diff --git "a/AdultNoteBook/Kernels/ExtraTrees/.ipynb_checkpoints/11-adult-checkpoint.ipynb" "b/AdultNoteBook/Kernels/ExtraTrees/.ipynb_checkpoints/11-adult-checkpoint.ipynb"
new file mode 100644--- /dev/null
+++ "b/AdultNoteBook/Kernels/ExtraTrees/.ipynb_checkpoints/11-adult-checkpoint.ipynb"
@@ -0,0 +1,4523 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "vAXJY9IYpyo_"
+   },
+   "source": [
+    "# IMPORT LIBRARIES"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "id": "BkN0B_q5pUNz"
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import io\n",
+    "import requests\n",
+    "from matplotlib import pyplot as plt\n",
+    "import seaborn as sns\n",
+    "#import pickle\n",
+    "import os\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "pd.options.display.float_format = '{:,.1f}'.format"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "1qve4Lzq_bld"
+   },
+   "source": [
+    "# DATA EXPLORATION"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "id": "W97jFjE-_xwp"
+   },
+   "outputs": [],
+   "source": [
+    "columns = ['age', 'workClass', 'fnlwgt', 'education', 'education-num','marital-status', 'occupation', 'relationship','race', 'sex', 'capital-gain', 'capital-loss', 'hours-per-week', 'native-country', 'income']\n",
+    "train_data = pd.read_csv('../input/adult-census-income/adult.csv', names=columns, na_values='?',skiprows=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "id": "OBaOogmcCkfE",
+    "outputId": "1c5fa89c-3407-4cd5-dbf4-f92ca6db71f4"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['age', 'fnlwgt', 'education-num', 'capital-gain', 'capital-loss',\n",
+       "       'hours-per-week'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(32561, 6)\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_numerics = ['int8','int16', 'int32', 'int64', 'float16', 'float32', 'float64']\n",
+    "display(train_data.select_dtypes(include=data_numerics).columns)\n",
+    "print(train_data.select_dtypes(include=data_numerics).shape)\n",
+    "data_numerics = train_data.select_dtypes(include=data_numerics)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "id": "DrkiCYxjCxMa",
+    "outputId": "1d324e48-962a-406e-eb11-4136159e6d78"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['workClass', 'education', 'marital-status', 'occupation',\n",
+       "       'relationship', 'race', 'sex', 'native-country', 'income'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(32561, 9)\n"
+     ]
+    }
+   ],
+   "source": [
+    "display(train_data.select_dtypes(include=['object']).columns)\n",
+    "print(train_data.select_dtypes(include=object).shape)\n",
+    "data_cat = train_data.select_dtypes(include=['object'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "id": "pTtZfXVYDNpq",
+    "outputId": "d803856f-045d-4b2b-f980-6343b1f92c82"
+   },
+   "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>age</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education-num</th>\n",
+       "      <th>capital-gain</th>\n",
+       "      <th>capital-loss</th>\n",
+       "      <th>hours-per-week</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>32,561.0</td>\n",
+       "      <td>32,561.0</td>\n",
+       "      <td>32,561.0</td>\n",
+       "      <td>32,561.0</td>\n",
+       "      <td>32,561.0</td>\n",
+       "      <td>32,561.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>38.6</td>\n",
+       "      <td>189,778.4</td>\n",
+       "      <td>10.1</td>\n",
+       "      <td>1,077.6</td>\n",
+       "      <td>87.3</td>\n",
+       "      <td>40.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>13.6</td>\n",
+       "      <td>105,550.0</td>\n",
+       "      <td>2.6</td>\n",
+       "      <td>7,385.3</td>\n",
+       "      <td>403.0</td>\n",
+       "      <td>12.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>17.0</td>\n",
+       "      <td>12,285.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>28.0</td>\n",
+       "      <td>117,827.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>40.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>37.0</td>\n",
+       "      <td>178,356.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>40.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>48.0</td>\n",
+       "      <td>237,051.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>45.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>90.0</td>\n",
+       "      <td>1,484,705.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>99,999.0</td>\n",
+       "      <td>4,356.0</td>\n",
+       "      <td>99.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           age      fnlwgt  education-num  capital-gain  capital-loss  \\\n",
+       "count 32,561.0    32,561.0       32,561.0      32,561.0      32,561.0   \n",
+       "mean      38.6   189,778.4           10.1       1,077.6          87.3   \n",
+       "std       13.6   105,550.0            2.6       7,385.3         403.0   \n",
+       "min       17.0    12,285.0            1.0           0.0           0.0   \n",
+       "25%       28.0   117,827.0            9.0           0.0           0.0   \n",
+       "50%       37.0   178,356.0           10.0           0.0           0.0   \n",
+       "75%       48.0   237,051.0           12.0           0.0           0.0   \n",
+       "max       90.0 1,484,705.0           16.0      99,999.0       4,356.0   \n",
+       "\n",
+       "       hours-per-week  \n",
+       "count        32,561.0  \n",
+       "mean             40.4  \n",
+       "std              12.3  \n",
+       "min               1.0  \n",
+       "25%              40.0  \n",
+       "50%              40.0  \n",
+       "75%              45.0  \n",
+       "max              99.0  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data[['age', 'fnlwgt', 'education-num', 'capital-gain', 'capital-loss','hours-per-week']].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "id": "nBMJC9MqDokX",
+    "outputId": "8fc621d3-2e1b-4051-9c11-84a3a3fc749d"
+   },
+   "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>workClass</th>\n",
+       "      <th>education</th>\n",
+       "      <th>marital-status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>native-country</th>\n",
+       "      <th>income</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>30725</td>\n",
+       "      <td>32561</td>\n",
+       "      <td>32561</td>\n",
+       "      <td>30718</td>\n",
+       "      <td>32561</td>\n",
+       "      <td>32561</td>\n",
+       "      <td>32561</td>\n",
+       "      <td>31978</td>\n",
+       "      <td>32561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>unique</th>\n",
+       "      <td>8</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14</td>\n",
+       "      <td>6</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>41</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>top</th>\n",
+       "      <td>Private</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>freq</th>\n",
+       "      <td>22696</td>\n",
+       "      <td>10501</td>\n",
+       "      <td>14976</td>\n",
+       "      <td>4140</td>\n",
+       "      <td>13193</td>\n",
+       "      <td>27816</td>\n",
+       "      <td>21790</td>\n",
+       "      <td>29170</td>\n",
+       "      <td>24720</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       workClass education      marital-status      occupation relationship  \\\n",
+       "count      30725     32561               32561           30718        32561   \n",
+       "unique         8        16                   7              14            6   \n",
+       "top      Private   HS-grad  Married-civ-spouse  Prof-specialty      Husband   \n",
+       "freq       22696     10501               14976            4140        13193   \n",
+       "\n",
+       "         race    sex native-country income  \n",
+       "count   32561  32561          31978  32561  \n",
+       "unique      5      2             41      2  \n",
+       "top     White   Male  United-States  <=50K  \n",
+       "freq    27816  21790          29170  24720  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data[['workClass', 'education', 'marital-status', 'occupation',\n",
+    "       'relationship', 'race', 'sex', 'native-country', 'income']].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "id": "SKHiu-CxC9LI",
+    "outputId": "bb7c9c3e-c0cb-4fa9-82f1-d290cae54112"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function matplotlib.pyplot.show(*args, **kw)>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x504 with 6 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "features = ['age', 'fnlwgt', 'education-num', 'capital-gain', 'capital-loss','hours-per-week']\n",
+    "plt.figure(figsize=(15, 7))\n",
+    "for i in range(0, len(features)):\n",
+    "    plt.subplot(1, 6, i+1)\n",
+    "    sns.boxplot(train_data[features[i]],color='#982642')\n",
+    "    plt.tight_layout()\n",
+    "    \n",
+    "plt.show"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "id": "S8cNXUfoEVst",
+    "outputId": "6b59f746-413f-40ca-d2eb-7f460b4f9c45"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function matplotlib.pyplot.show(*args, **kw)>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x432 with 12 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_num = train_data[features]\n",
+    "k = len(data_num.columns)\n",
+    "n = 3\n",
+    "m = (k - 1) // n + 1\n",
+    "fig, axes = plt.subplots(m, n, figsize=(n * 5, m * 3))\n",
+    "for i, (name, col) in enumerate(data_num.iteritems()):\n",
+    "    r, c = i // n, i % n\n",
+    "    ax = axes[r, c]\n",
+    "    col.hist(ax=ax, color='#73bbff')\n",
+    "    ax2 = col.plot.kde(ax=ax, secondary_y=True, title=name, color='red')\n",
+    "    ax2.set_ylim(0)\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "plt.show"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "id": "4IEC7GjPVsoL",
+    "outputId": "6832a800-aa9e-4517-e1f3-290eaec37e5d"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_category = list(train_data['workClass'].unique())\n",
+    "\n",
+    "c = [data_category]\n",
+    "plt.figure(figsize=(15,10))\n",
+    "for i in range(0, len(c)):\n",
+    "    plt.subplot(1, 1, i+1)\n",
+    "    ax = sns.countplot(x='workClass',data=train_data[train_data['workClass'].isin(c[i])])\n",
+    "    for p in ax.patches:\n",
+    "        ax.annotate('{:.0f}'.format(p.get_height()),\n",
+    "        xy = (p.get_x() + p.get_width() / 2, p.get_height()),     \n",
+    "        xytext=(0,3),fontsize=10,\n",
+    "        textcoords=\"offset points\",\n",
+    "        ha ='center', va ='bottom')\n",
+    "        plt.xticks(rotation=90)\n",
+    "        \n",
+    "ax.set_ylabel(\"\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "id": "3giwLdRCaK2O",
+    "outputId": "d84bfc30-bf47-46dc-8bc0-f1d4473d5406"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 864x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_category = list(train_data['occupation'].unique())\n",
+    "\n",
+    "c = [data_category]\n",
+    "plt.figure(figsize=(12,10))\n",
+    "for i in range(0, len(c)):\n",
+    "    plt.subplot(1, 1, i+1)\n",
+    "    ax = sns.countplot(x='occupation',data=train_data[train_data['occupation'].isin(c[i])])\n",
+    "    for p in ax.patches:\n",
+    "        ax.annotate('{:.0f}'.format(p.get_height()),\n",
+    "        xy = (p.get_x() + p.get_width() / 2, p.get_height()),     \n",
+    "        xytext=(0,3),fontsize=10,\n",
+    "        textcoords=\"offset points\",\n",
+    "        ha ='center', va ='bottom')\n",
+    "        plt.xticks(rotation=90)\n",
+    "        \n",
+    "ax.set_ylabel(\"\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JmzmOzDQ6gUd"
+   },
+   "source": [
+    "# DATA CLEANSING"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "B3cyeO0vBAP2"
+   },
+   "source": [
+    "## Missing Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "id": "rcaIZodRAquM",
+    "outputId": "35f2c412-21d2-47cc-ccbd-7cbdd7f59614"
+   },
+   "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>feature</th>\n",
+       "      <th>missing_value</th>\n",
+       "      <th>percentage</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>occupation</td>\n",
+       "      <td>1843</td>\n",
+       "      <td>5.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>workClass</td>\n",
+       "      <td>1836</td>\n",
+       "      <td>5.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>native-country</td>\n",
+       "      <td>583</td>\n",
+       "      <td>1.8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          feature  missing_value  percentage\n",
+       "0      occupation           1843         5.7\n",
+       "1       workClass           1836         5.6\n",
+       "2  native-country            583         1.8"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_missing_value = train_data.isnull().sum().reset_index()\n",
+    "data_missing_value.columns = ['feature','missing_value']\n",
+    "data_missing_value['percentage'] = round((data_missing_value['missing_value']/len(train_data))*100,2)\n",
+    "data_missing_value = data_missing_value.sort_values('percentage', ascending=False).reset_index(drop=True)\n",
+    "data_missing_value = data_missing_value[data_missing_value['percentage']>0]\n",
+    "data_missing_value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "id": "pZNefImBAs14",
+    "outputId": "f0962e5c-23b4-4efb-9894-5eaf06493077"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function matplotlib.pyplot.show(*args, **kw)>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = data_missing_value['feature']\n",
+    "y = data_missing_value['percentage']\n",
+    "plt.figure(figsize=(10,8))\n",
+    "barh = plt.bar(x=x, height=y, data=data_missing_value, \n",
+    "       color = '#842e2e', \n",
+    "       edgecolor= '#2e2e2e',\n",
+    "       linewidth = 2) \n",
+    "\n",
+    "plt.title('Missing Value', fontsize = 16)\n",
+    "plt.ylabel('Persentage', fontsize=14)\n",
+    "plt.xlabel('Feature', fontsize=14)\n",
+    "\n",
+    "x_numbers = range(len(x))\n",
+    "for i in x_numbers:\n",
+    "    plt.text(x = x_numbers[i]-0.12,y = y[i]+0.08,s = str(round(y[i],2))+'%',size = 15)\n",
+    "plt.tight_layout\n",
+    "plt.show"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iDKUpT6GMBoV"
+   },
+   "source": [
+    "### Missing Values 'workClass'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "id": "ppXXU_vTLVFd",
+    "outputId": "3d4371e7-350e-46dc-c02c-45f9a353dab3"
+   },
+   "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>age</th>\n",
+       "      <th>workClass</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>90</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>82</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>66</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>54</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>41</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32556</th>\n",
+       "      <td>22</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32557</th>\n",
+       "      <td>27</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32558</th>\n",
+       "      <td>40</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32559</th>\n",
+       "      <td>58</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32560</th>\n",
+       "      <td>22</td>\n",
+       "      <td>Private</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>32561 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       age workClass\n",
+       "0       90       NaN\n",
+       "1       82   Private\n",
+       "2       66       NaN\n",
+       "3       54   Private\n",
+       "4       41   Private\n",
+       "...    ...       ...\n",
+       "32556   22   Private\n",
+       "32557   27   Private\n",
+       "32558   40   Private\n",
+       "32559   58   Private\n",
+       "32560   22   Private\n",
+       "\n",
+       "[32561 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data[['age','workClass']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "id": "o8g1EqubK3DY"
+   },
+   "outputs": [],
+   "source": [
+    "def conditions(s):\n",
+    "    if (s['age'] >= 18) and (s['workClass'] is np.nan):\n",
+    "        return 'Without-pay'\n",
+    "    elif (s['age'] < 18) and (s['workClass'] is np.nan):\n",
+    "        return 'Never-worked'\n",
+    "    else:\n",
+    "        return s['workClass']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "id": "G59SP1PBLX2P"
+   },
+   "outputs": [],
+   "source": [
+    "train_data['workClass'] = train_data.apply(conditions, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nYoyHVdLMxdu"
+   },
+   "source": [
+    "### Missing Values 'Occupation'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "id": "x86v6dG0M4Iy"
+   },
+   "outputs": [],
+   "source": [
+    "train_data['occupation'] = train_data['occupation'].fillna('Other')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "uLTdEdqsMSoa"
+   },
+   "source": [
+    "### Missing Values 'Native-country'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "id": "twCospnVGFuS"
+   },
+   "outputs": [],
+   "source": [
+    "train_data.dropna(subset=['native-country'],inplace=True)\n",
+    "train_data.dropna(subset=['income'],inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Rmc1C2ErBFob"
+   },
+   "source": [
+    "## Duplicate Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "id": "VczFlH1jptIL",
+    "outputId": "b10e1771-9710-4ffe-dc29-0098fcb69109"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Jumlah duplicate values yang ada di data frame ada 23\n"
+     ]
+    },
+    {
+     "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>age</th>\n",
+       "      <th>workClass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education-num</th>\n",
+       "      <th>marital-status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital-gain</th>\n",
+       "      <th>capital-loss</th>\n",
+       "      <th>hours-per-week</th>\n",
+       "      <th>native-country</th>\n",
+       "      <th>income</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>32419</th>\n",
+       "      <td>35</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>379959</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18906</th>\n",
+       "      <td>35</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>379959</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19832</th>\n",
+       "      <td>44</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>367749</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>13</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23720</th>\n",
+       "      <td>44</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>367749</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>13</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7978</th>\n",
+       "      <td>25</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>308144</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>13</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8453</th>\n",
+       "      <td>25</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>308144</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>13</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11777</th>\n",
+       "      <td>28</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>274679</td>\n",
+       "      <td>Masters</td>\n",
+       "      <td>14</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>50</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27133</th>\n",
+       "      <td>28</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>274679</td>\n",
+       "      <td>Masters</td>\n",
+       "      <td>14</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>50</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28796</th>\n",
+       "      <td>27</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>255582</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9067</th>\n",
+       "      <td>27</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>255582</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32065</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>251579</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7615</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>251579</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8356</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>250051</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12202</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>250051</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17344</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>243368</td>\n",
+       "      <td>Preschool</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Farming-fishing</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>50</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11261</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>243368</td>\n",
+       "      <td>Preschool</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Farming-fishing</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>50</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22595</th>\n",
+       "      <td>23</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>240137</td>\n",
+       "      <td>5th-6th</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Handlers-cleaners</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26738</th>\n",
+       "      <td>23</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>240137</td>\n",
+       "      <td>5th-6th</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Handlers-cleaners</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29604</th>\n",
+       "      <td>38</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>207202</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>48</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&gt;50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8500</th>\n",
+       "      <td>38</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>207202</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>48</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&gt;50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29051</th>\n",
