category_01_hr/01_HR_Analytics/Clone__HR_Analytics_for_beginners.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "minus-winner",
   "metadata": {},
   "source": [
    "## HR Analytics (Analysis Code - Best Basic Kenel)\n",
    "### Reference : HR Analytics for begineer - S P Rakshith)\n",
    "----------------------\n",
    "**1. Importing the necessary libraries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "matched-harvey",
   "metadata": {},
   "outputs": [],
   "source": [
    "# To prevent the annoying warning from scikit learn package\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "prospective-session",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_style('dark')\n",
    "cmap = sns.cm.mako_r\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix, classification_report, accuracy_score"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adolescent-greene",
   "metadata": {},
   "source": [
    "**2. Importing the Data using Pandas read_csv(). And calling head() and info() on the DataFrame**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "periodic-access",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clone__HR_Analytics_for_beginners.ipynb\n",
      "Clone__Predict_who_will_move_to_a_new_job.ipynb\n",
      "HR_Analytics.ipynb\n",
      "\u001b[1m\u001b[36mcatboost_info\u001b[m\u001b[m/\n",
      "\u001b[1m\u001b[36mdata\u001b[m\u001b[m/\n",
      "submission.csv\n"
     ]
    }
   ],
   "source": [
    "ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "hungarian-yugoslavia",
   "metadata": {},
   "outputs": [],
   "source": [
    "aug_train = pd.read_csv('./data/aug_train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "narrative-exchange",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>enrollee_id</th>\n",
       "      <th>city</th>\n",
       "      <th>city_development_index</th>\n",
       "      <th>gender</th>\n",
       "      <th>relevent_experience</th>\n",
       "      <th>enrolled_university</th>\n",
       "      <th>education_level</th>\n",
       "      <th>major_discipline</th>\n",
       "      <th>experience</th>\n",
       "      <th>company_size</th>\n",
       "      <th>company_type</th>\n",
       "      <th>last_new_job</th>\n",
       "      <th>training_hours</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8949</td>\n",
       "      <td>city_103</td>\n",
       "      <td>0.920</td>\n",
       "      <td>Male</td>\n",
       "      <td>Has relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>&gt;20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29725</td>\n",
       "      <td>city_40</td>\n",
       "      <td>0.776</td>\n",
       "      <td>Male</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>15</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>&gt;4</td>\n",
       "      <td>47</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11561</td>\n",
       "      <td>city_21</td>\n",
       "      <td>0.624</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>Full time course</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>never</td>\n",
       "      <td>83</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33241</td>\n",
       "      <td>city_115</td>\n",
       "      <td>0.789</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>Business Degree</td>\n",
       "      <td>&lt;1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>never</td>\n",
       "      <td>52</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>666</td>\n",
       "      <td>city_162</td>\n",
       "      <td>0.767</td>\n",
       "      <td>Male</td>\n",
       "      <td>Has relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Masters</td>\n",
       "      <td>STEM</td>\n",
       "      <td>&gt;20</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Funded Startup</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   enrollee_id      city  city_development_index gender  \\\n",
       "0         8949  city_103                   0.920   Male   \n",
       "1        29725   city_40                   0.776   Male   \n",
       "2        11561   city_21                   0.624    NaN   \n",
       "3        33241  city_115                   0.789    NaN   \n",
       "4          666  city_162                   0.767   Male   \n",
       "\n",
       "       relevent_experience enrolled_university education_level  \\\n",
       "0  Has relevent experience       no_enrollment        Graduate   \n",
       "1   No relevent experience       no_enrollment        Graduate   \n",
       "2   No relevent experience    Full time course        Graduate   \n",
       "3   No relevent experience                 NaN        Graduate   \n",
       "4  Has relevent experience       no_enrollment         Masters   \n",
       "\n",
       "  major_discipline experience company_size    company_type last_new_job  \\\n",
       "0             STEM        >20          NaN             NaN            1   \n",
       "1             STEM         15        50-99         Pvt Ltd           >4   \n",
       "2             STEM          5          NaN             NaN        never   \n",
       "3  Business Degree         <1          NaN         Pvt Ltd        never   \n",
       "4             STEM        >20        50-99  Funded Startup            4   \n",
       "\n",
       "   training_hours  target  \n",
       "0              36     1.0  \n",
       "1              47     0.0  \n",
       "2              83     0.0  \n",
       "3              52     1.0  \n",
       "4               8     0.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "catholic-composite",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 19158 entries, 0 to 19157\n",
      "Data columns (total 14 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   enrollee_id             19158 non-null  int64  \n",
      " 1   city                    19158 non-null  object \n",
      " 2   city_development_index  19158 non-null  float64\n",
      " 3   gender                  14650 non-null  object \n",
      " 4   relevent_experience     19158 non-null  object \n",
      " 5   enrolled_university     18772 non-null  object \n",
      " 6   education_level         18698 non-null  object \n",
      " 7   major_discipline        16345 non-null  object \n",
      " 8   experience              19093 non-null  object \n",
      " 9   company_size            13220 non-null  object \n",
      " 10  company_type            13018 non-null  object \n",
      " 11  last_new_job            18735 non-null  object \n",
      " 12  training_hours          19158 non-null  int64  \n",
      " 13  target                  19158 non-null  float64\n",
      "dtypes: float64(2), int64(2), object(10)\n",
      "memory usage: 2.0+ MB\n"
     ]
    }
   ],
   "source": [
    "aug_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sitting-starter",
   "metadata": {},
   "source": [
    "-------------------------\n",
    "**3. Calling isna() and checking the total number of Null Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "peaceful-atlantic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "enrollee_id                  0\n",
       "city                         0\n",
       "city_development_index       0\n",
       "gender                    4508\n",
       "relevent_experience          0\n",
       "enrolled_university        386\n",
       "education_level            460\n",
       "major_discipline          2813\n",
       "experience                  65\n",
       "company_size              5938\n",
       "company_type              6140\n",
       "last_new_job               423\n",
       "training_hours               0\n",
       "target                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "secondary-content",
   "metadata": {},
   "source": [
    "------------\n",
