Matplotlib 102 - Basic Introduction to Multiplot, Subplot and Gridspec

matplotlib-102.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6cbf01db",
   "metadata": {},
   "source": [
    "# Matplotlib 102 - Multiplot, Subplot and Gridspec"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f54b8f70",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "important-broad",
   "metadata": {
    "cell_id": "00002-94309874-e505-4511-a0d8-8dac57f2c441",
    "deepnote_cell_type": "markdown"
   },
   "source": [
    "## Import packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "positive-direction",
   "metadata": {
    "cell_id": "00004-9fa0fdf0-ab30-4904-a32b-aa27cda0ccc5",
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 2559354,
    "execution_start": 1625709476752,
    "scrolled": true,
    "source_hash": "87b319d5"
   },
   "outputs": [],
   "source": [
    "# Dataframe manipulation\n",
    "import pandas as pd\n",
    "\n",
    "# Matrices operation\n",
    "import numpy as np\n",
    "\n",
    "# Data viz with matplotlib\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "import matplotlib.gridspec as gridspec\n",
    "import matplotlib.patches as mpatches\n",
    "\n",
    "# Data viz with seaborn\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "liberal-substance",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pandas      1.4.2\n",
      "numpy       1.23.4\n",
      "matplotlib  3.5.1\n",
      "seaborn     0.11.2\n"
     ]
    }
   ],
   "source": [
    "# Check packages' version\n",
    "print('pandas     ', pd.__version__)\n",
    "print('numpy      ', np.__version__)\n",
    "print('matplotlib ', matplotlib.__version__)\n",
    "print('seaborn    ', sns.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "educated-router",
   "metadata": {},
   "source": [
    "## Import data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "regulation-friendly",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the data set into Python\n",
    "df = pd.read_csv(filepath_or_buffer = 'data/WA_Fn-UseC_-Telco-Customer-Churn.csv', sep = ';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "crazy-fountain",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
       "0  No phone service             DSL             No  ...               No   \n",
       "1                No             DSL            Yes  ...              Yes   \n",
       "2                No             DSL            Yes  ...               No   \n",
       "3  No phone service             DSL            Yes  ...              Yes   \n",
       "4                No     Fiber optic             No  ...               No   \n",
       "\n",
       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
       "0          No          No              No  Month-to-month              Yes   \n",
       "1          No          No              No        One year               No   \n",
       "2          No          No              No  Month-to-month              Yes   \n",
       "3         Yes          No              No        One year               No   \n",
       "4          No          No              No  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod MonthlyCharges  TotalCharges  Churn  \n",
       "0           Electronic check          29.85         29.85     No  \n",
       "1               Mailed check          56.95       1889.50     No  \n",
       "2               Mailed check          53.85        108.15    Yes  \n",
       "3  Bank transfer (automatic)          42.30       1840.75     No  \n",
       "4           Electronic check          70.70        151.65    Yes  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print top 5 rows\n",
    "df.head(n = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "moving-bristol",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   gender            7043 non-null   object \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   object \n",
      " 4   Dependents        7043 non-null   object \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   object \n",
      " 7   MultipleLines     7043 non-null   object \n",
      " 8   InternetService   7043 non-null   object \n",
      " 9   OnlineSecurity    7043 non-null   object \n",
      " 10  OnlineBackup      7043 non-null   object \n",
      " 11  DeviceProtection  7043 non-null   object \n",
      " 12  TechSupport       7043 non-null   object \n",
      " 13  StreamingTV       7043 non-null   object \n",
      " 14  StreamingMovies   7043 non-null   object \n",
      " 15  Contract          7043 non-null   object \n",
      " 16  PaperlessBilling  7043 non-null   object \n",
      " 17  PaymentMethod     7043 non-null   object \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7043 non-null   float64\n",
      " 20  Churn             7043 non-null   object \n",
      "dtypes: float64(2), int64(2), object(17)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# Metadata\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "optimum-bunch",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change column types\n",
    "df = df.astype({'SeniorCitizen': object})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "artificial-survival",
   "metadata": {},
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "premium-corporation",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customerID          0\n",
       "gender              0\n",
       "SeniorCitizen       0\n",
       "Partner             0\n",
       "Dependents          0\n",
       "tenure              0\n",
       "PhoneService        0\n",
       "MultipleLines       0\n",
       "InternetService     0\n",
       "OnlineSecurity      0\n",
       "OnlineBackup        0\n",
       "DeviceProtection    0\n",
       "TechSupport         0\n",
       "StreamingTV         0\n",
       "StreamingMovies     0\n",
       "Contract            0\n",
       "PaperlessBilling    0\n",
       "PaymentMethod       0\n",
       "MonthlyCharges      0\n",
       "TotalCharges        0\n",
       "Churn               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of missing values in a data frame\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "historic-logic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7043.000000</td>\n",
       "      <td>7043.000000</td>\n",
       "      <td>7043.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32.371149</td>\n",
       "      <td>64.761692</td>\n",
       "      <td>2279.734304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>24.559481</td>\n",
       "      <td>30.090047</td>\n",
       "      <td>2266.794470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>398.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.350000</td>\n",
       "      <td>1394.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>89.850000</td>\n",
       "      <td>3786.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            tenure  MonthlyCharges  TotalCharges\n",
       "count  7043.000000     7043.000000   7043.000000\n",
       "mean     32.371149       64.761692   2279.734304\n",
       "std      24.559481       30.090047   2266.794470\n",
       "min       0.000000       18.250000      0.000000\n",
       "25%       9.000000       35.500000    398.550000\n",
       "50%      29.000000       70.350000   1394.550000\n",
       "75%      55.000000       89.850000   3786.600000\n",
       "max      72.000000      118.750000   8684.800000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary statistics\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "important-cinema",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7590-VHVEG    1\n",
      "3791-LGQCY    1\n",
      "6008-NAIXK    1\n",
      "5956-YHHRX    1\n",
      "5365-LLFYV    1\n",
      "             ..\n",
      "9796-MVYXX    1\n",
      "2637-FKFSY    1\n",
      "1552-AAGRX    1\n",
      "4304-TSPVK    1\n",
      "3186-AJIEK    1\n",
      "Name: customerID, Length: 7043, dtype: int64 \n",
      "\n",
      "Male      3555\n",
      "Female    3488\n",
      "Name: gender, dtype: int64 \n",
      "\n",
      "0    5901\n",
      "1    1142\n",
      "Name: SeniorCitizen, dtype: int64 \n",
      "\n",
      "No     3641\n",
      "Yes    3402\n",
      "Name: Partner, dtype: int64 \n",
      "\n",
      "No     4933\n",
      "Yes    2110\n",
      "Name: Dependents, dtype: int64 \n",
      "\n",
      "Yes    6361\n",
      "No      682\n",
      "Name: PhoneService, dtype: int64 \n",
      "\n",
      "No                  3390\n",
      "Yes                 2971\n",
      "No phone service     682\n",
      "Name: MultipleLines, dtype: int64 \n",
      "\n",
      "Fiber optic    3096\n",
      "DSL            2421\n",
      "No             1526\n",
      "Name: InternetService, dtype: int64 \n",
      "\n",
      "No                     3498\n",
      "Yes                    2019\n",
      "No internet service    1526\n",