+       "      <td>42</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>204235</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&gt;50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13260</th>\n",
+       "      <td>42</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>204235</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&gt;50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15603</th>\n",
+       "      <td>25</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>195994</td>\n",
+       "      <td>1st-4th</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Priv-house-serv</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Guatemala</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23660</th>\n",
+       "      <td>25</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>195994</td>\n",
+       "      <td>1st-4th</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Priv-house-serv</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Guatemala</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9305</th>\n",
+       "      <td>25</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>195994</td>\n",
+       "      <td>1st-4th</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Priv-house-serv</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Guatemala</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18417</th>\n",
+       "      <td>46</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>173243</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19067</th>\n",
+       "      <td>46</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>173243</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22934</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>146679</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Exec-managerial</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>Black</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17456</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>146679</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Exec-managerial</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>Black</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10307</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>138153</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Adm-clerical</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22783</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>138153</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Adm-clerical</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14634</th>\n",
+       "      <td>46</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>133616</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Adm-clerical</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31060</th>\n",
+       "      <td>46</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>133616</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Adm-clerical</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14346</th>\n",
+       "      <td>20</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>107658</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Tech-support</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9269</th>\n",
+       "      <td>20</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>107658</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Tech-support</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19622</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>97261</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Farming-fishing</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20507</th>\n",
+       "      <td>19</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>97261</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Farming-fishing</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8645</th>\n",
+       "      <td>90</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>52386</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>Asian-Pac-Islander</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6227</th>\n",
+       "      <td>90</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>52386</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Never-married</td>\n",
+       "      <td>Other-service</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>Asian-Pac-Islander</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10357</th>\n",
+       "      <td>49</td>\n",
+       "      <td>Self-emp-not-inc</td>\n",
+       "      <td>43479</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23827</th>\n",
+       "      <td>49</td>\n",
+       "      <td>Self-emp-not-inc</td>\n",
+       "      <td>43479</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11121</th>\n",
+       "      <td>49</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>31267</td>\n",
+       "      <td>7th-8th</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23276</th>\n",
+       "      <td>49</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>31267</td>\n",
+       "      <td>7th-8th</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29334</th>\n",
+       "      <td>39</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>30916</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26531</th>\n",
+       "      <td>39</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>30916</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Married-civ-spouse</td>\n",
+       "      <td>Craft-repair</td>\n",
+       "      <td>Husband</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       age         workClass  fnlwgt     education  education-num  \\\n",
+       "32419   35           Private  379959       HS-grad              9   \n",
+       "18906   35           Private  379959       HS-grad              9   \n",
+       "19832   44           Private  367749     Bachelors             13   \n",
+       "23720   44           Private  367749     Bachelors             13   \n",
+       "7978    25           Private  308144     Bachelors             13   \n",
+       "8453    25           Private  308144     Bachelors             13   \n",
+       "11777   28           Private  274679       Masters             14   \n",
+       "27133   28           Private  274679       Masters             14   \n",
+       "28796   27           Private  255582       HS-grad              9   \n",
+       "9067    27           Private  255582       HS-grad              9   \n",
+       "32065   19           Private  251579  Some-college             10   \n",
+       "7615    19           Private  251579  Some-college             10   \n",
+       "8356    21           Private  250051  Some-college             10   \n",
+       "12202   21           Private  250051  Some-college             10   \n",
+       "17344   21           Private  243368     Preschool              1   \n",
+       "11261   21           Private  243368     Preschool              1   \n",
+       "22595   23           Private  240137       5th-6th              3   \n",
+       "26738   23           Private  240137       5th-6th              3   \n",
+       "29604   38           Private  207202       HS-grad              9   \n",
+       "8500    38           Private  207202       HS-grad              9   \n",
+       "29051   42           Private  204235  Some-college             10   \n",
+       "13260   42           Private  204235  Some-college             10   \n",
+       "15603   25           Private  195994       1st-4th              2   \n",
+       "23660   25           Private  195994       1st-4th              2   \n",
+       "9305    25           Private  195994       1st-4th              2   \n",
+       "18417   46           Private  173243       HS-grad              9   \n",
+       "19067   46           Private  173243       HS-grad              9   \n",
+       "22934   19           Private  146679  Some-college             10   \n",
+       "17456   19           Private  146679  Some-college             10   \n",
+       "10307   19           Private  138153  Some-college             10   \n",
+       "22783   19           Private  138153  Some-college             10   \n",
+       "14634   46           Private  133616  Some-college             10   \n",
+       "31060   46           Private  133616  Some-college             10   \n",
+       "14346   20           Private  107658  Some-college             10   \n",
+       "9269    20           Private  107658  Some-college             10   \n",
+       "19622   19           Private   97261       HS-grad              9   \n",
+       "20507   19           Private   97261       HS-grad              9   \n",
+       "8645    90           Private   52386  Some-college             10   \n",
+       "6227    90           Private   52386  Some-college             10   \n",
+       "10357   49  Self-emp-not-inc   43479  Some-college             10   \n",
+       "23827   49  Self-emp-not-inc   43479  Some-college             10   \n",
+       "11121   49           Private   31267       7th-8th              4   \n",
+       "23276   49           Private   31267       7th-8th              4   \n",
+       "29334   39           Private   30916       HS-grad              9   \n",
+       "26531   39           Private   30916       HS-grad              9   \n",
+       "\n",
+       "           marital-status         occupation   relationship  \\\n",
+       "32419            Divorced      Other-service  Not-in-family   \n",
+       "18906            Divorced      Other-service  Not-in-family   \n",
+       "19832       Never-married     Prof-specialty  Not-in-family   \n",
+       "23720       Never-married     Prof-specialty  Not-in-family   \n",
+       "7978        Never-married       Craft-repair  Not-in-family   \n",
+       "8453        Never-married       Craft-repair  Not-in-family   \n",
+       "11777       Never-married     Prof-specialty  Not-in-family   \n",
+       "27133       Never-married     Prof-specialty  Not-in-family   \n",
+       "28796       Never-married  Machine-op-inspct  Not-in-family   \n",
+       "9067        Never-married  Machine-op-inspct  Not-in-family   \n",
+       "32065       Never-married      Other-service      Own-child   \n",
+       "7615        Never-married      Other-service      Own-child   \n",
+       "8356        Never-married     Prof-specialty      Own-child   \n",
+       "12202       Never-married     Prof-specialty      Own-child   \n",
+       "17344       Never-married    Farming-fishing  Not-in-family   \n",
+       "11261       Never-married    Farming-fishing  Not-in-family   \n",
+       "22595       Never-married  Handlers-cleaners  Not-in-family   \n",
+       "26738       Never-married  Handlers-cleaners  Not-in-family   \n",
+       "29604  Married-civ-spouse  Machine-op-inspct        Husband   \n",
+       "8500   Married-civ-spouse  Machine-op-inspct        Husband   \n",
+       "29051  Married-civ-spouse     Prof-specialty        Husband   \n",
+       "13260  Married-civ-spouse     Prof-specialty        Husband   \n",
+       "15603       Never-married    Priv-house-serv  Not-in-family   \n",
+       "23660       Never-married    Priv-house-serv  Not-in-family   \n",
+       "9305        Never-married    Priv-house-serv  Not-in-family   \n",
+       "18417  Married-civ-spouse       Craft-repair        Husband   \n",
+       "19067  Married-civ-spouse       Craft-repair        Husband   \n",
+       "22934       Never-married    Exec-managerial      Own-child   \n",
+       "17456       Never-married    Exec-managerial      Own-child   \n",
+       "10307       Never-married       Adm-clerical      Own-child   \n",
+       "22783       Never-married       Adm-clerical      Own-child   \n",
+       "14634            Divorced       Adm-clerical      Unmarried   \n",
+       "31060            Divorced       Adm-clerical      Unmarried   \n",
+       "14346       Never-married       Tech-support  Not-in-family   \n",
+       "9269        Never-married       Tech-support  Not-in-family   \n",
+       "19622       Never-married    Farming-fishing  Not-in-family   \n",
+       "20507       Never-married    Farming-fishing  Not-in-family   \n",
+       "8645        Never-married      Other-service  Not-in-family   \n",
+       "6227        Never-married      Other-service  Not-in-family   \n",
+       "10357  Married-civ-spouse       Craft-repair        Husband   \n",
+       "23827  Married-civ-spouse       Craft-repair        Husband   \n",
+       "11121  Married-civ-spouse       Craft-repair        Husband   \n",
+       "23276  Married-civ-spouse       Craft-repair        Husband   \n",
+       "29334  Married-civ-spouse       Craft-repair        Husband   \n",
+       "26531  Married-civ-spouse       Craft-repair        Husband   \n",
+       "\n",
+       "                     race     sex  capital-gain  capital-loss  hours-per-week  \\\n",
+       "32419               White  Female             0             0              40   \n",
+       "18906               White  Female             0             0              40   \n",
+       "19832               White  Female             0             0              45   \n",
+       "23720               White  Female             0             0              45   \n",
+       "7978                White    Male             0             0              40   \n",
+       "8453                White    Male             0             0              40   \n",
+       "11777               White    Male             0             0              50   \n",
+       "27133               White    Male             0             0              50   \n",
+       "28796               White  Female             0             0              40   \n",
+       "9067                White  Female             0             0              40   \n",
+       "32065               White    Male             0             0              14   \n",
+       "7615                White    Male             0             0              14   \n",
+       "8356                White  Female             0             0              10   \n",
+       "12202               White  Female             0             0              10   \n",
+       "17344               White    Male             0             0              50   \n",
+       "11261               White    Male             0             0              50   \n",
+       "22595               White    Male             0             0              55   \n",
+       "26738               White    Male             0             0              55   \n",
+       "29604               White    Male             0             0              48   \n",
+       "8500                White    Male             0             0              48   \n",
+       "29051               White    Male             0             0              40   \n",
+       "13260               White    Male             0             0              40   \n",
+       "15603               White  Female             0             0              40   \n",
+       "23660               White  Female             0             0              40   \n",
+       "9305                White  Female             0             0              40   \n",
+       "18417               White    Male             0             0              40   \n",
+       "19067               White    Male             0             0              40   \n",
+       "22934               Black    Male             0             0              30   \n",
+       "17456               Black    Male             0             0              30   \n",
+       "10307               White  Female             0             0              10   \n",
+       "22783               White  Female             0             0              10   \n",
+       "14634               White  Female             0             0              40   \n",
+       "31060               White  Female             0             0              40   \n",
+       "14346               White  Female             0             0              10   \n",
+       "9269                White  Female             0             0              10   \n",
+       "19622               White    Male             0             0              40   \n",
+       "20507               White    Male             0             0              40   \n",
+       "8645   Asian-Pac-Islander    Male             0             0              35   \n",
+       "6227   Asian-Pac-Islander    Male             0             0              35   \n",
+       "10357               White    Male             0             0              40   \n",
+       "23827               White    Male             0             0              40   \n",
+       "11121               White    Male             0             0              40   \n",
+       "23276               White    Male             0             0              40   \n",
+       "29334               White    Male             0             0              40   \n",
+       "26531               White    Male             0             0              40   \n",
+       "\n",
+       "      native-country income  \n",
+       "32419  United-States  <=50K  \n",
+       "18906  United-States  <=50K  \n",
+       "19832         Mexico  <=50K  \n",
+       "23720         Mexico  <=50K  \n",
+       "7978          Mexico  <=50K  \n",
+       "8453          Mexico  <=50K  \n",
+       "11777  United-States  <=50K  \n",
+       "27133  United-States  <=50K  \n",
+       "28796  United-States  <=50K  \n",
+       "9067   United-States  <=50K  \n",
+       "32065  United-States  <=50K  \n",
+       "7615   United-States  <=50K  \n",
+       "8356   United-States  <=50K  \n",
+       "12202  United-States  <=50K  \n",
+       "17344         Mexico  <=50K  \n",
+       "11261         Mexico  <=50K  \n",
+       "22595         Mexico  <=50K  \n",
+       "26738         Mexico  <=50K  \n",
+       "29604  United-States   >50K  \n",
+       "8500   United-States   >50K  \n",
+       "29051  United-States   >50K  \n",
+       "13260  United-States   >50K  \n",
+       "15603      Guatemala  <=50K  \n",
+       "23660      Guatemala  <=50K  \n",
+       "9305       Guatemala  <=50K  \n",
+       "18417  United-States  <=50K  \n",
+       "19067  United-States  <=50K  \n",
+       "22934  United-States  <=50K  \n",
+       "17456  United-States  <=50K  \n",
+       "10307  United-States  <=50K  \n",
+       "22783  United-States  <=50K  \n",
+       "14634  United-States  <=50K  \n",
+       "31060  United-States  <=50K  \n",
+       "14346  United-States  <=50K  \n",
+       "9269   United-States  <=50K  \n",
+       "19622  United-States  <=50K  \n",
+       "20507  United-States  <=50K  \n",
+       "8645   United-States  <=50K  \n",
+       "6227   United-States  <=50K  \n",
+       "10357  United-States  <=50K  \n",
+       "23827  United-States  <=50K  \n",
+       "11121  United-States  <=50K  \n",
+       "23276  United-States  <=50K  \n",
+       "29334  United-States  <=50K  \n",
+       "26531  United-States  <=50K  "
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print('Jumlah duplicate values yang ada di data frame ada' ,train_data.duplicated().sum())\n",
+    "duplicate_data = train_data[train_data.duplicated(keep=False)]\n",
+    "duplicate_data.sort_values('fnlwgt', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "id": "ignrn5Yo6i-P"
+   },
+   "outputs": [],
+   "source": [
+    "train_data = train_data.drop_duplicates()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "id": "XVKS613_ld3I",
+    "outputId": "44ecb7cd-3102-4af5-977a-cb61d364a2b8"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---- age ---\n",
+      "36    875\n",
+      "23    870\n",
+      "31    870\n",
+      "34    862\n",
+      "33    862\n",
+      "     ... \n",
+      "83      6\n",
+      "85      3\n",
+      "88      3\n",
+      "87      1\n",
+      "86      1\n",
+      "Name: age, Length: 73, dtype: int64\n",
+      "---- workClass ---\n",
+      "Private             22264\n",
+      "Self-emp-not-inc     2498\n",
+      "Local-gov            2067\n",
+      "Without-pay          1759\n",
+      "State-gov            1279\n",
+      "Self-emp-inc         1074\n",
+      "Federal-gov           943\n",
+      "Never-worked           71\n",
+      "Name: workClass, dtype: int64\n",
+      "---- fnlwgt ---\n",
+      "203488    13\n",
+      "123011    13\n",
+      "113364    12\n",
+      "121124    12\n",
+      "148995    12\n",
+      "          ..\n",
+      "48702      1\n",
+      "378045     1\n",
+      "34361      1\n",
+      "357943     1\n",
+      "125489     1\n",
+      "Name: fnlwgt, Length: 21406, dtype: int64\n",
+      "---- education ---\n",
+      "HS-grad         10362\n",
+      "Some-college     7178\n",
+      "Bachelors        5208\n",
+      "Masters          1673\n",
+      "Assoc-voc        1366\n",
+      "11th             1167\n",
+      "Assoc-acdm       1055\n",
+      "10th              921\n",
+      "7th-8th           626\n",
+      "Prof-school       559\n",
+      "9th               506\n",
+      "12th              417\n",
+      "Doctorate         390\n",
+      "5th-6th           317\n",
+      "1st-4th           161\n",
+      "Preschool          49\n",
+      "Name: education, dtype: int64\n",
+      "---- education-num ---\n",
+      "9     10362\n",
+      "10     7178\n",
+      "13     5208\n",
+      "14     1673\n",
+      "11     1366\n",
+      "7      1167\n",
+      "12     1055\n",
+      "6       921\n",
+      "4       626\n",
+      "15      559\n",
+      "5       506\n",
+      "8       417\n",
+      "16      390\n",
+      "3       317\n",
+      "2       161\n",
+      "1        49\n",
+      "Name: education-num, dtype: int64\n",
+      "---- marital-status ---\n",
+      "Married-civ-spouse       14686\n",
+      "Never-married            10473\n",
+      "Divorced                  4392\n",
+      "Separated                 1005\n",
+      "Widowed                    979\n",
+      "Married-spouse-absent      397\n",
+      "Married-AF-spouse           23\n",
+      "Name: marital-status, dtype: int64\n",
+      "---- occupation ---\n",
+      "Prof-specialty       4034\n",
+      "Craft-repair         4025\n",
+      "Exec-managerial      3991\n",
+      "Adm-clerical         3719\n",