    "As we can see that there are a lot of missing values and most of them are Categorical and it is not feasible to fill those values as we may end up providing completly wrong data to the training set. So, I prefer dropping them instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "color-review",
   "metadata": {},
   "outputs": [],
   "source": [
    "aug_train.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "floppy-isaac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 8955 entries, 1 to 19155\n",
      "Data columns (total 14 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   enrollee_id             8955 non-null   int64  \n",
      " 1   city                    8955 non-null   object \n",
      " 2   city_development_index  8955 non-null   float64\n",
      " 3   gender                  8955 non-null   object \n",
      " 4   relevent_experience     8955 non-null   object \n",
      " 5   enrolled_university     8955 non-null   object \n",
      " 6   education_level         8955 non-null   object \n",
      " 7   major_discipline        8955 non-null   object \n",
      " 8   experience              8955 non-null   object \n",
      " 9   company_size            8955 non-null   object \n",
      " 10  company_type            8955 non-null   object \n",
      " 11  last_new_job            8955 non-null   object \n",
      " 12  training_hours          8955 non-null   int64  \n",
      " 13  target                  8955 non-null   float64\n",
      "dtypes: float64(2), int64(2), object(10)\n",
      "memory usage: 1.0+ MB\n"
     ]
    }
   ],
   "source": [
    "aug_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "revolutionary-magazine",
   "metadata": {},
   "source": [
    "-------------\n",
    "**4. As most of the Data is Categorical we plot Bar/Pie to visualize the Categorical Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "occasional-intersection",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Male      8073\n",
       "Female     804\n",
       "Other       78\n",
       "Name: gender, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train['gender'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "daily-harvey",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Male', 'Female', 'Other'], dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train['gender'].value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "false-proxy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8073,  804,   78])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train['gender'].value_counts().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "nutritional-creativity",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to Plot Bar Graph\n",
    "def plot_bar_graph(column, order=None):\n",
    "    x = aug_train[column].value_counts().index\n",
    "    y = aug_train[column].value_counts().values\n",
    "    sns.barplot(x, y, order=order)\n",
    "    \n",
    "# Function to Plot Pie Chart\n",
    "def plot_pie_chart(column, title=''):\n",
    "    values = aug_train[column].value_counts().values\n",
    "    labels = aug_train[column].value_counts().index\n",
    "    plt.figure(figsize=(6,6))\n",
    "    plt.title(title)\n",
    "    plt.pie(x=values, labels=labels, autopct='%1.2f%%', textprops={'color':'w'})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "chemical-accessory",
   "metadata": {},
   "source": [
    "1. Pie Chart for Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "robust-sharing",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pie_chart('gender', title='Pie Chart For Gender')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "promotional-wedding",
   "metadata": {},
   "source": [
    "As we can see that most of the Candidates working are Male"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "social-paste",
   "metadata": {},
   "source": [
    "__________\n",
    "1. Pie Chart for Relevent Experience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "corporate-server",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NvPzFCSUTflrjdx7JUYYBp/+ms3vDkT3ipsnjxeHg9YAOXJCcp6KWpspwXPfsRMp54KmRc4ru/mRmKJHWWrRsXquSMH89pkf1IT3aVRWHg6cAn/udSWRTVNTSFHWuiKeeXVGZ3PP3L4wv+WHROr/zSBN0QPc23DukT3UoYNxfHA7eAKT8ziRSGxW1NCVGOuNcmMq4dz70xazwfz7/MZTK6P0r2651aZj7hvSJ9erYbHZZJHQcMNvvTCIbUlFLU9GuIp56c9Ga+G6XvTi+ZMZS7VqU+mEYMGxA18zVh1nxopB5sWkYz/mdSaQmFbU0BXvHkun3nvxmbvmdH88I6b7Q0hB6dCjnkaH9Ys2j4Q9KI8FhgPapSE5QUUsuM5Jp55Jkxrn9ipcmREdMW+Z3HslzkZDJ347tFT96tw5rSoqCJwCj/M4koqKWXBWtjKcfX1mVOPacJ8aUzF0Z8zuPFJDBPdtz+ym7VYcC5i2RUOAf6CIp4iMVteSiLpXx9PCvfly+/VUvT4pWpzJ+55EC1L48wqND96zq2rrk89JI8BRAd3MRX6ioJdccGkumX7vzoxklj309J+B3GCls4YDJXafvUX3Azm1+LI0EDwG0/0UanYpacoURT2VuSKSdP1/07HfRUbN1/wTJHVcf1j01bGDXVcXh4IHANL/zSGFRUUsuKKqIp15bsLr6wPOeHFuyZF3c7zwiv3JS307uzcf3rCwOB48HPvU7jxQOFbX4raQinho+es6qvpc+Nz6azOiYHcld++zYikeH7lldFDJ/HwqYT/idRwqDilr81KIynv78o6lLul/z2uSIzo+WpqBbmxJeuHDvWHkkdH80HLgeHREuDUxFLX5pV5lIf/Pqdz91+vt7U4v0NpSmpFVJmGfP36tq+1Yln5QWBU8HtL9GGoyKWvzQpSqR/uaRL2e3vWfEzJDfYUS2RVHQ5L4hfar36dZqUlkkdDCgk/2lQaiopbHtEkumv7ptuN3iyW/m6vQradJMA+4d0ic+qHvbcdnTt7RmLfVORS2NqU91MvPZX976vuz18QtMv8OI1IeAafDAGX2rB+zUanRZJHQ4kPA7k+QXFbU0loHVycwHf3h5YsmHPywx/A4jUp+CpsFDZ/eL7d211TelkeDRQNLvTJI/VNTSGPaJJdMf//aZcSVf/7jC7ywiDSIUMHhs6G9i/bq0+KI0EjwOSPmdSfKDNj9KQ+tVncwMv+S58SppyWupjMuFz3xXPGnBmgMq4+nXgKDfmSQ/qKilIe0YS6a/uPb1yaVfzFjudxaRBpfMOAx7amzxD4vWHlIZT78E6IBJqTMVtTSU9lWJ9Ne3fDC92TuTFmmftBSMRNph6BNjiqcvWXdEZSL9HPqclTrSG0gaQlllIv3lo1/Nbv3Mt/O0RiEFJ5F2OPvxMcU/Lqs8piqRfsDvPNK0qailvoUq46n3/zt5cee7P9HFTKRwVacyDH18dMnqWHJoKuP8zu880nSpqKU+GZWJ9BOTFqztd/2bUyJ+hxHx27p4mjMeHV1cnczcBgz2O480TSpqqTfVycyNS9bGT7jwme+KdYMNEc/8VTGGPTU2GkumXwN6+p1Hmh4VtdQLx3FPq0qmrz3j0VElsWTG7zgiOeW7eau54c3vS2KJ9Aigjd95pGlRUUt92CWezjw+9PExxcsqdPVEkdq8OWGh8dzoeS0q4ql30DnWshVU1FJXxVWJ9Pv/eG9adOridX5nEclpt3wwPfzDonW7VSXSd/mdRZoOFbXUSWUi/cgXM5Z3eGHMfL2XRDbDceGiZ8cVVybSwxzXPcPvPNI06MNVtlnacYaujaWOv+bVSVG/s4g0FWurUwx9fExxPJV5FOjjdx7JfSpq2Va7JtPOg+c/PbakSgePiWwVe2kF170+JVqVSL8DFPudR3Kbilq2RUllIv3fv707NTJ9SYXfWUSapHcmLTI+n7G8lfZXy+aoqGWrVcbTj302fVm7l8f+pPePSB1c/8bkaCLtnAUc4ncWyV36oJWtknHc89ZUJ4+99vXJ2i8tUkfrqtNc8dKE4lgy/RLQ3O88kptU1LI1rEQ6c/+wp8YW66ImIvXjq5kreGvCotKKeOpRv7NIblJRy5YyKuKp524fbkdmLK30O4tIXrn5valFlYn0kcBJfmeR3KOili3iuO45i9fGd31q5Fy9Z0TqWXUqw++eH19cncw8CbT3O4/kFn3oypZok0g59/7h5YkluteGSMMYP38NT42cE6mIp54HDL/zSO5QUctmVcRTD7w0dn74h0W6RKhIQ7rz4xmh5RWJ/hnHPd/vLJI7VNSyOQcl085Rtw23i/wOIpLvUhmXS54bX5LMOHejTeCSpaKWTYlUJdLP/On1yTrKW6SR2EsreHH0/FBlPH2b31kkN6ioZaOqk5kbR81e2WLEtGV+RxEpKHd/MiPs4p4E7O53FvGfilo2ZhfHdf/w5zen6DrEIo1sXTzNrR/aRRXx1CPowLKCp6KW2pgV8dRztw23i5auS/idRaQgvTBmvrkmluoJHOt3FvGXilpqc9KydYldnvlW50yL+CXjuNzw5pSSqkT6QSDsdx7xjz6IZUOBynj69pvfm6pzpkV89uXMFUxasKY8mXYu9zuL+EdFLRsaMm9VVcvPZyz3O4eIADe+9UNJxnFvAlr7nUX8oaKWmoJVifSt/3x/WqnfQUTEM2t5Ja+PXxCsSqT/7XcW8YeKWv7Hcd2hM5ZWlI2ctdLvKCJSw+0f2UUunAn09DuLND4VtawXrk5m/q21aZHcsyaW4t4RM4vWVadu8TuLND4VtQCQcdzzv1+0tuS7eav9jiIitXh+1DwzYBqHADv6nUUa1+aKehDw0gaP3QKc2xBhapgLRBpw+icA2zXg9DfmXHLznMhIIp35x7/en1bidxARqV1VMsMz384LVCXS1/udRRpXoa5RXwGU+zDfp4B3fJjvJqUzzkXj5q0umrRgrd9RRGQTnvhmTihgGmeiI8ALSl2KOgA8BgwHvgNuzj5+IjAa+Bp4rpZ5fA68CnwCFAGPA19mhx+0wbCdgQ+Az7I/OwOXA3/NPl8ETMe7GMBlwLfAyOww4BXjw9mMk4G+wFHAHsAz/PIiAqFaspQDU4HeQI/sNNY/9nB2uHeAko2MD/A98AbwInATcHH28X8D32Qzn1Ljtbk7+9qMAbpkH/8L3ms8Ebgo+1hty7stipMZ56ZbPpiutWmRHLe8IsF7kxeTSGWu8DuLNJ4tKeqD8Apk/Z8zso93BkYBg4GBwCXZx4cAd2Uf+4ja11xfAA4BhgErgP2B44AHNhjuduBe4MDs77cAzwKn4l3/9ljgPWAn4LTsPAcCxwNWdhrzshnvA34LvI9XeEOBZI15XVBLlnV4m6sfBZ7MjrMOKAaez85rOl551jY+QCnel5ghNeZ1BNAVGJBdthuA5tnnxmRfm4+z4/TJDt8f2BfvC0PPTSzvVsk47rCxc1aHdK9pkabhP5/9GHVcrsD7HJICENyCYT4FTq/x9/VHHa4CfoNXNOvw1m4BrgKuxyvuacBbtUzTzv7sDeyHV0Lr87SqMVxv4M/AtXjFnARWAxPwCupc4I/AbnhrnyOy47XAK2+ywwL8hFeMG7OxLGOANdl5T8w+l8JbcwZvjfYIILOJZVm/vDXn1Q/viw94a+Pr155r5m2PV8BjstOP4W22P3Ujy7vhfDbHqE5mrn3wix+1Ni3SRMxeUcWYuavMgTu1Pi9gGhuu3Egeqsum73PxCuxM4A68b3cG3lrrTcAB2b+fUMu4TvbndLxNwoPwyu5VvCKmxvPXZp+/CHgt+/ijwJVANDuMDfyA96VhEN4m7ynZYWu7EKbDr5d9Y1lOBiqBdPZ38Ip1/e3nBmTnvallWb+8Nef1WXbYg4BXgNkbyTsdb5O9mZ3vx5tZ3q1x8KqqZPNRs1dtw6gi4pd7PplZEk9lbsTbBSl5ri5FPQI4Em+N8kFgJt6R1GPwyuRTvDXC9zYxjYeBXYAvstOZxy9L7Wq8/dFf4O1Tnpx9/AugF15BAUzK5vkab1/uzsDCTcx3ZHZ6LTeTpTPeZuuLs3/+yc9rvtdm59cxO+7mlqWmd/HK/ytgHF45V2xk2InAh3j7s7/G2+S+tctbq3XVqese/GKW1qZFmpjx81czd2VVCd4xQZLnDNfVnRe2wVy8Uo77nKMudqhKpKft+Y9PItWpjN9ZRGQrHdqjHXecsvu08mioJ7VvOZQ8UainZxW86lTmspfH/mSqpEWapk+mLaUqme4M7ON3FmlYKuptswNNe206hMv5z4+ep3vcijRRrgvPjJxXXBFPXbz5oaUpU1EXpqNmLa80Zy2v8juHiNTBGxMWmKGAeRI6VSuvqagL0NpY6sonv5lT5ncOEambpesSTPxpTQbvWgqSp1TUhadTKGj0f3/KYr9ziEg9eH7UvLI1seRlfueQhqOiLjCpjHPuOxMXEU9t7MwxEWlKPpq6lHDQ3APo5HcWaRgq6gITS2aGvjVxYUPemUxEGlEi7fDh90vcjOOe5ncWaRgq6sLSOWgancfO1T2nRfLJmxMWRisT6Qv8ziENQ0VdQBzXPW7E9GVOxtG1EUTyychZKwkYxg7Ajn5nkfqnoi4g66pTZ78/eZFO4xDJMxnH5d3Ji0hnnCGbH1qaGhV14WgeDQf2+HLGCr9ziEgDeGvCwkgsmTnf7xxS/1TUhePIsXNWJ3TJUJH8NHbuKgKm0QEd/Z13VNQFYm116sy3Jy3URU5E8pTjwqjZK9PAwX5nkfqloi4MRZGQedCn05b5nUNEGtCIactK11anjvU7h9QvFXVhOOjHpZXJlVVJv3OISAP6+scVhALGQYDhdxapPyrqAlAZT5/+9qRFpX7nEJGGNX9VjOpkJgTs6ncWqT9BvwNIwzMMjvpk6tKc+1IWNA3uOHV3OrUoJuO4XP/GZK48pDttyooA6NQiyoT5a7jsxQm/GO/SQd04ZNd2hAImz46axyvf/cR9Q/rUOt6/TujFrh3KeXbUPN4Yv5CyoiB/P74Xf3h5YmMvrkij+HzGcvOkvp0OBqb6nUXqh4o6/3V0oWT2ity7peWBu7QlYBqc9OBIBu7UmqsHW1zy3HgAyqNBXrpwb/7+3i8/a/besSV9u7TgpIdGEg0F+O3+3vUd1pd5zfGaF4doXVrEiQ+O5MUL9+aN8Qu59MBuPPj5j427oCKN6At7efTgXdqe0Lw4fJ/fWaR+qKjzX//JC9YkgZy7vvfs5VUETRPDgNJIkHTm5yum/eGQ7jw1ch7LKxK/GGf/ndtgL6ngkbP7UVoU4l//nfaL52uOFw0FCAZMioImiVSGTi2iRMNBZiytbJTlE/HDyFkriIYD++B9vqf9ziN1l3ObQ6V+xVOZgd/OWpmT+6djyTSdWkQZcdUB3HJib578Zi4ArUrCDNipNa+N++lX47QoCdO7YzMufX48N7w5hbtP3+N/z204XnUqwydTl3LfkD7cM2Imlx+8M09+M4e/HtODG4/elWgo0BiLKdKoVlQmWbo2ngL29DuL1A8VdZ6rTmUOHj9/dU7+O58/sCtfzljOQXd8wRH3fMUdp+5OUdDkiN4deHviImq7JPmaWJIvZy4nlXGZvaKKZNqhVUkYoNbxXhgznwufGQcYzFsZY0C31oyZs4rv5q7muD22a5wFFWlkI6YvK0pnnEP9ziH1Iyc/wKXehErCwV0m/7TW7xy1WludoiLubZlbE0sRChiYhsHAnVrzuV37Od9j567mgO5tAGhbVkQ0FGB1zDvtbFPjXbBfVx7/ejbRcADHdXGBkiLt+ZH89MWM5eGKRPp4v3NI/dAnVX7rvawinqhIpMN+B6nN41/P4daTd+OVi/YhHDC49UOb6lSGHduU8NOq2C+GvePU3bljuM2n05exV9eWvP27AZiGwf97+/v/rUHXNh7AMbt1YMS0pcRTDu9PXsz9Z/TBceGyF8c3xmKKNLpJP62hJBzsgXc+tW6X18QZrqt/wzx26RvjF9x21SuTdMcskQIz+a+HVZdHQ7sA8/3OInWjTd95bG0sedDoOatU0iIFaMbSiiTQ2+8cUncq6jxmmsa+E+av9juGiPhgysK1xa7rqqjzgIo6f7UKBcxWPy7TOcMihWjqonWhtdWp/n7nkLpTUeevPjOXVVbXdoqTiOQ/e2kFhmHs4XcOqTsVdf7a8cdllSG/Q4iIP2YuraQkHOgE6HOgiVNR56lk2tlp1vLKqN85RMQf1akMq6qScWBnv7NI3aio81RVMt1r/sqY7kkrUsCmL6lwgF5+55C6UVHnKQO6LVj964t/iEjhmPTTmtJUxtnd7xxSNyrqPBUJBbb7aVW13zFExEfTl1SYlYn03n7nkLpRUeenMtMwipZXJjY/pIjkrZ9WxzBge79zSN2oqPNT1+UVCa1OixS4lZVJQgGzld85pG5U1Pmp6/xVMZ1BLVLgVlQmiIQC5Xg355AmSkWdn3actbwy4ncIEfFXIu2QzjgZoNzvLLLtVNR5qCqRtuasqCryO4eI+G9tPJUE2vqdQ7adijoPJdJO9wWrtYtaRGBVVTKDirpJU1Hnp5brqlN+ZxCRHLC8ImGgom7SVNR5yDQoXxdXUYsILF0XD6GibtJU1HkoaJqlFfG03zFEJAcsWZsocl1XRd2EqajzUDBglFQmVNQiAisqE2ZVIqOLnjRhKur8Y4QCZqRCm75FBO9c6mTG6eh3Dtl2Kur8EwZIZXS9ExGB7G6wln7nkG2nos4/RWnHyfgdQkRyQ9pxAAJ+55Btp6LOP0WpjKuiFhEAvJ5WUTdlKur8E0lnsv81RaTgpR0HA4J+55Btp6LOP0WpjKuiFhEAMo4LWqNu0vQtK/+EU9n/mVLYLhzYxblmUEdAb4dCZhgGjpFomT3OVJogFXX+SQUDhm5pJ8xbVW2GiiIw/lmMKS/7HUf80rYnHHJThd8xZNupqPNPVSQY0C4N4aOpyzj/+e957IyzYPFE15j4vL7AFSIzBLhxv2PIttMHev6pKgqa+gImAHw6fRnnPTsF98jbDbfvudoGXoi8jwNdqrAJU1Hnn6pQ0Az5HUJyxxczV3DW05NxD/+34e51oQ40LDRmEFwVdVOmos4/acdxM0VB/dPKz0bOWslpT0zEPfhvhrv3pSrrQmIGAFdF3YTp0zwPpR03GQ3rbAz5pbFzV3Py45MM58C/GO6AK1XWhUKbvps8FXUeyjhuvCSs3dTya+Pnr+b4RyYYzv5/Mtz9/6Qr2BWCSDkY5lq/Y8i2U1HnoYzjVmuNWjZmysK1HPPQOCOz7xWme+ANKut8V9oeQtG5fseQbaeizkOO61YXq6hlE6YuruDIB8cZ6f6Xmu4hN6ms81n5dilC0fl+x5Btp6LOQ45LlYpaNmfG0koGP/Cdke53oekO/rfKOl817xwHFvsdQ7adijo/VUVD2kctmzd7eRWH3D/WSO1+tukeeZvKOh+Vbeegom7SVNR5yDRY1KasyO8Y0kTMWxnjwPvGGMleQ0z3mHsy6Aq0+aWsnYmKuklTUeehskjoh+1bFuv0G9liC1fHGXT3GCOxy4mGe+wDKut8Em1ZBCzxO4ZsOxV1HgqYxqxubUtifueQpmXxujj73TXarN75GMM94dEMhj4emrxQFAIhE1jtdxTZdvqfmJ/mdG1dov2NstWWVyYZeOdoM9Z1sOGe/ETGu6qVNFml7SFVvQbd67RJU1HnpznbNYvq5rOyTVbFkgy461uzcvuDDPeUZzLoHi9NV1k7yKSW+x1D6kZFnZ8WF4cDoUhI/7yybdbE0ux7xyhz3Xb7Ge7pL2QI6D4vTVJpe8Bd5HcMqRt9kucnpzqVWd6pRbHfOaQJq4h7Zb2m3d64Q17OENBGmianrB0EwnP9jiF1o6LOU6mMO7ezilrqqCqZZsAdIwOrWvXDPet1h6BO+2tSyjulKSqb43cMqRsVdZ4KBYzpnVtG/Y4heSCWdBhwx7eB5c12c92z33IIRvyOJFuq055VwBS/Y0jdqKjzVFkkNK1r65KU3zkkP8TTDgPv/DawtLSH657zrkNIW2uahPa9i4DxfseQulFR56853dqUVvsdQvJHMu0w8I5vAosiO7nuue87hEv9jiSbUr4dmMEUsNDvKFI3Kur8NdVqX6bLS0m9Sjuw313fBuYHu7jueR84FJX5HUk2psPukIp9j86hbvJU1PlrevPiULBFsU6rkfrlOHDgPaMCc+jousM+cog08zuS1KbDHg7hsq/8jiF1p6LOX04skZmyR+cWfueQPOQ4cNA9owIzUm1d9/yPXaJ6n+Wc7fepJBge43cMqTsVdR4rLQp+3K9Lc11KVBrM4PtHB6ZWt3TcCz5xKW7pT4iO/eDc97zf2/eG8z7w/n7WG1DS5pfDGiYcdz8MGw7n/RdadPUeb2PBsA+9x4+6g/9d5/zou+GCT2D3072/F5XDiY80ymLVWYfdguhAsrygos5joaA5ct9urSv9ziH57aj/jAlMrih33As+dSlp3bgzH3AFHHsf/ztl7PBb4IM/wVNHw7R3YeCVvxzeOsL7+cRg+OxfMPif3t8P/n8w4u/e46EoWEdCtAWUtoHHD4U+Z3nD7XcVfH1XoyxanZS2hVDUAOb6HUXqTkWd30b32K48auqQMmlgxz00NvDd6mLXvfAzl9J2jTfjVXPg5bN+/vtrw2BJ9rRhMwDpxC+Hn/4+vHuF93uzzlCVvQz2y2fDvJEQCEFpO6ha5o1rhrwvAekENO8CoWJYNq3hl6uu2u8GydhUdCBZXlBR57eVqYyzslsbnUYjDe+UR78zv10WctwLP3Mp69A4M532Djjpn/9eudT72Xkv2Ou38O0Dvx7HycDxD8KRt8LUt73HXMcr7ktHQ3ErWDETUjGwP4CTHofPb4EDroHRD8ER/weD/0VOn0veYQ+XULEOJMsTKuo857iM6rO9DvSRxnHGE+MDXy0yvTXrZp38CdHzRDj6LnjhVIitrH2Yty6B+/rBMff8XLhrf4L7+sJ3T3hFDDDuSXjpDDAMWDUXuh7grXn/NBp6n9Ioi7NNtt+nklBEB5LlCRV1nmsWDY3o37VlzO8cUjiGPj3eHDHf8cq6+faNO/PdToW9LvT2Ua+eW8vzp8HAq7zfU9XguuBmYMiL0HJH7/FEpbeGXdM+v4dRD3j7r52MN164pEEXpU62290ExvkdQ+qHijr/jdqra8v05gcTqT8XPDfR/O+spOte+NnPR1Y3NMOEI26FolI47VnvyO9B13vPnfAQNOvkHWDWYTfviO+z3oAPr/P2P399l7c5/Jx3vSO8R/z95+n2OsnbBJ6qhqlvwb6Xwd6XwA9vNs5yba0WXSFcmgF+9DuK1A/DdXWsQZ4LJdNOZb+bPw5XJNTX0rjuObW3c+wuJabx+GGwUr3RKPpf7HLgDS8TKR/idxSpH1qjzn+pWDI9ae9urfzOIQXoilemmK/9UOm6F3zinassDa/XiRVEyl/xO4bUHxV1ASiPhl48rEc73aBDfHHN698bL0xc67rDPoK2PfyOk9+KyqDDHhHgY7+jSP1RURcA0zDeP7RHO+3jEN/c8PYPxlPjVrnusA+9q4dJw+h2EKRi3wG60FEeUVEXhhkB01jbc7tyv3NIAfvbe9OMR0evcN3zPoAOe/gdJz/temyMaIsX/Y4h9UtFXSACpvHmwbu203W/xVf/+mC68cDIpbjnvu9do1vqj2FC98Em8K7fUaR+qagLRHE4+MYxu3Wo8juHyO3Dbe7+chHu0Hegc3+/4+SPTnuC6ywB5vkdReqXirpwfNm5ZbHZsXnU7xwi3DNiJrd/tgD37Dehy75+x8kP1pFpgkWv+h1D6p+KunCkUhnn3cN7tddBZZITHvh8Fv/6eB7uma9B1/39jtP09TyhmmAkR6/CInWhoi4gZZHQsyf27Vjhdw6R9R79ag5/+3Au7pCXvCOWZds0357sXct0fe88pKIuLCO6tSkNtisv8juHyP88NXIuN7w/G/e052HnQ/2O0zR1HwyZ1AeADhjNQyrqwpJMpp0PjujVQZu/Jae8MHo+170zE/eUZ8A60u84TU/fcyqIlD/vdwxpGCrqAlMeDf3nvAE76OhvyTkvf7eAq96cgXvS47i7Hqsvk1uqdXdo1c0B/ut3FGkYKurC81mrkqJ1fXWPaslBb05YyGWvTocTHjbcnieqrLdEv/OSYDwG6K47eUpFXXjcSNi8Y9jAHXSPaslJ701ZzMUvTYXjHjDc3U5TWW9KIAR9zsoQij7sdxRpOCrqAhQ0zacO2bWd2aI45HcUkVoNn7qU81/4Affouw13j7NU1hvT/QhwnWnATL+jSMNRURemVamM8+4pe3Z2/A4isjGfTl/Gec9OwT3yNsPtd57Kujb9L6ok2vwuv2NIw1JRF6iySOjOYQO6VhuG30lENu6LmSs46+nJuIf903D3+q2+WNbUckfo2Bfgdb+jSMNSUReu0cVFgSUDurX2O4fIJo2ctZLTnpyEe/BNhrvP71TW6/W/OIHLI8DW3mt+ELAG6FzjsVuAc+sll2cuEKnH6W3oBGC7Bpz+xpwLHNvYM1VRFy63tCh4+7CBXXWqluS8sXNXc9JjEwxn0A2GO+BKlXW4BPqc5RIuvncbp5AEngSa6ja1KwA/7tv7FPBOY89URV3ATMN4ft9urUxdqUyaggk/reW4h8cbzv5/MtwDri3sK3DtPsTFSX/Jtt8p61NgFfC7Wp77IzAW+Bb4v1qe/xx4FfgEKAIeB74EvsZbW6+pM/AB8Fn2Z2fgcuCv2eeLgOlAGLgsO8+R2WHAK8aHgeHAZKAvcBSwB/BMdrz1QrVkKQemAr2BHtlprH/s4exw7wAlGxkf4HvgDeBF4Cbg4uzj/wa+yWY+pcZrc3f2tRkDdMk+/hfgO2AicFH2sdqWt1Yq6sJWkXHcl4bstb3Ov5Qm4ftF6zjqoXFGZp/LTffAvxTumvWAK6qINPt3HadyCfAHYOcaj/UGTgX2zf7ZGTi6lnFfAA4BhgErgP2B44AHNhjuduBe4MDs77cAz2bnYeBtRn4P2Ak4DRiY/XM8YGWnMQ8YDNwH/BZ4H6/whuJtGVjvglqyrMPbXP0o3haEodnHioHns/OajleetY0PUArcDAypMa8jgK7AgOyy3QA0zz43JvvafJwdp092+P54r2kPoOcmlvdXVNQFrqQoeMewgV1TxeGA31FEtsj0xRUc+eA4I93/EsM95G+FV9bdDoJI8xXAF3Wc0krgSry11vVdsAswCkgBLvAVXqlsyM7+7A0cibcm+ToQBFrVGK438Ofs8/8PaAusBibgFdS5wGNAL7y1zxF4a/ut8Mqb7LAAP7Hp/d4byzIGb5/8UryCJ7t8X2Z/H4lXkptalvXLW3Ne/bLDfoi3Nr5+7XnDvFY2QwaI4W2277mJ5f0VFbX8YMAn5+67Q2FvSpQmZcbSSgY/8J2R7neB4R5+S2G9dw+7uZJI+Q14RVpX7+KV0LnZv0/HW/ML4q3x7g/MqGU8p8bwL+JtJj4Cb5P46hrDTQeuzT5/EfBa9vFH8b4kRLPD2MAPeGung/C+PEzJDlvbcjr8ur82luVkoBLvym0nZ4cNAbtnfx+QnfemlmXDL4TT8TbnDwIOAl4BZm8k73S8TfZmdr4fb2Z5f0VFLZRFQn