236+aTc+38WpSlnlaa2NtLHe0/DnLekoUnL2hqZGZI30ybeAz0TE82lAwPpAI/2yG3AY8GZgT+BeSXMjYkmzgxukGumTtwILgDcBLwHukPTLiFjf5Nistn7bzzs5q64DGFdYHkv630xP21jvaejzlvQq4Arg2Ih4oo9iG6wa6ZM2YHZOzEYBx0naEhE39kmEg1Ojf7/WRsQGYIOku4DJgJOz5mikT04Dvhbp+lZLJT0E/BXwm74J0arot/28D2tWNw+YKGlCnpB5MjCnos0cYEY+m+Nw4E8R8XhfBzqI1O0TSeOBG4D3eQSgT9Ttk4iYEBGtEdEK/A/wj07Mmq6Rv18/Av5G0m6SXgBMA37bx3EOJo30yaOkkUwkjQZeBizr0yitUr/t5z1yVkVEbJF0JunssqHAlRGxWNIZuf4y4GbgOGAp8GfS/3qsSRrsk/OB/YHv5JGaLb6ZcPM02CfWxxrpl4j4raRbgfuBrcAVEVH1cgK28xr8rXwJuErSA6TDaZ+JiLX9FvQgIOka0pmxoyR1AJ8HhkH/7+d9hwAzMzOzEvFhTTMzM7MScXJmZmZmViJOzszMzMxKxMmZmZmZWYk4OTMzMzMrESdnZjZgSApJ3y8s7yZpjaQfV7T7kaR7K8q+IOkxSQskPSjplELdVZIeynULJb25UPcLSW35+cOSHsjtFki6qGL9hZKWSJqVb21lZtaFkzMzG0g2AJMk7ZmXjwYeKzaQNBI4lHQT4wkV638zIqaQbnj875KGFeo+les+Tvf3Cj0qIqbkx1kV608mXVz0/4Cf5wuSmpltx8mZmQ00twBvy89PAa6pqH8ncBMwm3Sl9i4i4g+ki06+sEr1vezEzY8j+SawEjh2R7djZgOXkzMzG2hmAydLGg68Cvh1RX1nwnZNft6FpEOBP0TE6irV04Ebu3n9nxcOa57dTbv7SPdONDPbjm/fZGYDSkTcL6mVlHjdXKzL9yx8KXB3RISkLZImFW5ddLakDwMvJiVhRV+XdAHwIuDwbkI4qsHb7qiBNmY2CHnkzMwGojnAhXQ9pPke0qHKhyQ9DLSy/aHNb0bEy3K7WXn0rdOnSIndecB/9kKMr8Y3GzezKpycmdlAdCUwMyIeqCg/BZgeEa0R0QocRpV5ZxFxA9AOvL+ifCvwbWCIpLfuSGBKzgIOBG7dkW2Y2cDm5MzMBpyI6IiIbxfL8qHO8cDcQruHgPWSplXZzEzgHEnb/Z2MiAC+DHy6xssX55zNKpR/XdJCYAnwGtLhz2d7+NbMbBBQ+jtjZmZmZmXgkTMzMzOzEnFyZmZmZlYiTs7MzMzMSsTJmZmZmVmJODkzMzMzKxEnZ2ZmZmYl4uTMzMzMrEScnJmZmZmVyP8Hite4wuCf09cAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 720x144 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Correlation betweem the different collums and the outcome\n",
"for i in df:\n",
" fig ,ax = plt.subplots(figsize=(10,2)) \n",
" ax = sns.scatterplot(x=i,y=\"OUTCOME\",data=df)\n",
" plt.title(\"correlation between \"+i+\" and Outcome\")\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4 - Machine Learning model training"
]
},
{
"cell_type": "code",
"execution_count": 195,
"metadata": {},
"outputs": [],
"source": [
"Y = df1[\"OUTCOME\"]\n",
"X = df1.drop([\"OUTCOME\"],axis=1) \n",
"\n",
"#split data into train and test\n",
"from sklearn.model_selection import train_test_split\n",
"X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=30)"
]
},
{
"cell_type": "code",
"execution_count": 196,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Decision tree regression\n",
"The accuricy for the train set is :1.0\n",
"The accuricy for the test set is :0.7885480572597137\n"
]
}
],
"source": [
"#Building a decision tree classifier model to make predictions\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"modelDT = DecisionTreeClassifier()\n",
"modelDT = modelDT.fit(X_train, y_train)\n",
"modelDT.predict(X_test)\n",
"print(\"Decision tree regression\")\n",
"print (\"The accuricy for the train set is :\" + str(modelDT.score(X_train,y_train)))\n",
"print (\"The accuricy for the test set is :\" + str(modelDT.score(X_test,y_test)))\n"
]
},
{
"cell_type": "code",
"execution_count": 197,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The accuricy for the train set is :0.7507012622720898\n",
"The accuricy for the test set is :0.6470347648261758\n"
]
}
],
"source": [
"#Building a KNeighbours classifier model to make predictions\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"modelKNC = KNeighborsClassifier()\n",
"modelKNC = modelKNC.fit(X_train,y_train)\n",
"modelKNC.predict(X_test)\n",
"print (\"The accuricy for the train set is :\" + str(modelKNC.score(X_train,y_train)))\n",
"print (\"The accuricy for the test set is :\" + str(modelKNC.score(X_test,y_test)))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 5 - Hyper Parameter tuning - Grid Search for Decision Tree and KNeightboursClassifier"
]
},
{
"cell_type": "code",
"execution_count": 198,
"metadata": {},
"outputs": [],
"source": [
"#decision tree classifiers possible parameters\n",