+      "Sales                3584\n",
+      "Other-service        3209\n",
+      "Machine-op-inspct    1964\n",
+      "Other                1816\n",
+      "Transport-moving     1572\n",
+      "Handlers-cleaners    1349\n",
+      "Farming-fishing       987\n",
+      "Tech-support          911\n",
+      "Protective-serv       644\n",
+      "Priv-house-serv       141\n",
+      "Armed-Forces            9\n",
+      "Name: occupation, dtype: int64\n",
+      "---- relationship ---\n",
+      "Husband           12941\n",
+      "Not-in-family      8144\n",
+      "Own-child          5001\n",
+      "Unmarried          3383\n",
+      "Wife               1534\n",
+      "Other-relative      952\n",
+      "Name: relationship, dtype: int64\n",
+      "---- race ---\n",
+      "White                 27409\n",
+      "Black                  3027\n",
+      "Asian-Pac-Islander      955\n",
+      "Amer-Indian-Eskimo      311\n",
+      "Other                   253\n",
+      "Name: race, dtype: int64\n",
+      "---- sex ---\n",
+      "Male      21356\n",
+      "Female    10599\n",
+      "Name: sex, dtype: int64\n",
+      "---- capital-gain ---\n",
+      "0        29297\n",
+      "15024      341\n",
+      "7688       275\n",
+      "7298       242\n",
+      "99999      152\n",
+      "         ...  \n",
+      "5060         1\n",
+      "1639         1\n",
+      "2538         1\n",
+      "7978         1\n",
+      "1111         1\n",
+      "Name: capital-gain, Length: 119, dtype: int64\n",
+      "---- capital-loss ---\n",
+      "0       30472\n",
+      "1902      197\n",
+      "1977      163\n",
+      "1887      157\n",
+      "1848       51\n",
+      "        ...  \n",
+      "3004        1\n",
+      "1844        1\n",
+      "2489        1\n",
+      "2201        1\n",
+      "2472        1\n",
+      "Name: capital-loss, Length: 92, dtype: int64\n",
+      "---- hours-per-week ---\n",
+      "40    14920\n",
+      "50     2770\n",
+      "45     1783\n",
+      "60     1439\n",
+      "35     1276\n",
+      "      ...  \n",
+      "92        1\n",
+      "94        1\n",
+      "87        1\n",
+      "74        1\n",
+      "82        1\n",
+      "Name: hours-per-week, Length: 94, dtype: int64\n",
+      "---- native-country ---\n",
+      "United-States                 29153\n",
+      "Mexico                          639\n",
+      "Philippines                     198\n",
+      "Germany                         137\n",
+      "Canada                          121\n",
+      "Puerto-Rico                     114\n",
+      "El-Salvador                     106\n",
+      "India                           100\n",
+      "Cuba                             95\n",
+      "England                          90\n",
+      "Jamaica                          81\n",
+      "South                            80\n",
+      "China                            75\n",
+      "Italy                            73\n",
+      "Dominican-Republic               70\n",
+      "Vietnam                          67\n",
+      "Japan                            62\n",
+      "Guatemala                        62\n",
+      "Poland                           60\n",
+      "Columbia                         59\n",
+      "Taiwan                           51\n",
+      "Haiti                            44\n",
+      "Iran                             43\n",
+      "Portugal                         37\n",
+      "Nicaragua                        34\n",
+      "Peru                             31\n",
+      "Greece                           29\n",
+      "France                           29\n",
+      "Ecuador                          28\n",
+      "Ireland                          24\n",
+      "Hong                             20\n",
+      "Cambodia                         19\n",
+      "Trinadad&Tobago                  19\n",
+      "Thailand                         18\n",
+      "Laos                             18\n",
+      "Yugoslavia                       16\n",
+      "Outlying-US(Guam-USVI-etc)       14\n",
+      "Honduras                         13\n",
+      "Hungary                          13\n",
+      "Scotland                         12\n",
+      "Holand-Netherlands                1\n",
+      "Name: native-country, dtype: int64\n",
+      "---- income ---\n",
+      "<=50K    24262\n",
+      ">50K      7693\n",
+      "Name: income, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "for column in train_data.columns:\n",
+    "    print (\"---- %s ---\" % column)\n",
+    "    print (train_data[column].value_counts())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9Hg4lwR6qlOc"
+   },
+   "source": [
+    "## Drop Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "id": "tcAh7OEDqqxX"
+   },
+   "outputs": [],
+   "source": [
+    "train_data=train_data.drop('fnlwgt', 1)\n",
+    "train_data=train_data.drop('education-num', 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nko9YZQMJajO"
+   },
+   "source": [
+    "## Outliers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "id": "G41KZFOgJkTM"
+   },
+   "outputs": [],
+   "source": [
+    "Q1 = train_data['age'].quantile(0.25)\n",
+    "Q3 = train_data['age'].quantile(0.75)\n",
+    "IQR = Q3 - Q1\n",
+    "low_limit = Q1 - (1.5 * IQR)\n",
+    "high_limit = Q3 + (1.5 * IQR)\n",
+    "filtered_entries = ((train_data['age'] >= low_limit) & (train_data['age'] <= high_limit))\n",
+    "train_data = train_data[filtered_entries]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "id": "h0yFok34dZxw"
+   },
+   "outputs": [],
+   "source": [
+    "Q1 = train_data['capital-gain'].quantile(0.25)\n",
+    "Q3 = train_data['age'].quantile(0.75)\n",
+    "IQR = Q3 - Q1\n",
+    "low_limit = Q1 - (1.5 * IQR)\n",
+    "high_limit = Q3 + (1.5 * IQR)\n",
+    "filtered_entries = ((train_data['age'] >= low_limit) & (train_data['age'] <= high_limit))\n",
+    "train_data = train_data[filtered_entries]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "id": "1fL-dqFMdjaJ"
+   },
+   "outputs": [],
+   "source": [
+    "Q1 = train_data['capital-loss'].quantile(0.25)\n",
+    "Q3 = train_data['age'].quantile(0.75)\n",
+    "IQR = Q3 - Q1\n",
+    "low_limit = Q1 - (1.5 * IQR)\n",
+    "high_limit = Q3 + (1.5 * IQR)\n",
+    "filtered_entries = ((train_data['age'] >= low_limit) & (train_data['age'] <= high_limit))\n",
+    "train_data = train_data[filtered_entries]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "id": "VALcRwTmXosh"
+   },
+   "outputs": [],
+   "source": [
+    "Q1 = train_data['hours-per-week'].quantile(0.25)\n",
+    "Q3 = train_data['hours-per-week'].quantile(0.75)\n",
+    "IQR = Q3 - Q1\n",
+    "low_limit = Q1 - (1.5 * IQR)\n",
+    "high_limit = Q3 + (1.5 * IQR)\n",
+    "filtered_entries = ((train_data['hours-per-week'] >= low_limit) & (train_data['hours-per-week'] <= high_limit))\n",
+    "train_data = train_data[filtered_entries]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "6LdheajiKV9a"
+   },
+   "source": [
+    "## Copy Train_Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "id": "eTDhhv3WQCpw"
+   },
+   "outputs": [],
+   "source": [
+    "train_datavis = train_data.copy()\n",
+    "train_data_onehot = train_data.copy()\n",
+    "train_clust = train_data.copy()\n",
+    "train_clustvis = train_clust\n",
+    "train_clustvis_rel = train_clustvis\n",
+    "train_clustvis_rel['relationship'] = train_clustvis_rel['relationship'].map({'Not-in-family': 'Not In Family', 'Wife': 'In Family', 'Unmarried': 'Not In Family', 'Other-relative': 'In Family','Husband':'In Family','Own-child': 'In Family'}).astype(str)\n",
+    "train_clustvis_rel['age'] = train_clustvis_rel['age'].map({17: 'Productive-age',18: 'Productive-age',19: 'Productive-age',20: 'Productive-age',21: 'Productive-age',22: 'Productive-age',23: 'Productive-age',24: 'Productive-age',25: 'Productive-age',26: 'Productive-age',27: 'Productive-age',28: 'Productive-age',29: 'Productive-age',30: 'Productive-age',31: 'Productive-age',32: 'Productive-age',33: 'Productive-age',34: 'Productive-age',35: 'Productive-age',36: 'Productive-age',37: 'Productive-age',38: 'Productive-age',39: 'Productive-age',40: 'Productive-age',41: 'Productive-age',42: 'Productive-age',43: 'Productive-age',44: 'Productive-age',45: 'Productive-age',46: 'Productive-age',47: 'Productive-age',48: 'Above-productive',49: 'Above-productive',50: 'Above-productive',51: 'Above-productive',52: 'Above-productive',53: 'Above-productive',54: 'Above-productive',55: 'Above-productive',56: 'Above-productive',57: 'Above-productive',58: 'Above-productive',59: 'Above-productive',60: 'Above-productive',61: 'Above-productive',62: 'Above-productive',63: 'Above-productive',64: 'Aged',65: 'Aged',66: 'Aged',67: 'Aged',68: 'Aged',69: 'Aged',70: 'Aged',71: 'Aged',72: 'Aged',73: 'Aged',74: 'Aged',75: 'Aged',76: 'Aged',77: 'Aged',78: 'Aged',79: 'Aged',80: 'Aged',81: 'Aged',82: 'Aged',83: 'Aged',84: 'Aged',85: 'Aged',86: 'Aged',87: 'Aged',88: 'Aged',90: 'Aged'}).astype(str) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "t3BuqQiuUVbx"
+   },
+   "source": [
+    "Section ini kami lakukan untuk membedakan dataset mana yang kami gunakan untuk visualisasi dan feature enginering one-hot encoding maupun label encoding, dengan alasan mempermudah kami melakukan coding secara terpisah."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "YUcVSDAcL9Hf"
+   },
+   "source": [
+    "# FEATURE ENGGINERING"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "lxmIMOuNxtyD"
+   },
+   "source": [
+    "## Train Data One Hot Encoding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "id": "4e_x4HA3qe0-"
+   },
+   "outputs": [],
+   "source": [
+    "train_data_onehot['age'] = train_data_onehot['age'].map({17: 'Productive-age',18: 'Productive-age',19: 'Productive-age',20: 'Productive-age',21: 'Productive-age',22: 'Productive-age',23: 'Productive-age',24: 'Productive-age',25: 'Productive-age',26: 'Productive-age',27: 'Productive-age',28: 'Productive-age',29: 'Productive-age',30: 'Productive-age',31: 'Productive-age',32: 'Productive-age',33: 'Productive-age',34: 'Productive-age',35: 'Productive-age',36: 'Productive-age',37: 'Productive-age',38: 'Productive-age',39: 'Productive-age',40: 'Productive-age',41: 'Productive-age',42: 'Productive-age',43: 'Productive-age',44: 'Productive-age',45: 'Productive-age',46: 'Productive-age',47: 'Productive-age',48: 'Above-productive',49: 'Above-productive',50: 'Above-productive',51: 'Above-productive',52: 'Above-productive',53: 'Above-productive',54: 'Above-productive',55: 'Above-productive',56: 'Above-productive',57: 'Above-productive',58: 'Above-productive',59: 'Above-productive',60: 'Above-productive',61: 'Above-productive',62: 'Above-productive',63: 'Above-productive',64: 'Aged',65: 'Aged',66: 'Aged',67: 'Aged',68: 'Aged',69: 'Aged',70: 'Aged',71: 'Aged',72: 'Aged',73: 'Aged',74: 'Aged',75: 'Aged',76: 'Aged',77: 'Aged',78: 'Aged',79: 'Aged',80: 'Aged',81: 'Aged',82: 'Aged',83: 'Aged',84: 'Aged',85: 'Aged',86: 'Aged',87: 'Aged',88: 'Aged',90: 'Aged'}).astype(str)\n",
+    "train_data_onehot['income'] = train_data_onehot['income'].map({'<=50K': 0, '>50K': 1}).astype(int)\n",
+    "train_data_onehot['marital-status'] = train_data_onehot['marital-status'].map({'Widowed': 'Not married', 'Married-spouse-absent': 'Married', 'Married-civ-spouse': 'Married', 'Married-AF-spouse': 'Married', 'Divorced': 'Not married','Separated': 'Not married', 'Never-married': 'Married'}).astype(str)\n",
+    "train_data_onehot['workClass'] = train_data_onehot['workClass'].map({'Self-emp-inc': 'Without-pay', 'Without-pay': 'Without-pay','Federal-gov': 'Government', 'State-gov': 'Government', 'Local-gov': 'Government','Private': 'Private', 'Self-emp-not-inc': 'Without-pay','Never-worked':'Not-work'}).astype(str)\n",
+    "train_data_onehot['education'] = train_data_onehot['education'].map({'Preschool': 'Preschool', '1st-4th': 'Primary-school', '5th-6th': 'Primary-school', '7th-8th': 'Junior-high-school','9th': 'Junior-high-school','10th': 'Senior-high-school', '11th': 'Senior-high-school', '12th': 'Senior-high-school','HS-grad': 'Senior-high-school','Prof-school': 'Senior-high-school','Assoc-voc': 'Senior-high-school','Assoc-acdm': 'Senior-high-school', 'Some-college': 'Senior-high-school','Bachelors': 'Bachelors', 'Masters': 'Masters', 'Doctorate': 'Doctorate' }).astype(str)\n",
+    "train_data_onehot['native-country'] = train_data_onehot['native-country'].map({'Canada': 'USA','Outlying-US(Guam-USVI-etc)': 'USA','United-States': 'USA','Cambodia': 'Asia','China': 'Asia','Hong': 'Asia','India': 'Asia','Iran': 'Asia','Japan': 'Asia','Laos': 'Asia','Philippines': 'Asia','Taiwan': 'Asia','Thailand': 'Asia','Vietnam': 'Asia', 'Columbia': 'South America','Cuba': 'South America','Dominican-Republic': 'South America','Ecuador': 'South America','El-Salvador': 'South America','Guatemala': 'South America','Haiti': 'South America','Honduras': 'South America','Jamaica': 'South America','Mexico': 'South America','Nicaragua': 'South America','Peru': 'South America','Puerto-Rico': 'South America','South': 'South America','Trinadad&Tobago': 'South America','England': 'Europe','France': 'Europe','Germany': 'Europe','Greece': 'Europe','Holand-Netherlands': 'Europe','Hungary': 'Europe','Ireland': 'Europe','Italy': 'Europe','Poland': 'Europe','Portugal': 'Europe','Scotland': 'Europe','Yugoslavia': 'Europe'}).astype(str)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "id": "eghD4NyZxjMV"
+   },
+   "outputs": [],
+   "source": [
+    "train_data_One = pd.get_dummies(train_data_onehot)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "QmJhO_AakpJm"
+   },
+   "source": [
+    "## Train Data Label Encoding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "id": "z0lnUq6hMBQk"
+   },
+   "outputs": [],
+   "source": [
+    "train_data['age'] = train_data['age'].map({17: 0,18: 0,19: 0,20: 0,21: 0,22: 0,23: 0,24: 0,25: 0,26: 0,27: 0,28: 0,29: 0,30: 0,31: 0,32: 0,33: 0,34: 0,35: 0,36: 0,37: 0,38: 0,39: 0,40: 0,41: 0,42: 0,43: 0,44: 0,45: 0,46: 0,47: 0,48: 1,49: 1,50: 1,51: 1,52: 1,53: 1,54: 1,55: 1,56: 1,57: 1,58: 1,59: 1,60: 1,61: 1,62: 1,63: 1,64: 2,65: 2,66: 2,67: 2,68: 2,69: 2,70: 2,71: 2,72: 2,73: 2,74: 2,75: 2,76: 2,77: 2,78: 2,79: 2,80: 2,81: 2,82: 2,83: 2,84: 2,85: 2,86: 2,87: 2,88: 2,90: 2}).astype(int)\n",
+    "train_data['income'] = train_data['income'].map({'<=50K': 0, '>50K': 1}).astype(int)\n",
+    "train_data['capital-gain'] = train_data['capital-gain'].map({0: 0, 114: 1,401: 1,594: 1,914: 1,991: 1,1055: 1,1086: 1,1111: 1,1151: 1,1173: 1,1409: 1,1424: 1,1455: 1,1471: 1,1506: 1,1639: 1,1797: 1,1831: 1,1848: 1,2009: 1,2036: 1,2050: 1,2062: 1,2105: 1,2174: 1,2176: 1,2202: 1,2228: 1,2290: 1,2329: 1,2346: 1,2354: 1,2387: 1,2407: 1,2414: 1,2463: 1,2538: 1,2580: 1,2597: 1,2635: 1,2653: 1,2829: 1,2885: 1,2907: 1,2936: 1,2961: 1,2964: 1,2977: 1,2993: 1,3103: 1,3137: 1,3273: 1,3325: 1,3411: 1,3418: 1,3432: 1,3456: 1,3464: 1,3471: 1,3674: 1,3781: 1,3818: 1,3887: 1,3908: 1,3942: 1,4064: 1,4101: 1,4386: 1,4416: 1,4508: 1,4650: 1,4687: 1,4787: 1,4865: 1,4931: 1,4934: 1,5013: 1,5060: 1,5178: 1,5455: 1,5556: 1,5721: 1,6097: 1,6360: 1,6418: 1,6497: 1,6514: 1,6723: 1,6767: 1,6849: 1,7298: 1,7430: 1,7443: 1,7688: 1,7896: 1,7978: 1,8614: 1,9386: 1,9562: 1,10520: 1,10566: 1,10605: 1,11678: 1,13550: 1,14084: 1,14344: 1,15020: 1,15024: 1,15831: 1,18481: 1,20051: 1,22040: 1,25124: 1,25236: 1,27828: 1,34095: 1,41310: 1,99999: 1}).astype(int)\n",
+    "train_data['capital-loss'] = train_data['capital-loss'].map({0: 0, 155: 1,213: 1,323: 1,419: 1,625: 1,653: 1,810: 1,880: 1,974: 1,1092: 1,1138: 1,1258: 1,1340: 1,1380: 1,1408: 1,1411: 1,1485: 1,1504: 1,1539: 1,1564: 1,1573: 1,1579: 1,1590: 1,1594: 1,1602: 1,1617: 1,1628: 1,1648: 1,1651: 1,1668: 1,1669: 1,1672: 1,1719: 1,1721: 1,1726: 1,1735: 1,1740: 1,1741: 1,1755: 1,1762: 1,1816: 1,1825: 1,1844: 1,1848: 1,1876: 1,1887: 1,1902: 1,1944: 1,1974: 1,1977: 1,1980: 1,2001: 1,2002: 1,2042: 1,2051: 1,2057: 1,2080: 1,2129: 1,2149: 1,2163: 1,2174: 1,2179: 1,2201: 1,2205: 1,2206: 1,2231: 1,2238: 1,2246: 1,2258: 1,2267: 1,2282: 1,2339: 1,2352: 1,2377: 1,2392: 1,2415: 1,2444: 1,2457: 1,2467: 1,2472: 1,2489: 1,2547: 1,2559: 1,2603: 1,2754: 1,2824: 1,3004: 1,3683: 1,3770: 1,3900: 1,4356: 1}).astype(int)\n",
+    "train_data['sex'] = train_data['sex'].map({'Female': 0, 'Male': 1}).astype(int)\n",
+    "train_data['race'] = train_data['race'].map({'Other': 0, 'White': 1,'Black': 2, 'Asian-Pac-Islander': 3, 'Amer-Indian-Eskimo': 4}).astype(int)\n",
+    "train_data['marital-status'] = train_data['marital-status'].map({'Widowed': 0, 'Married-spouse-absent': 1, 'Married-civ-spouse': 1, 'Married-AF-spouse': 1, 'Divorced': 0,'Separated': 0, 'Never-married': 1}).astype(int)\n",
+    "train_data['workClass'] = train_data['workClass'].map({'Self-emp-inc': 0, 'Without-pay': 0,'Federal-gov': 1, 'State-gov': 1, 'Local-gov': 1,'Private': 3, 'Self-emp-not-inc': 0,'Never-worked':2}).astype(int)\n",
+    "train_data['education'] = train_data['education'].map({'Preschool': 0, '1st-4th': 1, '5th-6th': 1, '7th-8th': 2,'9th': 2,'10th': 3, '11th': 3, '12th': 3,'HS-grad': 3,'Prof-school': 3,'Assoc-voc': 3,'Assoc-acdm': 3, 'Some-college': 3,'Bachelors': 4, 'Masters': 5, 'Doctorate': 6 }).astype(int)\n",
+    "train_data['occupation'] = train_data['occupation'].map({ 'Tech-support': 1, 'Handlers-cleaners': 2, 'Adm-clerical': 3, 'Farming-fishing': 4, 'Prof-specialty': 5,'Machine-op-inspct': 6, 'Exec-managerial': 7,'Priv-house-serv': 8,'Craft-repair': 9,'Sales': 10, 'Transport-moving': 11, 'Armed-Forces': 12, 'Other-service': 13,'Protective-serv':14,'Other':15}).astype(int)\n",
+    "train_data['relationship'] = train_data['relationship'].map({'Not-in-family': 0, 'Wife': 1, 'Unmarried': 2, 'Other-relative': 3,'Husband': 4,'Own-child': 5}).astype(int)\n",
+    "train_data['native-country'] = train_data['native-country'].map({'Canada': 0,'Outlying-US(Guam-USVI-etc)': 0,'United-States': 0,'Cambodia': 1,'China': 1,'Hong': 1,'India': 1,'Iran': 1,'Japan': 1,'Laos': 1,'Philippines': 1,'Taiwan': 1,'Thailand': 1,'Vietnam': 1, 'Columbia': 2,'Cuba': 2,'Dominican-Republic': 2,'Ecuador': 2,'El-Salvador': 2,'Guatemala': 2,'Haiti': 2,'Honduras': 2,'Jamaica': 2,'Mexico': 2,'Nicaragua': 2,'Peru': 2,'Puerto-Rico': 2,'South': 2,'Trinadad&Tobago': 2,'England': 3,'France': 3,'Germany': 3,'Greece': 3,'Holand-Netherlands': 3,'Hungary': 3,'Ireland': 3,'Italy': 3,'Poland': 3,'Portugal': 3,'Scotland': 3,'Yugoslavia': 3}).astype(int)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "fSFEbsYnievJ"
+   },
+   "source": [
+    "# DATA VISUALIZATION"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "id": "noyyFnueA2C4",
+    "outputId": "d2e1a660-fb68-4d47-c43c-fb0c32b83f16"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_datavis.hist(figsize=(10,10));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "NjqNbT8_RYef"
+   },
+   "source": [
+    "## Distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Vol3FWBNV_CT"
+   },
+   "source": [
+    "### Visualization Distribution Data of Age"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "id": "UDGvbwXwQyZe",
+    "outputId": "57093c20-c8b8-462c-b74c-b8687ddbdd80"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "ax=sns.distplot(train_datavis['age'],hist_kws=dict(edgecolor=\"k\", linewidth=2),kde_kws={\"color\": \"#ce0d55\", \"lw\": 2})\n",
+    "ax.set_title('Age Distribution')\n",
+    "ax.set_xlabel('Age',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iYHOm9ZlWKlt"
+   },
+   "source": [
+    "### Visualization Distribution Data of Hours/Week"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "id": "4z8BDW02R5M6",
+    "outputId": "91ddf143-5308-49ec-9a65-5f4f7eb7d2fa"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "ax=sns.distplot(train_datavis['hours-per-week'],hist_kws=dict(edgecolor=\"k\", linewidth=2),kde_kws={\"color\": \"#ce0d55\", \"lw\": 2})\n",
+    "ax.set_title('Hours/Week Distribution')\n",
+    "ax.set_xlabel('Hours Per Week', fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "id": "T3tLkbugSjK8",
+    "outputId": "7aa2f3b2-6ff7-478f-c7f6-edefeba0cd12"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "num_col = train_datavis.dtypes[train_datavis.dtypes != 'object']\n",
+    "\n",
+    "fig = plt.figure(figsize = (15,8))\n",
+    "sns.heatmap(train_datavis[list(num_col.index)].corr(),annot = True,square = True)\n",
+    "ax.set_title('')\n",
+    "ax.set_xlabel('Hours Per Week', fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "id": "LfWaV4FCQSOh"
+   },
+   "outputs": [],
+   "source": [
+    "ocpt = pd.crosstab(train_datavis['occupation'], train_datavis['income'])\n",
+    "age= pd.crosstab(train_datavis['age'], train_datavis['income'])\n",
+    "wc= pd.crosstab(train_datavis['workClass'], train_datavis['income'])\n",
+    "edu = pd.crosstab(train_datavis['education'], train_datavis['income'])\n",
+    "marit_stat = pd.crosstab(train_datavis['marital-status'], train_datavis['income'])\n",
+    "race = pd.crosstab(train_datavis['race'], train_datavis['income'])\n",
+    "country = pd.crosstab(train_datavis['native-country'], train_datavis['income'])\n",
+    "relasi = pd.crosstab(train_datavis['relationship'], train_datavis['income'])\n",
+    "sextype = pd.crosstab(train_datavis['sex'], train_datavis['income'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2rJfZ0NlFL-H"
+   },
+   "source": [
+    "## Occupation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MWCTXwKuWWQZ"
+   },
+   "source": [
+    "### Visualization Proportion Data of Occupation vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "id": "eOJ0NflbQXYF",
+    "outputId": "11eeeb96-6ea0-4eec-9736-771e3562d413"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,1)\n",
+    "(ocpt.div(ocpt.sum(axis= 1),axis = 0)*100).sort_values(by= '<=50K').plot(kind = 'bar',ax=ax);\n",
+    "plt.xlabel(\"Occupation\",fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "id": "PwUEf99QxWJl",
+    "outputId": "73f72331-dae3-403f-9ecb-786a8dff9c9c"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (10,6))\n",
+    "ax=sns.countplot(train_datavis['occupation'], hue=train_datavis['income'])\n",
+    "ax.set_title('Occupation vs Income')\n",
+    "plt.xlabel(\"Occupation\",fontsize = 10);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "R_UeFzSOXJPu"
+   },
+   "source": [