+6dNBOydKioN9RRLbY7OVVHHTvGCO121mGe+QdhVHW1pHQbPtlwEv1ONUr+fnI8Sl4pfMN3lrgXOCtTYz7MN5a+Bd4a6bz+GWpXY23P/oLvH3Kk7OPf4G3Fv1U9u+T8NYuv8bbl7szsHAT8x2ZnV7LzWTpjLfZ+uLsn3/y85rvtdn5dcyOu7llqeldvPL/ChiHV84bu4XwRLy17m+y83t+a5fXcF1dR0CgIp569fGv5xx/9ycz1dbSpHRsHuHTy/dywtPecI33rgiQr59phgmXT6iixQ6n4+3XlW03F6+U4z7n2CJaoxYAyiKh6y7cb8d0s6guKypNy8I1cQbdPcaM73KC4R73nwz5ehWf3idDtOVsvIOppICoqGW9Wa7LaxcfsGPK7yAiW2vxujj73zXarN7paMM98dEMRp59tAVCcOg/YkTKL6N+9k0Xuh1oImvToKKWGkojwb+cs+8OmZYl4c0PLJJjllcmGXjnaDO2w2DDPfnJDGYencnQ9xyXUGQ8dT/SW5ogFbXUNM91ef7SQd2Smx9UJPesiiUZcNe3ZmXnAw331GczmHlwyEUoCgfdGCfS7Eq/o4g/VNTyCyVFwb+e2b9Lpk2prlYmTdOaWJp97xxlrusw0HBPf9Eh0MSPu+h/cQbD+Azv6GIpQCpq2dBC13WfvPzgnRN+BxHZVhXxNPveMcpc03Yv1x3ySoZAE92dE2kG+12dItLsar+jiH9U1PIrxUXBv53cr1N657alfkcR2WZVyTQD7vw2sKpVX8M963WHYBPcSjTgihS4bwLT/I4i/lFRS22WhQLGn+46bY+qfD3TRQpDLOkw4I5vzeXNdnPds992CEX9jrTlSttC/0vSFJVd73cU8ZeKWmoVDJgPdWlVPHvIb7YvvGspS16Jpx0G3vltYEnJLq479F2HULHfkbbMMffEwH2Ibb9DluQJFbVsjFMWCZ3556N2TejAMmnqkmmH/e4cGVhY1M11z/2vQzjHd+v0OA522H8V4ZIb/I4i/lNRy6ZMCRjGgzcf3zPmdxCRuko7sP/d3wbmB7Z33WEfOhSV+x2pdtEWcMy91RSVns7P1+CWAqailk2KhgM37rdzm4oDurfxO4pInTkOHHjvqMBsdzvXHTbcIdLM70i/dtSd1QSCT+PdxEFERS2bFSspCp572ym7xSIhvV2k6XMcOPieUYEZqbaue/4nLtEWfkf6WffB0P2wtYRLdTqW/I8+eWVLfBgNBT6+6tDuumKZ5I3B948O/FDdwnEvGOFS3MrvON4508c/GCNcegZQ5XccyR0qatkiZZHQxWfvvUPKalfmdxSRenP0f8YEJq0rc9wLPnUp8Xn3zuG3VBMoehn4zN8gkmtU1LKlloSD5tX3DNmjKmjq5GrJH8c/PDYwdlXUcS/8zKW0nT8hdjwQehxXRVHplf4EkFymopYtFjCNRzo2j353zWBLm8Alr5z62HeBb5cFvbIu365xZx4ugRMfiREuORtY17gzl6ZARS1bwymLhE49e58uVQN2yoF9eiL16Iwnxge+XGS47oWfujTr3HgzPvTmOKHIu8CHjTdTaUpU1LK1lhWHg6c8cEbf6la6b7XkmXOenmB+Ms/xyrp5l4af4U4Hw+5Dqikqv6ThZyZNlYpatsWIcNB84P4z+sR0LXDJNxc+N9H876yk6174KbTcseFm1HJHOOXpasLFxwKrG25G0tSpqGWbFIeDf+7dsfnM3x24U9rvLCL17XcvTjLfsqsc94JPoNVO9T+DcCmc/WYVwaKrga/rfwaST1TUsq1SpZHgUZcO6lap/dWSj/7wyvfmK99XuO4Fn0Abq/4mbBhwypMxilu/TiD8YP1NWPKVilrqYmFxOHjig2f1q+7QLOJ3FpF6d+0bPxgvTFzrusM+grY96mei+1+bYvt9ZlJU+lvArZ+JSj5TUUtdfVYUMP/xxLm/qQoH9HaS/HPD2z8YT45b5brDhkP73nWbmHUEDLiigqKyI4BEvQSUvKdPVqmzolDg351bFH/97xN7x/3OItIQ/v7eNOPR0ctc97wPYLs+2zaR1jvDiY/FCBcfCSyu14CS11TUUh/c0kjwlMG92s/9wyHdU36HEWkI//rANu7/ZgnuOe9Bpz23buSicjj7rRjBosuA0Q0SUPKWilrqS0VpUXDQhft1XXnGXttn/A4j0hDu+GgGd325EPfst6Fz/y0byTDg1GdiRJo/TyD0RMMmlHykopb6tLS4KLj/jUf3qDy0h0/XTBZpYPeO+JFbP1uAe/ab0GXA5kc46MYUnfacSlHp7xo+neQjFbXUt5nRcODQe07fI9avSw7d51ekHj34+Sz++fE83DNfha4HbHzAPkMd+l+8mqKyowDtFpJtoqKWhjC2OBw86anzflPdrU2p31lEGsRjX83hpg/n4A55Ebod/OsBep3kcsT/rSVcMhBY1ugBJW+oqKWhfBgNBy5+5aK9Y+3Ki/zOItIgnh45jz+/Nxv3tOdg58N+fqL74XDs/RWEiw8AZvoWUPKC4bo6314aTiKVuX7JuvgNx9z3dcm6uK42KvnplD07ceuxO2O8fj4kq2DIi1WESw4ExvqdTZo+FbU0NCOWTD8wY2nl0NMf+bYknnL8ziPSII7bYzvuPtEC3IQRLhkMfOF3JskP2vQtDc0tDgd/v3Pb0vdeuWifqrKioN95RBrEgtXVVBOOG+GSi1BJSz3SGrU0FrMqkf7P4rXxs057+NuSlVVJv/OI1Js9u7Tg6WF7xUqKgicCw/3OI/lFRS2NyahOZv61Opa8/KQHRxYvXqsrjkrT95sdWvD0eXvFiouCJwAf+Z1H8o+KWhpdPJW5pjKevumUh78tnrOiyu84Ittsn26teGzonrGSouBxwCd+55H8pKIWX6QyzgWxZObe0x/5NjptcYXfcUS22kl9O7k3H9+zsjgcPBb43O88kr9U1OIbx3FPiSUzTw99Ykx0/PzVfscR2WJXH9Y9NWxg11XF4eCBwDS/80h+U1GL3w6vSqRfv+jZccVf/7jC7ywim1QUNLnztD2qD9i5zY+lkeAh6Ipj0ghU1JILBsaS6Q9ufOuHktfHLzD8DiNSmxbFIZ4etlfVjq1LPyuNBE8Fqv3OJIVBRS25omdVIv3h2xMXtfnrO98XpTJ6X0ru6Nq6hBcu7B9rFg09VBwOXgPoyj3SaFTUkkuaVcRTr85fFdv3vCfHliyrSPidR4S9urbk8XP2rI6GAlcGA+YjfueRwqOillxjVqcyNyZSmT9d+Mx3xWPn6iAz8c8JfTq6/zyhV1VxOHgi8LHfeaQwqaglVx1ency8cuvw6cVPfjM34HcYKSzRUIC/H9czflTvDmuKi4KHAt/7nUkKl4pactmOlYn0h1/Yyzv98dWJUd3QQxpDjw7lPDK0X1XzaPjD0khwGLDO70xS2FTUkuuKK+Ppp5ZXJo4854kxJfNXxfzOI3nKMOD8AV0zfzzMiheFzItNw3jO70wioKKWpsFIpp3LkhnnlhvenBJ5e+IincIl9ap1aZj7hvSJ9e7YfHZpJHgcMNvvTCLrqailKdmzMpF+bdTslW3+9Nrk4lW6A5fUgwO6t+HeIX2qwwHzvmg48Bcg5XcmkZpU1NLURGLJ9L/TGfeia16bHB3+wxK/80gTFQ6Y/PmoXROn7tmpsjgcPAndQ1pylIpamqp9qxLpV76csbzlDW99H9XatWyN3Ts1467T9qhqU1b0VVkkdCawyu9MIhujopamrDiWTN+ScdwLbnrnh8jr4xdq37VsUsuSMH8+ctfqI3u3T0RCgcuzB4zpQ1Bymopa8kG/ynj6hWmL13X846uTdGS4/IppwJn9uzjXHrFLwoCnSoqC1wNr/c4lsiVU1JIvgol05uqM4974yJezw498OTsYS2b8ziQ5oO/2zbnt5N0r25YX2WWR0HnAFL8ziWwNFbXkm64V8dRdjstht344PfLy2J+MtKP3eCFqXRrmxqN7VB/ao128OBz8HfAS2swtTZCKWvJV33XVqfurkund/v7u1JIPvtfR4YUiYBoM3aeLc/VhVsIweLQ4HPwLUOF3LpFtpaKWfHdoRTx1/8I11dvd9M4PpaNm6+DefGUYcGSvDlx3xC6VzYtDP5RFQsOAqX7nEqkrFbUUAhM4rSqRvmvSgjWlf393asn0JVrByheGAUf0as91R+xa2aI4NL8sEvojMBxt5pY8oaKWQhJOZ5yLUxn35k+mLQ3d8ZEdnbtSR4g3VaYBh/dqz7WH71LZsiS8IFvQH6CCljyjopZCVB5PZf7kulw+4afVxoOfzyr9auYKvzPJFgoHTE7o29G98pCdYyXh4NzyaOg64H1U0JKnVNRSyKKO655ZlUjfsLY61frBz2eVvDF+oVGd0mlduai0KMgZ/bd3Lh3ULW4Yxvhm0dBfgC9RQUueU1GLgAEMWlud+nPQNAa+MGZ+4Klv5oYWrqn2O5cAfTo354z+21cfvdt2RspxPiqPhP4KTPQ7l0hjUVGL/NKOVYn0VQHTOO+bH1e4D30xq2Ts3NV+Zyo4rUvDnNi3kzN0ny6xZtHQukgocH8oYD4NLPI7m0hjU1GL1K4s47jnVqcy162uSpa9Om5B8fuTFwVmLa/yO1feCpoGB+7SlrP37lK5V9eWgVTGeassEnoAGIk2b0sBU1GLbJqJd6euMw2D05dXJAKvjVtQ/P7kxYHZK1Ta9aFbm1KG7NU5eeqenTOuy4xmxaF7gFeBSr+zieQCFbXIljOBAVWJ9FmGwanLKxKBV7OlPUelvcVCAYM9u7Tk4F3bpg7v1T7esiScMQzjiWgo8Ahg+51PJNeoqEW2TYBsaZuGcerSdXHztfELij+dtiwwbck69N/ql9qXRxhkteHwXu0r9t6xVTiRysyJhoOvhoPme8B3gON3RpFcpaIWqbsAMLAqkT7Tcd2jTMNoOWbOqtSn05eVjZy1klnLC28LbtA06NulBQfv0jZ1RK8O8bblRWYi7YxoFg29infVsOV+ZxRpKlTUIvWvI3BgRTx1lGkYh2Rct2TCvNWpb2atLBs3b7Xx/cK1JNL5swJpGtC1dQk9t2vG7p2bpfp1aRnbpX1ZJJF25kdDgfVrzWMAnaAusg1U1CINrwuwT1UiPSiVcQ4sCQe7zl5RFft+4drw9CUV0dkrKpm9vIqfVsXI9VtyBkyDndqU0qtjObt3bp7s16VF9U5tS4tTaXd1ynEmNIuEvjRNYxwwDtDl3kTqgYpapPGVAP2AnrFkunc85ewRDpjdIiGz1fLKRGz28ip32uJ10ZnLKkOzl1cyZ0UVKyqTjRYuGgqwXfMInVoU07F5lM4tizM7ti6J7dimxO3SqiQaT2eWO447rjwa+tI0jPHABEAnm4s0EBW1SO6IAN0Ay3Vda1083cdx3Z7RUKBLOGAWx9OZRGUina6IpzNrYynWVKeMVVXJ4MrKRHhtdSq4tjrFuuoUyYxDKGASNE1CQYNwwCQYMAkFDELZx0Km6YaDZqY0Ekx3aBZNtisvcluXFpnNi0ORgGEY1anMilTG/SloGjPLIsFphmHMA2YDk9G9nUUalYpapGkIAc2AFkDzDX8m007reCrTNu24bYCIAQkMEiYkDcNImKaRCBhGtWkSD5lm3DSNJJACqoClwJIafyrQBUZEcoaKWkREJIeZfgcQERGRjVNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5DAVtYiISA5TUYuIiOQwFbWIiEgOU1GLiIjkMBW1iIhIDlNRi4iI5LD/DyrFylGmLqggAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pie_chart('relevent_experience', title='Pie Chart For Relevent Experience')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "contained-consumption",
   "metadata": {},
   "source": [
    "-----------------\n",
    "1. Enrolled University"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "through-desert",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pie_chart('enrolled_university', title='Pie Chart For Enrolled University')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eight-convenience",
   "metadata": {},
   "source": [
    "_________\n",
    "2. Education Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "adequate-premium",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pie_chart('education_level', title='Pie Chart For Education Level')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "major-polls",
   "metadata": {},
   "source": [
    "___________\n",
    "1. Major Discipline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "spectacular-willow",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_bar_graph('major_discipline')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "finite-picture",
   "metadata": {},
   "source": [
    "Most of the Candidates are from STEM. That is their major discipline was in one of the Following:\n",
    "\n",
    "1. Science\n",
    "2. Technology\n",
    "3. Engineering\n",
    "4. Mathematics\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "informational-agreement",
   "metadata": {},
   "source": [
    "____________\n",
    "1. Company Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "continuing-portugal",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "order = ['<10', '10/49', '50-99', '100-500', '500-999', '1000-4999', '5000-9999', '10000+']\n",
    "plot_bar_graph('company_size',order=order)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marine-complement",
   "metadata": {},
   "source": [
    "-------------\n",
    "1. Company Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "instrumental-observer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,5))\n",