"ParamsDT = {\"criterion\":[\"gini\", \"entropy\", \"log_loss\"],\n",
" \"splitter\":[\"best\",\"random\"],\n",
" \"max_depth\" : [1,3,5,7,9,11],\n",
" \"min_samples_leaf\":[1,3,5,7,9],\n",
" \"min_weight_fraction_leaf\":[0.1,0.3,0.5,0.7,0.9],\n",
" \"max_features\":[\"auto\",\"log2\",\"sqrt\",None]}\n",
"\n",
"ParamsKNC = {\"n_neighbors\":[5,7, 8, 10],\n",
" \"metric\": [\"euclidean\", \"manhattan\", \"chebyshev\", \"minkowski\"],\n",
" \"algorithm\" : [\"auto\",\"ball_tree\",\"kd_tree\",\"brute\"],\n",
" \"weights\": [\"uniform\",\"distance\"]}"
]
},
{
"cell_type": "code",
"execution_count": 199,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"from sklearn.model_selection import GridSearchCV\n",
"\n",
"#grid search for decision tree classifier\n",
"tuningDT=GridSearchCV(modelDT,param_grid=ParamsDT,scoring='neg_mean_squared_error',cv=3,verbose=3)\n",
"tuningDT.fit(X_train,y_train)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 200,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'criterion': 'entropy', 'max_depth': 9, 'max_features': None, 'min_samples_leaf': 1, 'min_weight_fraction_leaf': 0.1, 'splitter': 'random'}\n"
]
}
],
"source": [
"#print best combination of parameters\n",
"print(str(tuningDT.best_params_))"
]
},
{
"cell_type": "code",
"execution_count": 201,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"from sklearn.model_selection import GridSearchCV\n",
"\n",
"#grid search for Kneighbours classification\n",
"tuningKNC=GridSearchCV(modelKNC,param_grid=ParamsKNC,scoring='neg_mean_squared_error',cv=3,verbose=3)\n",
"tuningKNC.fit(X_train,y_train)\n"
]
},
{
"cell_type": "code",
"execution_count": 202,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'algorithm': 'auto', 'metric': 'manhattan', 'n_neighbors': 10, 'weights': 'uniform'}\n"
]
}
],
"source": [
"#print best combination of parameters\n",
"print(str(tuningKNC.best_params_))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 6 - Re-Run the models using the best combination of parameters"
]
},
{
"cell_type": "code",
"execution_count": 203,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Decision tree regression\n",
"The accuricy for the train set is :0.7994389901823282\n",
"The accuricy for the test set is :0.8065439672801636\n"
]
}
],
"source": [
"#Decision tree classifier using the best parameters found\n",
"modelDT = DecisionTreeClassifier(criterion=\"entropy\",max_depth=11,max_features=None,min_samples_leaf=9,min_weight_fraction_leaf=0.1,splitter=\"random\")\n",
"modelDT = modelDT.fit(X_train, y_train)\n",
"modelDT.predict(X_test)\n",
"print(\"Decision tree regression\")\n",
"print (\"The accuricy for the train set is :\" + str(modelDT.score(X_train,y_train)))\n",
"print (\"The accuricy for the test set is :\" + str(modelDT.score(X_test,y_test)))"
]
},
{
"cell_type": "code",
"execution_count": 204,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The accuricy for the train set is :0.7109046283309958\n",
"The accuricy for the test set is :0.6850715746421268\n"
]
}
],
"source": [
"#KNeighbours Classifier using the best parameters found\n",
"modelKNC = KNeighborsClassifier(algorithm=\"auto\",metric=\"manhattan\",n_neighbors=10,weights=\"uniform\")\n",
"modelKNC = modelKNC.fit(X_train,y_train)\n",
"modelKNC.predict(X_test)\n",
"print (\"The accuricy for the train set is :\" + str(modelKNC.score(X_train,y_train)))\n",
"print (\"The accuricy for the test set is :\" + str(modelKNC.score(X_test,y_test)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In both tuned models the score obtained in the training set were infiriors to the ones obtained using default parameteres,\n",
"but, the score obtained by the tuned models in the test set were better than using the default parameters"
]
}
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