+    "### Visualization Occupation <=50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "id": "IvASVPMh8LbO",
+    "outputId": "6117cc86-dc7f-4b3c-9267-571e71838d26"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (15,10))\n",
+    "ax=sns.countplot(train_datavis['occupation'],\n",
+    "                order = train_datavis['occupation'].value_counts().index)\n",
+    "ax.set_title('Occupation <=50K')\n",
+    "plt.xlabel(\"Occupation\",fontsize = 15);\n",
+    "plt.xticks(rotation=90, fontsize = 10)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aw30EhqXlybB"
+   },
+   "source": [
+    "### Visualization Occupation <=50K in Family"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "id": "2U8BHj7LU2-h",
+    "outputId": "ab703035-08e0-4c8c-c427-b23a0f69031a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuIAAAITCAYAAABCLXmDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzde7y19Zz/8ddbkaYUKelESZhyKJJz4zAIUU4zEWKQQwbDMDJmHJsxxmHESJHKISmKEDr8KGZS7kwHFSMdlKK7cbqdlc/vj+va3everb3vve/2vb/Xuu/X8/FYj73Wda219mevfXqv7/X5fq9UFZIkSZIW1y1aFyBJkiStjQzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJek1SjJr5LcpXUdkyDJtkkqybqL+Dkfk+Szi/X5FkqS9ZJ8N8kdWtciadUZxCUNVpLnJrkgyW+S/DjJIUlu27qumST5WpIXjG6rqg2r6tLV9Pm2THLVmO2HJvnAyO1bJvn1DNseuDpqm0mSuyU5Lsl1SX6R5Pwkr0qyzmLWMeJfgLevridPcnmS3/ZvyH6V5ORp+5+Z5Ir+e/HZJJuM7Fvh5ynJw5P8LMk+VfV74CPAP6yu2iWtfgZxSYOU5NXAvwGvATYGHgjcGTglya1a1jYgjwe+PGb7GcBfjNzeFfghsPu0bQDnrJ7SbirJ9sBZwJXAvapqY+DpfS23Waw6Ruq5P7BxVX1zjvfffBU/1RP7N2QbVtVjRp5vJ+BQ4NnA5sBvgA+Me4IkjwE+C/xNVR3Tbz4a2C/JeqtYl6TGDOKSBifJRsCbgb+tqi9X1R+r6nLgr+jC+LP6+62T5PVJfpBkWZJzkmzT79spySlJfprkJ0le328/MsnbRj7Xw0dHlfsRzAOTXNSPPh6R5Nb9vtsl+UKSpf2+LyTZut93EPAw4P39yOf7++2V5K799Y2TfLR//BVJ3pDkFv2+5yb5RpJ39s99WZLHreSlejxw0pjtpwN/nmTT/vbDgGOADaZtO7Oq/pjkdSOv4UVJnjzyeqyT5F39CPZlSV422j7Sf02HJ7kmyY+SvG2W0e03A/9dVa+qqmsAqup7VfXMqvr59DsneV6Si/u6Lk3yopF9m/av/8/77/HXR17Lf+hrWZbke0keNUM9j+tfqxkluWOS1yS5CHjTbPddBfsCn6+qM6rqV8A/AU9JssKbkiR7AscCz6yqE6a2V9VVwM/o3qRKmkAGcUlD9GDg1sDxoxv7sPIl4NH9plcBz6ALpBsBfwP8pg8yp9KNFm8J3BU4bR6ff1/gscD2wN2AN/TbbwEcQfdm4E7Ab4H397X9I/B14GX9yOfLxjzv++hG9+9CN2L9HOB5I/sfAHwP2BR4B3B4kowrMMkt6Ua4T5m+rw9oV9CFbfr7fR3472nbzuiv/6DfvjFdWP54ki36fS+kC6w7A/cF9p726Y4Crqd7jXcBHgO8gPH+Evj0DPvGuRbYk+57+zzgPUnu2+97NXAVsBndaPLrgUpyd+BlwP2r6jZ038fLZ3j+e9G93itI17bzlCSf7/ffG3g5cMDIfc7v3wSMu0wf1f5E/+br5CT3Gdm+E3De1I2q+gHwB7qfuSlPBD4OPK2qxr3puhi4z5jtkiaAQVzSEG0KXFdV14/Zd02/H7rA94Z+VLWq6ryq+j+68PbjqnpXVf2uqpZV1Vnz+Pzvr6orq+qnwEF0YZ+q+r+q+kxV/aaqlvX7/mK2J5rSjxL/NXBgX8/lwLvo2hKmXFFVH6qqG+gC7hZ0IXOc3YHz+jrGOR3YvR8l3g34Jl0Yn9r2kP4+VNVxVXV1Vf2pqj4FfL9/DHRHId5bVVdV1c8Y6afuWzUeB7yyqn5dVdcC7wH2maGm29N9/+akqr5YVT/ov7enAyez/I3EH+lenzv3R0y+XlUF3ACsB+yY5JZVdXkfcMe5LbDC65fkrcCPgFcCJwBbV9Wzq+rUqvrTSG33rqrbznB56chT7gtsS/fm7avAV7J8nsOGwC+m1fQLVmzTeQTwv8B/zfA1LOu/DkkTyCAuaYiuAzbN+NUztuj3A2xDN5o73Uzb5+rKketX0I2qk+TP0k2EvCLJL+lGlG87SyvGqE2BW/XPN/rcW43c/vHUlar6TX91wxmeb6a2lCln0IX1ewGX9s/3jZFt69P1a5PkOUnOnRrRBe7J8jc7W7Li6zF6/c7ALYFrRh57KDDTSh7/R/f9m5Mkj0vyzb715Of91zxV178DlwAn920rrwOoqkvoQvSbgGuTHJNkyxk+xc+4aW/63fuv6Vzg/Fne6MxJVf1XVf22f/P2r8DPWf5m4ld0o/2jNmLFNwf/BPwe+GzG94Lfpn9OSRPIIC5piM6kCx9PGd2YZAO6EdipNpMr6dpHpptpO8CvgT8buX3HMffZZuT6nYCr++uvpgtqD6iqjVg++XGqfaRm+JzQvXn4I114HX3uH83ymNk8HvjiLPvPoGtZeALdSDjAhXRf2xOAb1XV75LcGfgQXTvH7avqtsB3WP41XQNsPfK8o6/NlXTfp01HRoM3qqqdZqjpVOCpc/ni+tD5GeCdwOZ9XSdN1dUfVXh1Vd2Frn3jVVO94FV1dFU9lO61LrpJv+Ocz4ptIFTVX9G14VwHfCrJhX0P/ehrQL/9VzNcPjjLl1Ysf20vZKStJN0yl+vRjYBP+TXd93pj4NN9S9KoP2ekvUXSZDGISxqcqvoFXa/y+5Ls0ffsbgscR9cX/LH+rh8G3ppkh3TuneT2wBeAOyZ5Zbr1lm+T5AH9Y84FHp9kkyR3pBs9ne6AJFunW0ru9cCn+u23oesL/3m/743THvcTuv7vcV/TDXQT7g7q67kzXY/7x+f14gBJtgPWq6rvznSffmT4J8Ar6IN437pxVr9tqj98A7pwuLR/7ufRjYhPORZ4RZKt+paKG5fL6ydcngy8K8lGSW6RZPskM7XrvBF4cJJ/7197ktw1ycdz02Upb0UXSpcC16ebuDq64sie/WMD/JKuJeWGJHdP8sg+yP+O7vt1wwz1nMSY1qKquqKq3kLX9/5SujdfFyZ508h9dhpZCWX65cV9jXdK8pAkt0py6ySvoRvRn2oz+QTwxCQP699kvgU4fvoofH97D7qjE0dPHYFJshWwCV3bkaQJZBCXNEhV9Q66EPxOuqA1tezdo/o1lAHeTRcUT+7vcziwfh9cHk03Uvpjup7nR/SP+RjdCOLl/eOmQvaoo/t9l/aXqVVW/oOupeM6uvAzfenA9wJPS7fqycFjnvdv6UY4L6VrEzmabi3o+XoCs7elTDmDbjLjaH/x1+laR84AqKqL6HrVz6QL7veadv8P0b0W5wP/03/e61kebp9DF5ovomv1+DQztJ/0vdoPouuZvjDJL+hGvZcwrVe7/x6+nO77+zPgmcCJI3fZgW6E/Vd97R+oqq/Rhfe3032Pftx/ra+foZ5vA78YeZM2fX9V1elV9Ty6EDzfE//cBjikr/9HdGH6cf08BqrqQuDFdIH82v7+Lx33RP2qMo+mG8H/aN/n/0zgqJHfB0kTJt0AiSQJuuULgRdU1amta5lJkpPoJpTOJYwv9Od+HPDBqrrzSu88AdKtz/3Sqpq+Gsyg9SP+5wG795NkJU0gR8QlafJ8jW4FjtUuyfpJHp9k3b4V4o10q4msEarq5EkL4QBV9fuquochXJpsBnFJmjBV9Y6q+u0ifbrQ9ev/jK415WLgnxfpc0vSGs3WFEmSJKkBR8QlSZKkBgzikiRJUgPjzlq3Vth0001r2223bV2GJEmS1mDnnHPOdVW12bh9a20Q33bbbVmyZEnrMiRJkrQGS3LFTPtsTZEkSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktRAsyCeZJskX01ycZILk7yi3/6mJD9Kcm5/efzIYw5MckmS7yV57Mj2+yW5oN93cJK0+JokSZKkuVq34ee+Hnh1VX07yW2Ac5Kc0u97T1W9c/TOSXYE9gF2ArYETk1yt6q6ATgE2B/4JnASsAfwpUX6OiRJkqR5axbEq+oa4Jr++rIkFwNbzfKQvYBjqur3wGVJLgF2S3I5sFFVnQmQ5KPA3swziC895OPz/yJWo81e8qzWJUiSJGk1GkSPeJJtgV2As/pNL0tyfpKPJLldv20r4MqRh13Vb9uqvz59uyRJkjRYzYN4kg2BzwCvrKpf0rWZbA/sTDdi/q6pu455eM2yfdzn2j/JkiRLli5derNrlyRJklZV0yCe5JZ0IfwTVXU8QFX9pKpuqKo/AR8CduvvfhWwzcjDtwau7rdvPWb7TVTVYVW1a1Xtutlmmy3sFyNJkiTNQ8tVUwIcDlxcVe8e2b7FyN2eDHynv34isE+S9ZJsB+wAnN33mi9L8sD+OZ8DfG5RvghJkiRpFbVcNeUhwLOBC5Kc2297PfCMJDvTtZdcDrwIoKouTHIscBHdiisH9CumALwEOBJYn26SpiumSJIkadBarpryDcb3d580y2MOAg4as30JcM+Fq06SJElavZpP1pQkSZLWRgZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAaaBfEk2yT5apKLk1yY5BX99k2SnJLk+/3H24085sAklyT5XpLHjmy/X5IL+n0HJ0mLr0mSJEmaq5Yj4tcDr66qPwceCByQZEfgdcBpVbUDcFp/m37fPsBOwB7AB5Ks0z/XIcD+wA79ZY/F/EIkSZKk+WoWxKvqmqr6dn99GXAxsBWwF3BUf7ejgL3763sBx1TV76vqMuASYLckWwAbVdWZVVXAR0ceI0mSJA3SIHrEk2wL7AKcBWxeVddAF9aBO/R32wq4cuRhV/XbtuqvT98+7vPsn2RJkiVLly5dyC9BkiRJmpfmQTzJhsBngFdW1S9nu+uYbTXL9pturDqsqnatql0322yz+RcrSZIkLZCmQTzJLelC+Ceq6vh+80/6dhP6j9f2268Cthl5+NbA1f32rcdslyRJkgar5aopAQ4HLq6qd4/sOhHYr7++H/C5ke37JFkvyXZ0kzLP7ttXliV5YP+czxl5jCRJkjRI6zb83A8Bng1ckOTcftvrgbcDxyZ5PvBD4OkAVXVhkmOBi+hWXDmgqm7oH/cS4EhgfeBL/WWNd/V/vqp1CSvY8oB3r/xOkiRJAhoG8ar6BuP7uwEeNcNjDgIOGrN9CXDPhatOkiRJWr2aT9aUJEmS1kYGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVID67YuQGuPMw/bs3UJK3jQ/l9oXYIkSVqLOSIuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgPNgniSjyS5Nsl3Rra9KcmPkpzbXx4/su/AJJck+V6Sx45sv1+SC/p9ByfJYn8tkiRJ0ny1HBE/EthjzPb3VNXO/eUkgCQ7AvsAO/WP+UCSdfr7HwLsD+zQX8Y9pyRJkjQozYJ4VZ0B/HSOd98LOKaqfl9VlwGXALsl2QLYqKrOrKoCPgrsvXoqliRJkhbOEHvEX5bk/L515Xb9tq2AK0fuc1W/bav++vTtYyXZP8mSJEuWLl260HVLkiRJcza0IH4IsD2wM3AN8K5++7i+75pl+1hVdVhV7VpVu2622WY3t1ZJkiRplc0riCe5NMmTZtm/Z5JLV7WYqvpJVd1QVX8CPgTs1u+6Cthm5K5bA1f327ces12SJEkatHXnef9tgQ1n2b8BcOdVLSbJFlV1TX/zycDUiionAkcneTewJd2kzLOr6oYky5I8EDgLeA7wvlX9/NJ0nz5iWHN/n/a8L7cuQZIkLZD5BvGV2Rz4zVzumOSTwMOBTZNcBbwReHiSnenaSy4HXgRQVRcmORa4CLgeOKCqbuif6iV0K7CsD3ypv0iSJEmDttIgnmR3usA85SlJ7jrmrpvQLTF47lw+cVU9Y8zmw2e5/0HAQWO2LwHuOZfPKUmSJA3FXEbEH0E3Wg3dSPVT+ss4lwB/twB1SZIkSWu0uQTx/6Br/QhwKfBK4HPT7lPAr6pqruuCS5IkSWu1lQbxqvoF8AuAJI8ALq6qa1d3YZIkSdKabF6TNavq9NVViCRJkrQ2mfeqKUnuRLeayQ7A7bnpSXWqqh61ALVJkiRJa6x5BfEkjwNOAG4FLAPsCZckSZJWwXxHxP8VuA7Yu182UJIkSdIqmNcp7oF7AP9hCJckSZJunvkG8aXAH1ZHIZIkSdLaZL5B/GPAU1dHIZIkSdLaZL494kcCj0jyOeC9wGXADdPvVFU/vPmlSZIkSWuu+Qbx79KdRTPAnrPcb51VrkiSJElaC8w3iL+FLohLkiRJuhnme2bNN62mOiQtkIM/8djWJdzo5ft+pXUJkiQN1nwna0qSJElaAPM9s+buc7lfVZ2xauVIkiRJa4f59oh/jbn1iDtZU5IkSZrFfIP482Z4ju2B5wKXA4fevJIkSZKkNd98J2seNdO+JP8OfPtmVyRJkiStBRZssmZV/Qz4MPDahXpOSZIkaU210Kum/Ay4ywI/pyRJkrTGWbAgnuTWwLOBHy/Uc0qSJElrqvkuX/iRGXZtAjwI2Ax4zc0tSpIkSVrTzXfVlOfOsP2nwP8Cf1dVR9+siiRJkqS1wHxXTfFMnJIkSdICMFhLkiRJDcy3NQWAJBsBf8nyFVIuBU6pqmULVZgkSZK0Jpt3EE/yAuBdwIZA+s0F/CrJq6rq8AWsT5IkSVojzXfVlCcBh9GNgP8z8J1+107A3wKHJbm2qj6/oFVKkiRJa5j5joi/FrgYeEBV/Wpk+2lJjgC+CfwDYBCXJEmSZjHfyZr3AY6cFsIB6PvDj+rvI0mSJGkWq7JqSmbZV6taiCRJkrQ2mW8QPw/YL8kG03ck2ZDuhD/nLUBdkiRJ0hptvj3i7wSOB76d5GDgon771GTNuwJPWbjyJEmSpDXTfM+s+dkkLwP+DXgfy1tRAvwaeFlVfW5hS5QkSZLWPPNeR7yqPpDkaODRwHZ0IfwHdCf0+cUC1ydJkiStkVbpzJpV9XPguAWuRZIkSVprrHSyZpJ1krw9yYtXcr+XJPmXJLOtqiJJkiSJua2a8izgNcC3VnK/s+lO5vOMm1uUJEmStKabSxD/K+DUqjpntjv1+7+CQVySJElaqbkE8fsBp87x+b4K7Lrq5UiSJElrh7kE8U2Aa+f4fEv7+0uSJEmaxVyC+DJg0zk+3+2BX616OZIkSdLaYS5B/ELgMXN8vkf395ckSZI0i7kE8eOBv0yy12x3SvIkuiD+mYUoTJIkSVqTzeWEPocCLwGOTfJO4ENVdfnUziTbAi8A/h743/7+kjQnzzthj9YlrOCIJ3+5dQmSpLXESoN4Vf02yROALwAHAq9Lsgz4JXAbYCO609x/D9izqn63GuuVJEmS1ghzaU2hqi4BdgZeAXwDuB64I3AD8PV++32r6gerqU5JkiRpjTKX1hQA+pHu9/UXSZIkSTfDnEbEJUmSJC0sg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ00C+JJPpLk2iTfGdm2SZJTkny//3i7kX0HJrkkyfeSPHZk+/2SXNDvOzhJFvtrkSRJkuar5Yj4kcAe07a9DjitqnYATutvk2RHYB9gp/4xH0iyTv+YQ4D9gR36y/TnlCRJkganWRCvqjOAn07bvBdwVH/9KGDvke3HVNXvq+oy4BJgtyRbABtV1ZlVVcBHRx4jSZIkDdbQesQ3r6prAPqPd+i3bwVcOXK/q/ptW/XXp28fK8n+SZYkWbJ06dIFLVySJEmaj6EF8ZmM6/uuWbaPVVWHVdWuVbXrZptttmDFSZIkSfM1tCD+k77dhP7jtf32q4BtRu63NXB1v33rMdslSZKkQRtaED8R2K+/vh/wuZHt+yRZL8l2dJMyz+7bV5YleWC/WspzRh4jSZIkDda6rT5xkk8CDwc2TXIV8Ebg7cCxSZ4P/BB4OkBVXZjkWOAi4HrggKq6oX+ql9CtwLI+8KX+IkmSJA1asyBeVc+YYdejZrj/QcBBY7YvAe65gKVJkiRJq93QWlMkSZKktYJBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqYFmJ/SRpEn1+BPe1rqEFZz05De0LkGStAocEZckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAdcQlaS3whM98uHUJN/riU1/QugRJGgRHxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ2s27oASZKme+Knj29dwgo+/7SntC5B0hrIEXFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqYN3WBUiStCZ48me+0bqEFZzw1Ie2LkHSSjgiLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1MMggnuTyJBckOTfJkn7bJklOSfL9/uPtRu5/YJJLknwvyWPbVS5JkiTNzSCDeO8RVbVzVe3a334dcFpV7QCc1t8myY7APsBOwB7AB5Ks06JgSZIkaa6GHMSn2ws4qr9+FLD3yPZjqur3VXUZcAmwW4P6JEmSpDkbahAv4OQk5yTZv9+2eVVdA9B/vEO/fSvgypHHXtVvu4kk+ydZkmTJ0qVLV1PpkiRJ0sqt27qAGTykqq5OcgfglCTfneW+GbOtxt2xqg4DDgPYddddx95HkiRJWgyDHBGvqqv7j9cCJ9C1mvwkyRYA/cdr+7tfBWwz8vCtgasXr1pJkiRp/gYXxJNskOQ2U9eBxwDfAU4E9uvvth/wuf76icA+SdZLsh2wA3D24lYtSZIkzc8QW1M2B05IAl19R1fVl5N8Czg2yfOBHwJPB6iqC5McC1wEXA8cUFU3tCldkiRJmpvBBfGquhS4z5jt/wc8aobHHAQctJpLkyRJkhbM4FpTJEmSpLWBQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNDG7VFEmStDhefsKVrUu40cFP3mbld5LWMI6IS5IkSQ0YxCVJkqQGbE2RJEkT4fhPX9e6hBU85Wmbti5BE84RcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDbh8oSRJ0mryPx++tnUJK9jlBXdoXYJGOCIuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktSAQVySJElqwCAuSZIkNWAQlyRJkhowiEuSJEkNGMQlSZKkBgzikiRJUgMGcUmSJKkBg7gkSZLUgEFckiRJasAgLkmSJDVgEJckSZIaMIhLkiRJDRjEJUmSpAYM4pIkSVIDBnFJkiSpAYO4JEmS1IBBXJIkSWrAIC5JkiQ1YBCXJEmSGjCIS5IkSQ0YxCVJkqQGDOKSJElSAwZxSZIkqQGDuCRJktTAuq0LWChJ9gDeC6wDfLiq3t64JEmSpIny43de0rqEFdzx7+/auoTVao0YEU+yDvCfwOOAHR45ptEAACAASURBVIFnJNmxbVWSJEnSzNaUEfHdgEuq6lKAJMcAewEXNa1KkiRJq9VPDv5a6xJWsPnLHz7n+6aqVl8liyTJ04A9quoF/e1nAw+oqpdNu9/+wP79zbsD31sN5WwKXLcannd1mrSaJ61esObFMGn1gjUvhkmrFyav5kmrF6x5MUxavbD6ar5zVW02bseaMiKeMdtu8g6jqg4DDluthSRLqmrX1fk5Ftqk1Txp9YI1L4ZJqxeseTFMWr0weTVPWr1gzYth0uqFNjWvET3iwFXANiO3twaublSLJEmStFJrShD/FrBDku2S3ArYBzixcU2SJEnSjNaI1pSquj7Jy4Cv0C1f+JGqurBROau19WU1mbSaJ61esObFMGn1gjUvhkmrFyav5kmrF6x5MUxavdCg5jVisqYkSZI0adaU1hRJkiRpohjEJUmSpAYM4pIkSVIDBvGbKck6Sf6udR0atiS3SLJR6zrWNEleMZdtWjVJXjXm8vwkO7eubU3R/214cOs65iPJx+ayTZokSW6X5N6L/nmdrHnzJflaVT28dR1rsiRLgCOAo6vqZ63rmYskRwMvBm4AzgE2Bt5dVf/etLBpkrxqtv1V9e7FqmW+kny7qu47bdv/VNUurWqaTZIA+wJ3qaq3JLkTcMeqOrtxaWP1P8O7Ap/vNz2BbrnYewDHVdU7WtU2myQbAL+tqj8luRtdvV+qqj82Lm2sJGdW1YNa1zFX03/vkqwDXFBVOzYsa6WSfJ6bnuzvF8AS4NCq+t3iVzW7JO8FPlVV/926lrlIch7wKbqaf9C6npVJ8jXgSXSrCJ4LLAVOr6pZ/y8uJEfEF8Z/JXl/koclue/UpXVR4yRZluSXYy7LkvyydX2z2AfYEvhWkmOSPLYPNUO2Y1X9EtgbOAm4E/DstiWNdZuVXAYnyTP6f6rbJTlx5PJV4P9a1zeLDwAPAp7R314G/Ge7clbq9sB9q+rVVfVqulC+GbA78NyWha3EGcCtk2wFnAY8DziyaUWzOznJU4f+Ny3JgUmWAfce/d8BXAt8rnF5c3Ep8CvgQ/3ll8BPgLv1t4fo28AbklyS5N+TDP1MlU8CrgeOTfKtJH/fDzgM1cb9/+mnAEdU1f2Av1zMAhwRXwD9P//pqqoeuejFrOGS3ALYEzgE+BPwEeC9VfXTpoWNkeRCYGfgaOD9VXV6kvOq6j6NS5t4Se4MbAf8K/C6kV3LgPOr6vomha3E1Eji6Kj9kH8mklwM3Keq/tDfXg84t6r+fOBHHqZe578F1q+qdwy83mXABnRHz34LhO5/yODa2fq/wR+uqr9pXct8JTmjqnYfty3JhVW1U6vaVibJJsBT6Qal7lRVOzQuaaWS7AD8E7BvVa3Tup5xklwAPAY4CvjHqvpWkvOratFaVNaIE/q0VlWPaF3DqkpyB+DWU7er6ocNy5lV37v1PODxwGeATwAPBf4fXeAdmkOBy4HzgDP68DjYow5Jbg08H9iJFX8mBvcPt6quAK5Isi9w9dQh5STrA1vTve5D9Mf+MH4BJNmM7g3lUB0NfDPJ1GjnE4FP9q0fF7Ura6WS5EF0bUDP77cN9v9dVQ3yyNM4fbvPIN84zsFmSe409X+uH6ndtN/3h3Zlzcld6VqstmXYv3sk2Rb4K+Cv6d5cvrZlPSvxFrqTQf5XH8LvAnx/MQtwRPxmSPKsqvr4TD22A++tfRLwLrp2j2uBOwMXD3VEIMk5wM+Bw4HPVNXvR/YdX1VPaVbcPCRZd8CjtccB3wWeSffHaV+6n4nBTn7s5w48eGTE9lZ0f1Dv37ay8fo3Dn8N3JduBOZpwBuq6rimhc2iPxT+ELpR2m9U1ZLGJa1Ukt2Bv6f7Wfi3/p/rK6vq5Y1LG2tk7sB2VfXWJNsAWwx47sB/AkdW1bda1zIfSR4PfBD4Ad3P83bAS4GvAS+sqv9oV914Sf6Nrm3iB3S91ydU1c/bVjWzJGcBtwSOBY6tqksblzR4BvGbIcmLqurQJG8ct7+q3rzYNc1VP6HikcCpVbVLkkcAz6iq/RuXNlaSu0z/hU6yXVVd1qqmlUmyOfAvwJZV9bgkOwIPqqrDG5c21tSh+6nDckluCXxlyC1WSc6tqp2nbRtsqwdAknsAj6ILAqdV1cWNS5pVP4K/OSMjygM/crYO8Paqek3rWuYqyVSr3SP7tp/bAScP+A3lRXR91VcAv2Z5K82irzgxX3171T3oav7uECdoTunfoL0BOKSqrmtdz8r0bUuvraq3t65lrtJN5j4E2Lyq7tkfeX9SVb1t0WowiK+dkiypql37QL5Lf7jx7KrarXVt42T86hjn9BMrBinJl+hWevnHqrpPknWB/6mqezUubayp73+SM+hGiX4MnF1Vd2lc2oySnAK8r6pO7G/vBby8qh7VtrLxkjwQuLCqlvW3b0M3qfestpWN1/dYv5FuQtsNTEjgSvL/hvwGcroJnDtw53Hb+5axQUu3VOS2rPjG8qPNClqJof+fm25cH/6QJTkdeA3dqjlTv3vfqap7LlYNg+2ZmyST1Fs74udJNqRbXeATSa6lm+k8KP3o4U7AxklG2082YuS1HqhNq+rYJAcCVNX1SW5oXdQsDutH4t4AnAhsCPxz25JW6sV0P79TK49cCTynYT0rcwhdW8qUX4/ZNiSvAO5eVUNeiWac/0lyInAc3WsMQFUd366kWU3U3IGquqLvE39Yv+nrVXVey5rmIt1a59vTLVM39be4gMEGcbo5GvefoDagU5L8PV0bzejv3uAWVOj9WVWdnRUXLFrULGQQXxgfo+utfSwjvbVNK1q5vYDfAX9HV+/GdLUPzd3pVkm5Ld1EsSnLgBc2qWjufp3k9iz/5/pAujVrB6mqPtxfPQMY7Cj4qH6d2gf2byozNdI8YKmRw5D9kagh/x2+kgH/zM5iE7plLEdHxQsYahA/GDgBuEOSg+jnDrQtaWbpTpr1Qpa/nh9PclhVva9hWXOxK90RqElqBXgE8OIklzMZbUBTA5AHjGwrhvs/5bok27P8//TTgGsWswBbUxbAJPbWTpokD6qqM1vXMR/p1pJ/H3BP4Dt06y8/rarOb1rYDJL8C/COqYlA/ej4q6tqyIHg9nStEw+l+0P6DeAtQx3BTXI83cSwQ/pNLwUeUVV7NytqFkkOp3sz/EXgxgnSQ56IPqkmae5AkvPp5rv8ur+9AXDmgMMhcOOE9JdX1aIGrZtjktuAJkE/kfsw4MHAz4DLgGdV1eWLVcOQR2ImydTZ2n6e5J50vbXbtitnZkm+UVUPTbdu7ei7sEGuW5vkfSx/p/qM6fuHugoCQFV9O8lf0AWZAN+rgZ7Zr/e4qnr91I2q+lm/ysBggzhwDN0I/lP72/vSHRJd1BMyzMOL6UY/30D3c30aMMgJ0r0f9pdb9ZeJMIQJWKvg+3TLm64L3dJ6A54UG5a3dsDy+QNDtylwUZKzWfGN5ZPalTS7vg3oocAOVXVE37a0Yeu6ZpLkz4BX0a11vn+6tcTvXlVfaFzaWP0iEH/Zv5m8RYujqo6IL4AkL6Bb1/redJPzNgT+qaoObVrYGiDJfrPtr6qjFquWuZrWy34TQ+1T7Ue57j+1NGS6NbmX1ECXtITxE5mmJiK3qkntDWEC1nxM2qTYdEv27kfXThO6Vscjh7j836h+YOQmqur0xa5lrvpV2XalC7N3S7IlcFxVPaRxaWMl+RRwDvCc/k3w+nRHS4Z4ro9BHAk2iK+F+iWGzh/qP6VJl+SIWXbXUCfxJnkt3emJj6Abrf0b4MSqekfTwmaR5J3AEro1a6Hrrd2pqsYuKdpKktdWd3bHG4/wjBrakZ0k/1FVr0zyecbXO9gRRIAk36qq+09bheQmS10ORZJLgAcMtaVqnL717qH9za9X1f+0rGdNleRcYBfg2yM/y4t65sf5GFmRbVJWALrJGXfHrdK2OtmasgD6PtU30Z30ooCvA28d6h/VfoLYeQM/9LmC/nDcPwA7suLKNIPrw6+q57WuYVX0QfEClvepvrWqvtK4rJV5Ed1h0I/R1XwLukmyr2JYrVZT/b6DPxlO72P9x3c2rWLVNZ+ANU+TOik2dKu7DLotZdJaMqf5Q1VVkqmf5Q1aF7QSf+hHwafq3Z6RNqABWifJetOOBK+3mAUYxBfGpPWpAmwBXNj3yo0uMTTUka5P0L2mT6Drs90PWNq0ojlI8gRuuqzlEFenAaCqvgR8qXUdc1UTcmrwqvp8f/X8SRg5rKpz+qubACfVyJlsJ8QBdBOw7pHkR/QTsNqWdFNZflbmS4GvJZmISbFJ/hl4Ol1LZoAjkhw31B78qnpo/3Ei/l5Mc2ySQ4HbJnkh3ZHKDzWuaTZvBL4MbJPkE3QDlM9tWtHsPg6c1h/JnjoSvKgtr7amLIBJ7FOdtF65qdd49JBcktOrauzXMQRJPgj8Gd3yUx+ma5s4u6qe37SwaSZ5tCjJQ4Bzq+rXSZ5Ftx73fwz1SE+Sr9K9CT4OOKaqLmxc0qz6f06PpBtoOIZuNajBnW9gJi0nYM1FZjgrc6+G+qY9ycV0J4L7XX97fbrWiT9vW9nKZcLOFAuQ5NHAY+j+Jn+lqk5pXNKs+i6BB9LV+80a6FlBkwTYmm6w7C/p6j15sY8EG8QXwKT0qU7XL4u0Q1Wd2s90XmfA/7C+WVUPTPIVulUnrgY+XVXbNy5tRiPLWU593BA4vqoe07q2NUU/wfQ+dBOlPwYcDjxl4G/Q7gj8FfDXdCem+tRQRxIB+uVYH0dX70OBU6rqBW2rml2605g/lZueQXGowfbpVXXcyrYNRbqzBj9jZILbbYGPV9WebSub3bRJsVMnTBrspFi48c3k76rqhiR3p1uF60tDXYFrhsGR99ZAl1scN5C66DUYxG++fiRxA7pf7ALWYXm7xyBHFPtDXPsDm1TV9v0SQx+s4Z4afE+63vtt6Nbm3gh4c/WnNh+iJGdV1QOSfBN4CvBT4IKq2qFxaTcxqRN4s/zU4P8M/KiqDl/siTarKsm9gNcCf11Vg14asA/jewDPAx5WVZs1LmlWSb5M13N9DiPL7FXVu5oVNYtxP7ND/jlO8lng/sApdP/zHk23hv+1MLzJx1MmdFLsOXRnML0d8E26Qb/fVNW+TQubwbTBkY8CH2HAgyPpzsp8ZDU8c6k94gtgQvvODgB2A84CqKrvJ7lD25JmVsvXIP0FXavHJPhCP1L0DrpAAF2LyuBM4gTe3rIkB9L1/+7eH3a+ZeOaZpTkz+lGlp9Gd+bHY4BXNy1qFkn2APah+537Gt3P71+1rGmOtq6qPVoXsTJJHgc8HtgqycEjuzZikU+zPU8n9JcpX2tUx3xN4qTYVNVvkjwfeF8/qX7I80yu7yeX7gUc3A+OzLoMcWPNz1xqEF8AfZ/RvsB2VfXWJNsAW1TV2Y1Lm83vq+oPXemQ7jTbgzs8MmnLvgEkuT9wZVW9tb+9IXAB8F3gPS1rW4lJm8ALXah9JvD8qvpxkjsB/964ptkcAXwSeExVXd26mDl4Lt2bhRdN2ITN/05yr6q6oHUhK3E13Qjn04H/pfsbdwNd68TfNaxrVlV1VJJbAfegq/l7VfWHxmXNaFInxfaS5EF0GWNqftGQs9tEDY7Qtd01NeRv5iT5AF1byiOBtwK/Av6T7tDdUJ2e5PXA+v1EkJcCn1/JY1qYtGXfAA6lXzEnye7A24G/BXamW8nhae1Km9WbWxcwX1X1Y+DdI7d/SHc4dHD6f0g/qKr3tq5lrqpqnySbA4/u37SfXVXXNi5rLh4KPDfJZXSBa6gnyLmILmDdim61htC13x0BDPJMhADpzrh7KPADupq3S/KiftWlIZo6aj2JZ4p9BXAgcEJVXZjulOxfbVzTbCZqcKS6M5feh679B7o18c9bzBrsEV8AI32qE7GAPdzYE/x8RmZiAx8ufyButtHvfd9/trSq3tTfHuxJRWCyJvACU2cx/TfgDnQ/x4Ne6aXvXX7SkEcPRyV5Ot1a4l+je20fBrymqj7dsq6V6X+Ob2JoE8aSvIfuTMyvmvo9S7IR3Wv+26p6Rcv6ZpLku8CeVXVJf3t74ItVdY+2lc1d/z9ww6r6Zeta5irJHfvBh4mQZM8a6KntpyR5BfBCYOqM108GDquq9y1aDeaumy/JWcCDgW/1gXwzuiVwdlnJQzVHSU4Bnl4rnob2mKp6bNvKbirJd4Cdq+r6/h/W/lV1xtS+oU6InLQJvHDj5KsnVtXFK73zAKRbD/i+wIms2P4zyEPjSc4DHj01Ct7/bTt1yIMMo/p5L6Nr+A9q/kOS7wN3mz4A0h89+e4QJ3YDJDmjqnYfuR3g9NFtQ5TkaLrzUNxAN29nY+DdVTXYEdtRQ57AO84k1NtPLn1QVf26v70BcKY94pPnYLqJK3dIchBd68Eb2pY0u3RnUJz+LuwXdC0gbxvgrPLNpkI4QFX9bMCTSz9J1/pzHfBbutVeSHJXhj1RaKIm8PZ+MikhvHd1f7kFyw+XD9ktprWi/B9d7YOW5EnAu4At6VbyuDNdm9tOLesao8YdheyXqhvyKNmFSU6iW7K36Hrcv9UfoaKqjp/twQ3tWFW/TLIvcBLd2ZrPYcCtE9MM+gymY0xCvWFkZaX++qLWbRC/mfrDW5fRLUM2dWrwvScgHHyJ7gfu6P72Pv3HXwJHAk9sUNNsbhhd0aM/9DzIf1RVdVCS0+gmP5488o/2FnS94kM1ERN4p1mS5FPAZ1lx8tUgg0BVvRm6UZepEZiB+3K6tfs/2d/+aybjzKtvpTuhyKlVtUuSRwDPaFzTOBcleU5VrTCvId36y99tVNNc3JpuQunUknRL6c7C+kS6vxmD/P0DbpluKc69gfdX1R8H/oZnuiGfUXOcF7UuYA6OAM5KMrUK0N5056NYNLamLIAkZ1bVg1rXMR9J/quqHjJuW5ILquperWobp19G7TBg6syfu9O1fCzqGbDWZEneAfwceA7dG4aXAhdV1T82LWwW6c78OF1V1d8sejFz0K9+cDhdb+qd+klCL6qqlzYubUZJnkp3muoAZ1TVCSt5SHPpz2zct9bs0i/PeXZV7da6tlFJtqILrb+lG5ktukn+6wNPrqofNSxvjZPk5XSj4OcBTwDuRHcioofN+sDGkjyUbu7OEX172IZVdVnrusbp5xa9GrhTVb2wb3G8+5B7xZPcl26C99TfuEVdHtIgvgCSvBk4n+6siRPxgvb/oPavqrP627sBH6qq+4xOOh2SJJuy/LS5Z9ZAT5s7qZzAu/r180meBpw4MrF7sPMGpvQTCEfPUPnThuWsVJJT6Ua23g7cnq495f5V9eCmhc0gySPp2mYCXFhVpzUuaVb9G+BxLTWDfAM8myTrVtVg12xP8kZgV7owe7ckWwLHTR9IG4r+COU5wHOq6p5J1qf7fz2oRQqSHFlVz+2v71dVRzWrxf+xN1+Wn1nzeuB3DHzlBrhxreuP0M3YD11LyguAC4EnVNWxDcu7iX4y0L7AXarqLf2SSHesYa/VrtUkE7i+PDB6ttWJWGEpyYuAt9CN2P6J5X/b7tK0sJXoJ1z9lq4dbF+6SXmfGODcl4nUHyWZcmu6lSauHvDv3bOq6uNZvp74CoY6WRq6lbaAXYBvj/zNOH8xJxPOx8jRqEH/jZtWX9NJpfaIL4CawDNrVnc613sl2ZjuDdnPR3YPKoT3RtdqfwuwDPgMw16rfSLMMHH3RgP9gz+J68sDXJnkwUClOyHKy1n+tQzR3wM7TdrRp6r6dZYvxXlUf7h8ndZ1rSmq6jOjt5N8Eji1UTlz8Wf9x4n7Xw38oapqqpe9f5M5ZH/oR8Gn6t2ekfk7AzKYUWiD+AJL8qbq14weuiRPoDsceuupCXpV9ZamRc3sAdWv1Q43rpoyKSdkGLo9WxcwX1X1+f7jjYcTMxlr7L4YeC+wFXAVcDLdajVD9QPgN62LmK/RpTiB7ele7w/STajXwtuBrt96qLbvP15UVcc1rWT+ju2XPb1t/3P9Nwx70uYbgS8D2yT5BN38kuc2rWi8rZMcTHeUb+r6jRbz6I6tKQus9SGOuUryQbpRgkcAH6brWz27qp4/6wMbiWu1r3ZJtgOuqarf9bfXBzavqsubFjZHk/K7N0mS7EK/qgArrkozyBaEKf3h/N2As0YOPw9uEvqk6tsxR8PDj4EDp4+UD0V/1O++dD8PE/c3It3Zr2+cu1NVpzQuaVZJbs/y+VzfHOIRtST7zbZ/MXvGHRFfeJOwbibAg6vq3n2v2ZuTvIvhLjkFy9dq3zwTslb7BDqO7s3OlBv6bZPS/jP4371+ZZq30fUvfxm4D/DKqvp408Jmdijw/4AL6FrDJsUkLsU5MSawHfPLwHXABklGz6Q5CfO5/o5ucuagw/eUJA8Bzq2qL/bLcL4+yXtrYGe1HRe0Wx1VHfyJGSZB/4M35X5jtg3Rb/uPv+lnYf8R2K5hPbOqqk/QrdX+L3QnRNl7Ag8xDt26NXLq9f76JLX/DPlw7ZTHVHdK7T3pWlPuBrymbUmzur6qXlVVR1TVUVOX1kXNwelJXg+s348mHgd8vnFNa4wkD5nqVU7yrCTv7nvyB6mqXlNVGwNfrKqNRi63GXII720EfCXJ15MckGTz1gWtxCF0ueI+dH/brgA+OvtDBuOkFp/UIL4w3jd1par+NH3bQH0hyW3pzij2beBy4JimFa3c1ISrW9Cts6uFtTTdGQkBSLIX3SjSoCW5b78+8Dr9erBDdsv+4+OBTw59GUDgq0n2T7JFkk2mLq2LmoPX0Z1k5gK6k4qchEfQFtJo2HotExK2qmqvqetJJmJuTFW9uap2optLsiXdm8whT4y9vl/ydi/g4Kp6L5MzSbbJUVV7xG+GdCfneDDwSuA9I7s2ojsZw6CW65lJkvWAW1fVYE+/nuSf6U6j/P/bu/Mwu6oqjcO/L4QZAoqIgCjYJiAigi02thODqNBNNNAODIqINDgRRaQbJwI4goo0QztAA42oKAICooDMoggBAgYQsBlEUXAkYQzD13/sfcitm1tTKrl7n6r1Pk+eqnvq3Moi3Lq1zj5rr/UD8vRS0u26zxQNbBzJu9tPJb3ZC7gHeKft/ysa2BA6XhdNWVXVrwtJXyDF+Aiphnl14Fzb/1Q0sEFI6jU0pPr2hWHpavZj5J+/39s+oW17NFoY73NI73XvAFattJsVki4jlQLtSRq89ydSqUr1+zMkvd/2cX3/eyMRX3ySXkva7LgvaUd+Yz5wju3biwQ2QrmN2voMHNRR5aqGpFtIE/I6NxJeZ/tFZSMbfyStQnpvmF86luG08XUh6RnAPNtP5tv7q7ag20srtLQVZ+u0OdlqqNLBdd0kvQ94O7AmcDpwmu2by0Y1uHzBsCupscIVeebHVrXlFsPd2evn3crYrDk2B9veVtKLbR9SOpjRkHQKqaXTHNKmPEi/wKr6YelwF2lwxKP58fKk1mphCbP9oKRzaUdbw7to2evC9t8AJH3D9r8DDxUOaUQ64q1ZG16z48HbScnWXrb/mJOtIwrHNFr7lA5ghJ5P2tA9p3QgI5EXFb7S8fi31JlXXEvKeURqvfm3/PnqwG/p4565SMTHZm1JryMNxtmcrvoi29eVCWtEXg5s7PbcEnkMuEnShaQfnu2AnzW9P2tvp9ZC65YOYITa/Lp4eekARqn6eJvODIO14iwZ23jSmWxJ+lfb51JnsjWApJ26Hj8XeAD4le37y0TVm6QpeWP34fnxgBXcWveXdLW2XI60L+bBvFm2GrY3gKdbOZ9t+7z8eHvg9f2MJRLxsfk0aVPQc+m4AsxMmgJZq7nAc4A/lA5khM7MfxqXFopjori+dAAj1JrXhaRJwJa2f54PVfWLfwTaFG/bW3G2yaHAuaWDGKG9gFcCl+THWwFXAdMkHWr7lFKB9fBt0h2ezpXbhoEq92l0t7aU9BbSfphabWF73+aB7R9LOqyfAUSN+BIg6VO2+/o/bqwkXQJsBlzNwEEd0wd9UiVyje16tm8sHUsoL09YnZYf3mr78ZLxDEXSL2y/snQcIyXprd1tQnsdq42kObY36zp2Q1s20LdJW2qtASSdA7zX9n358VqkDjDvBS63vUnJ+MYrSVfZ3rJ0HL1IOh+4AvgW6QJnd+C1tt/YrxhiRXwJsH1YTg6nkupVm+OXl4tqWLNKBzAaki4FppNes3NIrfYus71/0cDGkdzO6zBSTeJk2jHsYivgZFKtuEhjlfeo+GfvAkk7A2e0pCzsINJK8nDHavMnSdNtnw3tacXZUm2ptQZYv0nCs/uBabb/KqnKC3hJF9nedrhjtegq/5lEKmmr+b1uF+Bg0p1VA5fnY30TifgSIOm9wExSicoc0mjXX1BxaYrty0rHMEqr2Z6X/61PtH2wpFgRX7K+CuxEqpes+Y2z05dJQ3JuBZA0DfgOebBWhfYHVgaelPQIlV7s5DrJHYB1m3r7bArwRJmoRmVf4FRJx9DRirNsSONLZ9ctSRtBvV23OlyRN6I3F5I7A5fn7kV/LxfWoiStQJqd8ay80NeUpkwhtZit1Y4dnz9BWiR5c+9Ty8u19jMlrWL7wRIxRCK+ZMwk1R5eZXvr/KZUdRcVSVuShg69iLShYhngodoSgg6TJa0NvA34ROlgxql7gLktSsIBlm2ScADbt0ladqgnlNRdP1mxe4HZpLtQ13Ycnw98pEhEo5B732/ZplacbdLCrluND5CS71eREtv/BX6Q3/O2LhlYD/uQZpSsQ/oZbBLxecCxpYIaju09S8cwGvmC8nhgFeB5eUjVPrbf368YIhFfMh61/agkJC1v+9eSNiwd1DCOIQ0G+D7p1tG7SKU1tToUOB/4me1rJL0AqLpPewsdCJyXewR37hvo3ohck9mSTgCaTVa7MTBxrIokkWLcIJe0rQesbfvqwqENYPsGSXNJdxvaMNK+p5a14myTtnXdAtKtJ1Iv7tNLl2jm1AAAGCBJREFUxzIcp4mUR0n6kO3aJ3U/LXeiOZp0sWPgZ8BM278rGtjgjgTeCJwNT7/3vbafAcSI+yXjd0rj4s8CLpT0Q9KKUtVs/wZYxvaTtk8k7SCvku3v2960uUq1fYftnUvHNc58FniYtM9h1Y4/NXsfcBOwH+nO1M2ksoRaHUfq2rBrfvwgla5u2X4SWCNvhm2ztrTibJOm61arSNpJ0u2SHpA0T9J8SfNKxzWMp3J+AaRmBZL6tlq7GE4kJbXrkH72zsnHqmX7nq5DT/Y8cSmJFfElwPaM/Oms3I1kNdLUsZo9nH/BzpF0OKmN4cqFYxqRto0mbpFn2n5D6SBGw/ZjpNahX5G0tu3a23H+k9No8OshDfepPNG9G7hS0tl0DB6q/C5Jt7a04qxe7jpi0gX6zZLa1nXrcGBH27eUDmQU9rb99MV6fs/Ym3RRX6M188Je4yRJHy4WzfDuyeUpzu/F+wF9fX1EIj5GuTfwjU3boxZtgnwnqS78g6Saz/VItXNtoOFPCYvhp5LeYPuC0oEsph8BtV+gPS5pGXIXAUlrAk+VDWlI9+Y/k6j/7shgPipp02h3ukR8qXQAY3Rfy5JwgEmS1JQB5fePmi/e/yxpd9KmeUgdSP5SMJ7h7AscRVq9/x1wAWkvQd9EH/ElQNKpwEF5lGtYgiTNtH2UpFfZvjIf+4ztT5aObbzJE9FWJq1wPU6lHT0G04Z+xpJ2I40Hfxmp7eK/AZ9sQV/uVUmvhSJdBUarV7tTINqdLiGDTS61fVfRwIYh6ShSSc1ZDFzJP6NYUMOQdASpO83XSBfw+wL32P5oybgGI+l5pD1oryTF+3NSjfjdRQOrWCTiS4Cki0ldU65m4O3bam/TtaVndDOYI8pRwnAkvd92rbdrn5a7Km1L+pm7qOYVOkmbkDbCNuO1/wy8y/ZN5aIaXnNRltudrte0O7W9aenYxgNJs4F/tr0gP14OuNJ21ZNLJfWqVbbt9/Q9mBHKd933YeF7xgXA8XkPRxijfFH5IXIrzuZ4P/O3KE0ZA0kvBNZi0VaFrwN+3/+IRqUtPaNvkXQXsGZX3/DmwiF+sY6RpCEvcGxf169YFoekVwNTbR+XSz1WsX1n6biGcDupBdlkSCtIFd9N+wawv+1L4OkBSt9k4Pj4GkW706VrcpOEA9heUPleB6B9rfUAbD8l6STg4s5WrbXK78F7s2hiW+vFzlnACaRNpUXKBCMRH5uvAh/vrj2U9BBpUtMJRaIamVb0jLa9i6TnkFoXVnuHoeW+nD+uQGpLdgPpQmdT4JfAqwvFNSxJB5Ni3pC0M39Z0qjiV5WMazCSPkR6b7iPtDNfpNu3tV5Qrtwk4QC2L83DT2p3CNHudGlq1eRSSQfaPlzS0fSY8mh7vwJhjYik6cARpLrwDSRtBhxa8R33H5JGxv+UPncfWUyP2v6v4U9beiIRH5v1e20Asj1b0vr9D2dUWtMz2vYfgZfmFZdp+fCttqscSdw2trcGkPRd4N9t/yo/3gQ4oGRsIzAD2By4DsD2vbmeuVYzgQ1t17x5qdMdkj7Fwj7tuwM1321oNrOt13m3zPYdtGczehs0k0uPJSW2vyPNoqhVU/41u2gUi+dg4BXApQC251SeX6xk+z9KBzEKR+UFnQsYmAv17U5wJOJjs8IQX1uxb1Esns+SehivQN07sAGQ9DrSFLS7SKuI60naw/blRQMbXzZqknAA23Pz6kvNFti2pKajQO2rtfcAD5QOYhTeQ1pdPoP0c3c5UPXtfdtP5lXEI0vHMl65ZZNLbZ+TP7ZxONUTth9Is8Ba4VxJO9g+r3QgI/QSUhe5bVhYmuL8uC8iER+bayTtbfubnQcl7UXF0/2ytvWM/gppyt+tAJKmkdoj/WPRqMaXWyQdTyrtMGn18+ayIQ3re5K+Dqyee+u+h1TDXBVJTbeOO4BLJf2Iyu9EQepZDOwnaTXgqdoTrg4/l3QMcBoDN9BXvd+hLSStBXwOWMf29pI2Bl5pu+ZyTCS9nLRnoGlSAEDle43mStoVWEbSVFKf658XjmkRueuWSRfsH5f0GPBE/nJ1jSA6zABe0Lnnod+ia8oY5DejM4EFLEy8X05aYZ6RSyqqJOkLpM0fregZ3avjQXRBWLIkrUCaVPka0pvpdaTyq72KBjYMSdsBbyDFfL7tCwuHtIh863Mwtn1o34IZBUlbAP/Dwh7iDwDvsV31QkMerNbNtvu2yjWeSfoxaU/GJ2y/VNJk4HrbLykc2pAk3Qp8DPgVHRvzam6tJ2kl0sVDs3B2PnCY0zCzMEaSTgM+ZPv+YjFEIj52krYGNskPb7J9ccl4RqKrZ3T1V6257dRTLKxV3Y20c7/q2+Rtk0tRdiX1ur4TON32MWWjGj8kvbW7Z3ivY7XInYo+YPuK/PjVwHFxATwxSZps+wlJ19jeorN3f9NqtnSMQ5H0M9vVbj7vpW3vGZ0kzbI9q3QcQ8kzBzYFrqHQlNhIxEMrSFqeNO3q1SysVT0uVgXGLpf5vIOFE9BOAw6w/fyigY2ApJ2ALwLPJr0uquyH3+jVD7/mHvmSrrT9quGO1aatpRO1a16rOXnZGbgwP94S+KLt15WNcGiStiW9z11Eewb6tOo9o1Mb4sz7zxbhPk5JjxrxUP1Vax5ocK3tTUi14mHJ+jWp3dSOtn8DIOkjZUMascNJcVc7FAdA0vbADsC6kjpbZU1h4R2pGl2da/C/Q6r/fDupxv1lUHXN9Unk0on8+DbSBWYk4mPT7BjcHzgb+AdJVwJrkqbE1m5PYCNSm9POjXnVJeItfs/oVPUO05xbHJtzi2IiEQ+Q+nPPKh3EYPJAgxsqH3zSZjuTVsQvkfQT4LtU/gba4b7ak/DsXlLrtLeSkkKTeuzeB9R80dOUGnTXuP8zfe4sMErPsv09SQcB5HKKNvQ0rt2aHRuPzwTOI71XPAa8HliknW9lXlp7HXuH5j1jOgObP8yn4vcMSTOA8/Ld6qqbKdSSW0QiHqAdSdfawE2SrmZgF4Rahxq0hu0zgTNz67+3kN7k15L038CZlW/onZ0325xF3beabybta1iO1NlFwHqkVdtzC8Y1pKbHfAs9JGkN8vCWXDrRpraRtVoGWIVFf2esVCCWxXGVpI1t194NCts3ADdI+jbp37stMzSmA1+VdDnwXUnn2655Bb9XbmHbb+5XAFEjHpA0yXaR0a4jVUMd10Qi6Zmk1du319xpIm/i7WZXNk5Z0pGkBGb/pgWgpCnAl4BHbM8sGd9gJM0kXSzMJ7WFfBnwn5VfnJFLZ44mbaKfSy6dcI8BbGHk2lDzOxRJtwD/QNqI/hgL95RUu/m41wwNoOoZGpKWBbYnlbK9mrSX4L1lo+qtK7cQKd5dbL+4bzFEIj4xSToZmGn77/nxM4AvV5jArECa4vZCUsupEyq/ug5hEZJuB6a56w03T4H8te2pZSIbmqQbcnu6N5I2S38KOLENyVhuqbch6Zdr7auIrdDZJaVtlCbivAZYpFVh5e0LrwV27Z6hYbvqso+cjL+JVJf/GttrFg5pUB3dwt5Gukg7w/bR/fr7ozRl4tq0ScIhDe6QVOMb7MnA46TNhNsDG5PGhIcJTNKBtg+XdDS5/KCT7f0KhDUUdyfh+eCTylNBK9WUIOxASsBvyAlNlXIXnV6mSaqxZKltti0dwOKybUlH1p7A9rBsk4QD2L4tJ7lVkvQm0p6jrYFLgeNJCW5VBukWphLleJGIT1yTJD3DaXJeU4pQ4+th42ZzjaQTgKsLxxPq0GzQnF00ipG7WdK7bP9v50FJu5O61tTqWkkXABsAB0lalY5BKBXacYivVdkdo01s/7V0DGN0laQtbF9TOpBRuDb/7uucoVHzQK13kzb871N5e+FquoVFacoEJeldwEHA6aRfUG8DPmv7lCGf2GfdNYltr1EME5OkdUlJ4COkX6IGtgBWJE3h/X3B8AaV23ttBtxh++95A+S6UWsd2kjSzaRNj3eTNua1oUY8ZmgsBbm7yztIHaCabmHH296g77FEIj5x5SEX25B+uC+qcSd5bjnW7GQWKXF5mMoHt4T+yLcXDwDWp+OOTq0bTCVtA7yY9Pq9yfZFhUMaVr6IeD4D/32r3CjW0VqvJ9sxh2ACk9RzSFmtNeL5QvjG0n2uR6KZWqo0tbszsaz6d3VHt7BdSPnQyfS5W1gk4hNYHlc91faJktYEVrF9Z+m4QhgpSTcAXyOtMj/dJ9p2zbduW0PSF0mdD25m4b+va20bKqnpd74h6Y7D2fnxjsDltXZuCP0l6dnACs3jmudTSDoVOKjmGMeLUt3CIhGfoPIvrJcDG9qeJmkd4PuufHR1CJ0kXdvCzVetIelW0sbuVt0Gz3XtO3e0ilyV9P72prKRhZIkTQe+DKwD3E+603NLP1vVjZaki0kXldXP0GjTCn5NatycF/pjBrA5cB2A7XvzL6sQqpdXLgDOkfR+0pS/zoE+bd9UVos7SOPAW5WIA88DFnQ8XkAqXwoT22HAlsBPbW8uaWtSSULNDikdwEjVMqmybSIRn7gW5HZOzeS5lUsHFMIoNBsem1Z6H+v4moEX9D2i8elhYI6kixh4oVNbe8hupwBXSzqT9HqYQRqKEia2x23/RdKkPMjuklx+VZ0Wz9CIKdijFIn4xPU9SV8HVpe0N2ns9vGFYwphRErsbJ+gzmZhnXVr2P6spJ+QOk0A7Gn7+pIxhSr8XdIqpM4jp0q6H6g1uW3rDI3WrODXImrEJzBJ2wFvIK0qnm/7wsIhhTAqkj4AnNo1IXYX28eVjSyUlqeWrsXAbi9xu3wCakol8p3fR4BJpH7cq5HeP/5SNMAeJP2qY4bGZODqmlv3tngFv7hIxCcoSXvZPqHj8TLAJ23H1WxoDUlzbG/Wday1Y7hrI2kq8HnSalxnl4mqS38kfQg4GLiP1O2l+n7RYenpnD8h6Qe2dy4d03DaNkND0mkMXMG/23YbVvCLi9KUiWtbSTsDewFrACcCl5UNKYRRmyRJzfj4fEG5XOGYxpMTSQntkaSR1XuysC6/ZjNJHaGqW+kMRXS+Zqu+iOzwUknz8ucCVsyPa+3LHVOwF1Mk4hOU7V0lvZ10C+lh0u38KwuHFcJonU/a7/A10qa8fUlT0sKSsaLti/LFzt3ALElXkJLzmt0DPFA6iFAND/J5tWwvUzqGUXq8+cT2E1IbrtfrEKUpE1S+5XwyKRF/EWlgx/62Hy4aWAijkPvW7gNsS1opuoA0pvjJIZ8YRkTSlcBrgNOBi4HfA1+wvWHRwIaRV+Q2BH7EwG4vMVlzAuqY0Nw5nRnqXV1unZiCvfgiEZ+gJP0a+ECz2gXsD7yn5sEGIYT+krQFcAuwOqkH8xTgCNtXFQ1sGB0TNgeIPTAhhNpEIj5BSZpie17Xsam2by8VUwij1dbNhG2Q6+2/YPtjw54cQghhsUwqHUDoL0kHAtieJ+mtXV/es0BIIYzFicB/k3oBb00a2nJK0YjGAUmTc3nPP6qFxZ6S1pR0hKTzJF3c/CkdVwghdItEfOJ5R8fnB3V97U39DCSEJWBF2xeR7u7dbXsWsE3hmMaDpuPB9cAPJb1T0k7Nn5KBjdCpwK+BDUgDRu4CrikZUAgh9BJdUyYeDfJ5r8ch1O7RvGHzdkkfJG0mfHbhmMaTZwJ/IV3cmLzxCjijZFAjsIbtEyTNtH0ZcJmkaM8aQqhOJOITz1BtnGLDQGibDwMrAfuRNhNuA+xRNKLx4dmS9gfmsjABb7ThfaJppfYHSf8C3As8t2A8IYTQUyTiE08zJKBzQAD58QqDPy2E+thuyg0eJPY4LEnLAKvQ+y5ZGxLxz0haDfgocDSp28tHyoYUQgiLiq4pIYTWkXT2UF+3Pb1fsYxHtY/TDiGE8SJWxEMIbfRK0vTE7wC/JPY3LGmt/PeUdDRDrNjb3q+P4YQQwrAiEQ8htNFzgO2AXYBdSRMUv2P7pqJRjR/blg5gMc3u+PwQoOdgnxBCqEWUpoQQWk3S8qSE/AjgUNtHFw4pVEDS9bY3Lx1HCCEMJVbEQwitlBPwfyEl4esD/0X9bfVC/8QqUwihepGIhxBaR9LJwCbAj4FDbM8tHFIIIYQwalGaEkJoHUlPAQ/lh51vYgJse0r/owqlSZrPwtfDSsDDzZeI10UIoUKRiIcQQgghhFDApNIBhBBCCCGEMBFFIh5CCCGEEEIBkYiHEEKohqR3S7KkrUrHEkIIS1sk4iGE0CeSpkj6lKTrJM2X9LCkmyUdIWmt0vH1i6StJM2StHrpWEIIoaTYrBlCCH0gaRpwPvB8Ur/zS4DHgS2B3YF5wI62f1EsyD6RNIs09XID23d1fW0ZYFlgge2n+h9dCCH0T/QRDyGEpUzSSsA5wLqkZPtHHV/+hqTjgJ8CP5T0Etv3lYizBrafBJ4sHUcIIfRDlKaEEMLStxcwDTiyKwkHwPZs4OPAmsDHOr+mZG9Jv5T0YP7zK0mHdp23nKQDJc3JJS8PSJot6YMd55wkqedt0FyXfVLH4/XzsVmSdpF0o6RHJf02H5vc9fyNJB0n6aaOsptrJe3ddd5JpNVwgDvz3+G8Sj5ojbikZ0k6VtI9khbkj8dKWqPrvOb520g6QNL/SXpM0m2S9uj13x5CCKXEingIISx9/5Y/fnOIc04CvgrsDBzQcfwUYDfgl8Bngb8DG+Xv+WlISTip7GUr4ALgW8CjwEuAnYBjxhD7jsCHgWOBPwLTSYn084E9O87bCngtcC5wJ7Ay8FbSiv+zbH8+n/d1YAowA/gI8Od8/MbBApC0GvBz4IXA/wDXAZsD7wO2kfQK2/O7nvY5YMX89z2Wzz1J0m9sXzm6f4IQQlg6IhEPIYSlbxNgvu3fDHaC7Ycl3QpsImkV2w9KehspCf8WsEdnzbSkzjuaHyYlwp+3/fHO79t13uLYDNjC9nX5+x1DqnF/t6Sv274qn3eK7a91/d1HAhcD/ynpS7Yft/0LSTeSEvGzumvEB3EgMBX4gO3jOr7/HNJFxoHAp7qes3yOe0E+93TgDuCDQCTiIYQqRGlKCCEsfVOAB0ZwXnPOavnjbvnjAd0bF7se7wb8DRhQrtLjvMVxYZOE5+9n4PD8cEbH8YeazyWtkEtGnklaoZ9CWsVfXDOAPwHf6Dr+ddKK+oxFngHHNUl4ju/3wG2khD6EEKoQK+IhhLD0zSMlo8NpzmkS8qnAH0aweXMqMMf2o4sZ31Bu6XHs5vzxBc0BSasAs4C3Aev1eM4zxhDDBsBs2090HrT9RL6L8LIez7mjx7G/kEpqQgihCrEiHkIIS99cYIqkFw52Qu6ssiFwl+0Hm8PASHvMjuS8wTZqDrUoM9K//9vA/sB5pBX67YHtgCPz1/v9+2awzivqaxQhhDCESMRDCGHpOyN/fO8Q57wLWK7jXIBbgXVGMOznNuBFkpYf5ry/Akh6ZtfxF/Q4t7HxEMfuyN9vdeBfSXXi+9r+tu2f2P4psKDH80c7wOIOYMMenVomk7rR9Fr9DiGE6kUiHkIIS9/xwG+Aj0h6U/cXJb0M+DypDvqIji+dmj8e3r3pUpK6znsG8Mke37vzvNvyx9d3nfbRIWLfLsfX+f0OzA/Pyh+b1ecBq82S1qb3xUez4t99QTCYs0itHbu/1975+Jkj/D4hhFCVqBEPIYSlzPZDkqYDPwF+JOkHwKXAE8ArgHeSktO32P5jx/O+L+k00mr5VElnkzZlTgPeSOrGAnAUqc3gJyVtQdog+SjwYlK5S5N4f4fU1u8bkjYi1UxvDzxriPBvAC6WdCzwB+DN+fud0kwBtT1f0gXA7pIeAa4h1WLvQ2pluEbX92w6rXxR0qk51rm25w4Sw+GkVojH5ouC60ntC/ci3TU4fJDnhRBC1SIRDyGEPrB9i6RNgZmk3t47AMsAdwNHA1/qTMI77ApcQUo6P01afb4T+H7H914g6Q2kle1dScn2o8DtwIkd582TtAPwFdIAoQdJpTC7kxL8Xs4mJbsHkZL6+4HD8p9OuwNfIF0Q7JH/7k8Aj3fGkOO4UtJ/APuSeqtPBg4h1dIvwvYDkl6Vz5lO6l9+H/A14OAePcRDCKEVlDpRhRBCCAtJWp+U8B9ie1bRYEIIYZyKGvEQQgghhBAKiEQ8hBBCCCGEAiIRDyGEEEIIoYCoEQ8hhBBCCKGAWBEPIYQQQgihgEjEQwghhBBCKCAS8RBCCCGEEAqIRDyEEEIIIYQCIhEPIYQQQgihgEjEQwghhBBCKOD/AX0FQFCAYGJpAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 864x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "a= train_clustvis.loc[train_clustvis['relationship'] == 'In Family']\n",
+    "plt.figure(figsize=(12,7))\n",
+    "ax=sns.countplot(a['occupation'],\n",
+    "                order = a['occupation'].value_counts().index)\n",
+    "ax.set_title('Occupation / Wage Class (<=50K)')\n",
+    "ax.set_xlabel('Occupation',fontsize=18)\n",
+    "ax.set_ylabel('Count',fontsize=18)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "siQikbkEFVSl"
+   },
+   "source": [
+    "## WorkClass"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "N9LRf1qLhv9R"
+   },
+   "source": [
+    "### Visualization Proportion Data of Work Class vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "id": "fw0L0CZUQZKb",
+    "outputId": "36bf6b25-c3e1-49cf-d927-22b3840f7c04"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,2)\n",
+    "(wc.div(wc.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax=ax);\n",
+    "plt.xlabel(\"Workclass\",fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "id": "3Vqb7NjcFbkK",
+    "outputId": "b477719c-3639-42d7-dab6-c2ccaaffbfaa"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 648x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (9,6))\n",
+    "ax=sns.countplot(train_datavis['workClass'], hue=train_datavis['income'])\n",
+    "ax.set_title('WorkClass vs Income')\n",
+    "plt.xlabel(\"WorkClass\",fontsize = 14);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ARypYWDOFqrc"
+   },
+   "source": [
+    "## Education"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "S5pbvxMBiFOw"
+   },
+   "source": [
+    "### Visualization Proportion Data of Education vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "id": "kbLW1Li8QbMe",
+    "outputId": "4b882325-3ff7-4d4b-f189-aeddce1b92c9"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,1)\n",
+    "(edu.div(edu.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax =ax);\n",
+    "plt.xlabel('Education',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "id": "gwOKjBH2Fw9J",
+    "outputId": "ab05c368-04ad-44f2-d8d2-e9fc97cf9052"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 648x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (9,6))\n",
+    "ax=sns.countplot(train_datavis['education'], hue=train_datavis['income'])\n",
+    "ax.set_title('Education vs Income')\n",
+    "plt.xlabel(\"Education\",fontsize = 14);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "3Aceh81eiL56"
+   },
+   "source": [
+    "### Visualization Education <=50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "id": "jVjPQ4ou83Dq",
+    "outputId": "7f1ea74c-e6ed-4935-dcef-2bff1d466d17"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (15,8))\n",
+    "ax=sns.countplot(train_datavis['education'],\n",
+    "                order = train_datavis['education'].value_counts().index)\n",
+    "ax.set_title('education <=50K')\n",
+    "plt.xlabel(\"education\",fontsize = 15);\n",
+    "plt.xticks(rotation=90, fontsize = 10)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rlED7p3WF48O"
+   },
+   "source": [
+    "## Marital"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "L8WLHac_iaQa"
+   },
+   "source": [
+    "### Visualization Proportion Data of Marital vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "id": "3t5kvHIFQc_1",
+    "outputId": "38178071-b855-4d29-e445-8e7dfc91e13a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,2)\n",
+    "(marit_stat.div(marit_stat.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax = ax);\n",
+    "plt.xlabel('Marital Status',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "id": "a3-FAWIOF9FQ",
+    "outputId": "97ccce6c-e875-4669-ae38-9bda78b916fd"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (10,6))\n",
+    "ax=sns.countplot(train_datavis['marital-status'], hue=train_datavis['income'])\n",
+    "ax.set_title('Marital Status vs Income')\n",
+    "plt.xlabel(\"Marital Status\",fontsize = 14);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "EHKZesIXGSJL"
+   },
+   "source": [
+    "## Race"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "A_9wtGbZisGG"
+   },
+   "source": [
+    "### Visualization Proportion Data of Race vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "id": "qLNQimxQQe27",
+    "outputId": "a624095e-be02-4eb0-8a8d-81761a3f8c79"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,1)\n",
+    "(race.div(race.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax =ax);\n",
+    "plt.xlabel('Race',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "id": "s0Jzrjv3GQ9h",
+    "outputId": "554349d7-b716-4d08-e160-41a3aeb69ed8"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 648x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (9,6))\n",
+    "ax=sns.countplot(train_datavis['race'], hue=train_datavis['income'])\n",
+    "ax.set_title('Race vs Income')\n",
+    "plt.xlabel(\"Race\",fontsize = 14);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qccJxcnYGl-G"
+   },
+   "source": [
+    "## Sex"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "F2sf22IwiyLU"
+   },
+   "source": [
+    "### Visualization Proportion Data of Sex vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "id": "8-kIz56xZm--",
+    "outputId": "35b091fd-7619-4046-a057-67508d4c1926"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,1)\n",
+    "(sextype.div(sextype.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax =ax);\n",
+    "plt.xlabel('Sex',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "id": "jEnIBRxiGyCR",
+    "outputId": "d67b545a-d9d3-4502-b52f-7c941bec2865"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAisAAAGhCAYAAACgbfQLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3df7hWZZ3v8fdXUNAUVEQH2CgkHBFUUIEhG53SUdFJsHPUSMsfx2IGTZNsOjrNqRk7WmZXTY5ZY5LAZCI5jTiGmgc1Kw3FH0dUVEgTt1ASmGITKPg9fzwLeoQt4t6wn3tv3q/req691r3WvZ7v2l5bP973+hGZiSRJUqm2a3QBkiRJm2JYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFF2kZFxF9ExH0R8UpErIiIX0TEqEbX1ZKI+HVE/FWj65DUGF0bXYCk9hcRPYBbgUnATGAH4HBgdSPrkqSWOLIibZv+G0Bm3pCZazPzj5n5k8x8bN0OEfE/I2JBRLwcEXdExD5V+/+KiF9GRNdqfVJEPBER3Tf8kqr/h+rWu0bE7yLikIjoHhHfj4jlEfH7iHgwIvZ6p8Ij4syI+HlEfK2q7bmIOK5u++4RcV1ELKm231y37ZMRsagaSbolIvrWbcuIOCciFkbEyoj4UkTsGxH3R8SrETEzInao2/9DEfFoVft9EXHQu/kHIGnzGVakbdMzwNqImBYRx0XEbvUbI+JE4O+B/w70Bn4G3FBtvgJ4HfiHiBgMXAZ8LDNXtfA9NwAfrVs/FvhdZj4MnAH0BPoDvYC/Bf64mfX/OfA0sAfwVWBKRES17d+AnYBhwJ7AN6pzOhL4MnAK0Ad4HpixwXHHAocCY4DPAdcAp1U1HrDuXCLiEOB7wN9Utf8rcEtEdNvM+iW9C4YVaRuUma8CfwEk8F1gWTXSsG5k42+AL2fmgsxcQy2QjIiIfTLzTeB04HzgFuCrmfnI23zVD4BxEbFTtX5q1QbwBrX/0A+qRncequraHM9n5nczcy0wjVr42Csi+gDHAX+bmS9n5huZ+dOqz2nA9zLz4cxcDVwMvC8iBtQd9/LMfDUznwAeB36Smc9m5ivAbcDB1X6fBP41M+dWtU+jNoU2ZjPrl/QuGFakbVQVRM7MzCZqowZ9gX+uNu8DfLOa4vg9sAIIoF/V99fA3cAA4Fub+I5FwALghCqwjONPYeXfgDuAGdWUzVcjYvvNLP83dd/xX9XiztRGQFZk5sst9OlLbTRlXb/XgOXrzqny27rlP7awvnO1vA9w4brfT/U76l99h6QtzLAiicx8CphKLbQAvAD8TWbuWvfZMTPvA4iI44H3AXOoTQttyrqpoPHAk1WAoRr1+KfMHAocBnyI2ohNW7wA7B4Ru7awbQm1kEF1Du+hNrLzYiu/59INfj87ZeYN79hT0rtmWJG2QRExJCIujIimar0/tUDxy2qX7wAXR8SwanvPiDi5Wt4DmAJ8gtp1JydU4eXtzACOoXbn0bpRFSLigxFxYER0AV6lNi20ti3nlZlLqU3XXB0Ru0XE9hFxRLX5B8BZETGiurbkMmBuNUr0bn0X+NuI+POoeU9E/HVE7NKW+iW1zLAibZtWUrtIdW5E/IFaSHkcuBAgM/8DuJzaFM2r1bZ1d9xcA8zKzNmZuRw4G7g2Inq19EVVgLif2ujJjXWb/gy4iVpQWQD8FPj+Fji3j1MLPk8BLwEXVHXMAf438O/AUmBfYEJrviAz51G7buUq4GVgEXBmG+uW9DYiMxtdgyRJ0ttyZEWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtE67FuX99hjjxwwYECjy5AkSVvAQw899LvM7N3Stg4bVgYMGMC8efMaXYYkSdoCIuL5t9vmNJAkSSqaYUWSJBXNsCJJkorWYa9ZkSSpVG+88QbNzc2sWrWq0aUUp3v37jQ1NbH99ttvdh/DiiRJW1hzczO77LILAwYMICIaXU4xMpPly5fT3NzMwIEDN7uf00CSJG1hq1atolevXgaVDUQEvXr1etcjToYVSZK2AoNKy1rzezGsSJJUsMMOO6zRJTScYUWSpILdd999jS6h4QwrkiQVbOeddwbgnnvu4QMf+AAnnXQSQ4YM4bTTTiMzAXjwwQc57LDDGD58OKNHj2blypWsWrWKs846iwMPPJCDDz6Yu+++G4CpU6dy4okncsIJJzBw4ECuuuoqvv71r3PwwQczZswYVqxYAcCvfvUrxo4dy6GHHsrhhx/OU0891ZhfAN4NJElSh/HII4/wxBNP0LdvX97//vfzi1/8gtGjR/ORj3yEG2+8kVGjRvHqq6+y44478s1vfhOA+fPn89RTT3HMMcfwzDPPAPD444/zyCOPsGrVKgYNGsTll1/OI488wuTJk5k+fToXXHABEydO5Dvf+Q6DBw9m7ty5nHPOOdx1110NOW/DiiRJHcTo0aNpamoCYMSIEfz617+mZ8+e9OnTh1GjRgHQo0cPAH7+859z3nnnATBkyBD22Wef9WHlgx/8ILvssgu77LILPXv25IQTTgDgwAMP5LHHHuO1117jvvvu4+STT17/3atXr26389yQYUWSpA6iW7du65e7dOnCmjVryMwW77BZN0X0TsfZbrvt1q9vt912rFmzhjfffJNdd92VRx99dAtW33qGFUnbvEP/bnqjS9AGHrri9EaX0GEMGTKEJUuW8OCDDzJq1ChWrlzJjjvuyBFHHMH111/PkUceyTPPPMPixYvZb7/9ePjhh9/xmD169GDgwIH88Ic/5OSTTyYzeeyxxxg+fHg7nNHGvMBWkqQObIcdduDGG2/kvPPOY/jw4Rx99NGsWrWKc845h7Vr13LggQfykY98hKlTp75lROWdXH/99UyZMoXhw4czbNgwZs2atRXPYtNiU8NEJRs5cmTOmzev0WVI6gQcWSlPRx9ZWbBgAfvvv3+jyyhWS7+fiHgoM0e2tL8jK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkjdxzzz307NmTESNGMGLECC655JL1226//Xb2228/Bg0axFe+8pX17WeeeSY33XQTACtWrODggw/muuuua3MtPsFWkqStbEs/y6e1z6F5/fXXeeONN3jPe96zWfsffvjh3HrrrW9pW7t2Leeeey533nknTU1NjBo1inHjxjF06ND1+7zyyisce+yxTJw4kbPOOqtVtdZzZEWSpE5uwYIFXHjhhey3337rX2bYWg888ACDBg3ive99LzvssAMTJkx4y9NtX3vtNY477jhOPfVUJk2a1NbSAUdWJEnqlP7whz8wc+ZMpkyZQmZy1lln8dhjj7HLLrsAMHnyZO6+++6N+k2YMIGLLroIgPvvv5/hw4fTt29fvva1rzFs2DBefPFF+vfvv37/pqYm5s6du379M5/5DJ/4xCeYPHnyFjsXw4okSZ1Qnz59OOigg7j22msZMmTIRtu/8Y1vbLL/IYccwvPPP8/OO+/M7NmzOfHEE1m4cGGLb3Ouf+vzkUceyaxZs/jsZz/Lnnvu2fYTwWkgSZI6pZtuuol+/frx4Q9/mEsuuYTnn3/+LdsnT568/uLZ+s+6C2Z79OjBzjvvDMDxxx/PG2+8we9+9zuampp44YUX1h+nubmZvn37rl+fMGECkyZN4vjjj2flypVb5FwcWZEkqRM65phjOOaYY1i+fDnf//73GT9+PHvssQfXXnstAwYMeMeRld/85jfstddeRAQPPPAAb775Jr169WLXXXdl4cKFPPfcc/Tr148ZM2bwgx/84C19L7jgApYuXcqHP/xhZs+ezQ477NCmc3FkRZKkTqxXr158+tOf5tFHH+Wyyy6jS5cum9Xvpptu4oADDmD48OGcf/75zJgxg4iga9euXHXVVRx77LHsv//+nHLKKQwbNmyj/pdffjn9+/fn4x//OG+++WabziFamnvqCEaOHJnz5s1rdBmSOoEtfVup2q61t+aWYsGCBey///6NLqNYLf1+IuKhzBzZ0v6OrEiSpKIZViRJUtHeMaxExPci4qWIeLyubfeIuDMiFlY/d6vbdnFELIqIpyPi2Lr2QyNifrXtyqjuc4qIbhFxY9U+NyIGbNlTlCRJHdnmjKxMBcZu0HYRMCczBwNzqnUiYigwARhW9bk6ItZdyfNtYCIwuPqsO+bZwMuZOQj4BnB5a09GkiR1Pu8YVjLzXmDFBs3jgWnV8jTgxLr2GZm5OjOfAxYBoyOiD9AjM+/P2hW90zfos+5YNwFHRf3TZSRJ0jattdes7JWZSwGqn+seUdcPeKFuv+aqrV+1vGH7W/pk5hrgFaBXK+uSJEmdzJa+wLalEZHcRPum+mx88IiJETEvIuYtW7aslSVKkqQzzzyTgQMHrn9y7aOPPgpAZnL++eczaNAgDjroIB5++OH1fdY90RZg9uzZDB48mMWLF2/1Wlv7BNvfRkSfzFxaTfG8VLU3A/3r9msCllTtTS201/dpjoiuQE82nnYCIDOvAa6B2nNWWlm7JEntavElB27R4+39hfnvuM/LL7/Mbrvttsl9rrjiCk466aS3tN12220sXLiQhQsXMnfuXCZNmvSWFxUCzJkzh/POO4+f/OQn7L333u/+BN6l1o6s3AKcUS2fAcyqa59Q3eEzkNqFtA9UU0UrI2JMdT3K6Rv0WXesk4C7sqM+qU6SpEKMHDmSU089lbvuuqvFlw++nVmzZnH66acTEYwZM4bf//73LF26dP32n/3sZ3zyk5/kxz/+Mfvuu+/WKH0jm3Pr8g3A/cB+EdEcEWcDXwGOjoiFwNHVOpn5BDATeBK4HTg3M9dWh5oEXEvtottfAbdV7VOAXhGxCPgM1Z1FkiSp9Z555hlOPfVUrrrqKoYOHcpll13GkiVL3rLP5z//eQ466CAmT57M6tWrAXjxxRfp3/9PkyRNTU28+OKLAKxevZrx48dz8803t/gm561lc+4G+mhm9snM7TOzKTOnZObyzDwqMwdXP1fU7X9pZu6bmftl5m117fMy84Bq26fWjZ5k5qrMPDkzB2Xm6Mx8duucqiRJ244uXbrwoQ99iB/96Efce++9PPvss+y999488MADAHz5y1/mqaee4sEHH2TFihVcfnntySEtjcKsu0l3++2357DDDmPKlCntdyL4BFtJkjqtV155hWuuuYZx48bxzDPPMGXKFA466CAA+vTpQ0TQrVs3zjrrrPUhpqmpiRde+NONvc3NzfTt2xeA7bbbjpkzZ/Lggw9y2WWXtdt5GFYkSeqEPvaxj3HIIYfw7LPPMn36dO69917OOOMMunfvDrD+OpTM5Oabb+aAAw4AYNy4cUyfPp3M5Je//CU9e/akT58+64+70047ceutt3L99de32whLa+8GkiRJBTvllFOYOnUqXbu2/J/60047jWXLlpGZjBgxgu985zsAHH/88cyePZtBgwax0047cd11123Ud/fdd+f222/niCOOYI899mD8+PFb9VwMK5IkbWWbc6vxljZu3LhNbr/rrrtabI8IvvWtb7W47bXXXlu/3L9/f5577rnWF/guOA0kSZKKZliRJElFM6xIkqSiGVYkSdoKfBh7y1rzezGsSJK0hXXv3p3ly5cbWDaQmSxfvnz97dOby7uBJEnawpqammhubmbZsmWNLqU43bt3p6mp6Z13rGNYkSRpC9t+++0ZOHBgo8voNJwGkiRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSpam8JKREyOiCci4vGIuCEiukfE7hFxZ0QsrH7uVrf/xRGxKCKejohj69oPjYj51bYrIyLaUpckSeo8Wh1WIqIfcD4wMjMPALoAE4CLgDmZORiYU60TEUOr7cOAscDVEdGlOty3gYnA4OoztrV1SZKkzqWt00BdgR0joiuwE7AEGA9Mq7ZPA06slscDMzJzdWY+BywCRkdEH6BHZt6fmQlMr+sjSZK2ca0OK5n5IvA1YDGwFHglM38C7JWZS6t9lgJ7Vl36AS/UHaK5autXLW/YvpGImBgR8yJi3rJly1pbuiRJ6kDaMg20G7XRkoFAX+A9EfGxTXVpoS030b5xY+Y1mTkyM0f27t373ZYsSZI6oLZMA/0V8FxmLsvMN4AfAYcBv62mdqh+vlTt3wz0r+vfRG3aqLla3rBdkiSpTWFlMTAmInaq7t45ClgA3AKcUe1zBjCrWr4FmBAR3SJiILULaR+opopWRsSY6jin1/WRJEnbuK6t7ZiZcyPiJuBhYA3wCHANsDMwMyLOphZoTq72fyIiZgJPVvufm5lrq8NNAqYCOwK3VR9JkqTWhxWAzPwi8MUNmldTG2Vpaf9LgUtbaJ8HHNCWWiRJUufkE2wlSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0bo2uoCSHfp30xtdgjbw0BWnN7oESVI7c2RFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlobQorEbFrRNwUEU9FxIKIeF9E7B4Rd0bEwurnbnX7XxwRiyLi6Yg4tq790IiYX227MiKiLXVJkqTOo60jK98Ebs/MIcBwYAFwETAnMwcDc6p1ImIoMAEYBowFro6ILtVxvg1MBAZXn7FtrEuSJHUSrQ4rEdEDOAKYApCZr2fm74HxwLRqt2nAidXyeGBGZq7OzOeARcDoiOgD9MjM+zMzgel1fSRJ0jauLSMr7wWWAddFxCMRcW1EvAfYKzOXAlQ/96z27we8UNe/uWrrVy1v2L6RiJgYEfMiYt6yZcvaULokSeoo2hJWugKHAN/OzIOBP1BN+byNlq5DyU20b9yYeU1mjszMkb1793639UqSpA6oLWGlGWjOzLnV+k3Uwstvq6kdqp8v1e3fv65/E7Ckam9qoV2SJKn1YSUzfwO8EBH7VU1HAU8CtwBnVG1nALOq5VuACRHRLSIGUruQ9oFqqmhlRIyp7gI6va6PJEnaxrX1rcvnAddHxA7As8BZ1ALQzIg4G1gMnAyQmU9ExExqgWYNcG5mrq2OMwmYCuwI3FZ9JEmS2hZWMvNRYGQLm456m/0vBS5toX0ecEBbapEkSZ2TT7CVJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVrWujC5AkaUOLLzmw0SWozt5fmN/Q73dkRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFa3NYSUiukTEIxFxa7W+e0TcGRELq5+71e17cUQsioinI+LYuvZDI2J+te3KiIi21iVJkjqHLTGy8mlgQd36RcCczBwMzKnWiYihwARgGDAWuDoiulR9vg1MBAZXn7FboC5JktQJtCmsREQT8NfAtXXN44Fp1fI04MS69hmZuToznwMWAaMjog/QIzPvz8wEptf1kSRJ27i2jqz8M/A54M26tr0ycylA9XPPqr0f8ELdfs1VW79qecP2jUTExIiYFxHzli1b1sbSJUlSR9DqsBIRHwJeysyHNrdLC225ifaNGzOvycyRmTmyd+/em/m1kiSpI+vahr7vB8ZFxPFAd6BHRHwf+G1E9MnMpdUUz0vV/s1A/7r+TcCSqr2phXZJkqTWj6xk5sWZ2ZSZA6hdOHtXZn4MuAU4o9rtDGBWtXwLMCEiukXEQGoX0j5QTRWtjIgx1V1Ap9f1kSRJ27i2jKy8na8AMyPibGAxcDJAZj4RETOBJ4E1wLmZubbqMwmYCuwI3FZ9JEmStkxYycx7gHuq5eXAUW+z36XApS20zwMO2BK1SJKkzsUn2EqSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUVrdViJiP4RcXdELIiIJyLi01X77hFxZ0QsrH7uVtfn4ohYFBFPR8Sxde2HRsT8atuVERFtOy1JktRZtGVkZQ1wYWbuD4wBzo2IocBFwJzMHAzMqdaptk0AhgFjgasjokt1rG8DE4HB1WdsG+qSJEmdSKvDSmYuzcyHq+WVwAKgHzAemFbtNg04sVoeD8zIzNWZ+RywCBgdEX2AHpl5f2YmML2ujyRJ2sZtkWtWImIAcDAwF9grM5dCLdAAe1a79QNeqOvWXLX1q5Y3bG/peyZGxLyImLds2bItUbokSSpcm8NKROwM/DtwQWa+uqldW2jLTbRv3Jh5TWaOzMyRvXv3fvfFSpKkDqdNYSUitqcWVK7PzB9Vzb+tpnaofr5UtTcD/eu6NwFLqvamFtolSZLadDdQAFOABZn59bpNtwBnVMtnALPq2idERLeIGEjtQtoHqqmilRExpjrm6XV9JEnSNq5rG/q+H/g4MD8iHq3a/h74CjAzIs4GFgMnA2TmExExE3iS2p1E52bm2qrfJGAqsCNwW/WRJElqfVjJzJ/T8vUmAEe9TZ9LgUtbaJ8HHNDaWiRJUuflE2wlSVLRDCuSJKlohhVJklQ0w4okSSqaYUWSJBXNsCJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRDCuSJKlohhVJklS0ro0uQHo3Fl9yYKNLUJ29vzC/0SVI2gY4siJJkopmWJEkSUUzrEiSpKIZViRJUtEMK5IkqWiGFUmSVDTDiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkqmmFFkiQVzbAiSZKKZliRJElFM6xIkqSiGVYkSVLRigkrETE2Ip6OiEURcVGj65EkSWUoIqxERBfgW8BxwFDgoxExtLFVSZKkEhQRVoDRwKLMfDYzXwdmAOMbXJMkSSpAKWGlH/BC3Xpz1SZJkrZxXRtdQCVaaMuNdoqYCEysVl+LiKe3alUqzj6wB/C7Rtehyhdb+tOV2s6/9cK0z9/6Pm+3oZSw0gz0r1tvApZsuFNmXgNc015FqTwRMS8zRza6Dklbl3/rqlfKNNCDwOCIGBgROwATgFsaXJMkSSpAESMrmbkmIj4F3AF0Ab6XmU80uCxJklSAIsIKQGbOBmY3ug4Vz2lAadvg37rWi8yNrmOVJEkqRinXrEiSJLXIsCJJkopmWJEkSUUzrKh4UfOxiPhCtb53RIxudF2StryI2DEi9mt0HSqLYUUdwdXA+4CPVusrqb34UlInEhEnAI8Ct1frIyLCZ27JsKIO4c8z81xgFUBmvgzs0NiSJG0F/0jtxba/B8jMR4EBDaxHhTCsqCN4IyK6UL0vKiJ6A282tiRJW8GazHyl0UWoPIYVdQRXAv8B7BkRlwI/By5rbEmStoLHI+JUoEtEDI6IfwHua3RRajwfCqcOISKGAEdRe0P3nMxc0OCSJG1hEbET8HngGGp/63cAX8rMVQ0tTA1nWFGxImL3TW3PzBXtVYskqXEMKypWRDxH7TqVqGtet56Z+d6GFCZpi4qI/6S6Jq0lmTmuHctRgQwrkqSGioi/3NT2zPxpe9WiMhlW1CFExG7AYKD7urbMvLdxFUmS2kvXRhcgvZOI+ATwaaCJ2gOjxgD3A0c2si5JW1ZEDAa+DAzlrf9j4pTvNs5bl9URfBoYBTyfmR8EDgaWNbYkSVvBdcC3gTXAB4HpwL81tCIVwbCijmDVulsXI6JbZj4F+O4QqfPZMTPnULtE4fnM/EccQRVOA6ljaI6IXYGbgTsj4mVgSYNrkrTlrYqI7YCFEfEp4EVgzwbXpAJ4ga06lOqugZ7A7Zn5eqPrkbTlRMQoYAGwK/Alan/rX83MXza0MDWcYUUdQnU3UH/qRgMz8+HGVSRJai9OA6l4EfEl4EzgWf70AsPEuWypU4iIWza13YfCybCijuAUYF+nfaRO633AC8ANwFze+tRqybCiDuFxanPYL/uSJUQAAAPDSURBVDW6EElbxZ8BRwMfBU4FfgzckJlPNLQqFcNrVlS8iBgJzKIWWlava3doWOp8IqIbtdByBXBJZv5Lg0tSARxZUUcwDbgcmM+frlmR1IlUIeWvqQWVAcCVwI8aWZPK4ciKihcRP83MTb7oTFLHFRHTgAOA24AZmfl4g0tSYQwrKl5EfJ3a9M8tvHUayFuXpU4gIt4E/lCt1v9HKYDMzB7tX5VKYlhR8SLi7haaMzO9dVmStgGGFUmSVDRfZKjiRcReETElIm6r1odGxNmNrkuS1D4MK+oIpgJ3AH2r9WeACxpWjSSpXRlW1BHskZkzqW5bzsw1wNrGliRJai+GFXUEf4iIXlR3CUTEGOCVxpYkSWovPhROHcFnqN22vG9E/ALoDZzU2JIkSe3Fu4FUrIjYOzMXV8tdgf2oPXfh6cx8o6HFSZLajdNAKtnNdcs3ZuYTmfm4QUWSti2GFZWs/jXx721YFZKkhjKsqGT5NsuSpG2I16yoWBGxltr7QgLYEfivdZvwfSGStM0wrEiSpKI5DSRJkopmWJEkSUUzrEiSpKIZViS1u4joHRFXR8SvI2J1RPw2IuZExNGNrk1SeXzcvqRG+HdgJ+BsYBGwJ/CXQK9GFiWpTN4NJKldRcSuwMvA0Zn5f99mnx2ALwGnAbsBTwL/kJl3REQAP6F2C/vRmZkRsTPwCHBHZn6qPc5DUvtxGkhSe3ut+oyLiO5vs8911EZaTgUOBKYB/xkRw7P2f1hnACOAz1b7Xwm8Dvzd1ixcUmM4siKp3UXE/wC+S20q6BHgF8APM3NuROwLLAQGrHuRZdXnZmBJZp5TrZ8I3Ah8FfgcMDoz/1/7nomk9mBYkdQQ1ajK4cD7gLHVz89TCyozqT29uF434K7MPLbuGNcBZwKfy8wr2qFsSQ3gBbaSGiIzVwF3Vp9LIuJa4B+Bj1N7F9QoYMM3bP9x3UIVdkYBa4FB7VCypAYxrEgqxZPU/p20gNrFs3+WmXdvYv8rqI22HA3cERGzM3PW1i9TUntzGkhSu4qIXsAPge8BjwErgZHAvwDzM/PoiPg+tSmiC4GHgd2BDwDPZuaPImIscAtweHWdy98Dk4EDM/M37X1OkrYuw4qkdhUR3YAvUhsRGURtdORF4D+B/5OZKyJie2rXr5wONAErgAeAfwIWA/OBqzPzkuqY2wF3UZsmOj79F5vUqRhWJElS0XzOiiRJKpphRZIkFc2wIkmSimZYkSRJRTOsSJKkohlWJElS0QwrkiSpaIYVSZJUNMOKJEkq2v8H2aacfFegQ9YAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 648x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (9,6))\n",