    "plot_bar_graph('company_type')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "heavy-neighbor",
   "metadata": {},
   "source": [
    "-----------\n",
    "1. How many Jobs Candidates Worked before joining the current company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cardiovascular-structure",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,5))\n",
    "order = ['never', '1', '2', '3', '4', '>4']\n",
    "plot_bar_graph('last_new_job', order=order)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "capital-dispatch",
   "metadata": {},
   "source": [
    "-----------\n",
    "1. Let's play a Histogram to see the Distribution of the Training Hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "likely-warren",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='training_hours'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.distplot(aug_train['training_hours'], kde=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "consistent-neighbor",
   "metadata": {},
   "source": [
    "The Graph reveals the most of the Candidates train for 20 to 50 Hours"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "underlying-citation",
   "metadata": {},
   "source": [
    "---------\n",
    "Before moving on to the prediction part we will check relation between few features and Training Hours, as peaple looking for a Job Change tend to Train for longer hours.\n",
    "\n",
    "1. Relevent Experience vs Training Hours\n",
    "2. Education Level vs Training Hours\n",
    "3. Major Discipline vs Training Hours\n",
    "4. Company Size vs Training Hours\n",
    "5. Company Type vs Training Hours\n",
    "6. Last New Job vs Training Hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "treated-southwest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(3,2, figsize=(16,12))\n",
    "\n",
    "sns.scatterplot('relevent_experience', 'training_hours', data=aug_train, hue='target', ax=axes[0,0])\n",
    "sns.scatterplot('education_level', 'training_hours', data=aug_train, hue='target', ax=axes[0,1])\n",
    "sns.scatterplot('major_discipline', 'training_hours', data=aug_train, hue='target', ax=axes[1,0])\n",
    "sns.scatterplot('company_size', 'training_hours', data=aug_train, hue='target', ax=axes[1,1])\n",
    "sns.scatterplot('company_type', 'training_hours', data=aug_train, hue='target', ax=axes[2,0])\n",
    "sns.scatterplot('last_new_job', 'training_hours', data=aug_train, hue='target', ax=axes[2,1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "married-championship",
   "metadata": {},
   "source": [
    "--------------\n",
    "**5. Let's get to the prediction part**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exclusive-norman",
   "metadata": {},
   "source": [
    "1. Data preprocessing Phase\n",
    "* Using pandas get_dummies() to convert the Categorical Data to Numerical Features\n",
    "* Then Removing the Unnecessary Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "inside-drilling",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['enrollee_id', 'city', 'city_development_index', 'gender',\n",
       "       'relevent_experience', 'enrolled_university', 'education_level',\n",
       "       'major_discipline', 'experience', 'company_size', 'company_type',\n",
       "       'last_new_job', 'training_hours', 'target'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "active-amino",
   "metadata": {},
   "outputs": [
    {
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       "       city_1  city_10  city_100  city_101  city_102  city_103  city_104  \\\n",
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       "\n",
       "       city_91  city_93  city_94  city_97  city_98  city_99  \n",
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     "execution_count": 36,
     "metadata": {},
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    }
   ],
   "source": [
    "pd.get_dummies(aug_train['city'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "referenced-vertex",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_columns = ['city', 'gender', 'relevent_experience', 'enrolled_university', 'education_level',\n",
    "                   'major_discipline', 'experience', 'company_size', 'company_type', 'last_new_job']\n",
    "aug_train_dummies_df = []\n",
    "\n",
    "for col in list_of_columns:\n",
    "    dummy_train_df = pd.get_dummies(aug_train[col])\n",
    "    aug_train_dummies_df.append(dummy_train_df)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "departmental-coverage",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_columns.append('enrollee_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "lasting-victory",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "       city_development_index  training_hours  target\n",
       "1                       0.776              47     0.0\n",
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       "7                       0.762              18     1.0\n",
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       "19155                   0.920              44     0.0\n",
       "\n",
       "[8955 rows x 3 columns]"
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     "execution_count": 42,
     "metadata": {},
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   ],
   "source": [
    "aug_train.drop(columns=list_of_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "strong-tongue",
   "metadata": {},
   "outputs": [
    {
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       " 11          0        0         0         0         0         1         0   \n",
       " ...       ...      ...       ...       ...       ...       ...       ...   \n",
       " 19147       0        0         0         0         0         0         0   \n",
       " 19149       0        0         0         0         0         1         0   \n",
       " 19150       0        0         0         0         0         0         0   \n",
       " 19152       0        0         0         0         0         1         0   \n",
       " 19155       0        0         0         0         0         1         0   \n",
       " \n",
       "        city_105  city_106  city_107  ...  city_84  city_89  city_9  city_90  \\\n",
       " 1             0         0         0  ...        0        0       0        0   \n",
       " 4             0         0         0  ...        0        0       0        0   \n",
       " 7             0         0         0  ...        0        0       0        0   \n",
       " 8             0         0         0  ...        0        0       0        0   \n",
       " 11            0         0         0  ...        0        0       0        0   \n",
       " ...         ...       ...       ...  ...      ...      ...     ...      ...   \n",
       " 19147         0         0         0  ...        0        0       0        0   \n",
       " 19149         0         0         0  ...        0        0       0        0   \n",
       " 19150         0         0         0  ...        0        0       0        0   \n",
       " 19152         0         0         0  ...        0        0       0        0   \n",
       " 19155         0         0         0  ...        0        0       0        0   \n",
       " \n",
       "        city_91  city_93  city_94  city_97  city_98  city_99  \n",
       " 1            0        0        0        0        0        0  \n",
       " 4            0        0        0        0        0        0  \n",
       " 7            0        0        0        0        0        0  \n",
       " 8            0        0        0        0        0        0  \n",
       " 11           0        0        0        0        0        0  \n",
       " ...        ...      ...      ...      ...      ...      ...  \n",