      "Name: OnlineSecurity, dtype: int64 \n",
      "\n",
      "No                     3088\n",
      "Yes                    2429\n",
      "No internet service    1526\n",
      "Name: OnlineBackup, dtype: int64 \n",
      "\n",
      "No                     3095\n",
      "Yes                    2422\n",
      "No internet service    1526\n",
      "Name: DeviceProtection, dtype: int64 \n",
      "\n",
      "No                     3473\n",
      "Yes                    2044\n",
      "No internet service    1526\n",
      "Name: TechSupport, dtype: int64 \n",
      "\n",
      "No                     2810\n",
      "Yes                    2707\n",
      "No internet service    1526\n",
      "Name: StreamingTV, dtype: int64 \n",
      "\n",
      "No                     2785\n",
      "Yes                    2732\n",
      "No internet service    1526\n",
      "Name: StreamingMovies, dtype: int64 \n",
      "\n",
      "Month-to-month    3875\n",
      "Two year          1695\n",
      "One year          1473\n",
      "Name: Contract, dtype: int64 \n",
      "\n",
      "Yes    4171\n",
      "No     2872\n",
      "Name: PaperlessBilling, dtype: int64 \n",
      "\n",
      "Electronic check             2365\n",
      "Mailed check                 1612\n",
      "Bank transfer (automatic)    1544\n",
      "Credit card (automatic)      1522\n",
      "Name: PaymentMethod, dtype: int64 \n",
      "\n",
      "No     5174\n",
      "Yes    1869\n",
      "Name: Churn, dtype: int64 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Check the unique values of categorical columns\n",
    "for col in df.select_dtypes('object').columns:\n",
    "    print(df[str(col)].value_counts(), '\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5df9145c",
   "metadata": {},
   "source": [
    "## Aggregate data for samples"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dde296e",
   "metadata": {},
   "source": [
    "#### 1 Number of customer by payment method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "be84eb1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data aggregation - number of customer by payment method\n",
    "df_group_1 = df.groupby('PaymentMethod')[['customerID']].count().reset_index()\n",
    "# Reorder the PaymentMethod based on total customer\n",
    "df_group_1.sort_values(by = 'customerID', ascending = False, inplace = True)\n",
    "# Create new columns of cummulative percentage and cummulative sum\n",
    "df_group_1['CummulativePerc'] = (df_group_1['customerID'].cumsum() / df_group_1['customerID'].sum())\n",
    "df_group_1['CummulativeSum'] = df_group_1['customerID'].cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fe4b96b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>customerID</th>\n",
       "      <th>CummulativePerc</th>\n",
       "      <th>CummulativeSum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Electronic check</td>\n",
       "      <td>2365</td>\n",
       "      <td>0.335794</td>\n",
       "      <td>2365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mailed check</td>\n",
       "      <td>1612</td>\n",
       "      <td>0.564674</td>\n",
       "      <td>3977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>1544</td>\n",
       "      <td>0.783899</td>\n",
       "      <td>5521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>1522</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7043</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               PaymentMethod  customerID  CummulativePerc  CummulativeSum\n",
       "2           Electronic check        2365         0.335794            2365\n",
       "3               Mailed check        1612         0.564674            3977\n",
       "0  Bank transfer (automatic)        1544         0.783899            5521\n",
       "1    Credit card (automatic)        1522         1.000000            7043"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the data\n",
    "df_group_1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "004cacaf",
   "metadata": {},
   "source": [
    "#### 2 Number of customer by gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "feb74d08",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data aggregation - number of customer by gender\n",
    "df_group_2 = df.groupby('gender')[['customerID']].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f3df22da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>customerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>3488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>3555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  customerID\n",
       "0  Female        3488\n",
       "1    Male        3555"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the data\n",
    "df_group_2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe0de6dd",
   "metadata": {},
   "source": [
    "#### 3 Number of customer by senior citizen status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4b763f80",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data aggregation - number of customer by contract\n",
    "df_group_3 = df.groupby('Contract')[['customerID']].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e14535d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Contract</th>\n",
       "      <th>customerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>3875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>One year</td>\n",
       "      <td>1473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Two year</td>\n",
       "      <td>1695</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Contract  customerID\n",
       "0  Month-to-month        3875\n",
       "1        One year        1473\n",
       "2        Two year        1695"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the data\n",
    "df_group_3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6126d6ab",
   "metadata": {},
   "source": [
    "#### 4 Number of customer by paperless billing status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2fe11253",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data aggregation - number of customer by partner status\n",
    "df_group_4 = df.groupby('PaperlessBilling')[['customerID']].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6eb50783",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>customerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>2872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yes</td>\n",
       "      <td>4171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PaperlessBilling  customerID\n",
       "0               No        2872\n",
       "1              Yes        4171"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the data\n",
    "df_group_4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66af2a0a",
   "metadata": {},
   "source": [
    "#### 5 Number of customer by churn status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7e712ab5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data aggregation - number of customer by churn status\n",
    "df_group_5 = df.groupby('Churn')[['customerID']].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b2b7ea13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Churn</th>\n",
       "      <th>customerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>5174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yes</td>\n",
       "      <td>1869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Churn  customerID\n",
       "0    No        5174\n",
       "1   Yes        1869"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the data\n",
    "df_group_5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b44b1a50",
   "metadata": {},
   "source": [
    "## Multiplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "19cbd347",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure size\n",
    "fig = plt.figure(figsize = (10, 4.8))\n",
    "\n",
    "# Bar plot\n",
    "plt.bar(\n",
    "    x = 'PaymentMethod',\n",
    "    height = 'customerID',\n",
    "    data = df_group_1,\n",
    "    color = 'red'\n",
    ")\n",
    "# Line plot\n",
    "plt.plot(\n",
    "    'PaymentMethod',\n",
    "    'CummulativeSum',\n",
    "    data = df_group_1,\n",
    "    color = 'blue',\n",
    "    marker = 'o'\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "83f153c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots\n",
    "fig, ax = plt.subplots(figsize = (10, 5))\n",
    "\n",
    "# Make another axes object for secondary y-Axis\n",
    "ax2 = ax.twinx()\n",
    "\n",
    "# Bar plot\n",
    "ax.bar(\n",
    "    x = 'PaymentMethod',\n",
    "    height = 'customerID',\n",
    "    data = df_group_1,\n",
    "    color = 'red'\n",
    ")\n",
    "# Line plot\n",
    "ax2.plot(\n",
    "    'PaymentMethod',\n",
    "    'CummulativePerc',\n",
    "    data = df_group_1,\n",
    "    color = 'blue',\n",