+    "ax=sns.countplot(train_datavis['sex'], hue=train_datavis['income'])\n",
+    "ax.set_title('Sex vs Income')\n",
+    "plt.xlabel(\"Sex\",fontsize = 14);\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XyhnK0eyi2UO"
+   },
+   "source": [
+    "### Visualization Sex <=50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "id": "6f9pCCXb9yvB",
+    "outputId": "33f4c291-a913-4e27-bed8-5ffc14e120d8"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmMAAAGDCAYAAABnZBdiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAfH0lEQVR4nO3df7ReVX3n8ffHRAOiIEiwmERDa7Qlqb8IDP4sLW2h09bQNTCG1hKUmUxZaH/XQjsjUzuZkWrLSKdgGaEE64gZiiWrq1iZ+KutCAYVQgiUaChEIolKMWrBCXznj2en83Bzk5vcm7jvvXm/1nrWc853733OfvLHXZ/sc57npKqQJElSH0/rPQFJkqSDmWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYk6RxSnJKkieTfGvotWyofVaSq5N8M8lXk/z6UNv8JJVkZttPkj9Ock+SOT0+j6Q+ZvaegCRNBkkOBWZW1fZ9HPpQVc3dTdt/BhYALwS+D/hEkrur6qMjzh3gT4FXAT9SVQ/v4xwkTWGujEmaNJL8dpKvJNme5N4kp7b605JcmORLSb6eZFWSo1rbFUmuHzrGJUnWtICzN+c8OcmfAg8Bi/bzRzoH+P2qeqSqNgD/Ezh3RJ8ZwDXAYuAUg5h08DGMSZoUkrwEeCtwYlU9GzgNuL81/zJwBvAjwPOBR4A/aW2/Abw0yblJXgecByyrPTzrLcmxSd6eZAPwQQZB7JVVdUtrf22Sf9rD67VDhzsmycNJNiW5NMlh7RhHtrneMdT3DmDhiOl8EPhB4Meq6ut7/y8mabrwMqWkyeIJYBZwfJJtVXX/UNt/AN5aVZsBkvxn4IEkv1hV30nyJuCjwHbgbTv7jZTkBcDlwGuAj7Tj/u3I4FZVfwc8Zy/mfA/w8vb+QmAl8EftuM9qfR4d6v8o8OwRx/hJ4Peq6p/24nySpiFXxiRNClW1EfhVBvdZbU1yXZLnt+YXAh/ZuTIFbGAQ3p7Xxt4GfBkIsGoPpzmMwcrUZgarVBv2tIK2F3P+alXdXVVPVtUm4O3Ama35W+398KEhhzMIjMN+Brg4yVvGOw9JU5thTNKkUVX/q6peyyB8FXBJa3oQ+Kmqes7Q65Cq+gpAkgsYrKo9xCAQ7e74G4DvZ3DZ8wTgviSrk5yZZNbOfkleN+IbkiNfr9vdKRgEQqrqEWAL8LKh9pcB60eM+Qzws8B7k/z8mP9IkqadTOA/hZK037R7xuYAf88g1LwPeFpVnZvk14AlDO4F+8cks4FXV9WNSV4M3AqcAnwHuA340ar64l6c89nAv2VwU/1CBjfQ37kPcz6FwYrcg8Bc4Frg/qp6c2t/F4NvSJ7BYBXvE8Cbq+qjSeYDm4CnV9WOJD/B4NLpuVV1PZIOGq6MSZosZgHvAr4GfBU4Bvid1vZeYDXwsSTbgc8C/6r9RtefA5dU1R1VdV8b84Hhla7dqartVXVVVb0OOAnYuo9zfiVwC/BtBitcdzFYddvpYuBLwD8CnwLePfJnLYbmcjPwRuCaJD+7j/OQNIW5MiZJktSRK2OSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLU0ZR9HNLRRx9d8+fP7z0NSZKkMd1+++1fq6rZo7VN2TA2f/581q5d23sakiRJY0ryj7tr8zKlJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6mjMMJbk6iRbk9w1ov62JPcmWZ/kD4bqFyXZ2NpOG6qfkGRda7ssSVp9VpIPt/qtSebvv48nSZI0ue3Nytg1wOnDhSQ/CiwBXlpVC4H3tPrxwFJgYRtzeZIZbdgVwHJgQXvtPOZ5wCNV9SLgUuCSCXweSZKkKWXMMFZVnwa+MaJ8PvCuqnq89dna6kuA66rq8araBGwETkpyLHB4Vd1SVQVcC5wxNGZl274eOHXnqpkkSdJ0N957xl4MvK5dVvxUkhNbfQ7w4FC/za02p22PrD9lTFXtAB4FnjvOeUmSJE0p430c0kzgSOBk4ERgVZLvB0Zb0ao91Bmj7SmSLGdwqZMXvOAF+zhlSZKkyWe8K2ObgRtq4DbgSeDoVp831G8u8FCrzx2lzvCYJDOBI9j1sigAVXVlVS2uqsWzZ4/6rE1JkqQpZbxh7C+BHwNI8mLgGcDXgNXA0vYNyeMY3Kh/W1VtAbYnObndD3YOcGM71mpgWds+E/h4u69MkiRp2hvzMmWSDwGnAEcn2QxcDFwNXN1+7uK7wLIWoNYnWQXcDewALqiqJ9qhzmfwzcxDgZvaC+Aq4ANJNjJYEVu6fz7a/nXCb13bewrSQen2d5/TewqSdECNGcaq6uzdNL1pN/1XACtGqa8FFo1Sfww4a6x5SJIkTUf+Ar8kSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLU0ZhhLMnVSbYmuWuUtt9MUkmOHqpdlGRjknuTnDZUPyHJutZ2WZK0+qwkH271W5PM3z8fTZIkafLbm5Wxa4DTRxaTzAN+AnhgqHY8sBRY2MZcnmRGa74CWA4saK+dxzwPeKSqXgRcClwyng8iSZI0FY0Zxqrq08A3Rmm6FHg7UEO1JcB1VfV4VW0CNgInJTkWOLyqbqmqAq4Fzhgas7JtXw+cunPVTJIkabob1z1jSd4AfKWq7hjRNAd4cGh/c6vNadsj608ZU1U7gEeB5+7mvMuTrE2ydtu2beOZuiRJ0qSyz2EsyTOB3wXeMVrzKLXaQ31PY3YtVl1ZVYuravHs2bP3ZrqSJEmT2nhWxn4AOA64I8n9wFzg80m+j8GK17yhvnOBh1p97ih1hsckmQkcweiXRSVJkqadfQ5jVbWuqo6pqvlVNZ9BmHplVX0VWA0sbd+QPI7Bjfq3VdUWYHuSk9v9YOcAN7ZDrgaWte0zgY+3+8okSZKmvb35aYsPAbcAL0myOcl5u+tbVeuBVcDdwEeBC6rqidZ8PvB+Bjf1fwm4qdWvAp6bZCPw68CF4/wskiRJU87MsTpU1dljtM8fsb8CWDFKv7XAolHqjwFnjTUPSZKk6chf4JckSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdjRnGklydZGuSu4Zq705yT5I7k3wkyXOG2i5KsjHJvUlOG6qfkGRda7ssSVp9VpIPt/qtSebv348oSZI0ee3Nytg1wOkjajcDi6rqpcA/ABcBJDkeWAosbGMuTzKjjbkCWA4saK+dxzwPeKSqXgRcClwy3g8jSZI01YwZxqrq08A3RtQ+VlU72u5ngbltewlwXVU9XlWbgI3ASUmOBQ6vqluqqoBrgTOGxqxs29cDp+5cNZMkSZru9sc9Y28Bbmrbc4AHh9o2t9qctj2y/pQxLeA9Cjx3tBMlWZ5kbZK127Zt2w9TlyRJ6mtCYSzJ7wI7gA/uLI3SrfZQ39OYXYtVV1bV4qpaPHv27H2driRJ0qQz7jCWZBnwM8AvtEuPMFjxmjfUbS7wUKvPHaX+lDFJZgJHMOKyqCRJ0nQ1rjCW5HTgt4E3VNV3hppWA0vbNySPY3Cj/m1VtQXYnuTkdj/YOcCNQ2OWte0zgY8PhTtJkqRpbeZYHZJ8CDgFODrJZuBiBt+enAXc3O61/2xV/VJVrU+yCribweXLC6rqiXao8xl8M/NQBveY7bzP7CrgA0k2MlgRW7p/PpokSdLkN2YYq6qzRylftYf+K4AVo9TXAotGqT8GnDXWPCRJkqYjf4FfkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdTRmGEtydZKtSe4aqh2V5OYk97X3I4faLkqyMcm9SU4bqp+QZF1ruyxJWn1Wkg+3+q1J5u/fjyhJkjR57c3K2DXA6SNqFwJrqmoBsKbtk+R4YCmwsI25PMmMNuYKYDmwoL12HvM84JGqehFwKXDJeD+MJEnSVDNmGKuqTwPfGFFeAqxs2yuBM4bq11XV41W1CdgInJTkWODwqrqlqgq4dsSYnce6Hjh156qZJEnSdDfee8aeV1VbANr7Ma0+B3hwqN/mVpvTtkfWnzKmqnYAjwLPHee8JEmSppT9fQP/aCtatYf6nsbsevBkeZK1SdZu27ZtnFOUJEmaPMYbxh5ulx5p71tbfTMwb6jfXOChVp87Sv0pY5LMBI5g18uiAFTVlVW1uKoWz549e5xTlyRJmjzGG8ZWA8va9jLgxqH60vYNyeMY3Kh/W7uUuT3Jye1+sHNGjNl5rDOBj7f7yiRJkqa9mWN1SPIh4BTg6CSbgYuBdwGrkpwHPACcBVBV65OsAu4GdgAXVNUT7VDnM/hm5qHATe0FcBXwgSQbGayILd0vn0ySJGkKGDOMVdXZu2k6dTf9VwArRqmvBRaNUn+MFuYkSZIONv4CvyRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSepoQmEsya8lWZ/kriQfSnJIkqOS3JzkvvZ+5FD/i5JsTHJvktOG6ickWdfaLkuSicxLkiRpqhh3GEsyB/hlYHFVLQJmAEuBC4E1VbUAWNP2SXJ8a18InA5cnmRGO9wVwHJgQXudPt55SZIkTSUTvUw5Ezg0yUzgmcBDwBJgZWtfCZzRtpcA11XV41W1CdgInJTkWODwqrqlqgq4dmiMJEnStDbuMFZVXwHeAzwAbAEeraqPAc+rqi2tzxbgmDZkDvDg0CE2t9qctj2yLkmSNO1N5DLlkQxWu44Dng8cluRNexoySq32UB/tnMuTrE2ydtu2bfs6ZUmSpElnIpcpfxzYVFXbqur/AjcArwYebpceae9bW//NwLyh8XMZXNbc3LZH1ndRVVdW1eKqWjx79uwJTF2SJGlymEgYewA4Ockz27cfTwU2AKuBZa3PMuDGtr0aWJpkVpLjGNyof1u7lLk9ycntOOcMjZEkSZrWZo53YFXdmuR64PPADuALwJXAs4BVSc5jENjOav3XJ1kF3N36X1BVT7TDnQ9cAxwK3NRekiRJ0964wxhAVV0MXDyi/DiDVbLR+q8AVoxSXwssmshcJEmSpiJ/gV+SJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSRxN6HJIkaWIeeOcP956CdFB6wTvW9Z7Cv3BlTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHU0ojCV5TpLrk9yTZEOSVyU5KsnNSe5r70cO9b8oycYk9yY5bah+QpJ1re2yJJnIvCRJkqaKia6MvRf4aFX9IPAyYANwIbCmqhYAa9o+SY4HlgILgdOBy5PMaMe5AlgOLGiv0yc4L0mSpClh3GEsyeHA64GrAKrqu1X1T8ASYGXrthI4o20vAa6rqserahOwETgpybHA4VV1S1UVcO3QGEmSpGltIitj3w9sA/4syReSvD/JYcDzqmoLQHs/pvWfAzw4NH5zq81p2yPru0iyPMnaJGu3bds2galLkiRNDhMJYzOBVwJXVNUrgG/TLknuxmj3gdUe6rsWq66sqsVVtXj27Nn7Ol9JkqRJZyJhbDOwuapubfvXMwhnD7dLj7T3rUP95w2Nnws81OpzR6lLkiRNe+MOY1X1VeDBJC9ppVOBu4HVwLJWWwbc2LZXA0uTzEpyHIMb9W9rlzK3Jzm5fYvynKExkiRJ09rMCY5/G/DBJM8Avgy8mUHAW5XkPOAB4CyAqlqfZBWDwLYDuKCqnmjHOR+4BjgUuKm9JEmSpr0JhbGq+iKweJSmU3fTfwWwYpT6WmDRROYiSZI0FfkL/JIkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKmjCYexJDOSfCHJX7X9o5LcnOS+9n7kUN+LkmxMcm+S04bqJyRZ19ouS5KJzkuSJGkq2B8rY78CbBjavxBYU1ULgDVtnyTHA0uBhcDpwOVJZrQxVwDLgQXtdfp+mJckSdKkN6EwlmQu8NPA+4fKS4CVbXslcMZQ/bqqeryqNgEbgZOSHAscXlW3VFUB1w6NkSRJmtYmujL234G3A08O1Z5XVVsA2vsxrT4HeHCo3+ZWm9O2R9Z3kWR5krVJ1m7btm2CU5ckSepv3GEsyc8AW6vq9r0dMkqt9lDftVh1ZVUtrqrFs2fP3svTSpIkTV4zJzD2NcAbkvxr4BDg8CR/Djyc5Niq2tIuQW5t/TcD84bGzwUeavW5o9QlSZKmvXGvjFXVRVU1t6rmM7gx/+NV9SZgNbCsdVsG3Ni2VwNLk8xKchyDG/Vva5cytyc5uX2L8pyhMZIkSdPaRFbGduddwKok5wEPAGcBVNX6JKuAu4EdwAVV9UQbcz5wDXAocFN7SZIkTXv7JYxV1SeBT7btrwOn7qbfCmDFKPW1wKL9MRdJkqSpxF/glyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR2NO4wlmZfkE0k2JFmf5Fda/agkNye5r70fOTTmoiQbk9yb5LSh+glJ1rW2y5JkYh9LkiRpapjIytgO4Deq6oeAk4ELkhwPXAisqaoFwJq2T2tbCiwETgcuTzKjHesKYDmwoL1On8C8JEmSpoxxh7Gq2lJVn2/b24ENwBxgCbCydVsJnNG2lwDXVdXjVbUJ2AiclORY4PCquqWqCrh2aIwkSdK0tl/uGUsyH3gFcCvwvKraAoPABhzTus0BHhwatrnV5rTtkXVJkqRpb8JhLMmzgL8AfrWqvrmnrqPUag/10c61PMnaJGu3bdu275OVJEmaZCYUxpI8nUEQ+2BV3dDKD7dLj7T3ra2+GZg3NHwu8FCrzx2lvouqurKqFlfV4tmzZ09k6pIkSZPCRL5NGeAqYENV/dFQ02pgWdteBtw4VF+aZFaS4xjcqH9bu5S5PcnJ7ZjnDI2RJEma1mZOYOxrgF8E1iX5Yqv9DvAuYFWS84AHgLMAqmp9klXA3Qy+iXlBVT3Rxp0PXAMcCtzUXpIkSdPeuMNYVf0do9/vBXDqbsasAFaMUl8LLBrvXCRJkqYqf4FfkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdWQYkyRJ6sgwJkmS1JFhTJIkqSPDmCRJUkeGMUmSpI4MY5IkSR0ZxiRJkjoyjEmSJHVkGJMkSerIMCZJktSRYUySJKkjw5gkSVJHhjFJkqSODGOSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJEmSOjKMSZIkdTRpwliS05Pcm2Rjkgt7z0eSJOl7YVKEsSQzgD8Bfgo4Hjg7yfF9ZyVJknTgTYowBpwEbKyqL1fVd4HrgCWd5yRJknTATZYwNgd4cGh/c6tJkiRNazN7T6DJKLXapVOyHFjedr+V5N4DOitNJ0cDX+s9Ce27vGdZ7ylIe+Lflqnq4tGixwH1wt01TJYwthmYN7Q/F3hoZKequhK48ns1KU0fSdZW1eLe85A0vfi3RfvDZLlM+TlgQZLjkjwDWAqs7jwnSZKkA25SrIxV1Y4kbwX+BpgBXF1V6ztPS5Ik6YCbFGEMoKr+Gvjr3vPQtOXlbUkHgn9bNGGp2uU+eUmSJH2PTJZ7xiRJkg5KhjFNWUkqyQeG9mcm2Zbkr8YYd8pYfSRNf0meSPLFodf8A3iu+5McfaCOr6lt0twzJo3Dt4FFSQ6tqn8GfgL4Suc5SZo6/rmqXt57EpIrY5rqbgJ+um2fDXxoZ0OSk5J8JskX2vtLRg5OcliSq5N8rvXzMVzSQSzJCUk+leT2JH+T5NhW/2SSS5N8OsmGJCcmuSHJfUn+y9D4v2xj17cfKh/tHG9KcltbjfvT9nxmHcQMY5rqrgOWJjkEeClw61DbPcDrq+oVwDuA/zrK+N8FPl5VJwI/Crw7yWEHeM6SJodDhy5RfiTJ04E/Bs6sqhOAq4EVQ/2/W1WvB94H3AhcACwCzk3y3NbnLW3sYuCXh+oAJPkh4I3Aa9qq3BPALxzAz6gpwMuUmtKq6s52n8fZ7PrTKEcAK5MsYPB4raePcoifBN6Q5Dfb/iHAC4ANB2TCkiaTp1ymTLKIQbi6OQkMfvdyy1D/nT9Gvg5YX1Vb2rgvM3iKzNcZBLCfa/3mAQtafadTgROAz7VzHAps3b8fS1ONYUzTwWrgPcApwPD/Qn8f+ERV/VwLbJ8cZWyAf1NVPudUUhiErFftpv3x9v7k0PbO/ZlJTgF+HHhVVX0nyScZ/Adv5DlWVtVF+23WmvK8TKnp4GrgnVW1bkT9CP7/Df3n7mbs3wBvS/svapJXHJAZSpoK7gVmJ3kVQJKnJ1m4D+OPAB5pQewHgZNH6bMGODPJMe0cRyXZ7QOkdXAwjGnKq6rNVfXeUZr+APhvSf6eweWG0fw+g8uXdya5q+1LOghV1XeBM4FLktwBfBF49T4c4qMMVsjuZPC35LOjnONu4D8CH2v9bgaOnejcNbX5C/ySJEkduTImSZLUkWFMkiSpI8OYJElSR4YxSZKkjgxjkiRJHRnGJE16SeYmubE9B/BLSd6b5Bkd53NGkuOH9t+Z5Md7zUfS1GYYkzSptR/kvQH4y6paALwYeBZPfWbg99oZwL+Esap6R1X9n47zkTSFGcYkTXY/BjxWVX8GUFVPAL8GvCXJYUnek2RdkjuTvA0gyYlJPpPkjiS3JXl2knOT/I+dB03yV+3xNST5VpI/TPL5JGuSzG71f5/kc+04f5HkmUleDbyBwUPlv5jkB5Jck+TMNubUJF9oc7o6yaxWvz/J77VzrGu/0C5JhjFJk95C4PbhQlV9E3gA+HfAccArquqlwAfb5csPA79SVS9j8KzAfx7jHIcBn6+qVwKfAi5u9Ruq6sR2nA3AeVX1GQbPQ/2tqnp5VX1p50GSHAJcA7yxqn6YwfN/zx86z9faOa4AfhNJwjAmafILMNqjQgK8HnhfVe0AqKpvAC8BtlTV51rtmzvb9+BJBgEO4M+B17btRUn+Nsk64BcYBMM9eQmwqar+oe2vbHPc6Yb2fjswf4xjSTpIGMYkTXbrgcXDhSSHA/MYPajtLrzt4Kl/8w7Zwzl3jr8GeGtb5fq9McbsPPeePN7en2CwaiZJhjFJk94a4JlJzgFIMgP4QwZB6WPALyWZ2dqOAu4Bnp/kxFZ7dmu/H3h5kqclmQecNHSOpzF4QDTAzwN/17afDWxJ8nQGK2M7bW9tI90DzE/yorb/iwwue0rSbhnGJE1qVVXAzwFnJbkP+AfgMeB3gPczuHfsziR3AD9fVd8F3gj8cavdzGBF6++BTcA64D3A54dO821gYZLbGXxh4J2t/p+AW9sx7hnqfx3wW+1G/R8YmutjwJuB/90ubT4JvG9//VtImp4y+DsnSQevJN+qqmf1noekg5MrY5IkSR25MiZJktSRK2OSJEkdGcYkSZI6MoxJkiR1ZBiTJEnqyDAmSZLUkWFMkiSpo/8HlDDywq+VIpcAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (10,6))\n",
+    "ax=sns.countplot(train_datavis['sex'],\n",
+    "                order = train_datavis['sex'].value_counts().index)\n",
+    "ax.set_title('sex <=50K')\n",
+    "plt.xlabel(\"Occupation\",fontsize = 10);\n",
+    "plt.xticks()\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "id": "R2PUHMc9Uxcy",
+    "outputId": "822746c8-449f-4865-cd48-a9353013fce8"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,10))\n",
+    "ax=sns.countplot(train_clustvis_rel['sex'],\n",
+    "                order = train_clustvis_rel['sex'].value_counts().index)\n",
+    "ax.set_title('Sex / Wage Class (<=50K)',fontsize=18)\n",
+    "ax.set_xlabel('Sex',fontsize=15)\n",
+    "ax.set_ylabel('Count',fontsize=15)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "U1133R-7VlzW"
+   },
+   "source": [
+    "## Age"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "jdEzl92ojKKV"
+   },
+   "source": [
+    "### Visualization Proportion Data of Age vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "id": "XchoJNreVjhM",
+    "outputId": "ca58ac23-765d-4e48-d5ac-c53ad2aca212"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 2880x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (40,6))\n",
+    "ax = fig.add_subplot(1,2,2)\n",
+    "(age.div(age.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax = ax);\n",
+    "plt.xlabel('Age',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "id": "w_p4em4gHKt5",
+    "outputId": "87726880-48a5-48ff-e09b-f399487c3920"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 648x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (9,6))\n",
+    "ax=sns.countplot(train_data_onehot['age'], hue=train_datavis['income'])\n",
+    "ax.set_title('age vs Income')\n",
+    "plt.xlabel(\"age\",fontsize = 14);\n",
+    "plt.xticks()\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "id": "K9_tR2GikZaY",
+    "outputId": "09caad79-d781-4597-baea-073f34b7a173"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,10))\n",
+    "ax=sns.countplot(train_clustvis_rel['age'],\n",
+    "                order = train_clustvis_rel['age'].value_counts().index)\n",
+    "ax.set_title('Age / Wage Class (<=50K)',fontsize=18)\n",
+    "ax.set_xlabel('Age',fontsize=15)\n",
+    "ax.set_ylabel('Count',fontsize=15)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "85zad3kAG6Uo"
+   },
+   "source": [
+    "## Relationship"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yKWi2HHTn2au"
+   },
+   "source": [
+    "### Visualization Proportion Data of Relationship vs Income"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "id": "gYSV3AVenQ0Q",
+    "outputId": "fa45e90b-52f3-4e43-b737-20f5d7d6e9c0"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjUAAAGyCAYAAAAcSDVlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3deZhcZZn38e9NWAMk7EwggURBdsISEBEcAXFBVgVEUCGizMgO8jo4OoI4MqiIsjgqgizKIiIKCqgQYRABIQkIGpAoawAhhB3ZAvf7xzkdOqGX6u6qPlWH7+e66uqq55yq+nVdSffdz3mWyEwkSZI63UJVB5AkSWoGixpJklQLFjWSJKkWLGokSVItWNRIkqRasKiRJEm1sHDVAZpphRVWyPHjx1cdQ5IktdC0adMez8wVF2yvVVEzfvx4pk6dWnUMSZLUQhFxf0/tXn6SJEm1YFEjSZJqwaJGkiTVQq3G1PTklVdeYdasWbz44otVR2k7iy++OGPHjmWRRRapOookSUM2bEVNRPwQ2BF4LDPXL9uWA34CjAfuA/bMzCfLY58H9gdeBQ7NzN8M5n1nzZrF0ksvzfjx44mIIX8fdZGZzJkzh1mzZjFhwoSq40iSNGTDefnpbOD9C7QdDUzJzDWBKeVjImJdYC9gvfI5/xsRIwbzpi+++CLLL7+8Bc0CIoLll1/eHixJUm0MW1GTmdcBTyzQvAtwTnn/HGDXbu0XZuZLmXkv8Ddg88G+twVNz/xcJEl1UvVA4ZUz8xGA8utKZfuqwIPdzptVtr1BRBwQEVMjYurs2bNbGnbLLbds6etLkqTBq7qo6U1PXQjZ04mZeXpmTsrMSSuu+IbFBZvqhhtuaOnrS5Kkwau6qHk0IsYAlF8fK9tnAeO6nTcWeHiYs73BUkstBcC1117Lu9/9bnbffXfWXntt9tlnHzKLmuuWW25hyy23ZOLEiWy++eY8++yzvPjii0yePJkNNtiAjTfemGuuuQaAs88+m1133ZWddtqJCRMmcNppp3HSSSex8cYbs8UWW/DEE8XVur///e+8//3vZ9NNN2XrrbfmrrvuquYDkCSpjVVd1FwG7Fve3xe4tFv7XhGxWERMANYEbq4gX69uvfVWvv3tbzNjxgzuuece/vCHP/Dyyy/zkY98hJNPPpk//elPXH311SyxxBJ85zvfAeCOO+7gggsuYN999503QPfPf/4z559/PjfffDNf+MIXGDlyJLfeeivveMc7OPfccwE44IADOPXUU5k2bRonnngiBx54YGXftyRJ7Wo4p3RfALwbWCEiZgHHACcAF0XE/sADwB4AmfmXiLgImAHMBQ7KzFeHK2sjNt98c8aOHQvARhttxH333cfo0aMZM2YMm222GQCjRo0C4Prrr+eQQw4BYO2112b11Vfn7rvvBmCbbbZh6aWXZumll2b06NHstNNOAGywwQbcfvvtPPfcc9xwww3sscce8977pZdeGrbvU5KkTjFsRU1mfrSXQ9v1cv5Xga+2LtHQLLbYYvPujxgxgrlz55KZPc4o6ro01d/rLLTQQvMeL7TQQsydO5fXXnuNZZZZhttuu62J6SVJqp/aryg8nNZee20efvhhbrnlFjbbbDOeffZZllhiCd71rndx3nnnse2223L33XfzwAMPsNZaazF9+vR+X3PUqFFMmDCBn/70p+yxxx5kJrfffjsTJ04chu9IktSOxh99edNf874TPtj01xxuVY+pqZVFF12Un/zkJxxyyCFMnDiR7bffnhdffJEDDzyQV199lQ022ICPfOQjnH322fP10PTnvPPO48wzz2TixImst956XHrppf0/SZKkN5no69JIp5k0aVJOnTp1vrY777yTddZZp6JE7c/PR5I6z5u9pyYipmXmpAXb7amRJEm1YFEjSZJqwaJGkiTVgkWNJEmqBYsaSZJUC65TI0lquTf7bB0ND3tqOsC1117L6NGj2Wijjdhoo4047rjj5h379a9/zVprrcUaa6zBCSecMK99v/324+KLLwbgiSeeYOONN+ass84a9uySJA2XN11PTbP/WhjsXwovv/wyr7zyCksuuWRD52+99db86le/mq/t1Vdf5aCDDuKqq65i7NixbLbZZuy8886su+668855+umned/73scBBxzA5MmTB5VVkqROYE/NMLvzzjv57Gc/y1prrTVvU8vBuvnmm1ljjTV4y1vewqKLLspee+0132rDzz33HB/4wAfYe++9+cxnPjPU6JIktbU3XU9NFZ5//nkuuugizjzzTDKTyZMnc/vtt7P00ksDcMQRR3DNNde84Xl77bUXRx99NAA33ngjEydOZJVVVuHEE09kvfXW46GHHmLcuHHzzh87dix//OMf5z0+8sgj+dSnPsURRxzR4u9QkqTqWdQMgzFjxrDhhhtyxhlnsPbaa7/h+Le+9a0+n7/JJptw//33s9RSS3HFFVew6667MnPmzB53/+6+S/i2227LpZdeylFHHcVKK6009G9EkqQ2ZlEzDC6++GLOPPNMdtttNz760Y+y7777svrqq8873l9PzahRo+a17bDDDhx44IE8/vjjjB07lgcffHDesVmzZrHKKqvM9/ytttqKHXbYgWuuuWZez5CkvjlTR+pMFjXD4L3vfS/vfe97mTNnDj/+8Y/ZZZddWGGFFTjjjDMYP358vz01//jHP1h55ZWJCG6++WZee+01ll9+eZZZZhlmzpzJvffey6qrrsqFF17I+eefP99zDz/8cB555BF22203rrjiChZddNFWfquSJFXGgcLDaPnll+ewww7jtttu4/jjj2fEiBENPe/iiy9m/fXXZ+LEiRx66KFceOGFRAQLL7wwp512Gu973/tYZ5112HPPPVlvvfXe8Pyvfe1rjBs3jo9//OO89tprzf62JElqC2+6npp26QLefPPNGz734IMP5uCDD+7x2A477MAOO+zwhvazzz57vseuUSNJqjt7aiRJUi1Y1EiSpFqwqJEkSbVgUSNJkmrBokaSJNWCRY0kSaoFi5o2sN9++zFhwgQ22mgjNtpoI2677TYAMpNDDz2UNdZYgw033JDp06fPe85SSy017/4VV1zBmmuuyQMPPDDs2SVJahdvunVqOHZ0k1/v6X5PefLJJ1l22WX7POcb3/gGu++++3xtV155JTNnzmTmzJn88Y9/5DOf+cx8G1YCTJkyhUMOOYTf/va3rLbaagPPL0lSTdhTMwwmTZrE3nvvze9+97seN6HszaWXXsonPvEJIoItttiCp556ikceeWTe8d///vd8+tOf5vLLL+etb31rK6JLktQx3nw9NRW4++67ufLKKznttNM46KCD+PjHP85+++033+aTX/jCFzjuuOPYbrvtOOGEE1hsscV46KGHGDdu3Lxzxo4dy0MPPcSYMWN46aWX2GWXXbj22mt73Plbby5uwChJ9tQMixEjRrDjjjtyySWXcN1113HPPfew2mqrcfPNNwPwP//zP9x1113ccsstPPHEE3zta18D6LFXJyIAWGSRRdhyyy0588wzh+8bkSSpjVnUDJOnn36a008/nZ133pm7776bM888kw033BCAMWPGEBEstthiTJ48eV6xM3bsWB588MF5rzFr1qx5vTsLLbQQF110EbfccgvHH3/88H9DkiS1GYuaYfCxj32MTTbZhHvuuYdzzz2X6667jn333ZfFF18cYN44mczkF7/4Beuvvz4AO++8M+eeey6ZyU033cTo0aMZM2bMvNcdOXIkv/rVrzjvvPPssZEkvek5pmYY7Lnnnpx99tksvHDPH/c+++zD7NmzyUw22mgjvve97wHFDtxXXHEFa6yxBiNHjuxxp+3llluOX//617zrXe9ihRVWYJdddmnp9yJJUrt68xU1DUzBbradd965z+O/+93vemyPCL7zne/0eOy5556bd3/cuHHce++9gw8oSVINePlJkiTVgkWNJEmqBYsaSZJUC2+KomYgq/i+mfi5SJLqpPZFzeKLL86cOXP8Bb6AzGTOnDnzppVLktTpaj/7aezYscyaNYvZs2dXHaXtLL744owdO7bqGJIkNUXti5pFFlmECRMmVB1DkiS1WO0vP0mSpDcHixpJklQLFjWSJKkWLGokSVItWNRIkqRasKiRJEm1YFEjSZJqwaJGkiTVgkWNJEmqBYsaSZJUCxY1kiSpFixqJElSLVjUSJKkWrCokSRJtdAWRU1EHBERf4mIP0fEBRGxeEQsFxFXRcTM8uuyVeeUJEntq/KiJiJWBQ4FJmXm+sAIYC/gaGBKZq4JTCkfS5Ik9ajyoqa0MLBERCwMjAQeBnYBzimPnwPsWlE2SZLUASovajLzIeBE4AHgEeDpzPwtsHJmPlKe8wiwUk/Pj4gDImJqREydPXv2cMWWJEltpvKiphwrswswAVgFWDIiPtbo8zPz9MyclJmTVlxxxVbFlCRJba7yogZ4D3BvZs7OzFeAS4AtgUcjYgxA+fWxCjNKkqQ21w5FzQPAFhExMiIC2A64E7gM2Lc8Z1/g0orySZKkDrBw1QEy848RcTEwHZgL3AqcDiwFXBQR+1MUPntUl1KSJLW7yosagMw8BjhmgeaXKHptJEmS+tUOl58kSZKGzKJGkiTVQr+XnyJiGeBDwL8C44ElgNkUY2CuzMwbWhlQkiSpEb321ETEKhFxBsWCeF8AFgWmAr8F7qcocq6KiBkR8ZHhCCtJktSbvnpqbqPYnmBSZv6lpxMiYgmK7QuOjIhxmXliCzJKkiT1q6+iZr3M7HPfgcx8AbgAuCAiXM5XkiRVptfLT/0VNEM9X5IkqZkGNPspIpaKiK9FxC0RMT0iTomI5VoVTpIkqVEDXXzve0BSLJS3KPAZ4EfAB5ucS5IkaUD6LGoi4lOZeUa3pncAa2bma+XxGcAtLcwnSZLUkP4uP30gIq6NiDXLxzcBZ0bEByJiZ+DbwB9amlCSJKkBffbUZOaHI2JX4MqI+CFwCPB54L8pCqLrgWNbHVKSJKk//Q4UzsxfAJsAY4FrgJ9l5qaZuXFmHpKZc1odUpIkqT8NzX7KzGcy80CKgcGnl7OelmxtNEmSpMb1WdRExGoRcVFE3BER5wH3ApsCjwO3RcROwxFSkiSpP/311JwLvAb8P+Ax4PuZ+UpmHgfsBBwVET9tcUZJkqR+9bdOzSRgYmb+PSJ+Q9FTA0Bm3gX8a0Qc0MqAkiRJjeivqJkGHBcR5wDvAe5Y8ITMPL0VwSRJkgaiv8tPnwAWA74FrAr8W8sTSZIkDUJ/69TcD+w+TFkkSZIGrdeemohYeiAvNNDzJUmSmqmvy08zI+KLETG2txMiYqFyy4SrgIOaH0+SJKkxfV1+2hr4KnBPRNwOTAUeAV4ElgXWBbYAXgCOB37Q2qiSJEm967WoycyZwJ4RMQ7Yk6LIeTuwBMXie7cCpwNXdO3aLUmSVJX+pnSTmQ8C3yxvkiRJbamhvZ8kSZLanUWNJEmqBYsaSZJUCxY1kiSpFixqJElSLTRc1ETEyhFxVER8NyJWKNveGRETWhdPkiSpMQ0VNRGxKfBXYB9gf2BUeWh7igX6JEmSKtVoT82JwMmZuTHwUrf23wDvbHoqSZKkAWq0qNkUOKeH9keAlZsXR5IkaXAaLWpeoNjvaUFrA481L44kSdLgNFrUXAocExGLlY8zIsYDXwN+1oJckiRJA9JoUXMUsBwwGxgJXA/8DXgK+GJrokmSJDWu3w0tATLzGWCriNgW2ISiGJqemVe3MpwkSVKjGipqumTm74DftSiLJEnSoPVa1ETEkY2+SGae1Jw4kiRJg9NXT80hDb5GAhY1kiSpUr0WNZnp9geSJKljuKGlJEmqhYFsaLlrRFwXEY+Xt99HxG6tDCdJktSoRje0/CzwE4pNLT9X3u4Czo+Io1oXT5IkqTGNTuk+Cjg4M3/Qre2HEXEzcBzFhpeSJEmVafTy01LANT20X1MekyRJqlSjRc0vgN17aP8wcFnz4kiSJA1Oo5ef/gYcHRHbADeWbVuUt5O6L9TnQnySJKkKjRY1+wFPAm8rb12eBCZ3e+xCfJIkqRKNbmjpQnySJKmtDXjxvYhYKiKWbEUYSZKkwRrI4nsHRcQDwNPAMxFxf0Qc2LpokiRJjWvo8lNE/CfweYr1aK4vm7cGToiIUZl5QovySZIkNaTRgcL/DhyQmRd0a5sSETOB44EhFTURsQxwBrA+xWDjT1KsXvwTYDxwH7BnZj45lPeRJEn11ejlp5WAW3povxlYuQk5TgZ+nZlrAxOBO4GjgSmZuSYwpXwsSZLUo0aLmruBvXto35uiR2XQImIU8C7gTIDMfDkznwJ2Ac4pTzsH2HUo7yNJkuqt0ctPxwIXRcS7gD9QXCLaCvhXYI8hZngLMBs4KyImAtOAw4CVM/MRgMx8JCJWGuL7SJKkGmuopyYzLwHeDvwD2BHYuby/eWb+YogZFgY2Ab6bmRsDzzOAS00RcUBETI2IqbNnzx5iFEmS1Kka7akhM6cBH2tBhlnArMz8Y/n4Yoqi5tGIGFP20owBHusl1+nA6QCTJk3KFuSTJEkdYCDr1KwcEUdFxP9GxApl2zsjYkirDWfmP4AHI2Ktsmk7YAbFRpn7lm37ApcO5X0kSVK9NbpOzaYUM5DuBdajWK/mcWB7ir2gehpEPBCHAOdFxKLAPRT7SS1EMY5nf+ABhj52R5Ik1Vijl59OBE7OzGMi4tlu7b9h/g0tByUzbwMm9XBou6G+tiRJenNo9PLTprw+vbq7R2jOOjWSJElD0mhR8wKwbA/ta9PLAF5JkqTh1GhRcylwTEQsVj7OiBgPfA34WQtySZIkDUijRc1RwHIUi+SNpNjU8m/AU8AXWxNNkiSpcQ0NFM7MZ4CtImIbivE1CwHTM/PqVoaTJElqVL9FTUTsQbHv0iLA1Zl5YstTSZIkDVCfRU1EHAB8D5gJvAh8OCImZObnhyOcJElSo/obU3MI8NXMXCszJwL7Awe3PpYkSdLA9FfUvAU4q9vjHwGLRcS/tC6SJEnSwPVX1CwBPNf1IDNfBV6imAElSZLUNhqZ/fTvEfFct8cLA/tHxJyuhsw8qenJJEmSBqC/ouYB3ri30z+YfwPLBCxq1LDxR1/e9Ne874QPNv01JUmdpc+iJjPHD1MOSZKkIWl0RWFJkqS2ZlEjSZJqwaJGkiTVgkWNJEmqhV6Lmoj4UkSMLO+vFhExfLEkSZIGpq+emi8BS5X37wVWbH0cSZKkwelrSvdDwO4RcTkQwNiIWLynEzPzgVaEkyRJalRfRc1XgdOAUykW2Lulh3OiPDai+dEkSZIa12tRk5mnR8RFwHhgOvB+YE5v50uSJFWpvxWFnwJui4jJwP9l5kvDE0uSJGlgGtnQksw8ByAitgXWpbjkNCMzr2lhNkmSpIY1VNRExKrAz4FNgYfL5lUiYiqwW2Y+3OuTJUmShkFDRQ1wCvAqsEZm3gsQEW8Bflwe27018Wrs2NEteM2nm/+akiR1iEaLmu2Bd3cVNACZeU9EHApMaUkySZKkARjqNgmvNSWFJEnSEDXaUzMFOCUiPpqZD0KxdQJwMjXvqRl/9OUted37elzGUJIkDVajPTWHAiOBeyLi/oi4D/h72XZoi7JJkiQ1rNEp3Q8Cm0TE9sDaFCsJz8jMq1sZTpIkqVGNXn4CIDOvAq5qURZJkqRBG+pAYUmSpLZgUSNJkmrBokaSJNWCRY0kSaqFAQ0UBoiIZVigGMrMJ5qWSJIkaRAa3dBydeB7wDbAIt0PUezYPaL50SRJkhrXaE/NWcAywCcpdunOliWSJEkahEaLms2BLTLzz60MI0mSNFiNDhS+F1islUEkSZKGotGi5jDgfyJijVaGkSRJGqxGLz9dStFT89eIeAmY2/1gZo5qdjBpQI4d3YLXfLr5rylJaplGi5qDW5pCkiRpiBrdpfucVgeRJEkaioYX34uIxYB9gHUppnT/BbggM19qUTZJkqSGNTRQOCLWBWYCJwFvB7YAvg3cHRHrtC6eJElSYxqd/XQycCuwWmZunZlbA6sBf6IobiRJkirV6OWndwKbZeYzXQ2Z+UxEfAG4qSXJJEmSBqDRnpoXKbZJWNDo8pgkSVKlGi1qfgn8ICLeGREjyttWwPeBy1oXT5IkqTEDWVF4JvB7ip6ZF