       " 19147        0        0        0        0        0        0  \n",
       " 19149        0        0        0        0        0        0  \n",
       " 19150        0        0        0        0        0        0  \n",
       " 19152        0        0        0        0        0        0  \n",
       " 19155        0        0        0        0        0        0  \n",
       " \n",
       " [8955 rows x 116 columns],\n",
       "        Female  Male  Other\n",
       " 1           0     1      0\n",
       " 4           0     1      0\n",
       " 7           0     1      0\n",
       " 8           0     1      0\n",
       " 11          0     1      0\n",
       " ...       ...   ...    ...\n",
       " 19147       0     1      0\n",
       " 19149       0     1      0\n",
       " 19150       1     0      0\n",
       " 19152       1     0      0\n",
       " 19155       0     1      0\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Has relevent experience  No relevent experience\n",
       " 1                            0                       1\n",
       " 4                            1                       0\n",
       " 7                            1                       0\n",
       " 8                            1                       0\n",
       " 11                           1                       0\n",
       " ...                        ...                     ...\n",
       " 19147                        0                       1\n",
       " 19149                        1                       0\n",
       " 19150                        1                       0\n",
       " 19152                        1                       0\n",
       " 19155                        1                       0\n",
       " \n",
       " [8955 rows x 2 columns],\n",
       "        Full time course  Part time course  no_enrollment\n",
       " 1                     0                 0              1\n",
       " 4                     0                 0              1\n",
       " 7                     0                 0              1\n",
       " 8                     0                 0              1\n",
       " 11                    0                 0              1\n",
       " ...                 ...               ...            ...\n",
       " 19147                 1                 0              0\n",
       " 19149                 0                 0              1\n",
       " 19150                 0                 0              1\n",
       " 19152                 0                 0              1\n",
       " 19155                 0                 0              1\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Graduate  Masters  Phd\n",
       " 1             1        0    0\n",
       " 4             0        1    0\n",
       " 7             1        0    0\n",
       " 8             1        0    0\n",
       " 11            1        0    0\n",
       " ...         ...      ...  ...\n",
       " 19147         1        0    0\n",
       " 19149         0        1    0\n",
       " 19150         1        0    0\n",
       " 19152         1        0    0\n",
       " 19155         1        0    0\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Arts  Business Degree  Humanities  No Major  Other  STEM\n",
       " 1         0                0           0         0      0     1\n",
       " 4         0                0           0         0      0     1\n",
       " 7         0                0           0         0      0     1\n",
       " 8         0                0           0         0      0     1\n",
       " 11        0                0           0         0      0     1\n",
       " ...     ...              ...         ...       ...    ...   ...\n",
       " 19147     0                0           0         0      0     1\n",
       " 19149     0                0           0         0      0     1\n",
       " 19150     0                0           0         0      0     1\n",
       " 19152     0                0           1         0      0     0\n",
       " 19155     0                0           0         0      0     1\n",
       " \n",
       " [8955 rows x 6 columns],\n",
       "        1  10  11  12  13  14  15  16  17  18  ...  20  3  4  5  6  7  8  9  \\\n",
       " 1      0   0   0   0   0   0   1   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 4      0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 7      0   0   0   0   1   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 8      0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  1  0  0   \n",
       " 11     0   0   0   0   0   0   0   0   0   0  ...   0  0  0  1  0  0  0  0   \n",
       " ...   ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ...  .. .. .. .. .. .. .. ..   \n",
       " 19147  1   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 19149  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  1   \n",
       " 19150  0   1   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 19152  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  1  0  0   \n",
       " 19155  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " \n",
       "        <1  >20  \n",
       " 1       0    0  \n",
       " 4       0    1  \n",
       " 7       0    0  \n",
       " 8       0    0  \n",
       " 11      0    0  \n",
       " ...    ..  ...  \n",
       " 19147   0    0  \n",
       " 19149   0    0  \n",
       " 19150   0    0  \n",
       " 19152   0    0  \n",
       " 19155   0    1  \n",
       " \n",
       " [8955 rows x 22 columns],\n",
       "        10/49  100-500  1000-4999  10000+  50-99  500-999  5000-9999  <10\n",
       " 1          0        0          0       0      1        0          0    0\n",
       " 4          0        0          0       0      1        0          0    0\n",
       " 7          0        0          0       0      0        0          0    1\n",
       " 8          0        0          0       0      1        0          0    0\n",
       " 11         0        0          0       0      0        0          1    0\n",
       " ...      ...      ...        ...     ...    ...      ...        ...  ...\n",
       " 19147      0        1          0       0      0        0          0    0\n",
       " 19149      0        0          0       0      1        0          0    0\n",
       " 19150      0        1          0       0      0        0          0    0\n",
       " 19152      1        0          0       0      0        0          0    0\n",
       " 19155      0        0          0       0      1        0          0    0\n",
       " \n",
       " [8955 rows x 8 columns],\n",
       "        Early Stage Startup  Funded Startup  NGO  Other  Public Sector  Pvt Ltd\n",
       " 1                        0               0    0      0              0        1\n",
       " 4                        0               1    0      0              0        0\n",
       " 7                        0               0    0      0              0        1\n",
       " 8                        0               0    0      0              0        1\n",
       " 11                       0               0    0      0              0        1\n",
       " ...                    ...             ...  ...    ...            ...      ...\n",
       " 19147                    0               0    0      0              0        1\n",
       " 19149                    0               0    0      0              0        1\n",
       " 19150                    0               0    0      0              1        0\n",
       " 19152                    0               1    0      0              0        0\n",
       " 19155                    0               0    0      0              0        1\n",
       " \n",
       " [8955 rows x 6 columns],\n",