    "    marker = 'o'\n",
    ");\n",
    "\n",
    "# Plot title\n",
    "plt.title('Number of Customer by Payment Method', fontsize = 16, fontweight = 'bold', fontstyle = 'italic');\n",
    "# Vertical axis label (primary)\n",
    "ax.set_ylabel('# Customer', fontsize = 12, fontstyle = 'italic');\n",
    "# Vertical axis label (secondary)\n",
    "ax2.set_ylabel('Percentage (%)', fontsize = 12, fontstyle = 'italic');\n",
    "# Horizontal axis label\n",
    "ax.set_xlabel('Payment method', fontsize = 12, fontstyle = 'italic');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2774da9d",
   "metadata": {},
   "source": [
    "## Subplot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a86c6dee",
   "metadata": {},
   "source": [
    "### 1 Subplot with 1 row and 2 columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "edf985ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots (1 row & 2 columns)\n",
    "fig, ax = plt.subplots(nrows = 1, ncols = 2, figsize = (10, 4.8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e52be748",
   "metadata": {},
   "source": [
    "#### Basic solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ba24460a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots (1 row & 2 columns)\n",
    "fig, ax = plt.subplots(nrows = 1, ncols = 2, figsize = (10, 4.8))\n",
    "\n",
    "# Bar plot - 1\n",
    "ax[0].bar(\n",
    "    x = 'gender',\n",
    "    height = 'customerID',\n",
    "    data = df_group_2,\n",
    "    color = 'red'\n",
    ")\n",
    "# Bar plot - 2\n",
    "ax[1].bar(\n",
    "    x = 'Contract',\n",
    "    height = 'customerID',\n",
    "    data = df_group_3,\n",
    "    color = 'blue'\n",
    ");\n",
    "\n",
    "# Titles\n",
    "ax[0].set_title('# Customer by gender');\n",
    "ax[1].set_title('# Customer by contract');\n",
    "\n",
    "# Title the figure\n",
    "plt.suptitle('# Customer in Telco XYZ', fontsize = 14, fontweight = 'bold');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1914035",
   "metadata": {},
   "source": [
    "#### Alternative solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9b7ed362",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots (1 rows & 2 columns)\n",
    "fig, ((ax1, ax2)) = plt.subplots(nrows = 1, ncols = 2, figsize = (10, 4.8))\n",
    "\n",
    "# Bar plot - 1\n",
    "ax1.bar(\n",
    "    x = 'gender',\n",
    "    height = 'customerID',\n",
    "    data = df_group_2,\n",
    "    color = 'red'\n",
    ")\n",
    "\n",
    "# Bar plot - 2\n",
    "ax2.bar(\n",
    "    x = 'Contract',\n",
    "    height = 'customerID',\n",
    "    data = df_group_3,\n",
    "    color = 'blue'\n",
    ");\n",
    "\n",
    "# Titles\n",
    "ax1.set_title('# Customer by gender');\n",
    "ax2.set_title('# Customer by contract');\n",
    "\n",
    "# Title the figure\n",
    "plt.suptitle('# Customer in Telco XYZ', fontsize = 14, fontweight = 'bold');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75db109b",
   "metadata": {},
   "source": [
    "### 2 Subplot with 2 rows and 2 columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e96de49f",
   "metadata": {},
   "source": [
    "#### 1 Basic solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b443f0f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots (2 rows & 2 columns)\n",
    "fig, ax = plt.subplots(nrows = 2, ncols = 2, figsize = (10, 6))\n",
    "\n",
    "# Bar plot - 1\n",
    "ax[0, 0].bar(\n",
    "    x = 'gender',\n",
    "    height = 'customerID',\n",
    "    data = df_group_2,\n",
    "    color = 'red'\n",
    ")\n",
    "\n",
    "# Bar plot - 2\n",
    "ax[0, 1].bar(\n",
    "    x = 'Contract',\n",
    "    height = 'customerID',\n",
    "    data = df_group_3,\n",
    "    color = 'blue'\n",
    ");\n",
    "# Set x-ticks\n",
    "ax[0, 1].set_xticks([0, 1]);\n",
    "\n",
    "# Bar plot - 3\n",
    "ax[1, 0].bar(\n",
    "    x = 'PaperlessBilling',\n",
    "    height = 'customerID',\n",
    "    data = df_group_4,\n",
    "    color = 'green'\n",
    ");\n",
    "\n",
    "# Bar plot - 4\n",
    "ax[1, 1].bar(\n",
    "    x = 'Churn',\n",
    "    height = 'customerID',\n",
    "    data = df_group_5,\n",
    "    color = 'purple'\n",
    ");\n",
    "\n",
    "# Titles\n",
    "ax[0, 0].set_title('# Customer by gender');\n",
    "ax[0, 1].set_title('# Customer by contract');\n",
    "ax[1, 0].set_title('# Customer by paperless billing status');\n",
    "ax[1, 1].set_title('# Customer by churn status');\n",
    "\n",
    "# Title the figure\n",
    "plt.suptitle('# Customer in Telco XYZ', fontsize = 14, fontweight = 'bold');\n",
    "\n",
    "# Remove the overlaps between the axis names and the titles\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaa3fc1d",
   "metadata": {},
   "source": [
    "#### 2 Alternative solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c219336d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a grid for plots (2 rows & 2 columns)\n",
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows = 2, ncols = 2, figsize = (10, 6))\n",
    "\n",
    "# Bar plot - 1\n",
    "ax1.bar(\n",
    "    x = 'gender',\n",
    "    height = 'customerID',\n",
    "    data = df_group_2,\n",
    "    color = 'red'\n",
    ")\n",
    "\n",
    "# Bar plot - 2\n",
    "ax2.bar(\n",
    "    x = 'Contract',\n",
    "    height = 'customerID',\n",
    "    data = df_group_3,\n",
    "    color = 'blue'\n",
    ");\n",
    "\n",
    "# Bar plot - 3\n",
    "ax3.bar(\n",
    "    x = 'PaperlessBilling',\n",
    "    height = 'customerID',\n",
    "    data = df_group_4,\n",
    "    color = 'green'\n",
    ");\n",
    "\n",
    "# Bar plot - 4\n",
    "ax4.bar(\n",
    "    x = 'Churn',\n",
    "    height = 'customerID',\n",
    "    data = df_group_5,\n",
    "    color = 'purple'\n",
    ");\n",
    "\n",
    "# Titles\n",
    "ax1.set_title('# Customer by gender');\n",
    "ax2.set_title('# Customer by contract');\n",
    "ax3.set_title('# Customer by paperless billing status');\n",
    "ax4.set_title('# Customer by churn status');\n",
    "\n",
    "# Title the figure\n",
    "plt.suptitle('# Customer in Telco XYZ', fontsize = 14, fontweight = 'bold');\n",
    "\n",
    "# Remove the overlaps between the axis names and the titles\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e791503",
   "metadata": {},
   "source": [
    "### 3 Subplot with `gridspec`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6004fb34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure size\n",
    "fig = plt.figure(figsize = (10, 8))\n",
    "\n",
    "# Create a grid for plots (2 rows & 3 columns)\n",
    "gs = gridspec.GridSpec(nrows = 2, ncols = 3, figure = fig)\n",
    "\n",
    "ax1 = fig.add_subplot(gs[0, :]);\n",
    "ax1.set_title('# Customer by payment method');\n",
    "\n",
    "ax2 = fig.add_subplot(gs[1, 0]);\n",
    "ax2.set_title('# Customer by gender');\n",
    "\n",
    "ax3 = fig.add_subplot(gs[1, 1]);\n",
    "ax3.set_title('# Customer by paperless bill status');\n",
    "\n",
    "ax4 = fig.add_subplot(gs[1, 2]);\n",
    "ax4.set_title('# Customer by churn status');\n",
    "\n",
    "# Remove the overlaps between the axis names and the titles\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "233e407e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure size\n",
    "fig = plt.figure(figsize = (10, 8))\n",
    "\n",
    "# Create a grid for plots (2 rows & 3 columns)\n",
    "gs = gridspec.GridSpec(nrows = 2, ncols = 3, figure = fig)\n",
    "\n",
    "ax1 = fig.add_subplot(gs[0, :]);\n",
    "ax1.set_title('# Customer by payment method');\n",
    "\n",
    "ax2 = fig.add_subplot(gs[1, 0]);\n",
    "ax2.set_title('# Customer by gender');\n",
    "\n",
    "ax3 = fig.add_subplot(gs[1, 1]);\n",
    "ax3.set_title('# Customer by paperless bill status');\n",
    "\n",
    "ax4 = fig.add_subplot(gs[1, 2]);\n",
    "ax4.set_title('# Customer by churn status');\n",
    "\n",
    "# Bar plot - 1\n",
    "ax1.bar(\n",
    "    x = 'PaymentMethod',\n",
    "    height = 'customerID',\n",
    "    data = df_group_1,\n",
    "    color = 'orange'\n",
    ");\n",
    "\n",
    "# Bar plot - 2\n",
    "ax2.bar(\n",
    "    x = 'gender',\n",
    "    height = 'customerID',\n",
    "    data = df_group_2,\n",
    "    color = 'red'\n",
    ");\n",
    "\n",
    "# Bar plot - 3\n",
    "ax3.bar(\n",
    "    x = 'PaperlessBilling',\n",
    "    height = 'customerID',\n",
    "    data = df_group_4,\n",
    "    color = 'green'\n",
    ");\n",
    "\n",
    "# Bar plot - 4\n",
    "ax4.bar(\n",
    "    x = 'Churn',\n",
    "    height = 'customerID',\n",
    "    data = df_group_5,\n",
    "    color = 'purple'\n",
    ");\n",
    "\n",
    "\n",