4H/A+4GDm9NNEmSpMY1uk7NU8AuEbEmsDYQwIzM/Fsrw0mSJDWq4XVqADJzJkWPjSRJUlvptaiJiFOAz2fm8+X9XmXmoU1PJkmSNAB99dRsACzS7X5LRcQIYCrwUGbuGBHLAT8BxgP3AXtm5pOtziFJkjpTr0VNZm7T0/0WOgy4E+ja8ftoYEpmnhARR5eP/2MYckiSpA7U6DYJX4qIkT20LxERXxpqiIgYC3wQOKNb8y5A10aa5wC7DvV9JElSfTU6pfsYYKke2keWx4bq28DngNe6ta2cmY8AlF9X6umJEXFAREyNiKmzZ89uQhRJktSJGi1qgmJn7gVtDDwxlAARsSPwWGZOG8zzM/P0zJyUmZNWXHHFoUSRJEkdrM8p3RHxLEUxk8A9EdG9sBkBLA58b4gZ3gnsHBE7lK83KiJ+DDwaEWMy85GIGAM8NsT3kSRJNdbfOjUHU/TS/BD4AvB0t2MvA/dl5o1DCZCZnwc+DxAR7waOysyPRcQ3gH2BE8qvlw7lfSRJUr31WdRk5jkRsTCwJHBpZs4anlhAUcxcFBH7Aw8Aewzje0uSpA7T74rCmTk3Ir4O/KrVYTLzWuDa8v4cYLtWv6ckSaqHRgcK3wRs2sogkiRJQ9Ho3k8/AE6MiNWAacDz3Q9m5vRmB5MkSRqIRoua88uvJ/VwLClmQkmSJFWm0aJmQktTSJIkDVFDRU1m3t/qIJIkSUPR6EBhImLDiDi33JLglog4JyJavnu3JElSIxrd0HJnYDowDrgS+DWwGjA9InZqXTxJkqTGNDqm5r+Br2bmfJtXRsRx5bFfNjuYJEnSQDR6+eltwI96aP8RsFbz4kiSJA1Oo0XNY/S8+N6mwKPNiyNJkjQ4A1l87/sRsQZwA8XaNFsBRwHfaFE2SZKkhg1kTM1zwGeBr5RtDwPHAKe0IJckSdKANLpOTQLfAr4VEUuXbc+2MpgkSdJANNpTA0BEvBVYp7w/IzPvaUkqSZKkAWqoqImI5YEzgZ2B115vjl8Bn8zMOS3KJ0mS1JBGZz+dAawBbA0sXt7eRbEn1A9aE02SJKlxjV5+eh+wXWbe2K3tDxHxb8DVzY8lSZI0MI321MwGnu+h/Z+Al54kSVLlGi1qjgO+HRGrdjWU979ZHpMkSapUo5efDgfGA/dFxENl26rAi8BKEXFo14mZuWFTE0qSJDWg0aLm4pamkCRJGqJGF9/7cquDSJIkDcVAF9/bFliXYu+nv2Tmta0IJUmSNFCNLr63KvBzil25Hy6bV4mIqcBumflwr0+WJEkaBo3OfjoFeBVYIzPHZeY4YM2yzQ0tJUlS5Rq9/LQ98O7MvLerITPvKWc9TWlJMkmSpAFotKemN6/1f4okSVLrNVrUTAFOiYhxXQ0RsRpwMvbUSJKkNtBoUXMoMBK4JyLuj4j7gL+XbYf29URJkqTh0OiYmjnA5sA2wNpAADMy080sJUlSW+i3qImIEcDTwMTMvAq4quWpJEmSBqjfy0+Z+SpwP7Bo6+NIkiQNTqNjar4CnBARK7QyjCRJ0mA1OqbmKGAC8FBEzAKe737QnbklSVLVGi1qfkax35MkSVJbanSX7mNbnEOSJGlI+hxTExEjI+I7EfFQRDwWEec7rkaSJLWj/gYKfxnYD7gcuJBiD6jvtjiTJEnSgPV3+elDwP6ZeSFARPwY+ENEjCinekuSJLWF/npqxgG/73qQmTcDc4FVWhlKkiRpoPorakYALy/QNpfGZ01JkiQNi/6KkwB+HBEvdWtbHPhBRPyzqyEzd25FOEmSpEb1V9Sc00Pbj1sRRJIkaSj6LGoyc/JwBZEkSRqKRvd+kiRJamsWNZIkqRYsaiRJUi1Y1EiSpFqwqJEkSbVgUSNJkmrBokaSJNWCRY0kSaoFixpJklQLFjWSJKkWKi9qImJcRFwTEXdGxF8i4rCyfbmIuCoiZpZfl606qyRJal+VFzXAXOCzmbkOsAVwUESsCxwNTMnMNYEp5WNJkqQeVV7UZOYjmTm9vP8scCewKrALr+8Sfg6wazUJJUlSJ6i8qOkuIsYDGwN/BFbOzEegKHyAlXp5zgERMTUips6ePXu4okqSpDbTNkVNRCwF/Aw4PDOfafR5mXl6Zk7KzEkrrrhi6wJKkqS21hZFTUQsQlHQnJeZl5TNj0bEmPL4GOCxqvJJkqT2V3lRExEBnAncmZkndTt0GbBveX9f4NLhziZJkjrHwlUHAN4JfBy4IyJuK9v+EzgBuCgi9gceAPaoKJ8kSeoAlRc1mXk9EL0c3m44s0iSpM5V+eUnSZKkZrCokSRJtWBRI0mSasGiRpIk1YJFjSRJqgWLGkmSVAsWNZIkqRYsaiRJUi1Y1EiSpFqwqJEkSbVgUSNJkmrBokaSJNWCRY0kSaoFixpJklQLFjWSJKkWLGokSVItWNRIkqRasKiRJEm1YFEjSZJqwaJGkiTVgkWNJEmqBYsaSZJUCxY1kiSpFixqJElSLVjUSJKkWli46gCS2tSxo1vwmk83/zUlqWRPjSRJqgWLGkmSVAsWNZIkqRYsaiRJUi1Y1EiSpFqwqJEkSbVgUSNJkmrBokaSJNWCRY0kSaoFixpJklQLFjWSJKkWLGokSVItuKGlJA0HNwiVWs6eGkmSVAsWNZIkqRYsaiRJUi1Y1EiSpFpwoLAkqTM5+FoLsKdGkiTVgkWNJEmqBYsaSZJUCxY1kiSpFixqJElSLVjUSJKkWrCokSRJtWBRI0mSasHF9yRJUi0WM7SnRpIk1ULbFzUR8f6I+GtE/C0ijq46jyRJak9tXdRExAjgO8AHgHWBj0bEutWmkiRJ7aitixpgc+BvmXlPZr4MXAjsUnEmSZLUhtq9qFkVeLDb41llmyRJ0nwiM6vO0KuI2AN4X2Z+qnz8cWDzzDyk2zkHAAeUD9cC/jrsQQdnBeDxqkPUiJ9n8/mZNk9V6BwAABWvSURBVJefZ/P5mTZXJ32eq2fmigs2tvuU7lnAuG6PxwIPdz8hM08HTh/OUM0QEVMzc1LVOerCz7P5/Eyby8+z+fxMm6sOn2e7X366BVgzIiZExKLAXsBlFWeSJEltqK17ajJzbkQcDPwGGAH8MDP/UnEsSZLUhtq6qAHIzCuAK6rO0QIdd8mszfl5Np+faXP5eTafn2lzdfzn2dYDhSVJkhrV7mNqJEmSGmJRI0mSasGiRpIk1YJFjaR5IuLgiFi26hydLiKW6+tWdb5OFhFbRcTk8v6KETGh6kxqH20/+6kuImIk8Flgtcz8dESsCayVmb+qOFrHiYgP9XU8My8Zriw19C/ALRExHfgh8Jt0NsFgTAMSCGA14Mny/jLAA4C/iAchIo4BJlGsHn8WsAjwY+CdVebqRBHxLMW/0R5l5qhhjNM0zn4aJhHxE4ofdJ/IzPUjYgngxszcqOJoHScizirvrgRsCfyufLwNcG1m9ln0qG8REcB7gckUv0AuAs7MzL9XGqwDRcT3gMvKpSmIiA8A78nMz1abrDNFxG3AxsD0zNy4bLs9MzesNlnniojjgH8AP6IovPcBls7Mr1cabJC8/DR83lr+I3kFIDNfoPgHpAHKzMmZOZnir4x1M/PDmflhYL2Ko9VC2TPzj/I2F1gWuDgiOvKHXMU26ypoADLzSuBfK8zT6V4u/30mQEQsWXGeOnhfZv5vZj6bmc9k5neBD1cdarAsaobPy2XvTNd/xrcCL1UbqeONz8xHuj1+FHhbVWHqICIOjYhpwNeBPwAbZOZngE3p4B90FXo8Ir4YEeMjYvWI+AIwp+pQHeyiiPg+sExEfBq4GvhBxZk63asRsU9EjIiIhSJiH+DVqkMNlmNqhs8xwK+BcRFxHsU14P0qTdT5ro2I3wAXUBSLewHXVBup460AfCgz7+/emJmvRcSOFWXqZB+l+L//c4p/o9eVbRqEzDwxIrYHnqEYV/OlzLyq4lidbm/g5PKWFH/M7F1poiFwTE2LRcQ7M/MPEbEYsBSwBcVlp5sys1O2eG9b5aDhrcuH12Xmz6vM06n6m5GTmU8MV5Y6ioilMvO5qnN0uog4AvhpZs6qOovak0VNi0XEtMzcNCKmZ+YmVeeRehIR9/L6TIgFx3plZr5lmCPVQkRsCZwBLJWZq0XERODfMvPAiqN1pHL2057AE8CFwMWZ+Wi1qTpTRJxK37OfDh3GOE1jUdNiEXETcCewA/CTBY936j+cdlD20nyNYhZUlLfs1KmIqp+I+COwO8UMqK7ZOn/OzPWrTdbZImJD4CMU47xmZeZ7Ko7UcSJi376OZ+Y5w5WlmRxT03o7Au8BtqWY0q3m+TqwU2beWXWQThcRa2fmXRHRY29iZk4f7kx1kZkPFrPk5+nYQZht5DGK2XlzKP6o0QB1atHSH4uaFivHzVwYEXdm5p+qzlMzj1rQNM2RwAHAN3s4lhRFuQbuwfISVEbEosChFD23GoSI+AxFD82KwMXApzNzRrWpOlNEfDszD4+IX9LDZajM3LmCWEPm5acWi4jPZebXe7t+6eWnwYuIkylWwP0F3abHu6Kw2kVErEAxq+Q9FJdHfwsclplO6x6EiDgBuDAzb6s6S6eLiE0zc1pE9LhuUmb+33BnagaLmhaLiP+imMo9EXiZBQZh1rULcDh0W1m4u8zMTw57mJqIiBHAB4HxdOvJzcyTqsokRcSozHymt1l6zs5TFy8/td5oir/U1gH+BNxAsQ7Ajf5HHJpyVWE11y+BF4E7gNcqztKx7KFtuvMpxid231OrSwLOzhukiHgncCywOkVN0DXhoiM/U3tqhkl5PX0SxV5F7yhvT2XmupUG62ARsTiwP8X2CIt3tdtTM3juo9McEbFTZv6ytxkm9tCqXUTEXcARFAXjvEHsnXqJ1J6a4bMEMIqi52Y08DDFX8MavB8BdwHvA46j2IjNQZhDc2VEvDczf1t1kE5WFjQjgPUz8/9VnacuImJKZm7XX5sG5OlyT7JasKhpsYg4naIn4VngjxSXn07KzCcrDVYPa2TmHhGxS2aeExHnA7+pOlSHuwn4eUQsRLH5qmv/DFJmvhoRm1adow7KXtmRwAoRsSyvX34aBaxSWbAO1m35hmsi4hvAJcw/4aIjl3GwqGm91YDFgJnAQ8As4KlKE9XHK+XXpyJifYp1K8ZXF6cWvklxafSO9Np0M9waEZcBPwWe72p0ht6A/RtwOEUBM43Xi5pngO9UFarDLbh8w6Ru9zt2GQfH1AyDKFbeWo9iPM2WwPoUy3zfmJnHVJmtk0XEp4CfARsCZ1HsrfVfmfn9SoN1sHKD0A9kpoOEm8AZes0VEYdk5qlV51D7sqgZRhExlmJ37i0pRvIvn5nLVJtKel1EnE0xk+RK5u+Kdkr3AJVjak5wTE1zlb2y6zL/5IBzq0vU2SLieODrmflU+XhZ4LOZ+cVqkw3OQlUHqLuIODQiLoyIB4HrKIqZvwIfAvrcGVl9i4jlI+LUiJgeEdMi4tsRsXzVuTrcvcAUYFFg6W43DVBmvgq4iW0TlRtanlretqHYKqUjV75tIx/oKmgAyvGeO1SYZ0gcU9N64ymW8z4iMx+pOEvdXEhRKH64fLwPxaahbm43SJn55aoz1Mxtjqlpqt0pFjK9NTMnR8TKFLuga/BGRMRimfkSQEQsQTEOtCNZ1LRYZh5ZdYYaWy4zv9Lt8X9HxK6VpamBiFgR+BxvXPunIwcNtoHlKDZd7P75JcVMEw3cC5n5WkTMjYhRFBtbduQicW3kx8CUcvxXAp8EOnYdJYsadbJrImIv4KLy8e7A5RXmqYPzKHq7dgT+HdgXmF1pog7mqtdNNzUilgF+QDEL6jng5mojdbZy5evbeX1/sq9kZscujeFAYXWciHiW15dKX5JiFcygGCP2nGuqDF5ETMvMTbuvLBwR/5eZPW56p7656nXrRMR4YFRm3l5xlNqIiB0z81dV5xgKe2rUcTLTgaut07X2zyMR8UGKla/HVpin07nqdRN0Wyiux2OdulBcGzoO6Oiixp4adaxyI7bbMvP5iPgYxUyTb2fmAxVH61gRsSPwe2AcxQyTUcCXM/OySoN1qIi4NTM37ur5iohFgN84RmlgIuKaPg6nn2dzdP17rTrHUNhTo072XWBiREykGNx6JsVfxl4qGaCI+Fpm/gewRGY+DTxNMWVWQ+Oq102Qmf5bHB7/VnWAoXKdGnWyueVS/rsAJ2fmybimymDtUPYifL7qIDVzermY2X8BlwEzKNZW0SBExMiI+GK5px4RsWbZu6ghiIgtI2JvYO2I+EREfKLqTINlT4062bMR8XngY8C7yhVcF6k4U6f6NfA4sGREPFO2de2v44aWg5SZXWuo/B9OPW6GsyhmPW1ZPp5FsQZQR48DqVJE/Ah4K3AbxaQLKCZidOQqzY6pUceKiH8B9gZuyczfR8RqwLtdMn3wIuLSzNyl6hx1UU4//gTFJad5f0Rm5qFVZepkETE1Myd1H/sREX/KzIlVZ+tUEXEnsG5dNrC1p0YdKzP/AZzU7fEDdOhfF+2ie0FTh+mdbeAK4CbgDsBNQofu5XLF2wSIiLfSbY8yDcqfgX8BarHivT016ljd1quBYq+iRSjWqRldXar6iIjpmeneRUPgZ9hcEbE98EWKDS1/S7FB8H6ZeW2VuTpZObNsI4pFDLtvYtuRe2rZU6OOteB6NeUWCZtXFKeOov9T1I8fRcSnKcZ8dP+F8UR1kTpTRCwELEuxGfAWFP8+D8vMxysN1vmOrTpAM9lTo1qJiJsyc4uqc9RBRGyemS5BPwQRcRDwVeApXu9VzMx00PAgRMR1mfmuqnPUSUR8Evh9Zs6sOksz2FOjjhURH+r2cCFgEq//4tAgRcSWlANbI2JtAAdfD9qRwBr2JjTNVRFxFMX+ZN13Pbfna/DGAx+LiNUpZpb9nqLIua3SVINkT406VrmrbJe5wH3ADzLzsWoSdb7epnc6W2dwIuIyYK/M/GfVWeogIu7todmeryYoB2B/GjgKWDUzR1QcaVAsaiTNU7fpnVWLiJ9TbGZ5DfOPqbFIVFuIiC9SDLheCrgVuJ6ip6YjZ0N5+UkdJyJOpY/LTP7CGJJaTe9sA78ob2qyiDg9Mw+oOkcNfIiip/tyikUib8rMF6uNNHgWNepEU7vd/zJwTFVBamgFYEZE1GJ6Z9Uy85yqM9TYpKoD1EFmbhIRSwNbAdsDP4iIRzNzq4qjDYpFjTpO918UEXG4vzia6tiqA9RJuZP8scDqFD9vA8eADEo5pXuLzLyhbHLsXBOUG61uTbER8CTgQYrBwh3JMTXqaC5upnYWEXcBR1DMKukaeE1mzqksVAeLiBsz8x1V56iTiLgauJbi0tOtmflctYmGxp4aSUTE9Zm51QKrNMPrPQtuaDk4T2fmlVWHqJHfRsSHgUsczD40EbEwcDzFasLLAR8GxpazSr+Qma9UmW+w7KlRx1ngF+9IoGu6rL+A1VYi4gRgBHAJ849Rml5ZqA5W/t9fkqLX6wX8Pz9oEfEtYGngiMx8tmwbBZwIvJCZh1WZb7AsaiT1KCIOyMzTq87Rycp9deD1Irzrl/C2FUWSAIiImcDbFuzxiogRwF2ZuWY1yYbGokZSjxyvNHgRcWTX3fJrArOB6zOzpwXk1ICICGAfYEJmfiUixgFj3M5j4CLi7sx820CPtbuFqg4gqW25oeXgLV3elipvS1PMLLkyIvaqMliH+1/gHcDe5ePngO9UF6ejzYiITyzYGBEfA+6qIE9T2FMjaZ6ImNDVkxARYzNzVvc2DU1ELAdcbQ/Y4HT1HkbErZm5cdn2p8ycWHW2ThMRq1KM9XqBYnZeApsBSwC7ZeZDFcYbNGc/SeruZ8AmAJk5q2y7GNi0skQ1kplPlJdQNDivlGM+EiAiVgReqzZSZyqLlrdHxLYUW3kEcGVmTqk22dBY1Eii3I17PWD0ArufjwIWryZV/ZS/QJ6sOkcHOwX4ObBSRHwV2B34YrWROltm/g74XdU5msWiRhLAWsCOwDLATt3an6XYuVcDEBF38Mb9yZYDHgbeMI5BjcnM8yJiGrAdRc/Crpl5Z8Wx1EYcUyNpnoh4R2beWHWOThcRqy/QlMCczHy+ijx1Ul5+Wpluf5Rn5gPVJVI7saiRNE9EjAVOBd5J8Yv4euCwbuNrpMpExCEUG9g+SrEAX9e6PxtWGkxtw6JG0jwRcRVwPvCjsuljwD6ZuX11qaRCRPwNeLt7Z6k3rlMjqbuVMvOszJxb3s4GVqw6lFR6EHi66hBqXw4UltTd7HLxrQvKxx8F/KtYleq2QvM9wLURcTnz76V1UiXB1HYsaiR190ngNOBbFGNqbijbpCotXX59oLwtWt7gjbPM9CbmmBpJUkeIiD0y86f9tenNy6JGEhHxpT4OZ2Z+ZdjCSL3oaZNVN15Vd15+kgTQ0/opSwL7A8sDFjWqTER8ANgBWDUiTul2aBQwt5pUakcWNZLIzG923Y+IpYHDgMnAhcA3e3ueNEweBqYCewB3U4yjeZVivZojKsylNmNRIwmYt4P0kcA+wDnAJpnpPkVqBzMo/l0uSjFwPYBxwFnAryrMpTbjOjWSiIhvALdQ7PW0QWYea0GjNvJ1YFlg9czcJDM3Bt4CjAZOrDSZ2ooDhSUREa9RrPsxl/mnyHYtQz+qkmASEBEzgbflAr+wyn2g7srMNatJpnbj5SdJZKa9tmpnuWBBUza+GhH+Za55/EEmSWp3MyLiEws2lqtf31VBHrUpLz9JktpaRKwKXAK8AEyjuES6GbAEsFtmPlRhPLURixpJUkeIiG2B9SjGev0lM6dUHEltxqJGkiTVgmNqJElSLVjUSJKkWrCokdQyEXFfRBzVhNe5NiJOa0amBt9vfERkREwayjmShpdFjaQeRcTZ5S/tjIi5EfFARHw3IpZt4XvuFxHP9XDoQ8DnW/W+g/QgMAa4reogkgouviepL1cDH6f4WbEu8ENgGeCjwxkiM58YzvdrRGa+Cvyj6hySXmdPjaS+vJSZ/8jMWZn5W+AnwHu7DkbE5IiYEREvRsTdEXFERPT6cyUijoyI2yPi+Yh4KCLOiIhlymPvptigcMluPUTHlsfmu/wUEctGxDkR8WREvBARV0fEet2O7xcRz0XEdhHx5/L9romICd3OGRcRl0bEExHxz4i4KyL2WiDy6hFxVXl8RkRs3+35811+ioh3l493jIjbys9kWkRsOqhPXtKAWdRIakhEvAV4P/BK+fjTwPHAl4B1gM8C/wEc2MfLvAYcTrHWyN7A5sCp5bEbymP/pLisM4beNys8G3g7sEv5Gv8Efh0RS3Q7ZzGKS1afBN5B0cP0vW7H/xcYCWxT5jkceGqB9/kqcAowkWLDzwsjYqk+vj/KzP8BTALuAS6PiJH9PEdSE3j5SVJf3l+OcRkBLF62HVl+/S/gc5l5cfn43og4gaKo6XFQb2Z+u9vD+yLic8ClEbFvZr4cEU8Xp2Wvl3UiYk1gZ+BfM/O6su3jwAPAPsAZ5akLAwdl5l/Lc04EzoqIhTLzNWB14GeZ+aeu/D283bcy85fl8/8T+ASwEXB9b/mAr2Tmb8rnTAZmURRwZ/TxHElNYFEjqS/XAQdQLEf/aeCtwCkRsSIwDvh+RHy32/kLU6z22qNyRdjPU/TsjKYolhYF/gV4uMFM61D0+NzY1ZCZT0fEHRTjfrq81FXQlB4GFqHosXkCOBn4XkS8H5gC/Dwzpy3wXrcv8HyAlfrJ1z3Xcz3kktQiXn6S1Jd/ZubfMvOOzDyU4nLNf/H6z45/p+i56LqtT3Ep5w0iYnXgcuBOYA9gU4pLQ1AUNo3qtWii2BOoy9xeji0EkJlnAhMoxvG8DbihawxPN6/Me/Lry6/7c1NqU/7nlDQQX6YYLzICeAh4a1n0zHfr5bmTKIqXIzLzxsy8G1hlgXNeLl+7LzMofna9o6shIkYBG5THGlYOgD49M/ekGBt0wECe34stuuVakqLQu7MJryupH15+ktSwzLw2Iv4CfBE4Fjg1Ip4CrqC4tLMJsGpm/k8PT59JUYwcHhGXUPzyP3yBc+4DFi9nGd1K0VP0zwUyzIyISykufR1AMbj3q8AzwPmNfi8RcTJwJXA3MIpiEPSAiqJefDEiZlNcrvoSRaHWcC5Jg2dPjaSBOgnYH7iK4vLRx4E/Ab+n6OnoacAtmXk7cBjFQOMZwKeAoxY45waKGUoXALOBz/WSYTJwM3BZ+XUk8P7MfGEA38dCFDOvZpTfy6PAvgN4fm+OBr4JTAfWBHbMzOeb8LqS+uEu3ZLUBOU6O9cAK2bm4xXHkd6U7KmRJEm1YFEjSZJqwctPkiSpFuypkSRJtWBRI0mSasGiRpIk1YJFjSRJqgWLGkmSVAsWNZIkqRb+PwLMhcSY/xsPAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1440x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (20,6))\n",
+    "ax = fig.add_subplot(1,2,1)\n",
+    "(relasi.div(relasi.sum(axis = 1),axis = 0)*100).sort_values(by = '<=50K').plot(kind = 'bar',ax =ax);\n",
+    "plt.xlabel('Relationship',fontsize = 14);\n",
+    "plt.ylabel('Proportion of People (%)',fontsize = 14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "id": "gjnxUuW1pLww",
+    "outputId": "045460b7-df18-455b-beb7-c1cb2ab86613"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 864x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(12,7))\n",
+    "ax=sns.countplot(train_datavis['relationship'], hue=train_datavis['income'])\n",
+    "ax.set_title('Relationship Status / Wage Class')\n",
+    "ax.set_xlabel('Relationship')\n",
+    "ax.set_ylim(ymax=6500)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "id": "KZ7fiyDS32GP",
+    "outputId": "c608d29a-96ba-45ae-922a-08a943280fe2"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 864x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_datavis_rel = train_datavis.loc[train_datavis['income'] == '<=50K']\n",
+    "plt.figure(figsize=(12,7))\n",
+    "ax=sns.countplot(train_datavis_rel['relationship'],\n",
+    "                order = train_datavis_rel['relationship'].value_counts().index)\n",
+    "ax.set_title('Relationship Status / Wage Class (<=50K)')\n",
+    "ax.set_xlabel('Relationship')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "fmQgEXKMn8rZ"
+   },
+   "source": [
+    "### Visualization Relationship <=50K\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "id": "Jjg4mMGBUn97",
+    "outputId": "31f70fc5-9d27-4ca7-ff17-5c78e8c0c495"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,10))\n",
+    "ax=sns.countplot(train_clustvis_rel['relationship'],\n",
+    "                order = train_clustvis_rel['relationship'].value_counts().index)\n",
+    "ax.set_title('Relationship / Wage Class (<=50K)',fontsize=18)\n",
+    "ax.set_xlabel('Relationship',fontsize=15)\n",
+    "ax.set_ylabel('Count',fontsize=15)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zoOGhUIIN-P5"
+   },
+   "source": [
+    "## Capital gain"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WEJ5mrJ2kiaj"
+   },
+   "source": [
+    "### Visualization Capital gain <=50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "id": "E1zquue0ODGH",
+    "outputId": "acd2f7b5-d267-4346-9f8b-08837d01a0de"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3oAAAH1CAYAAACgKoxcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3df7ivZV0n+vdHthKl+IutQ3tjkKIT0ogHhuh4ajzDlOjpBDZSmzrKXHEOyUAn0+lKsxm9mpiT+YOOo1IYBHipSP4YqaQidfLYILoxElHJraDsINmmKYSg0Of88X1WfVmuvffaay1bm3u9Xtf1vb7P9/Pc9/PcD/yxr/d138+9qrsDAADAOB603gMAAABgbQl6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBD4AHhKr6qar641X0/+9V9X+u5ZgWXf/Kqjr9W3V9ANgXgh4Aa6qqfrKqtlfVnVV12xSA/pfVXre739zdPzx3n66qJ6z2unPXO7KqLquqXVX11ar6dFX916rauszxPbO7L1mr8azGFGrvnv4f3FlVNy46f2JVfaqq7qqq91fVd82du7iqfnXu95On/48v+qd8BgBWR9ADYM1U1QuT/EaS/5LksUkel+QNSU5ez3HtzRQYr0lya5KndvfBSZ6W5DNJVh1SVzm2x66w6znd/dDp86S56x2S5J1J/mOSRyXZnuRtu7n3MUnen+Tc7n71CscBwDoQ9ABYE1X18CS/kuTs7n5nd/9dd3+ju3+vu39hanN8VV1dVX87zRK9rqoeMneNrqr/u6o+W1VfrKpXVtWDpnP/rqo+OB1/YOryF9OM1U9U1SOr6venGbkvT8fLmo1L8vIkf9bdL+zunUnS3bd3929092XTPfd4/fmloQtjrapXTW1vqqpn7sN/y0dU1VlV9eEkFy+33zL9WJIbuvt3u/vuzJ79KVX1zxeN4fgkf5Lkl7r7dWs8BgC+xQQ9ANbK9yf5tiTv2kOb+5L8fJJDpvYnJvn3i9o8O8lxSf6nzGYCf3rxRbr7B6fDp0wzVm/L7N+030nyXZnNJH4tyXIDyr9J8o69tNnX639fkhsze9ZfT3JhVdXuGlfVg6rqh6rqLUk+l+SHM5sZ/dG5Nr8/heSlPr+/6JL/zxSW/6yqnj5Xf3KSv1j40d1/l9nM5ZPn2hyf5A+T/Hx3//YenhGA/ZSgB8BaeXSSL3b3vbtr0N3XdveHuvve7r45yW8l+VeLmr2iu7/U3Z/PbBnoacu5eXf/TXe/o7vv6u47kpy7xLV355Akf73wo6rOmcLTnVX1xhVe/3Pd/cbuvi/JJUkOzWw56zepqnOS3JzkFUk+lOTx3f3s7v5v3f2NuWf8ke5+xG4+PzJ3yV9M8t1JtiS5IMnvVdXjp3MPTfKVRUP4SpKHzf0+YapduYfnA2A/JugBsFb+JskhVbVpdw2q6onTrNRfV9VXM5uxOmRRs1vmjj+X5DuXc/Oq+vaq+q2q+tx07Q8keURVHbDMsR+68KO7X9fdj8gsaD54hdf/h+DY3XdNhw/dTdsjkjwyyXVJPjaNZ8W6+5ruvqO775k2iPmzJM+aTt+Z5OBFXQ5Ocsfc79cn+UiSq6rqkasZCwDrQ9ADYK1cneTuJKfsoc35ST6V5Mhpw5NfSrJ4OeNhc8ePy2yDlOV4UZInJfm+6doLyzt3u1xyznsze3ftW3X9PeruF2U2A3d9ktcmuamq/nNVHTnfbtrB9M7dfPY0+9Zz47whyVPmrvkdSR4/1Rfcl+Snknw+yR9V1eJgCMB+TtADYE1091eS/Kckr6+qU6YZsAdX1TOr6tenZg9L8tUkd06bf5y1xKV+Ydr45LAkP5fd7AiZ5AuZhaMFD8vsvbm/rapHJXnZPgz/5Ul+oKpeU1Vbkn/YnfJ71uj6e9Xdu7r7vO7+F0n+bZJHJLm6qi6aa/PMuZ00F3+eOY37EVX1jKr6tqraVFU/lVko/aPpMu9KcnRV/duq+rbM/p99rLs/tWg830hyapIvJnnPFAgBeIAQ9ABYM939miQvTPLLSXZltgzznCT/bWryH5L8ZGbLBN+YpUPcu5Ncm9kyxj9IcuFubvfyJJdM79L9eGbLLA/KLJh8KLPNRJY77r/M7L20rZnt5HlHZssdb83szxBkNdffV9O7jD+b2bLV39zH7g9O8quZ/ff/YpKfTXJKd984XXtXZkHy3CRfzmzTmG27GcfXM5vpvDuz9/wO2venAWA9VHev9xgAIMnszytktqxzx3qPBQAeyMzoAQAADEbQAwAAGIylmwAAAIMxowcAADAYQQ8AAGAwm9Z7ACt1yCGH9OGHH77ewwAAAFgX11577Re7e/NS5x6wQe/www/P9u3b13sYAAAA66KqPre7c5ZuAgAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwmE3rPYDRHfsLl673EAAecK595fPWewgA8IBmRg8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDB7DXpVdVhVvb+qPllVN1TVz031R1XVVVX16en7kXN9XlJVO6rqxqp6xlz92Kq6fjr32qqqqX5gVb1tql9TVYev/aMCAABsDMuZ0bs3yYu6+3uSnJDk7Ko6KsmLk7y3u49M8t7pd6Zz25I8OclJSd5QVQdM1zo/yZlJjpw+J031M5J8ubufkOS8JK9Yg2cDAADYkPYa9Lr7tu7+6HR8R5JPJtmS5OQkl0zNLklyynR8cpLLuvue7r4pyY4kx1fVoUkO7u6ru7uTXLqoz8K13p7kxIXZPgAAAPbNPr2jNy2pfGqSa5I8trtvS2ZhMMljpmZbktwy123nVNsyHS+u369Pd9+b5CtJHr3E/c+squ1VtX3Xrl37MnQAAIANY9lBr6oemuQdSV7Q3V/dU9Mlar2H+p763L/QfUF3H9fdx23evHlvQwYAANiQlhX0qurBmYW8N3f3O6fyF6blmJm+b5/qO5McNtd9a5Jbp/rWJer361NVm5I8PMmX9vVhAAAAWN6um5XkwiSf7O7XzJ26Isnp0/HpSd49V9827aR5RGabrnx4Wt55R1WdMF3zeYv6LFzrOUneN73HBwAAwD7atIw2T0vy3CTXV9V1U+2Xkvxaksur6owkn09yapJ09w1VdXmST2S2Y+fZ3X3f1O+sJBcnOSjJldMnmQXJN1XVjsxm8rat8rkAAAA2rL0Gve7+YJZ+hy5JTtxNn3OTnLtEfXuSo5eo350pKAIAALA6+7TrJgAAAPs/QQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGMxeg15VXVRVt1fVx+dqb6uq66bPzVV13VQ/vKq+NnfuN+f6HFtV11fVjqp6bVXVVD9wut6Oqrqmqg5f+8cEAADYOJYzo3dxkpPmC939E919THcfk+QdSd45d/ozC+e6+/lz9fOTnJnkyOmzcM0zkny5u5+Q5Lwkr1jRkwAAAJBkGUGvuz+Q5EtLnZtm5X48yVv3dI2qOjTJwd19dXd3kkuTnDKdPjnJJdPx25OcuDDbBwAAwL5b7Tt6P5DkC9396bnaEVX151X1p1X1A1NtS5Kdc212TrWFc7ckSXffm+QrSR691M2q6syq2l5V23ft2rXKoQMAAIxptUHvtNx/Nu+2JI/r7qcmeWGSt1TVwUmWmqHr6XtP5+5f7L6gu4/r7uM2b968imEDAACMa9NKO1bVpiQ/luTYhVp335Pknun42qr6TJInZjaDt3Wu+9Ykt07HO5MclmTndM2HZzdLRQEAANi71czo/Zskn+ruf1iSWVWbq+qA6fi7M9t05bPdfVuSO6rqhOn9u+cleffU7Yokp0/Hz0nyvuk9PgAAAFZgOX9e4a1Jrk7ypKraWVVnTKe25Zs3YfnBJB+rqr/IbGOV53f3wuzcWUl+O8mOJJ9JcuVUvzDJo6tqR2bLPV+8iucBAADY8Pa6dLO7T9tN/d8tUXtHZn9uYan225McvUT97iSn7m0cAAAALM9qN2MBAABgPyPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACD2WvQq6qLqur2qvr4XO3lVfVXVXXd9HnW3LmXVNWOqrqxqp4xVz+2qq6fzr22qmqqH1hVb5vq11TV4Wv7iAAAABvLcmb0Lk5y0hL187r7mOnzniSpqqOSbEvy5KnPG6rqgKn9+UnOTHLk9Fm45hlJvtzdT0hyXpJXrPBZAAAAyDKCXnd/IMmXlnm9k5Nc1t33dPdNSXYkOb6qDk1ycHdf3d2d5NIkp8z1uWQ6fnuSExdm+wAAANh3q3lH75yq+ti0tPORU21Lklvm2uycalum48X1+/Xp7nuTfCXJo5e6YVWdWVXbq2r7rl27VjF0AACAca006J2f5PFJjklyW5JXT/WlZuJ6D/U99fnmYvcF3X1cdx+3efPmfRsxAADABrGioNfdX+ju+7r775O8Mcnx06mdSQ6ba7o1ya1TfesS9fv1qapNSR6e5S8VBQAAYJEVBb3pnbsFz06ysCPnFUm2TTtpHpHZpisf7u7bktxRVSdM7989L8m75/qcPh0/J8n7pvf4AAAAWIFNe2tQVW9N8vQkh1TVziQvS/L0qjomsyWWNyf5mSTp7huq6vIkn0hyb5Kzu/u+6VJnZbaD50FJrpw+SXJhkjdV1Y7MZvK2rcWDAQAAbFR7DXrdfdoS5Qv30P7cJOcuUd+e5Ogl6ncnOXVv4wAAAGB5VrPrJgAAAPshQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGMxeg15VXVRVt1fVx+dqr6yqT1XVx6rqXVX1iKl+eFV9raqumz6/Odfn2Kq6vqp2VNVrq6qm+oFV9bapfk1VHb72jwkAALBxLGdG7+IkJy2qXZXk6O7+F0n+MslL5s59pruPmT7Pn6ufn+TMJEdOn4VrnpHky939hCTnJXnFPj8FAAAA/2CvQa+7P5DkS4tqf9zd904/P5Rk656uUVWHJjm4u6/u7k5yaZJTptMnJ7lkOn57khMXZvsAAADYd2vxjt5PJ7ly7vcRVfXnVfWnVfUDU21Lkp1zbXZOtYVztyTJFB6/kuTRS92oqs6squ1VtX3Xrl1rMHQAAIDxrCroVdVLk9yb5M1T6bYkj+vupyZ5YZK3VNXBSZaaoeuFy+zh3P2L3Rd093HdfdzmzZtXM3QAAIBhbVppx6o6PcmPJDlxWo6Z7r4nyT3T8bVV9ZkkT8xsBm9+eefWJLdOxzuTHJZkZ1VtSvLwLFoqCgAAwPKtaEavqk5K8otJfrS775qrb66qA6bj785s05XPdvdtSe6oqhOm9++el+TdU7crkpw+HT8nyfsWgiMAAAD7bq8zelX11iRPT3JIVe1M8rLMdtk8MMlV074pH5p22PzBJL9SVfcmuS/J87t7YXburMx28Dwos3f6Ft7ruzDJm6pqR2YzedvW5MkAAAA2qL0Gve4+bYnyhbtp+44k79jNue1Jjl6ifneSU/c2DgAAAJZnLXbdBAAAYD8i6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAg9lr0Kuqi6rq9qr6+FztUVV1VVV9evp+5Ny5l1TVjqq6saqeMVc/tqqun869tqpqqh9YVW+b6tdU1eFr+4gAAAAby3Jm9C5OctKi2ouTvLe7j0zy3ul3quqoJNuSPHnq84aqOmDqc36SM5McOX0WrnlGki939xOSnJfkFSt9GAAAAJYR9Lr7A0m+tKh8cpJLpuNLkpwyV7+su+/p7puS7EhyfFUdmuTg7r66uzvJpYv6LFzr7UlOXJjtAwAAYN+t9B29x3b3bUkyfT9mqm9Jcstcu51Tbct0vLh+vz7dfW+SryR59ArHBQAAsOGt9WYsS83E9R7qe+rzzRevOrOqtlfV9l27dq1wiAAAAGNbadD7wrQcM9P37VN9Z5LD5tptTXLrVN+6RP1+fapqU5KH55uXiiZJuvuC7j6uu4/bvHnzCocOAAAwtpUGvSuSnD4dn57k3XP1bdNOmkdktunKh6flnXdU1QnT+3fPW9Rn4VrPSfK+6T0+AAAAVmDT3hpU1VuTPD3JIVW1M8nLkvxaksur6owkn09yapJ09w1VdXmSTyS5N8nZ3X3fdKmzMtvB86AkV06fJLkwyZuqakdmM3nb1uTJAAAANqi9Br3uPm03p07cTftzk5y7RH17kqOXqN+dKSgCAACwemu9GQsAAADrTNADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAaz4qBXVU+qquvmPl+tqhdU1cur6q/m6s+a6/OSqtpRVTdW1TPm6sdW1fXTuddWVa32wQAAADaqFQe97r6xu4/p7mOSHJvkriTvmk6ft3Cuu9+TJFV1VJJtSZ6c5KQkb6iqA6b25yc5M8mR0+eklY4LAABgo1urpZsnJvlMd39uD21OTnJZd9/T3Tcl2ZHk+Ko6NMnB3X11d3eSS5OcskbjAgAA2HDWKuhtS/LWud/nVNXHquqiqnrkVNuS5Ja5Njun2pbpeHEdAACAFVh10KuqhyT50SS/O5XOT/L4JMckuS3JqxeaLtG991Bf6l5nVtX2qtq+a9euVY0bAABgVGsxo/fMJB/t7i8kSXd/obvv6+6/T/LGJMdP7XYmOWyu39Ykt071rUvUv0l3X9Ddx3X3cZs3b16DoQMAAIxnLYLeaZlbtjm9c7fg2Uk+Ph1fkWRbVR1YVUdktunKh7v7tiR3VNUJ026bz0vy7jUYFwAAwIa0aTWdq+rbk/xQkp+ZK/96VR2T2fLLmxfOdfcNVXV5kk8kuTfJ2d1939TnrCQXJzkoyZXTBwAAgBVYVdDr7ruSPHpR7bl7aH9uknOXqG9PcvRqxgIAAMDMWu26CQAAwH5C0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABrOqoFdVN1fV9VV1XVVtn2qPqqqrqurT0/cj59q/pKp2VNWNVfWMufqx03V2VNVrq6pWMy4AAICNbC1m9P7X7j6mu4+bfr84yXu7+8gk751+p6qOSrItyZOTnJTkDVV1wNTn/CRnJjly+py0BuMCAADYkL4VSzdPTnLJdHxJklPm6pd19z3dfVOSHUmOr6pDkxzc3Vd3dye5dK4PAAAA+2i1Qa+T/HFVXVtVZ061x3b3bUkyfT9mqm9Jcstc351Tbct0vLgOAADACmxaZf+ndfetVfWYJFdV1af20Hap9+56D/VvvsAsTJ6ZJI973OP2dawAAAAbwqpm9Lr71un79iTvSnJ8ki9MyzEzfd8+Nd+Z5LC57luT3DrVty5RX+p+F3T3cd193ObNm1czdAAAgGGtOOhV1XdU1cMWjpP8cJKPJ7kiyelTs9OTvHs6viLJtqo6sKqOyGzTlQ9PyzvvqKoTpt02nzfXBwAAgH20mqWbj03yrukvIWxK8pbu/sOq+kiSy6vqjCSfT3JqknT3DVV1eZJPJLk3ydndfd90rbOSXJzkoCRXTh8AAABWYMVBr7s/m+QpS9T/JsmJu+lzbpJzl6hvT3L0SscCAADAP/pW/HkFAAAA1pGgBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMZsVBr6oOq6r3V9Unq+qGqvq5qf7yqvqrqrpu+jxrrs9LqmpHVd1YVc+Yqx9bVddP515bVbW6xwIAANi4Nq2i771JXtTdH62qhyW5tqqums6d192vmm9cVUcl2ZbkyUm+M8mfVNUTu/u+JOcnOTPJh5K8J8lJSa5cxdgAAAA2rBXP6HX3bd390en4jiSfTLJlD11OTnJZd9/T3Tcl2ZHk+Ko6NMnB3X11d3eSS5OcstJxAQAAbHRr8o5eVR2e5KlJrplK51TVx6rqoqp65FTbkuSWuW47p9qW6XhxHQAAgBVYddCrqocmeUeSF3T3VzNbhvn4JMckuS3JqxeaLtG991Bf6l5nVtX2qtq+a9eu1Q4dAABgSKsKelX14MxC3pu7+51J0t1f6O77uvvvk7wxyfFT851JDpvrvjXJrVN96xL1b9LdF3T3cd193ObNm1czdAAAgGGtZtfNSnJhkk9292vm6ofONXt2ko9Px1ck2VZVB1bVEUmOTPLh7r4tyR1VdcJ0zeclefdKxwUAALDRrWbXzacleW6S66vquqn2S0lOq6pjMlt+eXOSn0mS7r6hqi5P8onMduw8e9pxM0nOSnJxkoMy223TjpsAAAArtOKg190fzNLv171nD33OTXLuEvXtSY5e6VgAAAD4R2uy6yYAAAD7D0EPAABgMIIeAADAYAQ9AACAwQh6AAAAg1nNn1cAAPZzn/+V713vIQA84DzuP12/3kNYNTN6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAcAADAYQQ8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAMRtADAAAYjKAHAAAwGEEPAABgMIIeAADAYAQ9AACAwQh6AAAAgxH0AAAABiPoAQAADEbQAwAAGIygBwAAMBhBDwAAYDCCHgAAwGAEPQAAgMEIegAAAIMR9AAAAAaz3wS9qjqpqm6sqh1V9eL1Hg8AAMAD1X4R9KrqgCSvT/LMJEclOa2qjlrfUQEAADww7RdBL8nxSXZ092e7++tJLkty8jqPCQAA4AFpfwl6W5LcMvd751QDAABgH21a7wFMaolaf1OjqjOTnDn9vLOqbvyWjgrGdkiSL673IGAp9arT13sIwD8N/xaxf3rZUvFkv/RduzuxvwS9nUkOm/u9Ncmtixt19wVJLvinGhSMrKq2d/dx6z0OADYu/xbBt87+snTzI0mOrKojquohSbYluWKdxwQAAPCAtF/M6HX3vVV1TpI/SnJAkou6+4Z1HhYAAMAD0n4R9JKku9+T5D3rPQ7YQFejsO4AAAZLSURBVCyDBmC9+bcIvkWq+5v2PAEAAOABbH95Rw8AAIA1IujBBlRVJ1XVjVW1o6pevN7jAWBjqaqLqur2qvr4eo8FRiXowQZTVQckeX2SZyY5KslpVXXU+o4KgA3m4iQnrfcgYGSCHmw8xyfZ0d2f7e6vJ7ksycnrPCYANpDu/kCSL633OGBkgh5sPFuS3DL3e+dUAwBgEIIebDy1RM32uwAAAxH0YOPZmeSwud9bk9y6TmMBAOBbQNCDjecjSY6sqiOq6iFJtiW5Yp3HBADAGhL0YIPp7nuTnJPkj5J8Msnl3X3D+o4KgI2kqt6a5OokT6qqnVV1xnqPCUZT3V7NAQAAGIkZPQAAgMEIegAAAIMR9AAAAAYj6AEAAAxG0AMAABiMoAfAfqOqfqyq3ldVf1tV91TVX1bVr1bVId+Cez29qrqqjp5+P6SqXl5Vx6zwejdX1auW0e7Aqvr5qvpIVd1RVXdX1aer6ryqOmIF9+2qOmclYwZgXJvWewAAkCRV9eokL0jyO0nOS/LVJEcleX6SJyd59hrf8qNJvj/JZ6bfD0nysiQ3J7luje+VJKmqb0/yx0m+N8l/TfLLSb6e5Ogk/1eS5yQ5bB8v+/1JblrDYQIwAEEPgHVXVf97khcmOaO7L5o79adVdUGSH17re3b3V5N8aK2vuxfnJjkmyfd19w1z9fdX1euT7PMfje7uf+pnAOABwNJNAPYHP5/ko4tCXpKku+/r7isXflfVr1XV9VV1Z1XtrKo3V9U/m++zsIyyqv5jVf311PbNVfXwuTb3W7qZ5I7p+3emelfV4cu9595Ms3lnJnnDopC38Jx/391vnGv/HVX1uqq6saruqqqbqur1VXXwouveb+lmVf33qnp7Vf1kVe2oqq9W1ZVVtXVfxgvAA5sZPQDWVVU9OMn/nOTVy+zymCT/JcmtSTYneVGS91XV93b3fXPtTkuyI7MlkYcm+fUkv53k1N1c918neV+SX03yB1Pttn28554cm2Rh6eZyfHuSA5K8NMmuzJZ0vjTJ7yZ5xl76fl+S75zGeVCS/zfJBUmetcx7A/AAJ+gBsN4eneTAJJ9fTuPu/umF46o6IMnVSXYmeVqSD8w1PSjJ/9bdd05t/y7Jm6rqe7r7k0tc+iPT92cWL4fch3vuyXdO37fMF6vqQZlbYdPd907fu5KcNdduU2bv4n2wqh7X3Xv673VwZs/+5anvP0tyXlUd1N1fW+Z4AXgAs3QTgP1FL6dRVT2zqv5HVX0lyb2ZBa4keeKiplcthLzJO5NUkn+5rwPbh3vu8TLT9+LnvCLJNxY+c0tJU1XPrao/r6o7p/MfXOZ9P7IQ8iafmL637MN4AXgAE/QAWG9/k+SeJI/bW8Oq+peZBaOdSZ6b2Y6TJ0ynv21R89vnf0wzWXdmtoxz2fbxnnvyV9P34nflXpBZ+Hz+ovs+O8mlmc0enjrdc2Hn0b3d928X/f76CsYLwAOYpZsArKvu/kZV/Vlm75398l6aPzuz99V+ors7Sarqu3bT9jHzP6rqoCQPzT++d7dc+3LPPbk2yV2Z7SD6voVid++YrvnQRe1PTXJNd//7hUJV/asV3BeADciMHgD7g99IclxVnb74RFU9qKpOmn4elOQbC4Fr8lO7ueYPLQpPP5bZssntu2m/u1mvfbnnbnX3XZltiHJ2VX3PMroclNlM57x9vi8AG5MZPQDWXXf/XlW9JsmFVfW0JO/ObJnlP89sSePNSf4wyVVJXlBVv5Hk9zLbrfP/2M1lv5bkD6rqlZkt13xlknd19yeWatzdX6+qm5L8eFV9PMndST62j/fcm5cmOT7J1VX1uiT/33SfLUlOT3Lf9DvTfV9fVS9Nck1mO2aeuML7ArDBCHoA7Be6+0VV9T+SnJPkLZnNaN2c2ftxr5ravKeqfjHJz2b2ZxOuTvIjSf5yiUteltnfxrswsyWbV2RuF8vdeP50rz/JbCfQI/bxnnt7xruq6l8nOTvJT2b2ft6mzHbifG+Spyws5UzyW0m+O8nPZTbLeNXUxx9IB2Cv6v4rUQDgga+qbk7y9u7+D+s9FgBYD97RAwAAGIygBwAAMBhLNwEAAAZjRg8AAGAwgh4AAMBgBD0AAIDBCHoAAACDEfQAAAAGI+gBAAAM5v8HJK4hygVu5wMAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize = (15,8))\n",