       "        1  2  3  4  >4  never\n",
       " 1      0  0  0  0   1      0\n",
       " 4      0  0  0  1   0      0\n",
       " 7      0  0  0  0   1      0\n",
       " 8      1  0  0  0   0      0\n",
       " 11     1  0  0  0   0      0\n",
       " ...   .. .. .. ..  ..    ...\n",
       " 19147  1  0  0  0   0      0\n",
       " 19149  1  0  0  0   0      0\n",
       " 19150  0  0  1  0   0      0\n",
       " 19152  1  0  0  0   0      0\n",
       " 19155  0  0  0  1   0      0\n",
       " \n",
       " [8955 rows x 6 columns]]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train_dummies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "assisted-recycling",
   "metadata": {},
   "outputs": [],
   "source": [
    "aug_train_dummies_df.insert(0, aug_train.drop(columns=list_of_columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "bound-swiss",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[       city_development_index  training_hours  target\n",
       " 1                       0.776              47     0.0\n",
       " 4                       0.767               8     0.0\n",
       " 7                       0.762              18     1.0\n",
       " 8                       0.920              46     1.0\n",
       " 11                      0.920             108     0.0\n",
       " ...                       ...             ...     ...\n",
       " 19147                   0.624              52     1.0\n",
       " 19149                   0.920              36     1.0\n",
       " 19150                   0.920              23     0.0\n",
       " 19152                   0.920              25     0.0\n",
       " 19155                   0.920              44     0.0\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        city_1  city_10  city_100  city_101  city_102  city_103  city_104  \\\n",
       " 1           0        0         0         0         0         0         0   \n",
       " 4           0        0         0         0         0         0         0   \n",
       " 7           0        0         0         0         0         0         0   \n",
       " 8           0        0         0         0         0         1         0   \n",
       " 11          0        0         0         0         0         1         0   \n",
       " ...       ...      ...       ...       ...       ...       ...       ...   \n",
       " 19147       0        0         0         0         0         0         0   \n",
       " 19149       0        0         0         0         0         1         0   \n",
       " 19150       0        0         0         0         0         0         0   \n",
       " 19152       0        0         0         0         0         1         0   \n",
       " 19155       0        0         0         0         0         1         0   \n",
       " \n",
       "        city_105  city_106  city_107  ...  city_84  city_89  city_9  city_90  \\\n",
       " 1             0         0         0  ...        0        0       0        0   \n",
       " 4             0         0         0  ...        0        0       0        0   \n",
       " 7             0         0         0  ...        0        0       0        0   \n",
       " 8             0         0         0  ...        0        0       0        0   \n",
       " 11            0         0         0  ...        0        0       0        0   \n",
       " ...         ...       ...       ...  ...      ...      ...     ...      ...   \n",
       " 19147         0         0         0  ...        0        0       0        0   \n",
       " 19149         0         0         0  ...        0        0       0        0   \n",
       " 19150         0         0         0  ...        0        0       0        0   \n",
       " 19152         0         0         0  ...        0        0       0        0   \n",
       " 19155         0         0         0  ...        0        0       0        0   \n",
       " \n",
       "        city_91  city_93  city_94  city_97  city_98  city_99  \n",
       " 1            0        0        0        0        0        0  \n",
       " 4            0        0        0        0        0        0  \n",
       " 7            0        0        0        0        0        0  \n",
       " 8            0        0        0        0        0        0  \n",
       " 11           0        0        0        0        0        0  \n",
       " ...        ...      ...      ...      ...      ...      ...  \n",
       " 19147        0        0        0        0        0        0  \n",
       " 19149        0        0        0        0        0        0  \n",
       " 19150        0        0        0        0        0        0  \n",
       " 19152        0        0        0        0        0        0  \n",
       " 19155        0        0        0        0        0        0  \n",
       " \n",
       " [8955 rows x 116 columns],\n",
       "        Female  Male  Other\n",
       " 1           0     1      0\n",
       " 4           0     1      0\n",
       " 7           0     1      0\n",
       " 8           0     1      0\n",
       " 11          0     1      0\n",
       " ...       ...   ...    ...\n",
       " 19147       0     1      0\n",
       " 19149       0     1      0\n",
       " 19150       1     0      0\n",
       " 19152       1     0      0\n",
       " 19155       0     1      0\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Has relevent experience  No relevent experience\n",
       " 1                            0                       1\n",
       " 4                            1                       0\n",
       " 7                            1                       0\n",
       " 8                            1                       0\n",
       " 11                           1                       0\n",
       " ...                        ...                     ...\n",
       " 19147                        0                       1\n",
       " 19149                        1                       0\n",
       " 19150                        1                       0\n",
       " 19152                        1                       0\n",
       " 19155                        1                       0\n",
       " \n",
       " [8955 rows x 2 columns],\n",
       "        Full time course  Part time course  no_enrollment\n",
       " 1                     0                 0              1\n",
       " 4                     0                 0              1\n",
       " 7                     0                 0              1\n",
       " 8                     0                 0              1\n",
       " 11                    0                 0              1\n",
       " ...                 ...               ...            ...\n",
       " 19147                 1                 0              0\n",
       " 19149                 0                 0              1\n",
       " 19150                 0                 0              1\n",
       " 19152                 0                 0              1\n",
       " 19155                 0                 0              1\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Graduate  Masters  Phd\n",
       " 1             1        0    0\n",
       " 4             0        1    0\n",
       " 7             1        0    0\n",
       " 8             1        0    0\n",
       " 11            1        0    0\n",
       " ...         ...      ...  ...\n",
       " 19147         1        0    0\n",
       " 19149         0        1    0\n",
       " 19150         1        0    0\n",
       " 19152         1        0    0\n",
       " 19155         1        0    0\n",
       " \n",
       " [8955 rows x 3 columns],\n",
       "        Arts  Business Degree  Humanities  No Major  Other  STEM\n",