    "# Remove the overlaps between the axis names and the titles\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "652f03fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xeh2eOHFCRUVFjn8XAQEBKioqUl5enlPyfbGNaQBA4r0F7y3+KyAgwJHYXuq6pX22YsUKxwq6qxUQEKCvvvqq3NeeNGmS00Z9v9SyZUunY3YwR2Uh8b6BLFiwQKdPn1ZaWpr+/Oc/a8OGDfLw8ND06dOVn5+vV199VdKFpUeXM3HiRKWkpGjs2LEuP/khScYYffjhhxowYICkCzuPfvPNN0519u7dq//85z8XHbTq1KmjBx54QEePHtWECRN08OBBtW7d+qIzlvfee68k6R//+IdjN2jpwg6rmZmZmjJlymXvqzxq1qyp7t27KyMjQ23btnV8al2ZVq5cqZdfftnxCe/p06e1evVqRUdHOy2bDgoK0oMPPqjk5GSdO3dO/fr1q9BSviVLljgtodqyZYsOHTqk0aNHS/rvYPPrT7kXLFhQ5vmuNp7y6Nu3r1JTU9W8eXPdfPPNlXLOX76mfH19K+WcF1OR109lzM736NFD7733ntO/R+nCDrWlf5ek7t27a+bMmVqyZInGjx/vqPfOO+9c8bUBuD/eW/DeolS3bt2Umprq9MFHSUmJli9f7lSvV69e8vT01L59+yptGXf37t313nvvadWqVU7LzX89hrVs2VK33nqrdu3apZdeeqlSrg2UF4n3DaT0E7zk5GT16NFDnTt3lnTh0+lnnnlGkZGR5T5XWFiY3n33XQ0ePFjt27fXuHHjHN/N3bNnj1JSUmSMcQyOQ4cO1cMPP6yxY8dq4MCBOnTokGbOnKn69es7nbdfv35q06aNIiMjVb9+fR06dEizZ89WaGiobr31VknS7bffLkl67bXXNGzYMHl5eally5Zq2bKlHnnkEc2ZM0c1atRQbGysDh48qOeee04hISGaOHHi1XXgL7z22mu66667FB0drUcffVRNmzbV6dOn9f3332v16tVav379VZ3fw8NDPXv2VEJCgkpKSjRjxgwVFBQoMTHRpe7//M//OJ7L0p8sKa/t27dr9OjRevDBB3X48GFNmTJFjRo1ciy3atWqlZo3b65nnnlGxhjVrVtXq1evVlpa2kXPeTXxlMf06dOVlpamqKgojR8/Xi1bttTPP/+sgwcPKjU1VfPnz3eZlbic0tfUjBkzFBsbKw8PD8ve+Ejlf/00b95cvr6+WrJkicLDw1W7dm0FBwdXaFY/Li5Oc+fO1bBhw3Tw4EHdfvvt+uKLL/TSSy+pd+/euu+++yRJMTExuvvuu/X000/rzJkzioyM1Jdffqm///3vlvQBAPfAewveW5SaMmWKVq9erR49emjKlCny9fXV/PnzdebMGUkXvu8tXfjAZPr06ZoyZYr279+v3/zmN7r55pt1/PhxffXVV6pVq1aZMV1KXFyc/vrXvyouLk4vvviibr31VqWmpmrt2rUudRcsWKDY2Fj16tVLw4cPV6NGjXTy5EllZmbq66+/dvmgAKg0VbmzG6694uJiU79+fbNgwQJjjDFff/21kXTZnUYvZt++fWbs2LHmlltuMXa73fj6+prWrVubhIQEp51BS0pKzMyZM02zZs2Mj4+PiYyMNOvXr3fZefTVV181UVFRpl69esbb29s0adLEjBo1yhw8eNDpupMmTTLBwcGmRo0aRpLZsGGD4/5mzJhhWrRoYby8vEy9evXMww8/7PgJplLdunUzt912m8v9hIaGmj59+riUSzKPPfaYU9mBAwfMyJEjTaNGjYyXl5epX7++iYqKctoRvHTn0eXLl5erP0t3Hp0xY4ZJTEw0jRs3Nt7e3qZDhw5m7dq1F23XtGlTEx4eXq5rGPPfnTrXrVtnhg4daurUqWN8fX1N7969zXfffedUd8+ePaZnz57mpptuMjfffLN58MEHTVZW1iV3ur5UPMOGDTO1atVyKa/Ic/LDDz+Y8ePHm7CwMOPl5WXq1q1rIiIizJQpU8yPP/5ojPlvX7788ssu5/x17IWFhWb06NGmfv36xmazlbmz7ZXGWnq9K3n9GGPM0qVLTatWrYyXl5dT3Bfrx6lTp7rs0J6Xl2fi4+NNUFCQ8fT0NKGhoWbSpEkuP5l26tQpM3LkSFOnTh1Ts2ZN07NnT/Pvf/+bXc0BXBLvLS640d9bGGPM5s2bTefOnY3dbjcNGzY0Tz31lONXNEp/xrPUhx9+aLp37278/PyM3W43oaGh5oEHHjCffvqpo05FxrojR46YgQMHmtq1a5ubbrrJDBw40GzZsqXMXwfZtWuXGTRokGnQoIHx8vIyDRs2NPfee6+ZP3++o07pe6X09PQK9QFwMTZjjLmGeT6ASvbNN9+oXbt2mjt3rmOm+nIWL16sESNGKD09vUKzEVbFAwAArh+VOZbHxMTo4MGD2rt3byVFB1RPLDUHqql9+/bp0KFDmjx5soKCglx+6uRGjwcAAFTM1Y7lCQkJ6tChg0JCQnTy5EktWbJEaWlpWrhwoTUBA9UIPycGVFN//vOf1bNnT/34449avnz5JXdlvRHjAQAAFXO1Y3lxcbGef/55xcbG6uGHH9ahQ4f097//XSNHjrQoYqD6YKk5AAAAAAAWqvCM96ZNm9SvXz8FBwfLZrPpww8/vGybjRs3KiIiQj4+PmrWrJnmz59/JbECAIByYrwGAOD6UeHE+8yZM2rXrp3eeOONctU/cOCAevfurejoaGVkZGjy5MkaP3683n///QoHCwAAyofxGgCA68dVLTW32Wz64IMP1L9//4vW+dOf/qRVq1YpMzPTURYfH69du3Zp69atV3ppAABQTozXAABULct3Nd+6datiYmKcynr16qWFCxfq/Pnz8vLycmlTWFiowsJCx3FJSYlOnjypgIAA2Ww2q0MGAKBSGWN0+vRpBQcHq0aN63NfU8ZrAACsG7MtT7xzcnIUGBjoVBYYGKiioiLl5uYqKCjIpU1SUpISExOtDg0AgGvq8OHDaty4cVWHUSbGawAA/quyx+xr8jvev/7Uu3R1+8U+DZ80aZISEhIcx/n5+WrSpIkOHz4sPz8/6wIFAMACBQUFCgkJ0U033VTVoVwS4zUA4EZn1ZhteeLdsGFD5eTkOJWdOHFCnp6eCggIKLON3W6X3W53Kffz82MgBwBUW9fz8mvGawAA/quyx2zLv2jWpUsXpaWlOZWtW7dOkZGRZX5fDAAAXHuM1wAAWKfCifePP/6onTt3aufOnZIu/PzIzp07lZWVJenCsrO4uDhH/fj4eB06dEgJCQnKzMxUSkqKFi5cqCeffLJy7gAAALhgvAYA4PpR4aXm27dvV/fu3R3Hpd/tGjZsmBYvXqzs7GzHoC5JYWFhSk1N1cSJEzV37lwFBwfr9ddf18CBAyshfAAAUBbGawAArh9X9Tve10pBQYH8/f2Vn5/Pd8YAANXOjTKO3Sj3CQBwX1aNZdfnj4kCAAAAAOAmSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAN5WcnKywsDD5+PgoIiJCmzdvvmT9JUuWqF27dqpZs6aCgoI0YsQI5eXlXaNoAQBwXyTeAAC4oWXLlmnChAmaMmWKMjIyFB0drdjYWGVlZZVZ/4svvlBcXJxGjRql3bt3a/ny5UpPT9fo0aOvceQAALgfEm8AANzQrFmzNGrUKI0ePVrh4eGaPXu2QkJCNG/evDLrb9u2TU2bNtX48eMVFhamu+66S2PGjNH27duvceQAALgfEm8AANzMuXPntGPHDsXExDiVx8TEaMuWLWW2iYqK0pEjR5SamipjjI4fP64VK1aoT58+1yJkAADcGok3AABuJjc3V8XFxQoMDHQqDwwMVE5OTpltoqKitGTJEg0ePFje3t5q2LCh6tSpozlz5lz0OoWFhSooKHB6AAAAVyTeAAC4KZvN5nRsjHEpK7Vnzx6NHz9ezz//vHbs2KE1a9bowIEDio+Pv+j5k5KS5O/v73iEhIRUavwAALgLEm8AANxMvXr15OHh4TK7feLECZdZ8FJJSUnq2rWrnnrqKbVt21a9evVScnKyUlJSlJ2dXWabSZMmKT8/3/E4fPhwpd8LAADugMQbAAA34+3trYiICKWlpTmVp6WlKSoqqsw2Z8+eVY0azm8LPDw8JF2YKS+L3W6Xn5+f0wMAALgi8QYAwA0lJCTozTffVEpKijIzMzVx4kRlZWU5lo5PmjRJcXFxjvr9+vXTypUrNW/ePO3fv19ffvmlxo8fr06dOik4OLiqbgMAALfgWdUBAACAyjd48GDl5eVp+vTpys7OVps2bZSamqrQ0FBJUnZ2ttNveg8fPlynT5/WG2+8oSeeeEJ16tTRvffeqxkzZlTVLQAA4DZs5mLrx64jBQUF8vf3V35+PsvYAADVzo0yjt0o9wkAcF9WjWUsNQcAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAHBTycnJCgsLk4+PjyIiIrR58+ZL1i8sLNSUKVMUGhoqu92u5s2bKyUl5RpFCwCA+/Ks6gAAAEDlW7ZsmSZMmKDk5GR17dpVCxYsUGxsrPbs2aMmTZqU2WbQoEE6fvy4Fi5cqFtuuUUnTpxQUVHRNY4cAAD3YzPGmKoO4nIKCgrk7++v/Px8+fn5VXU4AABUSFWMY507d1bHjh01b948R1l4eLj69++vpKQkl/pr1qzR73//e+3fv19169a9omsyXgMAqjurxjKWmgMA4GbOnTunHTt2KCYmxqk8JiZGW7ZsKbPNqlWrFBkZqZkzZ6pRo0Zq0aKFnnzySf30008XvU5hYaEKCgqcHgAAwBVLzQEAcDO5ubkqLi5WYGCgU3lgYKBycnLKbLN//3598cUX8vHx0QcffKDc3FyNHTtWJ0+evOj3vJOSkpSYmFjp8QMA4G6Y8QYAwE3ZbDanY2OMS1mpkpIS2Ww2LVmyRJ06dVLv3r01a9YsLV68+KKz3pMmTVJ+fr7jcfjw4Uq/BwAA3AEz3gAAuJl69erJw8PDZXb7xIkTLrPgpYKCgtSoUSP5+/s7ysLDw2WM0ZEjR3Trrbe6tLHb7bLb7ZUbPAAAbogZbwAA3Iy3t7ciIiKUlpbmVJ6WlqaoqKgy23Tt2lXHjh3Tjz/+6Cjbu3evatSoocaNG1saLwAA7o7EGwAAN5SQkKA333xTKSkpyszM1MSJE5WVlaX4+HhJF5aJx8XFOeoPGTJEAQEBGjFihPbs2aNNmzbpqaee0siRI+Xr61tVtwEAgFtgqTkAAG5o8ODBysvL0/Tp05Wdna02bdooNTVVoaGhkqTs7GxlZWU56teuXVtpaWl6/PHHFRkZqYCAAA0aNEgvvPBCVd0CAABug9/xBgDAYjfKOHaj3CcAwH3xO94AAAAAAFRDJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQCAm0pOTlZYWJh8fHwUERGhzZs3l6vdl19+KU9PT7Vv397aAAEAuEGQeAMA4IaWLVumCRMmaMqUKcrIyFB0dLRiY2OVlZV1yXb5+fmKi4tTjx49rlGkAAC4PxJvAADc0KxZszRq1CiNHj1a4eHhmj17tkJCQjRv3rxLthszZoyGDBmiLl26XKNIAQBwfyTeAAC4mXPnzmnHjh2KiYlxKo+JidGWLVsu2m7RokXat2+fpk6danWIAADcUDyrOgAAAFC5cnNzVVxcrMDAQKfywMBA5eTklNnmu+++0zPPPKPNmzfL07N8bw8KCwtVWFjoOC4oKLjyoAEAcGPMeAMA4KZsNpvTsTHGpUySiouLNWTIECUmJqpFixblPn9SUpL8/f0dj5CQkKuOGQAAd0TiDQCAm6lXr548PDxcZrdPnDjhMgsuSadPn9b27ds1btw4eXp6ytPTU9OnT9euXbvk6emp9evXl3mdSZMmKT8/3/E4fPiwJfcDAEB1x1JzAADcjLe3tyIiIpSWlqYBAwY4ytPS0nT//fe71Pfz89O3337rVJacnKz169drxYoVCgsLK/M6drtddru9coMHAMANkXgDAOCGEhISNHToUEVGRqpLly7629/+pqysLMXHx0u6MFt99OhRvf3226pRo4batGnj1L5Bgwby8fFxKQcAABVH4g0AgBsaPHiw8vLyNH36dGVnZ6tNmzZKTU1VaGioJCk7O/uyv+kNAAAqh80YY6o6iMspKCiQv7+/8vPz5efnV9XhAABQITfKOHaj3CcAwH1ZNZaxuRoAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgoStKvJOTkxUWFiYfHx9FRERo8+bNl6y/ZMkStWvXTjVr1lRQUJBGjBihvLy8KwoYAAAAAIDqpMKJ97JlyzRhwgRNmTJFGRkZio6OVmxsrLKyssqs/8UXXyguLk6jRo3S7t27tXz5cqWnp2v06NFXHTwAAAAAANe7Cifes2bN0qhRozR69GiFh4dr9uzZCgkJ0bx588qsv23bNjVt2lTjx49XWFiY7rrrLo0ZM0bbt2+/6uABAAAAALjeVSjxPnfunHbs2KGYmBin8piYGG3ZsqXMNlFRUTpy5IhSU1NljNHx48e1YsUK9enT58qjBgAAAACgmqhQ4p2bm6vi4mIFBgY6lQcGBionJ6fMNlFRUVqyZIkGDx4sb29vNWzYUHXq1NGcOXMuep3CwkIVFBQ4PQAAAAAAqI6uaHM1m83mdGyMcSkrtWfPHo0fP17PP/+8duzYoTVr1ujAgQOKj4+/6PmTkpLk7+/veISEhFxJmAAAAAAAVLkKJd716tWTh4eHy+z2iRMnXGbBSyUlJalr16566qmn1LZtW/Xq1UvJyclKSUlRdnZ2mW0mTZqk/Px8x+Pw4cMVCRMAAAAAgOtGhRJvb29vRUREKC0tzak8LS1NUVFRZbY5e/asatRwvoyHh4ekCzPlZbHb7fLz83N6AAAAAABQHVV4qXlCQoLefPNNpaSkKDMzUxMnTlRWVpZj6fikSZMUFxfnqN+vXz+tXLlS8+bN0/79+/Xll19q/Pjx6tSpk4KDgyvvTgAAAAAAuA55VrTB4MGDlZeXp+nTpys7O1tt2rRRamqqQkNDJUnZ2dlOv+k9fPhwnT59Wm+88YaeeOIJ1alTR/fee69mzJhReXcBAAAAAMB1ymYutt77OlJQUCB/f3/l5+ez7BwAUO3cKOPYjXKfAAD3ZdVYdkW7mgMAAAAAgPIh8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAICbSk5OVlhYmHx8fBQREaHNmzdftO7KlSvVs2dP1a9fX35+furSpYvWrl17DaMFAMB9kXgDAOCGli1bpgkTJmjKlCnKyMhQdHS0YmNjlZWVVWb9TZs2qWfPnkpNTdWOHTvUvXt39evXTxkZGdc4cgAA3I/NGGOqOojLsepHzAEAuBaqYhzr3LmzOnbsqHnz5jnKwsPD1b9/fyUlJZXrHLfddpsGDx6s559/vlz1Ga8BANWdVWMZM94AALiZc+fOaceOHYqJiXEqj4mJ0ZYtW8p1jpKSEp0+fVp169a9aJ3CwkIVFBQ4PQAAgCsSbwAA3Exubq6Ki4sVGBjoVB4YGKicnJxynePVV1/VmTNnNGjQoIvWSUpKkr+/v+MREhJyVXEDAOCuSLwBAHBTNpvN6dgY41JWlqVLl2ratGlatmyZGjRocNF6kyZNUn5+vuNx+PDhq44ZAAB35FnVAQAAgMpVr149eXh4uMxunzhxwmUW/NeWLVumUaNGafny5brvvvsuWddut8tut191vAAAuDtmvAEAcDPe3t6KiIhQWlqaU3laWpqioqIu2m7p0qUaPny43nnnHfXp08fqMAEAuGEw4w0AgBtKSEjQ0KFDFRkZqS5duuhvf/ubsrKyFB8fL+nCMvGjR4/q7bfflnQh6Y6Li9Nrr72mO++80zFb7uvrK39//yq7DwAA3AGJNwAAbmjw4MHKy8vT9OnTlZ2drTZt2ig1NVWhoaGSpOzsbKff9F6wYIGKior02GOP6bHHHnOUDxs2TIsXL77W4QMA4Fb4HW8AACx2o4xjN8p9AgDcF7/jDQAAAABANUTiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AALip5ORkhYWFycfHRxEREdq8efMl62/cuFERERHy8fFRs2bNNH/+/GsUKQAA7o3EGwAAN7Rs2TJNmDBBU6ZMUUZGhqKjoxUbG6usrKwy6x84cEC9e/dWdHS0MjIyNHnyZI0fP17vv//+NY4cAAD3YzPGmKoO4nIKCgrk7++v/Px8+fn5VXU4AABUSFWMY507d1bHjh01b948R1l4eLj69++vpKQkl/p/+tOftGrVKmVmZjrK4uPjtWvXLm3durVc12S8BgBUd1aNZcx4AwDgZs6dO6cdO3YoJibGqTwmJkZbtmwps83WrVtd6vfq1Uvbt2/X+fPnLYsVAIAbgWdVBwAAACpXbm6uiouLFRgY6FQeGBionJycMtvk5OSUWb+oqEi5ubkKCgpyaVNYWKjCwkLHcX5+vqQLswUAAFRHpWNYZS8MJ/EGAMBN2Ww2p2NjjEvZ5eqXVV4qKSlJiYmJLuUhISEVDRUAgOtKXl6e/P39K+18JN4AALiZevXqycPDw2V2+8SJEy6z2qUaNmxYZn1PT08FBASU2WbSpElKSEhwHJ86dUqhoaHKysqq1DcruDADExISosOHD/P9+UpG31qHvrUOfWud/Px8NWnSRHXr1q3U85J4AwDgZry9vRUREaG0tDQNGDDAUZ6Wlqb777+/zDZdunTR6tWrncrWrVunyMhIeXl5ldnGbrfLbre7lPv7+/NG0CJ+fn70rUXoW+vQt9ahb61To0blbofG5moAALihhIQEvfnmm0pJSVFmZqYmTpyorKwsxcfHS7owWx0XF+eoHx8fr0OHDikhIUGZmZlKSUnRwoUL9eSTT1bVLQAA4DaY8QYAwA0NHjxYeXl5mj59urKzs9WmTRulpqYqNDRUkpSdne30m95hYWFKTU3VxIkTNXfuXAUHB+v111/XwIEDq+oWAABwGyTeAAC4qbFjx2rs2LFl/m3x4sUuZd26ddPXX399xdez2+2aOnVqmcvPcXXoW+vQt9ahb61D31rHqr61mcreJ90CVv2IOQAA1wLjGAAANza+4w0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAACg3JKTkxUWFiYfHx9FRERo8+bNl6y/ceNGRUREyMfHR82aNdP8+fOvUaTVT0X6duXKlerZs6fq168vPz8/denSRWvXrr2G0VYvFX3dlvryyy/l6emp9u3bWxtgNVbRvi0sLNSUKVMUGhoqu92u5s2bKyUl5RpFW71UtG+XLFmidu3aqWbNmgoKCtKIESOUl5d3jaKtHjZt2qR+/fopODhYNptNH3744WXbVNY4RuINAADKZdmyZZowYYKmTJmijIwMRUdHKzY21un3wH/pwIED6t27t6Kjo5WRkaHJkydr/Pjxev/9969x5Ne/ivbtpk2b1LNnT6WmpmrHjh3q3r27+vXrp4yMjGsc+fWvon1bKj8/X3FxcerRo8c1irT6uZK+HTRokD777DMtXLhQ//nPf7R06VK1atXqGkZdPVS0b7/44gvFxcVp1KhR2r17t5YvX6709HSNHj36Gkd+fTtz5ozatWunN954o1z1K3UcM9VAfn6+kWTy8/OrOhQAACrMXcaxTp06mfj4eKeyVq1amWeeeabM+k8//bRp1aqVU9mYMWPMnXfeaVmM1VVF+7YsrVu3NomJiZUdWrV3pX07ePBg8+yzz5qpU6eadu3aWRhh9VXRvv3nP/9p/P39TV5e3rUIr1qraN++/PLLplmzZk5lr7/+umncuLFlMVZ3kswHH3xwyTqVOY4x4w0AAC7r3Llz2rFjh2JiYpzKY2JitGXLljLbbN261aV+r169tH37dp0/f96yWKubK+nbXyspKdHp06dVt25dK0Kstq60bxctWqR9+/Zp6tSpVodYbV1J365atUqRkZGaOXOmGjVqpBYtWujJJ5/UTz/9dC1CrjaupG+joqJ05MgRpaamyhij48ePa8WKFerTp8+1CNltVeY45lmZgQEAAPeUm5ur4uJiBQYGOpUHBgYqJyenzDY5OTll1i8qKlJubq6CgoIsi7c6uZK+/bVXX31VZ86c0aBBg6wIsdq6kr797rvv9Mwzz2jz5s3y9OSt8sVcSd/u379fX3zxhXx8fPTBBx8oNzdXY8eO1cmTJ/me9y9cSd9GRUVpyZIlGjx4sH7++WcVFRXpt7/9rebMmXMtQnZblTmOMeMNAADKzWazOR0bY1zKLle/rHJUvG9LLV26VNOmTdOyZcvUoEEDq8Kr1srbt8XFxRoyZIgSExPVokWLaxVetVaR121JSYlsNpuWLFmiTp06qXfv3po1a5YWL17MrHcZKtK3e/bs0fjx4/X8889rx44dWrNmjQ4cOKD4+PhrEapbq6xxjI/xAADAZdWrV08eHh4usy0nTpxwmQ0o1bBhwzLre3p6KiAgwLJYq5sr6dtSy5Yt06hRo7R8+XLdd999VoZZLVW0b0+fPq3t27crIyND48aNk3QhWTTGyNPTU+vWrdO99957TWK/3l3J6zYoKEiNGjWSv7+/oyw8PFzGGB05ckS33nqrpTFXF1fSt0lJSerataueeuopSVLbtm1Vq1YtRUdH64UXXmCF0RWqzHGMGW8AAHBZ3t7eioiIUFpamlN5WlqaoqKiymzTpUsXl/rr1q1TZGSkvLy8LIu1urmSvpUuzHQPHz5c77zzDt/jvIiK9q2fn5++/fZb7dy50/GIj49Xy5YttXPnTnXu3PlahX7du5LXbdeuXXXs2DH9+OOPjrK9e/eqRo0aaty4saXxVidX0rdnz55VjRrOqZ2Hh4ek/87QouIqdRyr8HZsVcBddoMFANyY3GUce/fdd42Xl5dZuHCh2bNnj5kwYYKpVauWOXjwoDHGmGeeecYMHTrUUX///v2mZs2aZuLEiWbPnj1m4cKFxsvLy6xYsaKqbuG6VdG+feedd4ynp6eZO3euyc7OdjxOnTpVVbdw3apo3/4au5pfXEX79vTp06Zx48bmgQceMLt37zYbN240t956qxk9enRV3cJ1q6J9u2jRIuPp6WmSk5PNvn37zBdffGEiIyNNp06dquoWrkunT582GRkZJiMjw0gys2bNMhkZGebQoUPGGGvHMRJvAAAs5k7j2Ny5c01oaKjx9vY2HTt2NBs3bnT8bdiwYaZbt25O9T///HPToUMH4+3tbZo2bWrmzZt3jSOuPirSt926dTOSXB7Dhg279oFXAxV93f4SifelVbRvMzMzzX333Wd8fX1N48aNTUJCgjl79uw1jrp6qGjfvv7666Z169bG19fXBAUFmT/84Q/myJEj1zjq69uGDRsu+f9OK8cxmzHX/9qDgoIC+fv7Kz8/X35+flUdDgAAFcI4BgDAjY3veAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAgGto165dstls+s9//iNJ+utf/6qmTZtW6Bz79+/XuHHj1KJFC/n6+qpmzZq67bbb9Oyzz+ro0aMWRC1t2bJF06ZN06lTpyw5f1U6ePCgbDabXnnllaoO5bo3fPjwCr9erwWbzaZx48Zdtt7nn38um82mzz//3FE2bdo02Ww2p3r33HOP7rnnnquO6+zZs5o2bZrT9Srq2LFjmjZtmnbu3HnV8aDqkHgDAABcQ+np6apTp45atGghSdq2bZs6depU7vYff/yx2rZtq48//liPPPKIPv74Y8d/r169Wn379rUk7i1btigxMdEtE2/cODp27KitW7eqY8eO1+R6Z8+eVWJi4lUn3omJiSTe1ZxnVQcAAABwI0lPT1enTp0cM2zbtm3T448/Xq62Bw4c0O9//3u1aNFCGzZskL+/v+Nv9957r8aPH68PPvjAkriru/Pnz8tms8nTk7e/V+Ls2bOqWbNmVYdx1fz8/HTnnXdWdRi4ATHjDQAAcA2VJt6SlJOTo6ysrHLPeM+aNUtnzpxRcnKyU9Jdymaz6Xe/+53juGnTpho+fLhLvV8voy0pKdELL7ygli1bytfXV3Xq1FHbtm312muvSbqwFPepp56SJIWFhclmszkt1y0pKdHMmTPVqlUr2e12NWjQQHFxcTpy5IjLddu0aaOtW7cqKipKvr6+atq0qRYtWiRJ+uSTT9SxY0fVrFlTt99+u9asWeMS+3fffachQ4aoQYMGstvtCg8P19y5c53qlC4n/vvf/64nnnhCjRo1kt1u1/fff3/J/i0pKdGLL76oJk2ayMfHR5GRkfrss88cf9+8ebNsNpuWLl3q0vbtt9+WzWZTenr6Rc+/ePFi2Ww2paWlacSIEapbt65q1aqlfv36af/+/U5109LSdP/996tx48by8fHRLbfcojFjxig3N9epXuky6YyMDP3ud7+Tn5+f/P399fDDD+uHH35wiWHZsmXq0qWLatWqpdq1a6tXr17KyMhwqjN8+HDVrl1b3377rWJiYnTTTTepR48eF70vY4ySk5PVvn17+fr66uabb9YDDzzgck8ZGRnq27ev47kLDg5Wnz59nF4ny5cvV+fOneXv76+aNWuqWbNmGjly5EWv/WsLFixQixYtZLfb1bp1a7377rtOfy9rqfnVWL9+ve655x4FBATI19dXTZo00cCBA3X27FkdPHhQ9evXlyQlJiY6/t2U/pv8/vvvNWLECN16662qWbOmGjVqpH79+unbb791iveOO+6QJI0YMcJxjmnTpkm6+JL4sr4SMG/ePLVr1061a9fWTTfdpFatWmny5MmV0g+4PBJvAAAAizVt2tTxhjkjI0MvvPCCbDabgoKCJEndunVzekN+MevWrVNgYGClz9jNnDlT06ZN00MPPaRPPvlEy5Yt06hRoxzLykePHu2YlV+5cqW2bt3qtFz30Ucf1Z/+9Cf17NlTq1at0p///GetWbNGUVFRLoliTk6ORowYodGjR+ujjz7S7bffrpEjR2r69OmaNGmSnn76ab3//vuqXbu2+vfvr2PHjjna7tmzR3fccYf+93//V6+++qo+/vhj9enTR+PHj1diYqLLfU2aNElZWVmaP3++Vq9erQYNGlyyH9544w2tWbNGs2fP1j/+8Q/VqFFDsbGx2rp1qyQpOjpaHTp0cEn0S9vecccdjiTpUkaNGqUaNWronXfe0ezZs/XVV1/pnnvucVrGv2/fPnXp0kXz5s3TunXr9Pzzz+tf//qX7rrrLp0/f97lnAMGDNAtt9yiFStWaNq0afrwww/Vq1cvp7ovvfSSHnroIbVu3Vrvvfee/v73v+v06dOKjo7Wnj17nM537tw5/fa3v9W9996rjz76qMz+LTVmzBhNmDBB9913nz788EMlJydr9+7dioqK0vHjxyVJZ86cUc+ePXX8+HHNnTtXaWlpmj17tpo0aaLTp09LkrZu3arBgwerWbNmevfdd/XJJ5/o+eefV1FR0WX7VJJWrVql119/XdOnT9eKFSsUGhqqhx56SCtWrChX+4o6ePCg+vTpI29vb6WkpGjNmjX6y1/+olq1auncuXMKCgpyfHg0atQox7+b5557TtKFJeQBAQH6y1/+ojVr1mju3Lny9PRU586dHXtAdOzY0fHB1LPPPus4x+jRoysU67vvvquxY8eqW7du+uCDD/Thhx9q4sSJOnPmTCX2CC7JVAP5+flGksnPz6/qUAAAqDDGMezevdtkZGSYmTNnGm9vb5Oenm4yMjJM//79TdeuXU1GRobJyMgwhw4duuR5fHx8zJ133lnu64aGhpphw4a5lHfr1s1069bNcdy3b1/Tvn37S57r5ZdfNpLMgQMHnMozMzONJDN27Fin8n/9619Gkpk8ebLTdSWZ7du3O8ry8vKMh4eH8fX1NUePHnWU79y500gyr7/+uqOsV69epnHjxi7/lsaNG2d8fHzMyZMnjTHGbNiwwUgyd9999yXvqdSBAweMJBMcHGx++uknR3lBQYGpW7euue+++xxlixYtMpJMRkaGo+yrr74yksxbb711yeuUth0wYIBT+ZdffmkkmRdeeKHMdiUlJeb8+fPm0KFDRpL56KOPHH+bOnWqkWQmTpzo1GbJkiVGkvnHP/5hjDEmKyvLeHp6mscff9yp3unTp03Dhg3NoEGDHGXDhg0zkkxKSopLLMOGDTOhoaGO461btxpJ5tVXX3Wqd/jwYePr62uefvppY4wx27dvN5LMhx9+eLHuMa+88oqRZE6dOnXROhcjyfj6+pqcnBxHWVFRkWnVqpW55ZZbHGWlr40NGzY4ykr78Jd+/W+kLCtWrDCSzM6dOy9a54cffjCSzNSpUy97D0VFRebcuXPm1ltvdXo+09PTjSSzaNEilzYXi/PXz9O4ceNMnTp1LhsDrMOMNwAAgMVat26t9u3b69ixY7rjjjsUGRmp9u3ba+/everZs6fat2+v9u3bq0mTJlUSX6dOnbRr1y6NHTtWa9euVUFBQbnbbtiwQZJcZus7deqk8PBwp6XakhQUFKSIiAjHcd26ddWgQQO1b99ewcHBjvLw8HBJ0qFDhyRJP//8sz777DMNGDBANWvWVFFRkePRu3dv/fzzz9q2bZvTtQYOHFju+5Ck3/3ud/Lx8XEc33TTTerXr582bdqk4uJiSdJDDz2kBg0aOM16z5kzR/Xr19fgwYPLdZ0//OEPTsdRUVEKDQ119KUknThxQvHx8QoJCZGnp6e8vLwUGhoqScrMzLzsOQcNGiRPT0/HOdeuXauioiLFxcU59Z2Pj4+6detW5tLr8vTfxx9/LJvNpocfftjpvA0bNlS7du0c573lllt08803609/+pPmz5/vMsMuybFaYNCgQXrvvfcqvEN/jx49FBgY6Dj28PDQ4MGD9f3337t87aEytG/fXt7e3nrkkUf01ltvuSytv5yioiK99NJLat26tby9veXp6Slvb2999913ZT7HV6NTp046deqUHnroIX300UcuK1FgPRJvAAAACxUXFzuSkY0bN+quu+5SUVGRTpw4oczMTHXt2lVFRUWOxO5SmjRpogMHDlR6jJMmTdIrr7yibdu2KTY2VgEBAerRo4e2b99+2bZ5eXmS5Fg2/0vBwcGOv5eqW7euSz1vb2+Xcm9vb0kXEu7S6xQVFWnOnDny8vJyevTu3VuSXJKJsmK6lIYNG5ZZdu7cOf3444+SJLvdrjFjxuidd97RqVOn9MMPP+i9997T6NGjZbfbr+o6pX1VUlKimJgYrVy5Uk8//bQ+++wzffXVV44PFn766afLntPT01MBAQGOc5Yu+b7jjjtc+m/ZsmUufVezZk35+fld9l6OHz8uY4wCAwNdzrtt2zbHef39/bVx40a1b99ekydP1m233abg4GBNnTrVsRz+7rvv1ocffuj4gKBx48Zq06ZNmd+pL8vF+lWSy+uwMjRv3lyffvqpGjRooMcee0zNmzdX8+bNHXsjXE5CQoKee+459e/fX6tXr9a//vUvpaenq127dmU+x1dj6NChSklJ0aFDhzRw4EA1aNBAnTt3VlpaWqVeBxfHto4AAAAW6tGjhzZu3Og4zsjI0IwZMxzHPXv2lKSLzjr+Uq9evTRnzhxt27atXN/z9vHxUWFhoUt5bm6u6tWr5zj29PRUQkKCEhISdOrUKX366aeaPHmyevXqpcOHD19yN+uAgABJUnZ2tho3buz0t2PHjjld52rcfPPN8vDw0NChQ/XYY4+VWScsLMzp+Ne/zXw5OTk5ZZZ5e3urdu3ajrJHH31Uf/nLX5SSkqKff/5ZRUVFio+Pv+rr3HLLLZKk//3f/9WuXbu0ePFiDRs2zFHnUpvD5eTkqFGjRo7joqIi5eXlOZ6f0ueh9LvPl1PevqtXr55sNps2b95c5gcPvyy7/fbb9e6778oYo2+++UaLFy/W9OnT5evrq2eeeUaSdP/99+v+++9XYWGhtm3bpqSkJA0ZMkRNmzZVly5dLhnLxfpV+u/rtLJFR0crOjpaxcXF2r59u+bMmaMJEyYoMDBQv//97y/Z9h//+Ifi4uL00ksvOZXn5uaqTp065bq+j4+P8vPzXcrLmtEeMWKERowYoTNnzmjTpk2aOnWq+vbtq71795brNYGrw4w3AACAhRYsWKD09HS99NJL8vX11bZt25Senq5+/frp7rvvVnp6utLT07VgwYLLnmvixImqVauWxo4dW+abbWOM08+JNW3aVN98841Tnb179zo2bipLnTp19MADD+ixxx7TyZMndfDgQUn/TaB+PRN37733SrqQRPxSenq6MjMzL7kbdkXUrFlT3bt3V0ZGhtq2bavIyEiXx9UmVytXrnTMsEvS6dOntXr1akVHR8vDw8NRHhQUpAcffFDJycmaP3+++vXrV6GvCSxZssTpeMuWLTp06JBjd+rSpPfXieylXiO/Pud7772noqIixzl79eolT09P7du3r8y+i4yMLHf8v9S3b18ZY3T06NEyz3n77be7tLHZbGrXrp3++te/qk6dOvr6669d6tjtdnXr1s3xIdWvd14vy2effeaY2ZcurDZZtmyZmjdv7vKhUGXz8PBQ586dHV9BKL2ni/27kS70w6+f408++cRlif2lztG0aVPt3bvX6QO2vLw8bdmy5aKx1qpVS7GxsZoyZYrOnTun3bt3l+cWcZWY8QYAALBQy5YtJUnJycnq0aOHOnfuLOlCIvHMM89UKOEJCwvTu+++q8GDB6t9+/YaN26cOnToIOnCjt8pKSkyxmjAgAGSLiwvffjhhzV27FgNHDhQhw4d0syZMx0/cVSqX79+atOmjSIjI1W/fn0dOnRIs2fPVmhoqG699VZJciRQr732moYNGyYvLy+1bNlSLVu21COPPKI5c+Y4dgE/ePCgnnvuOYWEhGjixIlX14G/8Nprr+muu+5SdHS0Hn30UTVt2lSnT5/W999/r9WrV2v9+vVXdX4PDw/17NlTCQkJKikp0YwZM1RQUFDmjt7/8z//43guS3edLq/t27dr9OjRevDBB3X48GFNmTJFjRo10tixYyVJrVq1UvPmzfXMM8/IGKO6detq9erVl1wWvHLlSnl6eqpnz57avXu3nnvuObVr106DBg2SdCFBmz59uqZMmaL9+/frN7/5jW6++WYdP35cX331lWrVqnXJncsvpmvXrnrkkUc0YsQIbd++XXfffbdq1aql7OxsffHFF7r99tv16KOP6uOPP1ZycrL69++vZs2ayRijlStX6tSpU45VH88//7yOHDmiHj16qHHjxjp16pRee+01eXl5qVu3bpeNpV69err33nv13HPPqVatWkpOTta///1vl58Uqyzz58/X+vXr1adPHzVp0kQ///yzUlJSJEn33XefpAv7BISGhuqjjz5Sjx49VLduXdWrV09NmzZV3759tXjxYrVq1Upt27bVjh079PLLL7t8SNC8eXP5+vpqyZIlCg8PV+3atRUcHKzg4GANHTpUCxYs0MMPP6w//vGPysvL08yZM12+JvDHP/5Rvr6+6tq1q4KCgpSTk6OkpCT5+/uXayd+VIIq3Nit3NgNFgBQnTGOobi42NSvX98sWLDAGGPM119/bSRddhfzi9m3b58ZO3asueWWW4zdbje+vr6mdevWJiEhwWnX8ZKSEjNz5kzTrFkz4+PjYyIjI8369etddkJ+9dVXTVRUlKlXr57x9vY2TZo0MaNGjTIHDx50uu6kSZNMcHCwqVGjhtPO0MXFxWbGjBmmRYsWxsvLy9SrV888/PDD5vDhw07tu3XrZm677TaX+wkNDTV9+vRxKZdkHnvsMaeyAwcOmJEjR5pGjRoZLy8vU79+fRMVFeW0I3jpztXLly8vV3+W