+    "ax=sns.countplot(train_data['capital-gain'],\n",
+    "                order = train_data['capital-gain'].value_counts().index)\n",
+    "ax.set_title('Capital Gain <=50K')\n",
+    "plt.xlabel(\"Capital Gain\",fontsize = 15);\n",
+    "plt.xticks()\n",
+    "plt.ylabel('');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "RCrC5vq6_3Uw"
+   },
+   "source": [
+    "# Modeling"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "80-9f3EAw0ot"
+   },
+   "source": [
+    "## Logistic Regression"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "id": "zkBOSGAkw6oL"
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "X_LG = train_data_One.drop(['income'], axis = 1) \n",
+    "y_LG = train_data_One.iloc[:,3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "id": "_B8fv_BMb-UG"
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split \n",
+    "LG_X_train, LG_X_test,LG_y_train,LG_y_test = train_test_split(X_LG,\n",
+    "                                                y_LG,\n",
+    "                                                test_size = 0.3,\n",
+    "                                                random_state = 42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "id": "-KcUUJ8MeiTy",
+    "outputId": "7429e9dc-4973-4e2d-aebd-501774758429"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "LogisticRegression(random_state=42)"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "logreg = LogisticRegression(random_state=42)\n",
+    "logreg.fit(LG_X_train, LG_y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "id": "bm2lSay5ezTq",
+    "outputId": "8860ec48-22da-4cf0-8cac-976f996a6277"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Confustion Matrix\n",
+      "[[4731  371]\n",
+      " [ 805 1011]]\n",
+      "\n",
+      "Test Accuracy\n",
+      "0.8300086730268864\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.85      0.93      0.89      5102\n",
+      "           1       0.73      0.56      0.63      1816\n",
+      "\n",
+      "    accuracy                           0.83      6918\n",
+      "   macro avg       0.79      0.74      0.76      6918\n",
+      "weighted avg       0.82      0.83      0.82      6918\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_predicted = logreg.predict(LG_X_test)\n",
+    "y_predicted\n",
+    "\n",
+    "from sklearn.metrics import classification_report, confusion_matrix\n",
+    "print('\\nConfustion Matrix') # generate the confusion matrix\n",
+    "print(confusion_matrix(LG_y_test, y_predicted))\n",
+    "\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "print('\\nTest Accuracy')\n",
+    "print(accuracy_score(LG_y_test, y_predicted))\n",
+    "\n",
+    "from sklearn.metrics import classification_report\n",
+    "print('\\nClassification Report')\n",
+    "print(classification_report(LG_y_test, y_predicted))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "wavCpyYGw7ua"
+   },
+   "source": [
+    "## Decision Tree"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "id": "MxTcB8M5ybTr"
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn import tree\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.metrics import confusion_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "id": "4xdrnB0NyU8T"
+   },
+   "outputs": [],
+   "source": [
+    "train_data_DT =  pd.get_dummies(train_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "id": "0H7Uflx6w-G4"
+   },
+   "outputs": [],
+   "source": [
+    "A = train_data_One.drop(['income'], axis = 1) \n",
+    "B = train_data_One.iloc[:,3]\n",
+    "X_trainDT, X_testDT, y_trainDT, y_testDT = train_test_split(A,B, test_size = 1/3 , random_state = 42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "id": "JBs_elSOylb5",
+    "outputId": "bdee423e-e82a-4230-b4c8-4383f32ada27"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DecisionTreeClassifier()"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dectree = tree.DecisionTreeClassifier()\n",
+    "dectree.fit(X_trainDT,y_trainDT)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "id": "sy99Cj2jx-Qr",
+    "outputId": "d0de23c0-97de-4793-ff3b-dd90e5bdb88c"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mean accuracy score: 0.8224\n"
+     ]
+    }
+   ],
+   "source": [
+    "predtree = dectree.predict(X_testDT)\n",
+    "accurtree = accuracy_score(y_testDT, predtree)\n",
+    "print(f'Mean accuracy score: {accurtree:.5}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "id": "jUn3Elds0SDw",
+    "outputId": "ac9a972e-991f-4c90-ec2d-31c0474d3a99"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Confusion Matrix\n",
+      "[[5141  540]\n",
+      " [ 825 1180]]\n",
+      "\n",
+      "Test Accuracy\n",
+      "0.8224043715846995\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.86      0.90      0.88      5681\n",
+      "           1       0.69      0.59      0.63      2005\n",
+      "\n",
+      "    accuracy                           0.82      7686\n",
+      "   macro avg       0.77      0.75      0.76      7686\n",
+      "weighted avg       0.82      0.82      0.82      7686\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report, confusion_matrix\n",
+    "print('\\nConfusion Matrix')\n",
+    "print(confusion_matrix(y_testDT,predtree))\n",
+    "\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "print('\\nTest Accuracy')\n",
+    "print(accuracy_score(y_testDT,predtree))\n",
+    "\n",
+    "from sklearn.metrics import classification_report\n",
+    "print('\\nClassification Report')\n",
+    "print(classification_report(y_testDT,predtree))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "id": "qtsXSQFtyNfH",
+    "outputId": "bd19494c-e22b-48fc-9b6b-838f5b0e3ff4"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0, 0.5, 'Income > 50 K'), Text(0, 1.5, 'Income < 50 K')]"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 576x504 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cmtree = confusion_matrix(y_testDT, predtree)\n",
+    "fig, (ax) = plt.subplots(1, 1, figsize=(8,7))\n",
+    "sns.heatmap(cmtree, annot=True, ax = ax,fmt='g')\n",
+    "ax.set_xlabel('Predicted labels')\n",
+    "ax.set_ylabel('True labels');\n",
+    "ax.set_title('Confusion Matrix')\n",
+    "sns.set(font_scale=1.5)\n",
+    "ax.xaxis.set_ticklabels(['Income > 50 K', 'Income < 50 K'])\n",
+    "ax.yaxis.set_ticklabels(['Income > 50 K', 'Income < 50 K'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mdITeNZNYxpj"
+   },
+   "source": [
+    "## Random Forest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "id": "klTxsyGvbZwm"
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.metrics import confusion_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "id": "rBPVx4_6bHBW"
+   },
+   "outputs": [],
+   "source": [
+    "train_data_RF =  pd.get_dummies(train_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "id": "FMCF6dWGRi3p"
+   },
+   "outputs": [],
+   "source": [
+    "X = train_data_One.drop(['income'], axis = 1) \n",
+    "y = train_data_One.iloc[:,3]\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 1/3 , random_state = 42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "id": "hoJhvHrVpa23",
+    "outputId": "ddd62b2a-9942-4fc1-e882-476ee04ec861"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "RandomForestClassifier(criterion='entropy', max_depth=25, min_samples_split=50,\n",
+       "                       n_estimators=200, oob_score=True, random_state=42)"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rf = RandomForestClassifier(max_depth=25,n_estimators=200, min_samples_leaf=1,min_samples_split=50,criterion='entropy', oob_score=True,random_state=42)\n",
+    "rf.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "id": "qV4h2RnbpHK9",
+    "outputId": "dffe2b68-86a7-4dde-9ec9-e400fc031a0f"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy score: 0.84218\n"
+     ]
+    }
+   ],
+   "source": [
+    "predrf = rf.predict(X_test)\n",
+    "accurrf = accuracy_score(y_test, predrf)\n",
+    "print(f'Accuracy score: {accurrf:.5}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "id": "RRVA6VjRoplN",
+    "outputId": "d9e0b535-c527-45ad-b69d-b71751ef2486"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Confusion Matrix\n",
+      "[[5313  368]\n",
+      " [ 845 1160]]\n",
+      "\n",
+      "Test Accuracy\n",
+      "0.8421805880822274\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.86      0.94      0.90      5681\n",
+      "           1       0.76      0.58      0.66      2005\n",
+      "\n",
+      "    accuracy                           0.84      7686\n",
+      "   macro avg       0.81      0.76      0.78      7686\n",
+      "weighted avg       0.84      0.84      0.83      7686\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report, confusion_matrix\n",
+    "print('\\nConfusion Matrix')\n",
+    "print(confusion_matrix(y_test,predrf))\n",
+    "\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "print('\\nTest Accuracy')\n",
+    "print(accuracy_score(y_test,predrf))\n",
+    "\n",
+    "from sklearn.metrics import classification_report\n",
+    "print('\\nClassification Report')\n",
+    "print(classification_report(y_test,predrf))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "85JBUyESwyG6"
+   },
+   "source": [
+    "## KNN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "id": "Q47sRU3bw19_"
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "id": "osk8hn0i1hF-"
+   },
+   "outputs": [],
+   "source": [
+    "train_data_RF =  pd.get_dummies(train_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "id": "nFwE8H1wxT7M"
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler\n",
+    "scaler = StandardScaler()\n",
+    "scaler.fit(X_train)\n",
+    "\n",
+    "X_train = scaler.transform(X_train)\n",
+    "X_test = scaler.transform(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "id": "blzIBgQRxUd-",
+    "outputId": "849c4d33-68f2-4c20-96e7-95ae56eb0cce"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "KNeighborsClassifier()"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "classifier = KNeighborsClassifier()\n",
+    "classifier.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "id": "yt7g5AKDxale"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = classifier.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "id": "fNiGn9uGxbNE",
+    "outputId": "76cc4d9b-4bb4-456b-aeaa-47a5540898fb"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Confusion Matrix\n",
+      "[[5025  656]\n",
+      " [ 866 1139]]\n",
+      "\n",
+      "Test Accuracy :  0.8019776216497528\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.85      0.88      0.87      5681\n",
+      "           1       0.63      0.57      0.60      2005\n",
+      "\n",
+      "    accuracy                           0.80      7686\n",
+      "   macro avg       0.74      0.73      0.73      7686\n",
+      "weighted avg       0.80      0.80      0.80      7686\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report, confusion_matrix\n",
+    "print('\\nConfusion Matrix')\n",
+    "print(confusion_matrix(y_test, y_pred))\n",
+    "print(\"\\nTest Accuracy : \",(accuracy_score(y_test,y_pred)))\n",
+    "print(\"\\nClassification Report\")\n",
+    "print(classification_report(y_test, y_pred))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "id": "jtr3Outh3efN",
+    "outputId": "05acad8f-5bcb-4959-cf48-c3bd7cec5320"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0, 0.5, 'Income > 50 K'), Text(0, 1.5, 'Income < 50 K')]"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 576x504 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cm = confusion_matrix(y_test, y_pred)\n",
+    "fig, (ax) = plt.subplots(1, 1, figsize=(8,7))\n",
+    "sns.heatmap(cm, annot=True, ax = ax,fmt='g')\n",
+    "# labels, title and ticks\n",
+    "ax.set_xlabel('Predicted labels')\n",
+    "ax.set_ylabel('True labels');\n",
+    "ax.set_title('Confusion Matrix')\n",
+    "sns.set(font_scale=1.5)\n",
+    "ax.xaxis.set_ticklabels(['Income > 50 K', 'Income < 50 K'])\n",
+    "ax.yaxis.set_ticklabels(['Income > 50 K', 'Income < 50 K'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MvubzVJQF_GN"
+   },
+   "source": [
+    "## XGBoost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "id": "Swtib-uEGFZr"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style type='text/css'>\n",
+       ".datatable table.frame { margin-bottom: 0; }\n",
+       ".datatable table.frame thead { border-bottom: none; }\n",
+       ".datatable table.frame tr.coltypes td {  color: #FFFFFF;  line-height: 6px;  padding: 0 0.5em;}\n",
+       ".datatable .bool    { background: #DDDD99; }\n",
+       ".datatable .object  { background: #565656; }\n",
+       ".datatable .int     { background: #5D9E5D; }\n",
+       ".datatable .float   { background: #4040CC; }\n",
+       ".datatable .str     { background: #CC4040; }\n",
+       ".datatable .row_index {  background: var(--jp-border-color3);  border-right: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  font-size: 9px;}\n",
+       ".datatable .frame tr.coltypes .row_index {  background: var(--jp-border-color0);}\n",
+       ".datatable th:nth-child(2) { padding-left: 12px; }\n",
+       ".datatable .hellipsis {  color: var(--jp-cell-editor-border-color);}\n",
+       ".datatable .vellipsis {  background: var(--jp-layout-color0);  color: var(--jp-cell-editor-border-color);}\n",
+       ".datatable .na {  color: var(--jp-cell-editor-border-color);  font-size: 80%;}\n",
+       ".datatable .footer { font-size: 9px; }\n",
+       ".datatable .frame_dimensions {  background: var(--jp-border-color3);  border-top: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  display: inline-block;  opacity: 0.6;  padding: 1px 10px 1px 5px;}\n",
+       ".datatable .frame thead tr.colnames {  background-image: url('data:image/png;base64,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');  background-repeat: repeat-x;  background-size: 14px;  height: 28px;}\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from xgboost import XGBClassifier\n",
+    "import xgboost as xgb\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.metrics import confusion_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "id": "HoLpCC3WIFLj"
+   },
+   "outputs": [],
+   "source": [
+    "X_GB = train_data_One.drop(['income'], axis = 1) \n",
+    "y_GB = train_data_One.iloc[:,3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "id": "exnXh6kTIvLQ",
+    "outputId": "d483db8b-160a-4da4-9219-60a0f1d2c919"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "XGBClassifier(n_estimators=300, reg_alpha=0.5, reg_lambda=0.5)"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split \n",
+    "GB_X_train, GB_X_test,GB_y_train,GB_y_test = train_test_split(X_GB,\n",
+    "                                                y_GB,\n",
+    "                                                test_size = 0.3,\n",
+    "                                                random_state = 42)\n",
+    "model = XGBClassifier(max_depth=3,learning_rate=0.1,n_estimators=300,booster=\"gbtree\",reg_lambda=0.5,reg_alpha=0.5)\n",
+    "model.fit(GB_X_train, GB_y_train)\n",
+    "model.fit(GB_X_test, GB_y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "id": "mBUue9MTIUx_"
+   },
+   "outputs": [],
+   "source": [
+    "Testpredxgb = model.predict(GB_X_test)\n",
+    "Trainpredxgb = model.predict(GB_X_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "id": "_cRA5f9GJxMe",
+    "outputId": "4bc3f209-0d79-471c-aec1-d6513909b318"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Confusion Matrix\n",
+      "[[11348   728]\n",
+      " [ 1631  2433]]\n",
+      "\n",
+      "Train Accuracy\n",
+      "0.8538413878562577\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.87      0.94      0.91     12076\n",
+      "           1       0.77      0.60      0.67      4064\n",
+      "\n",
+      "    accuracy                           0.85     16140\n",
+      "   macro avg       0.82      0.77      0.79     16140\n",
+      "weighted avg       0.85      0.85      0.85     16140\n",
+      "\n",
+      "\n",
+      "Confusion Matrix\n",
+      "[[4839  263]\n",
+      " [ 675 1141]]\n",
+      "\n",
+      "Test Accuracy\n",
+      "0.864411679676207\n",
+      "\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.88      0.95      0.91      5102\n",
+      "           1       0.81      0.63      0.71      1816\n",
+      "\n",
+      "    accuracy                           0.86      6918\n",
+      "   macro avg       0.85      0.79      0.81      6918\n",
+      "weighted avg       0.86      0.86      0.86      6918\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report, confusion_matrix\n",
+    "#train\n",
+    "print('\\nConfusion Matrix')\n",
+    "print(confusion_matrix(GB_y_train,Trainpredxgb))\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "print('\\nTrain Accuracy')\n",
+    "print(accuracy_score(GB_y_train,Trainpredxgb))\n",
+    "from sklearn.metrics import classification_report\n",
+    "print('\\nClassification Report')\n",
+    "print(classification_report(GB_y_train,Trainpredxgb))\n",
+    "\n",
+    "#test\n",
+    "print('\\nConfusion Matrix')\n",
+    "print(confusion_matrix(GB_y_test,Testpredxgb))\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "print('\\nTest Accuracy')\n",
+    "print(accuracy_score(GB_y_test,Testpredxgb))\n",
+    "from sklearn.metrics import classification_report\n",
+    "print('\\nClassification Report')\n",
+    "print(classification_report(GB_y_test,Testpredxgb))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8yiJdENCatmf"
+   },
+   "source": [
+    "# Cross Validation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "id": "yzHiZGeQavuu",
+    "outputId": "5974d60a-9996-492e-b7d3-8662481d96db"
+   },
+   "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>CV Mean</th>\n",
+       "      <th>Std</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Logistic Regression</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Decision Tree</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Random Forest</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>KNN</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>XGBoost</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     CV Mean  Std\n",
+       "Logistic Regression      0.8  0.1\n",
+       "Decision Tree            0.8  0.1\n",
+       "Random Forest            0.8  0.0\n",
+       "KNN                      0.8  0.0\n",
+       "XGBoost                  0.8  0.0"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "from sklearn.model_selection import cross_val_predict\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "\n",
+    "kfold = KFold(n_splits=10, random_state=22)\n",
+    "xyz=[]\n",
+    "accuracy=[]\n",
+    "std=[]\n",
+    "classifiers=['Logistic Regression','Decision Tree','Random Forest','KNN','XGBoost']\n",
+    "models=[LogisticRegression(),DecisionTreeClassifier(),RandomForestClassifier(), KNeighborsClassifier(n_neighbors=9),XGBClassifier()]\n",
+    "for i in models:\n",
+    "    model = i\n",
+    "    cv_result = cross_val_score(model,X,y, cv = kfold,scoring = \"accuracy\")\n",
+    "    cv_result=cv_result\n",
+    "    xyz.append(cv_result.mean())\n",
+    "    std.append(cv_result.std())\n",
+    "    accuracy.append(cv_result)\n",
+    "models_dataframe=pd.DataFrame({'CV Mean':xyz,'Std':std},index=classifiers)       \n",
+    "models_dataframe"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "j_ZffhTMRA76"
+   },
+   "source": [
+    "# Feature Importance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "id": "a-5Z9I9lObgQ",
+    "outputId": "3cf4fb40-affe-4d59-fbf4-3e76636c361c"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = train_data[['capital-loss','native-country','workClass','race','marital-status','age','sex','capital-gain', 'education','occupation','relationship']]\n",
+    "y = train_data['income']\n",
+    "from sklearn.ensemble import ExtraTreesClassifier\n",
+    "from sklearn import tree\n",
+    "\n",
+    "extree = ExtraTreesClassifier()\n",
+    "extree.fit(X, y)\n",
+    "relval = extree.feature_importances_\n",
+    "\n",
+    "fig = plt.figure(figsize = (15,10))\n",
+    "pos = np.arange(11) + 0.5\n",
+    "plt.barh(pos, relval, align='center')\n",
+    "plt.title(\"Feature Importance\",fontsize=18)\n",
+    "plt.xlabel(\"Model Accuracy\", fontsize=15)\n",
+    "plt.ylabel(\"Features\",fontsize=15)\n",
+    "plt.yticks(pos, ('capital-loss','native-country','workClass','race','marital-status','age','sex','capital-gain', 'education','occupation','relationship'))\n",
+    "plt.grid(True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}