       " 1         0                0           0         0      0     1\n",
       " 4         0                0           0         0      0     1\n",
       " 7         0                0           0         0      0     1\n",
       " 8         0                0           0         0      0     1\n",
       " 11        0                0           0         0      0     1\n",
       " ...     ...              ...         ...       ...    ...   ...\n",
       " 19147     0                0           0         0      0     1\n",
       " 19149     0                0           0         0      0     1\n",
       " 19150     0                0           0         0      0     1\n",
       " 19152     0                0           1         0      0     0\n",
       " 19155     0                0           0         0      0     1\n",
       " \n",
       " [8955 rows x 6 columns],\n",
       "        1  10  11  12  13  14  15  16  17  18  ...  20  3  4  5  6  7  8  9  \\\n",
       " 1      0   0   0   0   0   0   1   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 4      0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 7      0   0   0   0   1   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 8      0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  1  0  0   \n",
       " 11     0   0   0   0   0   0   0   0   0   0  ...   0  0  0  1  0  0  0  0   \n",
       " ...   ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ...  .. .. .. .. .. .. .. ..   \n",
       " 19147  1   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 19149  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  1   \n",
       " 19150  0   1   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " 19152  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  1  0  0   \n",
       " 19155  0   0   0   0   0   0   0   0   0   0  ...   0  0  0  0  0  0  0  0   \n",
       " \n",
       "        <1  >20  \n",
       " 1       0    0  \n",
       " 4       0    1  \n",
       " 7       0    0  \n",
       " 8       0    0  \n",
       " 11      0    0  \n",
       " ...    ..  ...  \n",
       " 19147   0    0  \n",
       " 19149   0    0  \n",
       " 19150   0    0  \n",
       " 19152   0    0  \n",
       " 19155   0    1  \n",
       " \n",
       " [8955 rows x 22 columns],\n",
       "        10/49  100-500  1000-4999  10000+  50-99  500-999  5000-9999  <10\n",
       " 1          0        0          0       0      1        0          0    0\n",
       " 4          0        0          0       0      1        0          0    0\n",
       " 7          0        0          0       0      0        0          0    1\n",
       " 8          0        0          0       0      1        0          0    0\n",
       " 11         0        0          0       0      0        0          1    0\n",
       " ...      ...      ...        ...     ...    ...      ...        ...  ...\n",
       " 19147      0        1          0       0      0        0          0    0\n",
       " 19149      0        0          0       0      1        0          0    0\n",
       " 19150      0        1          0       0      0        0          0    0\n",
       " 19152      1        0          0       0      0        0          0    0\n",
       " 19155      0        0          0       0      1        0          0    0\n",
       " \n",
       " [8955 rows x 8 columns],\n",
       "        Early Stage Startup  Funded Startup  NGO  Other  Public Sector  Pvt Ltd\n",
       " 1                        0               0    0      0              0        1\n",
       " 4                        0               1    0      0              0        0\n",
       " 7                        0               0    0      0              0        1\n",
       " 8                        0               0    0      0              0        1\n",
       " 11                       0               0    0      0              0        1\n",
       " ...                    ...             ...  ...    ...            ...      ...\n",
       " 19147                    0               0    0      0              0        1\n",
       " 19149                    0               0    0      0              0        1\n",
       " 19150                    0               0    0      0              1        0\n",
       " 19152                    0               1    0      0              0        0\n",
       " 19155                    0               0    0      0              0        1\n",
       " \n",
       " [8955 rows x 6 columns],\n",
       "        1  2  3  4  >4  never\n",
       " 1      0  0  0  0   1      0\n",
       " 4      0  0  0  1   0      0\n",
       " 7      0  0  0  0   1      0\n",
       " 8      1  0  0  0   0      0\n",
       " 11     1  0  0  0   0      0\n",
       " ...   .. .. .. ..  ..    ...\n",
       " 19147  1  0  0  0   0      0\n",
       " 19149  1  0  0  0   0      0\n",
       " 19150  0  0  1  0   0      0\n",
       " 19152  1  0  0  0   0      0\n",
       " 19155  0  0  0  1   0      0\n",
       " \n",
       " [8955 rows x 6 columns]]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train_dummies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "bronze-auction",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(aug_train_dummies_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "governmental-constant",
   "metadata": {},
   "outputs": [],
   "source": [
    "aug_train = pd.concat(aug_train_dummies_df, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "humanitarian-accountability",
   "metadata": {},
   "source": [
    "1. Split the Data in to Training(70%) and Tesing(30%) and train the model and Check it accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "demonstrated-theme",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "visible-alabama",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.776, 47.   ,  0.   , ...,  0.   ,  1.   ,  0.   ],\n",
       "       [ 0.767,  8.   ,  0.   , ...,  1.   ,  0.   ,  0.   ],\n",
       "       [ 0.762, 18.   ,  0.   , ...,  0.   ,  1.   ,  0.   ],\n",
       "       ...,\n",
       "       [ 0.92 , 23.   ,  0.   , ...,  0.   ,  0.   ,  0.   ],\n",
       "       [ 0.92 , 25.   ,  0.   , ...,  0.   ,  0.   ,  0.   ],\n",
       "       [ 0.92 , 44.   ,  0.   , ...,  1.   ,  0.   ,  0.   ]])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aug_train.dropna().drop(columns=['target']).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "fossil-roller",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = aug_train.dropna().drop(columns=['target']).values\n",
    "y = aug_train.dropna()['target'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "equal-hello",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_valid, y_train, y_valid = train_test_split(X,y,test_size=0.3, random_state=80)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "speaking-sullivan",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the Model is 0.8652772608857462\n"
     ]
    }
   ],
   "source": [
    "pipeline = make_pipeline(StandardScaler(), SVC(kernel='sigmoid'))\n",
    "pipeline.fit(X_train, y_train)\n",
    "prediction= pipeline.predict(X_valid)\n",
    "\n",
    "print(f'Accuracy of the Model is {accuracy_score(y_valid, prediction)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "level-complexity",
   "metadata": {},
   "source": [
    "1. Using Seaborn HeatMap we will plot Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "complicated-ethernet",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "conf_matrix = confusion_matrix(y_valid, prediction)\n",
    "sns.heatmap(conf_matrix, linewidths=1, cmap=cmap, annot=True)\n",
    "plt.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "figured-artwork",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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