7mo+Y8YMk5iYaBo3bmy8vb1Nhw4dzNq1ay/armnTpiY8PLxc1zDmv7uar1u3zgwdOtTUqVPH+Pr6mt69e5vvvvvOqe6ePXtMz549zU033WRuvvlm8+CDD5qsrCyXHbJLd+TesWOH6devn6ldu7a56aabzEMPPWSOHz/uEsOHH35ounfvbvz8/IzdbjehoaHmgQceMJ9++qmjzrBhw0ytWrXKvIdf75ZdKiUlxXTu3NnUqlXL+Pr6mubNm5u4uDjHDvb//ve/zUMPPWSaN29ufH19jb+/v+nUqZNZvHix4xwff/yxiY2NNY0aNTLe3t6mQYMGpnfv3mbz5s2X7dvS10pycrJp3ry58fLyMq1atTJLlixxqleZu5pv3brVDBgwwISGhhq73W4CAgJMt27dzKpVq5zqffrpp6ZDhw7GbrcbSY5fGvi///s/M2rUKNOgQQNTs2ZNc9ddd5nNmzeXee2lS5eaVq1aGS8vL5fXwFtvvWXCw8ONj4+Pad26tVm2bJnL8/TWW2+Z7t27m8DAQOPt7W2Cg4PNoEGDzDfffHPJe0TlsRljTBXk+xVSUFAgf39/5efnl2uTBwAArieMY4D7+eabb9SuXTvNnTvXMVN9OYsXL9aIESOUnp5+xUu7f23atGlKTEzUDz/8UGnfpwdQ+VhqDgAAAJTTvn37dOjQIU2ePFlBQUEuP6MGAGVhczUAAACgnP785z+rZ8+e+vHHH7V8+fJL7vgOAKVYag4AgMUYxwAAuLEx4w0AgBvatGmT+vXrp+DgYNlsNn344YeXbbNx40ZFRETIx8dHzZo10/z5860PFACAGwCJNwAAbujMmTNq166d3njjjXLVP3DggHr37q3o6GhlZGRo8uTJGj9+vN5//32LIwUAwP2xuRoAAG4oNjZWsbGx5a4/f/58NWnSRLNnz5YkhYeHa/v27XrllVc0cOBAi6IEAODGQOINAAC0detWxcTEOJX16tVLCxcu1Pnz5+Xl5eXSprCwUIWFhY7jkpISnTx5UgEBAbLZbJbHDABAZTPG6PTp0woODlaNGpW3QJzEGwAAKCcnR4GBgU5lgYGBKioqUm5uroKCglzaJCUlKTEx8VqFCADANXP48GE1bty40s5H4g0AACTJZZa69IdPLjZ7PWnSJCUkJDiO8/Pz1aRJEx0+fJjd2wEA1VJBQYFCQkJ00003Vep5SbwBAIAaNmyonJwcp7ITJ07I09NTAQEBZbax2+2y2+0u5X5+fiTeAIBqrbK/MsWu5gAAQF26dFFaWppT2bp16xQZGVnm97sBAED5kXgDAOCGfvzxR+3cuVM7d+6UdOHnwnbu3KmsrCxJF5aJx8XFOerHx8fr0KFDSkhIUGZmplJSUrRw4UI9+eSTVRE+AABuhaXmAAC4oe3bt6t79+6O49LvYg8bNkyLFy9Wdna2IwmXpLCwMKWmpmrixImaO3eugoOD9frrr/NTYgAAVAKbKd055TpWUFAgf39/5efn850xAEC1c6OMYzfKfQIA3JdVYxlLzQEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsNAVJd7JyckKCwuTj4+PIiIitHnz5kvWLyws1JQpUxQaGiq73a7mzZsrJSXligIGAAAAAKA68axog2XLlmnChAlKTk5W165dtWDBAsXGxmrPnj1q0qRJmW0GDRqk48ePa+HChbrlllt04sQJFRUVXXXwAAAAAABc72zGGFORBp07d1bHjh01b948R1l4eLj69++vpKQkl/pr1qzR73//e+3fv19169a9oiALCgrk7++v/Px8+fn5XdE5AACoKjfKOHaj3CcAwH1ZNZZVaKn5uXPntGPHDsXExDiVx8TEaMuWLWW2WbVqlSIjIzVz5kw1atRILVq00JNPPqmffvrpyqMGAAAAAKCaqNBS89zcXBUXFyswMNCpPDAwUDk5OWW22b9/v7744gv5+Pjogw8+UG5ursaOHauTJ09e9HvehYWFKiwsdBwXFBRUJEwAAAAAAK4bV7S5ms1mczo2xriUlSopKZHNZtOSJUvUqVMn9e7dW7NmzdLixYsvOuudlJQkf39/xyMkJORKwgQAAAAAoMpVKPGuV6+ePDw8XGa3T5w44TILXiooKEiNGjWSv7+/oyw8PFzGGB05cqTMNpMmTVJ+fr7jcfjw4YqECQAAAADAdaNCibe3t7ciIiKUlpbmVJ6WlqaoqKgy23Tt2lXHjh3Tjz/+6Cjbu3evatSoocaNG5fZxm63y8/Pz+kBAAAAAEB1VOGl5gkJCXrzzTeVkpKizMxMTZw4UVlZWYqPj5d0YbY6Li7OUX/IkCEKCAjQiBEjtGfPHm3atElPPfWURo4cKV9f38q7EwAAAAAArkMV/h3vwYMHKy8vT9OnT1d2drbatGmj1NRUhYaGSpKys7OVlZXlqF+7dm2lpaXp8ccfV2RkpAICAjRo0CC98MILlXcXAAAAAABcpyr8O95Vgd8FBQBUZzfKOHaj3CcAwH1dF7/jDQAAAAAAKobEGwAAN5WcnKywsDD5+PgoIiJCmzdvvmT9JUuWqF27dqpZs6aCgoI0YsQI5eXlXaNoAQBwXyTeAAC4oWXLlmnChAmaMmWKMjIyFB0drdjYWKd9WH7piy++UFxcnEaNGqXdu3dr+fLlSk9P1+jRo69x5AAAuB8SbwAA3NCsWbM0atQojR49WuHh4Zo9e7ZCQkI0b968Mutv27ZNTZs21fjx4xUWFqa77rpLY8aM0fbt269x5AAAuB8SbwAA3My5c+e0Y8cOxcTEOJXHxMRoy5YtZbaJiorSkSNHlJqaKmOMjh8/rhUrVqhPnz7XImQAANwaiTcAAG4mNzdXxcXFCgwMdCoPDAxUTk5OmW2ioqK0ZMkSDR48WN7e3mrYsKHq1KmjOXPmXPQ6hYWFKigocHoAAABXJN4AALgpm83mdGyMcSkrtWfPHo0fP17PP/+8duzYoTVr1ujAgQOKj4+/6PmTkpLk7+/veISEhFRq/AAAuAsSbwAA3Ey9evXk4eHhMrt94sQJl1nwUklJSerataueeuoptW3bVr169VJycrJSUlKUnZ1dZptJkyYpPz/f8Th8+HCl3wsAAO6AxBsAADfj7e2tiIgIpaWlOZWnpaUpKiqqzDZnz55VjRrObws8PDwkXZgpL4vdbpefn5/TAwAAuCLxBgDADSUkJOjNN99USkqKMjMzNXHiRGVlZTmWjk+aNElxcXGO+v369dPKlSs1b9487d+/X19++aXGjx+vTp06KTg4uKpuAwAAt+BZ1QEAAIDKN3jwYOXl5Wn69OnKzs5WmzZtlJqaqtDQUElSdna20296Dx8+XKdPn9Ybb7yhJ554QnXq1NG9996rGTNmVNUtAADgNmzmYuvHriMFBQXy9/dXfn4+y9gAANXOjTKO3Sj3CQBwX1aNZSw1BwAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAcFPJyckKCwuTj4+PIiIitHnz5kvWLyws1JQpUxQaGiq73a7mzZsrJSXlGkULAID78qzqAAAAQOVbtmyZJkyYoOTkZHXt2lULFixQbGys9uzZoyZNmpTZZtCgQTp+/LgWLlyoW265RSdOnFBRUdE1jhwAAPdjM8aYqg7icgoKCuTv76/8/Hz5+flVdTgAAFRIVYxjnTt3VseOHTVv3jxHWXh4uPr376+kpCSX+mvWrNHvf/977d+/X3Xr1r2iazJeAwCqO6vGMpaaAwDgZs6dO6cdO3YoJibGqTwmJkZbtmwps82qVasUGRmpmTNnqlGjRmrRooWefPJJ/fTTTxe9TmFhoQoKCpweAADAFUvNAQBwM7m5uSouLlZgYKBTeWBgoHJycspss3//fn3xxRfy8fHRBx98oNzcXI0dO1YnT5686Pe8k5KSlJiYWOnxAwDgbpjxBgDATdlsNqdjY4xLWamSkhLZbDYtWbJEnTp1Uu/evTVr1iwtXrz4orPekyZNUn5+vuNx+PDhSr8HAADcATPeAAC4mXr16snDw8NldvvEiRMus+ClgoKC1KhRI/n7+zvKwsPDZYzRkSNHdOutt7q0sdvtstvtlRs8AABuiBlvAADcjLe3tyIiIpSWluZUnpaWpqioqDLbdO3aVceOHdOPP/7oKNu7d69q1Kihxo0bWxovAADujsQbAAA3lJCQoDfffFMpKSnKzMzUxIkTlZWVpfj4eEkXlonHxcU56g8ZMkQBAQEaMWKE9uzZo02bNumpp57SyJEj5evrW1W3AQCAW2CpOQAAbmjw4MHKy8vT9OnTlZ2drTZt2ig1NVWhoaGSpOzsbGVlZTnq165dW2lpaXr88ccVGRmpgIAADRo0SC+88EJV3QIAAG6D3/EGAMBiN8o4dqPcJwDAffE73gAAAAAAVEMk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAAAAWIjEGwAAAAAAC5F4AwAAAABgIRJvAAAAAAAsROINAICbSk5OVlhYmHx8fBQREaHNmzeXq92XX34pT09PtW/f3toAAQC4QZB4AwDghpYtW6YJEyZoypQpysjIUHR0tGJjY5WVlXXJdvn5+YqLi1OPHj2uUaQAALg/Em8AANzQrFmzNGrUKI0ePVrh4eGaPXu2QkJCNG/evEu2GzNmjIYMGaIuXbpco0gBAHB/JN4AALiZc+fOaceOHYqJiXEqj4mJ0ZYtWy7abtGiRdq3b5+mTp1qdYgAANxQPKs6AAAAULlyc3NVXFyswMBAp/LAwEDl5OSU2ea7777TM888o82bN8vTs3xvDwoLC1VYWOg4LigouPKgAQBwY8x4AwDgpmw2m9OxMcalTJKKi4s1ZMgQJSYmqkWLFuU+f1JSkvz9/R2PkJCQq44ZAAB3ROINAICbqVevnjw8PFxmt0+cOOEyCy5Jp0+f1vbt2zVu3Dh5enrK09NT06dP165du+Tp6an169eXeZ1JkyYpPz/f8Th8+LAl9wMAQHXHUnMAANyMt7e3IiIilJaWpgEDBjjK09LSdP/997vU9/Pz07fffutUlpycrPXr12vFihUKCwsr8zp2u112u71ygwcAwA2ReAMA4IYSEhI0dOhQRUZGqkuXLvrb3/6mrKwsxcfHS7owW3306FG9/fbbqlGjhtq0aePUvkGDBvLx8XEpBwAAFUfiDQCAGxo8eLDy8vI0ffp0ZWdnq02bNkpNTVVoaKgkKTs7+7K/6Q0AACqHzRhjqjqIyykoKJC/v7/y8/Pl5+dX1eEAAFAhN8o4dqPcJwDAfVk1lrG5GgAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAAAADAQiTeAAAAAABYiMQbAAAAAAALkXgDAAAAAGAhEm8AAAAAACxE4g0AgJtKTk5WWFiYfHx8FBERoc2bN1+07sqVK9WzZ0/Vr19ffn5+6tKli9auXXsNowUAwH2ReAMA4IaWLVumCRMmaMqUKcrIyFB0dLRiY2OVlZVVZv1NmzapZ8+eSk1N1Y4dO9S9e3f169dPGRkZ1zhyAADcj80YY6o6iMspKCiQv7+/8vPz5efnV9XhAABQIVUxjnXu3FkdO3bUvHnzHGXh4eHq37+/kpKSynWO2267TYMHD9bzzz9frvqM1wCA6s6qsYwZbwAA3My5c+e0Y8cOxcTEOJXHxMRoy5Yt5TpHSUmJTp8+rbp16160TmFhoQoKCpweAADAFYk3AABuJjc3V8XFxQoMDHQqDwwMVE5OTrnO8eqrr+rMmTMaNGjQReskJSXJ39/f8QgJCbmquAEAcFck3gAAuCmbzeZ0bIxxKSvL0qVLNW3aNC1btkwNGjS4aL1JkyYpPz/f8Th8+PBVxwwAgDvyrOoAAABA5apXr548PDxcZrdPnDjhMgv+a8uWLdOoUaO0fPly3XfffZesa7fbZbfbrzpeAADcHTPeAAC4GW9vb0VERCgtLc2pPC0tTVFRURdtt3TpUg0fPlzvvPOO+vTpY3WYAADcMJjxBgDADSUkJGjo0KGKjIxUly5d9Le//U1ZWVmKj4+XdGGZ+NGjR/X2229LupB0x8XF6bXXXtOdd97pmC339fWVv79/ld0HAADugMQbAAA3NHjwYOXl5Wn69OnKzs5WmzZtlJqaqtDQUElSdna20296L1iwQEVFRXrsscf02GOPOcqHDRumxYsXX+vwAQBwK/yONwAAFrtRxrEb5T4BAO7ruvod7+TkZIWFhcnHx0cRERHavHlzudp9+eWX8vT0VPv27a/ksgAAAAAAVDsVTryXLVumCRMmaMqUKcrIyFB0dLRiY2OdlquVJT8/X3FxcerRo8cVBwsAAAAAQHVT4cR71qxZGjVqlEaPHq3w8HDNnj1bISEhmjdv3iXbjRkzRkOGDFGXLl2uOFgAAAAAAKqbCiXe586d044dOxQTE+NUHhMToy1btly03aJFi7Rv3z5NnTr1yqIEAAAAAKCaqtCu5rm5uSouLlZgYKBTeWBgoONnR37tu+++0zPPPKPNmzfL07N8lyssLFRhYaHjuKCgoCJhAgAAAABw3biizdVsNpvTsTHGpUySiouLNWTIECUmJqpFixblPn9SUpL8/f0dj5CQkCsJEwAAAACAKlehxLtevXry8PBwmd0+ceKEyyy4JJ0+fVrbt2/XuHHj5OnpKU9PT02fPl27du2Sp6en1q9fX+Z1Jk2apPz8fMfj8OHDFQkTAAAAAIDrRoWWmnt7eysiIkJpaWkaMGCAozwtLU3333+/S30/Pz99++23TmXJyclav369VqxYobCwsDKvY7fbZbfbKxIaAAAAAADXpQol3pKUkJCgoUOHKjIyUl26dNHf/vY3ZWVlKT4+XtKF2eqjR4/q7bffVo0aNdSmTRun9g0aNJCPj49LOQAAAAAA7qjCiffgwYOVl5en6dOnKzs7W23atFFqaqpCQ0MlSdnZ2Zf9TW8AAAAAAG4UNmOMqeogLqegoED+/v7Kz8+Xn59fVYcDAECF3Cjj2I1ynwAA92XVWHZFu5oDAAAAAIDyIfEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AALip5ORkhYWFycfHRxEREdq8efMl62/cuFERERHy8fFRs2bNNH/+/GsUKQAA7o3EGwAAN7Rs2TJNmDBBU6ZMUUZGhqKjoxUbG6usrKwy6x84cEC9e/dWdHS0MjIyNHnyZI0fP17vv//+NY4cAAD3YzPGmKoO4nIKCgrk7++v/Px8+fn5VXU4AABUSFWMY507d1bHjh01b948R1l4eLj69++vpKQkl/p/+tOftGrVKmVmZjrK4uPjtWvXLm3durVc12S8BgBUd1aNZcx4AwDgZs6dO6cdO3YoJibGqTwmJkZbtmwps83WrVtd6vfq1Uvbt2/X+fPnLYsVAIAbgWdVBwAAACpXbm6uiouLFRgY6FQeGBionJycMtvk5OSUWb+oqEi5ubkKCgpyaVNYWKjCwkLHcX5+vqQLswUAAFRHpWNYZS8MJ/EGAMBN2Ww2p2NjjEvZ5eqXVV4qKSlJiYmJLuUhISEVDRUAgOtKXl6e/P39K+18JN4AALiZevXqycPDw2V2+8SJEy6z2qUaNmxYZn1PT08FBASU2WbSpElKSEhwHJ86dUqhoaHKysqq1DcruDADExISosOHD/P9+UpG31qHvrUOfWud/Px8NWnSRHXr1q3U85J4AwDgZry9vRUREaG0tDQNGDDAUZ6Wlqb777+/zDZdunTR6tWrncrWrVunyMhIeXl5ldnGbrfLbre7lPv7+/NG0CJ+fn70rUXoW+vQt9ahb61To0blbofG5moAALihhIQEvfnmm0pJSVFmZqYmTpyorKwsxcfHS7owWx0XF+eoHx8fr0OHDikhIUGZmZlKSUnRwoUL9eSTT1bVLQAA4DaY8QYAwA0NHjxYeXl5mj59urKzs9WmTRulpqYqNDRUkpSdne30m95hYWFKTU3VxIkTNXfuXAUHB+v111/XwIEDq+oWAABwGyTeAAC4qbFjx2rs2LFl/m3x4sUuZd26ddPXX399xdez2+2aOnVqmcvPcXXoW+vQt9ahb61D31rHqr61mcreJ90CVv2IOQAA1wLjGAAANza+4w0AAAAAgIVIvAEAAAAAsBCJNwAAAAAAFiLxBgAA5ZacnKywsDD5+PgoIiJCmzdvvmT9jRs3KiIiQj4+PmrWrJnmz59/jSKtfirStytXrlTPnj1Vv359+fn5qUuXLlq7du01jLZ6qejrttSXX34pT09PtW/f3toAq7GK9m1hYaGmTJmi0NBQ2e12NW/eXCkpKdco2uqlon27ZMkStWvXTjVr1lRQUJBGjBihvLy8axRt9bBp0yb169dPwcHBstls+vDDDy/bprLGMRJvAABQLsuWLdOECRM0ZcoUZWRkKDo6WrGxsU4/S/ZLBw4cUO/evRUdHa2MjAxNnjxZ48eP1/vvv3+NI7/+VbRvN23apJ49eyo1NVU7duxQ9+7d1a9fP2VkZFzjyK9/Fe3bUvn5+YqLi1OPHj2uUaTVz5X07aBBg/TZZ59p4cKF+s9//qOlS5eqVatW1zDq6qGiffvFF18oLi5Oo0aN0u7du7V8+XKlp6dr9OjR1zjy69uZM2fUrl07vfHGG+WqX6njmKkG8vPzjSSTn59f1aEAAFBh7jKOderUycTHxzuVtWrVyjzzzDNl1n/66adNq1atnMrGjBlj7rzzTstirK4q2rdlad26tUlMTKzs0Kq9K+3bwYMHm2effdZMnTrVtGvXzsIIq6+K9u0///lP4+/vb/Ly8q5FeNVaRfv25ZdfNs2aNXMqe/31103jxo0ti7G6k2Q++OCDS9apzHGMGW8AAHBZ586d044dOxQTE+NUHhMToy1btpTZZuvWrS71e/Xqpe3bt+v8+fOWxVrdXEnf/lpJSYlOnz6tunXrWhFitXWlfbto0SLt27dPU6dOtTrEautK+nbVqlWKjIzUzJkz1ahRI7Vo0UJPPvmkfvrpp2sRcrVxJX0bFRWlI0eOKDU1VcYYHT9+XCtWrFCfPn2uRchuqzLHMc/KDAwAALin3NxcFRcXKzAw0Kk8MDBQOTk5ZbbJyckps35RUZFyc3MVFBRkWbzVyZX07a+9+uqrOnPmjAYNGmRFiNXWlfTtd999p2eeeUabN2+WpydvlS/mSvp2//79+uKLL+Tj46MPPvhAubm5Gjt2rE6ePMn3vH/hSvo2KipKS5Ys0eDBg/Xzzz+rqKhIv/3tbzVnzpxrEbLbqsxxjBlvAABQbjabzenYGONSdrn6ZZWj4n1baunSpZo2bZqWLVumBg0aWBVetVbevi0uLtaQIUOUmJioFi1aXKvwqrWKvG5LSkpks9m0ZMkSderUSb1799asWbO0ePFiZr3LUJG+3bNnj8aPH6/nn39eO3bs0Jo1a3TgwAHFx8dfi1DdWmWNY3yMBwAALqtevXry8PBwmW05ceKEy2xAqYYNG5ZZ39PTUwEBAZbFWt1cSd+WWrZsmUaNGqXly5frvvvuszLMaqmifXv69Glt375dGRkZGjdunKQLyaIxRp6enlq3bp3uvffeaxL79e5KXrdBQUFq1KiR/P39HWXh4eEyxujIkSO69dZbLY25uriSvk1KSlLXrl311FNPSZLatm2rWrVqKTo6Wi+88AIrjK5QZY5jzHgDAIDL8vb2VkREhNLS0pzK09LSFBUVVWabLl26uNRft26dIiMj5eXlZVms1c2V9K10YaZ7+PDheuedd/ge50VUtG/9/Pz07bffaufOnY5HfHy8WrZsqZ07d6pz587XKvTr3pW8brt27apjx47pxx9/dJTt3btXNWrUUOPGjS2Ntzq5kr49e/asatRwTu08PDwk/XeGFhVXqeNYhbdjqwLushssAODG5C7j2Lvvvmu8vLzMwoULzZ49e8yECRNMrVq1zMGDB40xxjzzzDNm6NChjvr79+83NWvWNBMnTjR79uwxCxcuNF5eXmbFihVVdQvXrYr27TvvvGM8PT3N3LlzTXZ2tuNx6tSpqrqF61ZF+/bX2NX84irat6dPnzaNGzc2DzzwgNm9e7fZuHGjufXWW83o0aOr6hauWxXt20WLFhlPT0+TnJxs9u3bZ7744gsTGRlpOnXqVFW3cF06ffq0ycjIMBkZGUaSmTVrlsnIyDCHDh0yxlg7jpF4AwBgMXcax+bOnWtCQ0ONt7e36dixo9m4caPjb8OGDTPdunVzqv/555+bDh06GG9vb9O0aVMzb968axxx9VGRvu3WrZuR5PIYNmzYtQ+8Gqjo6/aXSLwvraJ9m5mZae677z7j6+trGjdubBISEszZs2evcdTVQ0X79vXXXzetW7c2vr6+JigoyPzhD38wR44cucZRX982bNhwyf93WjmO2Yy5/tceFBQUyN/fX/n5+fLz86vqcAAAqBDGMQAAbmx8xxsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAAAAAYCESbwAAAAAALETiDQAAAACAhUi8AQAAAACwEIk3AAAAAAAWIvEGAAAAAMBCJN4AAAAAAFiIxBsAAAAAAAuReAMAANxAdu3aJZvNpv/85z+SpL/+9a9q2rRphc6xf/9+jRs3Ti1atJCvr69q1qyp2267Tc8++6yOHj1qQdTSli1bNG3aNJ06dcqS81elgwcPymaz6ZVXXqnqUPT555/LZrNpxYoVVR1KpTh79qymTZumzz///IrPcezYMU2bNk07d+6stLhw4yHxBgAAuIGkp6erTp06atGihSRp27Zt6tSpU7nbf/zxx2rbtq0+/vhjPfLII/r4448d/7169Wr17dvXkri3bNmixMREt0y8YZ2zZ88qMTHxqhPvxMREEm9cFc+qDgAAAADXTnp6ujp16iSbzSbpQuL9+OOPl6vtgQMH9Pvf/14tWrTQhg0b5O/v7/jbvffeq/Hjx+uDDz6wJO7q7vz587LZbPL05O23RH/gxsOMNwAAwA2kNPGWpJycHGVlZZV7xnvWrFk6c+aMkpOTnZLuUjabTb/73e8cx02bNtXw4cNd6t1zzz265557HMclJSV64YUX1LJlS/n6+qpOnTpq27atXnvtNUnStGnT9NRTT0mSwsLCZLPZZLPZHLOYJSUlmjlzplq1aiW73a4GDRooLi5OR44ccblumzZttHXrVkVFRcnX11dNmzbVokWLJEmffPKJOnbsqJo1a+r222/XmjVrXGL/7rvvNGTIEDVo0EB2u13h4eGaO3euU53S5dp///vf9cQTT6hRo0ay2+36/vvvL9m/JSUlevHFF9WkSRP5+PgoMjJSn332mePvmzdvls1m09KlS13avv3227LZbEpPT7/kNY4ePapHHnlEISEh8vb2VnBwsB544AEdP37cqd758+c1ZcoUBQcHy8/PT/fdd5/j6wmlyvv8Xqo/hg8frtq1a+v7779X7969Vbt2bYWEhOiJJ55QYWHhJe9FktavX6977rlHAQEB8vX1VZMmTTRw4ECdPXtWBw8eVP369SVJiYmJjtdNaczff/+9RowYoVtvvVU1a9ZUo0aN1K9fP3377bdOsd9xxx2SpBEjRjjOMW3atDLvtdTw4cNdvsIxb948tWvXTrVr19ZNN92kVq1aafLkyZe9R7gHPmICAABwc02bNtWhQ4ccxxkZGXrhhRccx926dZMkDRs2TIsXL77oedatW6fAwEDdeeedlRrfzJkzNW3aND377LO6++67df78ef373/92LCsfPXq0Tp48qTlz5mjlypUKCgqSJLVu3VqS9Oijj+pvf/ubxo0bp759++rgwYN67rnn9Pnnn+vrr79WvXr1HNfKycnRiBEj9PTTT6tx48aaM2eORo4cqcOHD2vFihWaPHmy/P39NX36dPXv31/79+9XcHCwJGnPnj2KiopSkyZN9Oqrr6phw4Zau3atxo8fr9zcXE2dOtXpviZNmqQuXbpo/vz5qlGjhho0aHDJfnjjjTcUGhqq2bNnOz5MiI2N1caNG9WlSxdFR0erQ4cOmjt3rh566CGXtnfccYcjSSzL0aNHdccdd+j8+fOaPHmy2rZtq7y8PK1du1b/93//p8DAQEfdyZMnq2vXrnrzzTdVUFCgP/3pT+rXr58yMzPl4eFxmWe0bBfrj/Pnz+u3v/2tRo0apSeeeEKbNm3Sn//8Z/n7++v555+/6PkOHjyoPn36KDo6WikpKapTp46OHj2qNWvW6Ny5cwoKCtKaNWv0m9/8RqNGjdLo0aMlyZGMHzt2TAEBAfrLX/6i+vXr6+TJk3rrrbfUuXNnZWRkqGXLlurYsaMWLVqkESNG6Nlnn1WfPn0kSY0bN67Qvb/77rsaO3asHn/8cb3yyiuqUaOGvv/+e+3Zs+dKuhLVkakG8vPzjSSTn59f1aEAAFBhjGOoart37zYZGRlm5syZxtvb26Snp5uMjAzTv39/07VrV5ORkWEyMjLMoUOHLnkeHx8fc+edd5b7uqGhoWbYsGEu5d26dTPdunVzHPft29e0b9/+kud6+eWXjSRz4MABp/LMzEwjyYwdO9ap/F//+peRZCZPnux0XUlm+/btjrK8vDzj4eFhfH19zdGjRx3lO3fuNJLM66+/7ijr1auXady4scu/5XHjxhkfHx9z8uRJY4wxGzZsMJLM3Xfffcl7KnXgwAEjyQQHB5uffvrJUV5QUGDq1q1r7rvvPkfZokWLjCSTkZHhKPvqq6+MJPPWW29d8jojR440Xl5eZs+ePRetUxp77969ncrfe+89I8ls3brVUVbe5/dS/TFs2DAjybz33ntO5b179zYtW7a85P2sWLHCSDI7d+68aJ0ffvjBSDJTp0695LmMMaaoqMicO3fO3HrrrWbixImO8vT0dCPJLFq0yKXNr++11LBhw0xoaKjjeNy4caZOnTqXjQHui6XmAAAAbq5169Zq3769jh07pjvuuEORkZFq37699u7dq549e6p9+/Zq3769mjRpUiXxderUSbt27dLYsWO1du1aFRQUlLvthg0bJMllyXOnTp0UHh7utFRbkoKCghQREeE4rlu3rho0aKD27ds7ZrYlKTw8XJIcKwV+/vlnffbZZxowYIBq1qypoqIix6N37976+eeftW3bNqdrDRw4sNz3IUm/+93v5OPj4zi+6aab1K9fP23atEnFxcWSpIceekgNGjRwWt4+Z84c1a9fX4MHD77k+f/5z3+qe/fujnu7lN/+9rdOx23btpUkp5UTFXWx/rDZbOrXr5/L9S53rfbt28vb21uPPPKI3nrrLe3fv79C8RQVFemll15S69at5e3tLU9PT3l7e+u7775TZmZmhc51OZ06ddKpU6f00EMP6aOPPlJubm6lnh/XPxJvAAAAN1ZcXOxIEDdu3Ki77rpLRUVFOnHihDIzM9W1a1cVFRU5ErtLadKkiQ4cOFDpMU6aNEmvvPKKtm3bptjYWAUEBKhHjx7avn37Zdvm5eVJkmP5+S8FBwc7/l6qbt26LvW8vb1dyr29vSVdSLhLr1NUVKQ5c+bIy8vL6dG7d29JckmmyorpUho2bFhm2blz5/Tjjz9Kkux2u8aMGaN33nlHp06d0g8//KD33ntPo0ePlt1uv+T5f/jhh3IvkQ4ICHA6Lj33Tz/9VK72ZblYf9SsWdPpA4fS65X2/cU0b95cn376qRo0aKDHHntMzZs3V/PmzR17A1xOQkKCnnvuOfXv31+rV6/Wv/71L6Wnp6tdu3ZXdZ9lGTp0qFJSUnTo0CENHDhQDRo0UOfOnZWWllap18H1i8QbAADAjfXo0cORIGZkZGjGjBny8vJSYGCgjDHq2bOnvLy81KNHj8ueq1evXjp+/LjLzO7F+Pj4lLlB1q8TVE9PTyUkJOjrr7/WyZMntXTpUh0+fFi9evXS2bNnL3mN0gQxOzvb5W/Hjh1z+n731bj55pvl4eGh4cOHKz09vcxHaQJeqnTn+PLKyckps8zb21u1a9d2lD366KM6f/68UlJS9P/+3/9TUVGR4uPjL3v++vXru2w4dzXK+/yWqmh/lEd0dLRWr16t/Px8bdu2TV26dNGECRP07rvvXrbtP/7xD8XFxemll15Sr1691KlTJ0VGRlZoNroifTBixAht2bJF+fn5+uSTT2SMUd++fa9qFQGqDxJvAAAAN7ZgwQKlp6frpZdekq+vr7Zt26b09HT169dPd999tyNpXLBgwWXPNXHiRNWqVUtjx45Vfn6+y9+NMU4/J9a0aVN98803TnX27t3rsjv2L9WpU0cPPPCAHnvsMZ08eVIHDx6UdPEZ13vvvVfShSTql9LT05WZmVmuDxTKo2bNmurevbsyMjLUtm1bRUZGujx+PUtcUStXrnSa5T19+rRWr16t6Ohopw3NgoKC9OCDDyo5OVnz589Xv379yvU1gdjYWG3YsOGS/V8RV/L8WsXDw0OdO3d2LMH/+uuvJV16pt5ms7msEvjkk0909OhRp7JLnaNp06bau3evU/Kdl5enLVu2XDTWWrVqKTY2VlOmTNG5c+e0e/fu8twiqjl2NQcAAHBjLVu2lCQlJyerR48e6ty5s6QLO5s/88wzioyMLPe5wsLC9O6772rw4MFq3769xo0bpw4dOki6sON3SkqKjDEaMGCApAvLax9++GGNHTtWAwcO1KFDhzRz5kzHrtKl+vXrpzZt2igyMlL169fXoUOHNHv2bIWGhurWW2+VJN1+++2SpNdee03Dhg2Tl5eXWrZsqZYtW+qRRx7RnDlzVKNGDcXGxjp2NQ8JCdHEiROvrgN/4bXXXtNdd92l6OhoPfroo2ratKlOnz6t77//XqtXr9b69euv6vweHh7q2bOnEhISVFJSohkzZqigoECJiYkudf/nf/7H8VyW/hza5UyfPl3//Oc/dffdd2vy5Mm6/fbbderUKa1Zs0YJCQlq1apVheIt7/Nrlfnz52v9+vXq06ePmjRpop9//lkpKSmSpPvuu0/She/Jh4aG6qOPPlKPHj1Ut25d1atXT02bNlXfvn21ePFitWrVSm3bttWOHTv08ssvuyzHb968uXx9fbVkyRKFh4erdu3aCg4OVnBwsIYOHaoFCxbo4Ycf1h//+Efl5eVp5syZ8vPzczrHH//4R/n6+qpr164KCgpSTk6OkpKS5O/vf8md6OFGqnZvt/JhN1gAQHXGOIaqVlxcbOrXr28WLFhgjDHm66+/NpIuu4v5xezbt8+MHTvW3HLLLcZutxtfX1/TunVrk5CQ4LTreElJiZk5c6Zp1qyZ8fHxMZGRkWb9+vUuO0G/+uqrJioqytSrV894e3ubJk2amFGjRpmDBw86XXfSpEkmODjY1KhRw0gyGzZscNzfjBkzTIsWLYyXl5epV6+eefjhh83hw4ed2nfr1s3cdtttLvcTGhpq+vTp41IuyTz22GNOZQcOHDAjR440jRo1Ml5eXqZ+/fomKirKvPDCC446pbt4L1++vFz9Wbqr+YwZM0xiYqJp3Lix8fb2Nh06dDBr1669aLumTZua8PDwcl2j1OHDh83IkSNNw4YNjZeXlwkODjaDBg0yx48fv2TspTH+cmfv8j6/l+qPYcOGmVq1armUT5061VwuVdm6dasZMGCACQ0NNXa73QQEBJhu3bqZVatWOdX79NNPTYcOHYzdbjeSHDux/9///Z8ZNWqUadCggalZs6a56667zObNm8vcqXzp0qWmVatWxsvLy2WX9LfeesuEh4cbHx8f07p1a7Ns2TKXXc3feust0717dxMYGGi8vb0d/f7NN99c8h7hPmzGGFMlGX8FFBQUyN/fX/n5+S6fHgEAcL1jHANQ2b755hu1a9dOc+fO1dixY6s6HACXwVJzAAAAoJrYt2+fDh06pMmTJysoKMjlZ9QAXJ/YXA0AAACoJv785z+rZ8+e+vHHH7V8+XLVrFmzqkMCUA4sNQcAwGKMYwAA3NiY8QYAwA1t2rRJ/fr1U3BwsGw2mz788MPLttm4caMiIiLk4+OjZs2aaf78+dYHCgDADYDEGwAAN3TmzBm1a9dOb7zxRrnqHzhwQL1791Z0dLQyMjI0efJkjR8/Xu+//77FkQIA4P7YXA0AADcUGxur2NjYctefP3++mjRpotmzZ0uSwsPDtX37dr3yyisaOHCgRVECAHBjYMYbAABo69atiomJcSrr1auXtm/frvPnz1dRVAAAuAdmvAEAgHJychQYGOhUFhgYqKKiIuXm5iooKMilTWFhoQoLCx3HJSUlOnnypAICAmSz2SyPGQCAymaM0enTpxUcHKwaNSpvnprEGwAASJJLslz6wycXS6KTkpKUmJhoeVwAAFxrhw8fVuPGjSvtfCTeAABADRs2VE5OjlPZiRMn5OnpqYCAgDLbTJo0SQkJCY7j/Px8NWnSRIcPH+Zn0wAA1VJBQYFCQkJ00003Vep5SbwBAIC6dOmi1atXO5WtW7dOkZGR8vLyKrON3W6X3W53Kffz8yPxBgBUa5X9lSk2VwMAwA39+OOP2rlzp3bu3Cnpws+F7dy5U1lZWZIuzFbHxcU56sfHx+vQoUNKSEhQZmamUlJStHDhQj355JNVET4AAG6FGW8AANzQ9u3b1b17d8dx6ZLwYcOGafHixcrOznYk4ZIUFham1NRUTZw4UXPnzlVwcLBef/11fkoMAIBKYDOlO6dcxwoKCuTv76/8/HyWrgEAqp0bZRy7Ue4TAOC+rBrLWGoOAAAAAICFSLwBAAAAALAQiTcAAAAAABYi8QYAAAAAwEIk3gAAAACA/9/e/cbWWZ73A78cO7YDk08VAiYQ1zVdaVOi0sVWgp1FVRlxFRBVpE3xxESABgmrtCHxYEuWiT8RktVORIUOp1ASEFLIPChMvPAAv9jAELYVz0xVE4mK0DqhNpFdYafQOY3z/F6g+DfXDuSY3P5z8vlIz4tzc9/nXM8tmyvf85zjh4QEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AaAAtXW1hY1NTVRXl4etbW10dXV9bHz9+7dG1deeWWcd955sXjx4rjlllticHBwmqoFgMIleANAAWpvb4/NmzfH9u3bo6enJ1avXh1r166N3t7eSee/+uqrsWHDhti4cWP8/Oc/j6effjp++tOfxq233jrNlQNA4RG8AaAA7dy5MzZu3Bi33nprLF26NH7wgx9EVVVV7Nq1a9L5//Ef/xGf+9znYtOmTVFTUxN/+qd/Grfddlu88cYb01w5ABQewRsACszx48eju7s7Ghsbx403NjbG/v37J13T0NAQR44ciY6OjsiyLN5777145pln4rrrrjvt64yMjMTw8PC4AwCYSPAGgAIzMDAQo6OjUVlZOW68srIy+vv7J13T0NAQe/fujaampigtLY2LL744PvOZz8QPf/jD075Oa2tr5HK5saOqquqsngcAFArBGwAKVFFR0bjHWZZNGDvlwIEDsWnTprj77ruju7s7XnjhhXjnnXeiubn5tM+/bdu2GBoaGjsOHz58VusHgEJRMtMFAABn16JFi6K4uHjC1e2jR49OuAp+Smtra6xatSruuuuuiIj4yle+Eueff36sXr067r///li8ePGENWVlZVFWVnb2TwAACowr3gBQYEpLS6O2tjY6OzvHjXd2dkZDQ8Okaz788MOYN2/8PwuKi4sj4qMr5QDA1AneAFCAWlpa4rHHHos9e/bEwYMHY8uWLdHb2zv20fFt27bFhg0bxuZff/318eyzz8auXbvi0KFD8dprr8WmTZtixYoVcckll8zUaQBAQfBRcwAoQE1NTTE4OBg7duyIvr6+WLZsWXR0dER1dXVERPT19Y27p/fNN98cx44di3/8x3+Mv/7rv47PfOYzcfXVV8f3vve9mToFACgYRdkc+PzY8PBw5HK5GBoaioqKipkuBwDycq70sXPlPAEoXKl6mY+aAwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJDSl4N3W1hY1NTVRXl4etbW10dXVddq5zz77bKxZsyYuvPDCqKioiPr6+njxxRenXDAAAADMJXkH7/b29ti8eXNs3749enp6YvXq1bF27dro7e2ddP4rr7wSa9asiY6Ojuju7o6vf/3rcf3110dPT8+nLh4AAABmu6Isy7J8FqxcuTKWL18eu3btGhtbunRprFu3LlpbW8/oOa644opoamqKu++++4zmp7qJOQBMh3Olj50r5wlA4UrVy/K64n38+PHo7u6OxsbGceONjY2xf//+M3qOkydPxrFjx2LhwoWnnTMyMhLDw8PjDgAAAJiL8greAwMDMTo6GpWVlePGKysro7+//4ye44EHHogPPvgg1q9ff9o5ra2tkcvlxo6qqqp8ygQAAIBZY0p/XK2oqGjc4yzLJoxNZt++fXHvvfdGe3t7XHTRRaedt23bthgaGho7Dh8+PJUyAQAAYMaV5DN50aJFUVxcPOHq9tGjRydcBf9D7e3tsXHjxnj66afjmmuu+di5ZWVlUVZWlk9pAAAAMCvldcW7tLQ0amtro7Ozc9x4Z2dnNDQ0nHbdvn374uabb46nnnoqrrvuuqlVCgAAAHNQXle8IyJaWlrixhtvjLq6uqivr49HH300ent7o7m5OSI++pj4u+++G08++WREfBS6N2zYEA8++GBcddVVY1fLFyxYELlc7iyeCgAAAMw+eQfvpqamGBwcjB07dkRfX18sW7YsOjo6orq6OiIi+vr6xt3T+5FHHokTJ07E7bffHrfffvvY+E033RRPPPHEpz8DAAAAmMXyvo/3THBfUADmsnOlj50r5wlA4ZoV9/EGAAAA8iN4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJCR4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3ABSotra2qKmpifLy8qitrY2urq6PnT8yMhLbt2+P6urqKCsri89//vOxZ8+eaaoWAApXyUwXAACcfe3t7bF58+Zoa2uLVatWxSOPPBJr166NAwcOxGc/+9lJ16xfvz7ee++92L17d/zxH/9xHD16NE6cODHNlQNA4SnKsiyb6SI+yfDwcORyuRgaGoqKioqZLgcA8jITfWzlypWxfPny2LVr19jY0qVLY926ddHa2jph/gsvvBB/+Zd/GYcOHYqFCxdO6TX1awDmulS9zEfNAaDAHD9+PLq7u6OxsXHceGNjY+zfv3/SNc8//3zU1dXF97///bj00kvj8ssvjzvvvDN+97vfTUfJAFDQfNQcAArMwMBAjI6ORmVl5bjxysrK6O/vn3TNoUOH4tVXX43y8vJ47rnnYmBgIL797W/Hb37zm9N+z3tkZCRGRkbGHg8PD5+9kwCAAuKKNwAUqKKionGPsyybMHbKyZMno6ioKPbu3RsrVqyIa6+9Nnbu3BlPPPHEaa96t7a2Ri6XGzuqqqrO+jkAQCEQvAGgwCxatCiKi4snXN0+evTohKvgpyxevDguvfTSyOVyY2NLly6NLMviyJEjk67Ztm1bDA0NjR2HDx8+eycBAAVE8AaAAlNaWhq1tbXR2dk5bryzszMaGhomXbNq1ar49a9/Hb/97W/Hxt56662YN29eLFmyZNI1ZWVlUVFRMe4AACYSvAGgALW0tMRjjz0We/bsiYMHD8aWLVuit7c3mpubI+Kjq9UbNmwYm3/DDTfEBRdcELfcckscOHAgXnnllbjrrrviW9/6VixYsGCmTgMACoI/rgYABaipqSkGBwdjx44d0dfXF8uWLYuOjo6orq6OiIi+vr7o7e0dm/9Hf/RH0dnZGd/97nejrq4uLrjggli/fn3cf//9M3UKAFAw3McbABI7V/rYuXKeABQu9/EGAACAOUjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAChQbW1tUVNTE+Xl5VFbWxtdXV1ntO61116LkpKS+OpXv5q2QAA4RwjeAFCA2tvbY/PmzbF9+/bo6emJ1atXx9q1a6O3t/dj1w0NDcWGDRviz/7sz6apUgAofII3ABSgnTt3xsaNG+PWW2+NpUuXxg9+8IOoqqqKXbt2fey62267LW644Yaor6+fpkoBoPAJ3gBQYI4fPx7d3d3R2Ng4bryxsTH2799/2nWPP/54vP3223HPPfec0euMjIzE8PDwuAMAmEjwBoACMzAwEKOjo1FZWTluvLKyMvr7+ydd84tf/CK2bt0ae/fujZKSkjN6ndbW1sjlcmNHVVXVp64dAAqR4A0ABaqoqGjc4yzLJoxFRIyOjsYNN9wQ9913X1x++eVn/Pzbtm2LoaGhsePw4cOfumYAKERn9pY2ADBnLFq0KIqLiydc3T569OiEq+AREceOHYs33ngjenp64jvf+U5ERJw8eTKyLIuSkpJ46aWX4uqrr56wrqysLMrKytKcBAAUEFe8AaDAlJaWRm1tbXR2do4b7+zsjIaGhgnzKyoq4mc/+1m8+eabY0dzc3N88YtfjDfffDNWrlw5XaUDQEFyxRsAClBLS0vceOONUVdXF/X19fHoo49Gb29vNDc3R8RHHxN/991348knn4x58+bFsmXLxq2/6KKLory8fMI4AJA/wRsAClBTU1MMDg7Gjh07oq+vL5YtWxYdHR1RXV0dERF9fX2feE9vAODsKMqyLJvpIj7J8PBw5HK5GBoaioqKipkuBwDycq70sXPlPAEoXKl6me94AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJCR4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJCR4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJCR4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3AAAAJCR4AwAAQEKCNwAAACQkeAMAAEBCgjcAAAAkJHgDAABAQoI3ABSotra2qKmpifLy8qitrY2urq7Tzn322WdjzZo1ceGFF0ZFRUXU19fHiy++OI3VAkDhErwBoAC1t7fH5s2bY/v27dHT0xOrV6+OtWvXRm9v76TzX3nllVizZk10dHREd3d3fP3rX4/rr78+enp6prlyACg8RVmWZTNdxCcZHh6OXC4XQ0NDUVFRMdPlAEBeZqKPrVy5MpYvXx67du0aG1u6dGmsW7cuWltbz+g5rrjiimhqaoq77777jObr1wDMdal6mSveAFBgjh8/Ht3d3dHY2DhuvLGxMfbv339Gz3Hy5Mk4duxYLFy4MEWJAHBOKZnpAgCAs2tgYCBGR0ejsrJy3HhlZWX09/ef0XM88MAD8cEHH8T69etPO2dkZCRGRkbGHg8PD0+tYAAocK54A0CBKioqGvc4y7IJY5PZt29f3HvvvdHe3h4XXXTRaee1trZGLpcbO6qqqj51zQBQiARvACgwixYtiuLi4glXt48ePTrhKvgfam9vj40bN8Y///M/xzXXXPOxc7dt2xZDQ0Njx+HDhz917QBQiARvACgwpaWlUVtbG52dnePGOzs7o6Gh4bTr9u3bFzfffHM89dRTcd11133i65SVlUVFRcW4AwCYyHe8AaAAtbS0xI033hh1dXVRX18fjz76aPT29kZzc3NEfHS1+t13340nn3wyIj4K3Rs2bIgHH3wwrrrqqrGr5QsWLIhcLjdj5wEAhUDwBoAC1NTUFIODg7Fjx47o6+uLZcuWRUdHR1RXV0dERF9f37h7ej/yyCNx4sSJuP322+P2228fG7/pppviiSeemO7yAaCguI83ACR2rvSxc+U8AShc7uMNAAAAc5DgDQAAAAkJ3gAAAJCQ4A0AAAAJCd4AAACQkOANAAAACQneAAAAkJDgDQAAAAkJ3gAAAJCQ4A0AAAAJCd4AAACQkOANAAAACQneAAAAkJDgDQAAAAkJ3gAAAJCQ4A0AAAAJCd4AAACQkOANAAAACQneAAAAkJDgDQAAAAkJ3gAAAJCQ4A0AAAAJCd4AAACQkOANAAAACQneAAAAkJDgDQAAAAkJ3gAAAJCQ4A0AAAAJCd4AAACQkOANAAAACU0peLe1tUVNTU2Ul5dHbW1tdHV1fez8l19+OWpra6O8vDwuu+yy+NGPfjSlYgGAM6dfA8DskHfwbm9vj82bN8f27dujp6cnVq9eHWvXro3e3t5J57/zzjtx7bXXxurVq6Onpyf+7u/+LjZt2hQ/+clPPnXxAMDk9GsAmD2KsizL8lmwcuXKWL58eezatWtsbOnSpbFu3bpobW2dMP9v//Zv4/nnn4+DBw+OjTU3N8f//M//xOuvv35Grzk8PBy5XC6GhoaioqIin3IBYMbNRB/TrwEgf6l6WUk+k48fPx7d3d2xdevWceONjY2xf//+Sde8/vrr0djYOG7sG9/4RuzevTt+//vfx/z58yesGRkZiZGRkbHHQ0NDEfHRJgDAXHOqf+X5XveU6dcAMDWpenZewXtgYCBGR0ejsrJy3HhlZWX09/dPuqa/v3/S+SdOnIiBgYFYvHjxhDWtra1x3333TRivqqrKp1wAmFUGBwcjl8slfx39GgA+nbPds/MK3qcUFRWNe5xl2YSxT5o/2fgp27Zti5aWlrHH77//flRXV0dvb++0/IPlXDI8PBxVVVVx+PBhHws8y+xtOvY2HXubxtDQUHz2s5+NhQsXTuvr6teFw+9mOvY2HXubjr1NJ1XPzit4L1q0KIqLiye8W3706NEJ75KfcvHFF086v6SkJC644IJJ15SVlUVZWdmE8Vwu5wcrkYqKCnubiL1Nx96mY2/TmDdveu7iqV8XLr+b6djbdOxtOvY2nbPds/N6ttLS0qitrY3Ozs5x452dndHQ0DDpmvr6+gnzX3rppairq5v0+2IAwKejXwPA7JJ3jG9paYnHHnss9uzZEwcPHowtW7ZEb29vNDc3R8RHHzvbsGHD2Pzm5ub41a9+FS0tLXHw4MHYs2dP7N69O+68886zdxYAwDj6NQDMHnl/x7upqSkGBwdjx44d0dfXF8uWLYuOjo6orq6OiIi+vr5x9witqamJjo6O2LJlSzz88MNxySWXxEMPPRR//ud/fsavWVZWFvfcc8+kH2fj07G36djbdOxtOvY2jZnYV/26sNjbdOxtOvY2HXubTqq9zfs+3gAAAMCZm56/8gIAAADnKMEbAAAAEhK8AQAAICHBGwAAABKaNcG7ra0tampqory8PGpra6Orq+tj57/88stRW1sb5eXlcdlll8WPfvSjaap07slnb5999tlYs2ZNXHjhhVFRURH19fXx4osvTmO1c0e+P7OnvPbaa1FSUhJf/epX0xY4h+W7tyMjI7F9+/aorq6OsrKy+PznPx979uyZpmrnlnz3du/evXHllVfGeeedF4sXL45bbrklBgcHp6naueOVV16J66+/Pi655JIoKiqKf/mXf/nENXO1j+nX6ejX6ejZ6ejZ6ejZZ9+M9utsFvinf/qnbP78+dmPf/zj7MCBA9kdd9yRnX/++dmvfvWrSecfOnQoO++887I77rgjO3DgQPbjH/84mz9/fvbMM89Mc+WzX757e8cdd2Tf+973sv/6r//K3nrrrWzbtm3Z/Pnzs//+7/+e5spnt3z39ZT3338/u+yyy7LGxsbsyiuvnJ5i55ip7O03v/nNbOXKlVlnZ2f2zjvvZP/5n/+Zvfbaa9NY9dyQ7952dXVl8+bNyx588MHs0KFDWVdXV3bFFVdk69atm+bKZ7+Ojo5s+/bt2U9+8pMsIrLnnnvuY+fP1T6mX6ejX6ejZ6ejZ6ejZ6cxk/16VgTvFStWZM3NzePGvvSlL2Vbt26ddP7f/M3fZF/60pfGjd12223ZVVddlazGuSrfvZ3Ml7/85ey+++4726XNaVPd16ampuzv//7vs3vuuUcTP4189/Zf//Vfs1wulw0ODk5HeXNavnv7D//wD9lll102buyhhx7KlixZkqzGQnAmjXyu9jH9Oh39Oh09Ox09Ox09O73p7tcz/lHz48ePR3d3dzQ2No4bb2xsjP3790+65vXXX58w/xvf+Ea88cYb8fvf/z5ZrXPNVPb2D508eTKOHTsWCxcuTFHinDTVfX388cfj7bffjnvuuSd1iXPWVPb2+eefj7q6uvj+978fl156aVx++eVx5513xu9+97vpKHnOmMreNjQ0xJEjR6KjoyOyLIv33nsvnnnmmbjuuuumo+SCNhf7mH6djn6djp6djp6djp49e5zNPlZyNgubioGBgRgdHY3Kyspx45WVldHf3z/pmv7+/knnnzhxIgYGBmLx4sXJ6p1LprK3f+iBBx6IDz74INavX5+ixDlpKvv6i1/8IrZu3RpdXV1RUjLjv3az1lT29tChQ/Hqq69GeXl5PPfcczEwMBDf/va34ze/+Y3vjP0fU9nbhoaG2Lt3bzQ1NcX//u//xokTJ+Kb3/xm/PCHP5yOkgvaXOxj+nU6+nU6enY6enY6evbscTb72Ixf8T6lqKho3OMsyyaMfdL8ycbJf29P2bdvX9x7773R3t4eF110Uary5qwz3dfR0dG44YYb4r777ovLL798usqb0/L5mT158mQUFRXF3r17Y8WKFXHttdfGzp0744knnvAO+iTy2dsDBw7Epk2b4u67747u7u544YUX4p133onm5ubpKLXgzdU+pl+no1+no2eno2eno2fPDmerj83423iLFi2K4uLiCe/eHD16dMK7C6dcfPHFk84vKSmJCy64IFmtc81U9vaU9vb22LhxYzz99NNxzTXXpCxzzsl3X48dOxZvvPFG9PT0xHe+852I+KjxZFkWJSUl8dJLL8XVV189LbXPdlP5mV28eHFceumlkcvlxsaWLl0aWZbFkSNH4gtf+ELSmueKqexta2trrFq1Ku66666IiPjKV74S559/fqxevTruv/9+Vys/hbnYx/TrdPTrdPTsdPTsdPTs2eNs9rEZv+JdWloatbW10dnZOW68s7MzGhoaJl1TX18/Yf5LL70UdXV1MX/+/GS1zjVT2duIj945v/nmm+Opp57yvZBJ5LuvFRUV8bOf/SzefPPNsaO5uTm++MUvxptvvhkrV66crtJnvan8zK5atSp+/etfx29/+9uxsbfeeivmzZsXS5YsSVrvXDKVvf3www9j3rzxbaK4uDgi/v+7vUzNXOxj+nU6+nU6enY6enY6evbscVb7WN5/ji2BU38uf/fu3dmBAweyzZs3Z+eff372y1/+MsuyLNu6dWt24403js0/9Wfdt2zZkh04cCDbvXu325OcRr57+9RTT2UlJSXZww8/nPX19Y0d77///kydwqyU777+IX8h9fTy3dtjx45lS5Ysyf7iL/4i+/nPf569/PLL2Re+8IXs1ltvnalTmLXy3dvHH388Kykpydra2rK33347e/XVV7O6urpsxYoVM3UKs9axY8eynp6erKenJ4uIbOfOnVlPT8/YbV8KpY/p1+no1+no2eno2eno2WnMZL+eFcE7y7Ls4Ycfzqqrq7PS0tJs+fLl2csvvzz232666absa1/72rj5//7v/579yZ/8SVZaWpp97nOfy3bt2jXNFc8d+ezt1772tSwiJhw33XTT9Bc+y+X7M/t/aeIfL9+9PXjwYHbNNddkCxYsyJYsWZK1tLRkH3744TRXPTfku7cPPfRQ9uUvfzlbsGBBtnjx4uyv/uqvsiNHjkxz1bPfv/3bv33s/zsLqY/p1+no1+no2eno2eno2WffTPbroizz2QMAAABIZca/4w0AAACFTPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICEBG8AAABISPAGAACAhARvAAAASEjwBgAAgIQEbwAAAEhI8AYAAICE/h8yHeID4CgasAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure size\n",
    "fig = plt.figure(figsize = (10, 8))\n",
    "\n",
    "# Create a grid for plots (3 rows & 2 columns)\n",
    "gs = gridspec.GridSpec(nrows = 3, ncols = 2, figure = fig)\n",
    "\n",
    "ax1 = fig.add_subplot(gs[:, :1]);\n",
    "ax1.set_title('# Customer by payment method');\n",
    "\n",
    "ax2 = fig.add_subplot(gs[0, 1]);\n",
    "ax2.set_title('# Customer by gender');\n",
    "\n",
    "ax3 = fig.add_subplot(gs[1, 1]);\n",
    "ax3.set_title('# Customer by paperless bill status');\n",
    "\n",
    "ax4 = fig.add_subplot(gs[2, 1]);\n",
    "ax4.set_title('# Customer by churn status');\n",
    "\n",
    "# Remove the overlaps between the axis names and the titles\n",
    "plt.tight_layout();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}