15th Feb (2).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7cb00bec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "368"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_titanic[df_titanic['Pclass']==2]['Pclass'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9dadb067",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Cabin Embarked  \n",
       "0        0         A/5 21171   7.2500   NaN        S  \n",
       "1        0          PC 17599  71.2833   C85        C  \n",
       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3        0            113803  53.1000  C123        S  \n",
       "4        0            373450   8.0500   NaN        S  \n",
       "..     ...               ...      ...   ...      ...  \n",
       "886      0            211536  13.0000   NaN        S  \n",
       "887      0            112053  30.0000   B42        S  \n",
       "888      2        W./C. 6607  23.4500   NaN        S  \n",
       "889      0            111369  30.0000  C148        C  \n",
       "890      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 12 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df_titanic=pd.read_csv(\"D:\\\\New folder\\\\titanic_train.csv\")\n",
    "df_titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a8878f37",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "class1=df_titanic[df_titanic['Pclass']==1]['Age'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2ad604c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "class2=df_titanic[df_titanic['Pclass']==2]['Age'].dropna()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "15b26a80",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "class3=df_titanic[df_titanic['Pclass']==3]['Age'].dropna()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8c5f5cce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x25d988660d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98866c90>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98872d90>,\n",
       "  <matplotlib.lines.Line2D at 0x25d988738d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98883b50>,\n",
       "  <matplotlib.lines.Line2D at 0x25d988846d0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x25d988676d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98870090>,\n",
       "  <matplotlib.lines.Line2D at 0x25d988804d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98881050>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98885190>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98885d10>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x25d98865350>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98872290>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98883090>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x25d98870c90>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98881990>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98886810>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x25d988711d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d988823d0>,\n",
       "  <matplotlib.lines.Line2D at 0x25d98887290>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1=[class1,class2,class3]\n",
    "plt.boxplot(l1,labels=['class1','class2','class3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7d0d973b",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name  Gender   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Cabin Embarked  \n",
       "0        0         A/5 21171   7.2500   NaN        S  \n",
       "1        0          PC 17599  71.2833   C85        C  \n",
       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3        0            113803  53.1000  C123        S  \n",
       "4        0            373450   8.0500   NaN        S  \n",
       "..     ...               ...      ...   ...      ...  \n",
       "886      0            211536  13.0000   NaN        S  \n",
       "887      0            112053  30.0000   B42        S  \n",
       "888      2        W./C. 6607  23.4500   NaN        S  \n",
       "889      0            111369  30.0000  C148        C  \n",
       "890      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 12 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df_titanic(columns=('Sex','Gender'),Implace=True)\n",
    "%matplotlib inline\n",
    "df_titanic.rename(columns={\"Sex\":'Gender'},inplace=True)\n",
    "df_titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "46806710",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0\n",
       "1      1\n",
       "2      1\n",
       "3      1\n",
       "4      0\n",
       "      ..\n",
       "886    0\n",
       "887    1\n",
       "888    1\n",
       "889    0\n",
       "890    0\n",
       "Name: Gender, Length: 891, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df_titanic['Gender'].replace(['female','male'],[1,0])\n",
    "#or df['Gender']=df['Gender']map({'male':0,'female':1})\n",
    "#or df = df_titanic['Gender'].replace({'female':1,\"male\":0}) \n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ca949a1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#male_survived=((df['Survived']==1)&(df['Sex'==0])).sum()\n",
    "#\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c1d221a8",
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "tips=sns.load_dataset('tips')\n",
    "tips.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "73f4694d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_10852\\4250775509.py:4: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(tips['total_bill'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='total_bill', ylabel='Density'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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8GAAAmM60cOVwOJSTk6OVK1d2u75y5UrNnDmzx9fMmDHjmPErVqzQ1KlTFRIS0uNrDMPQli1blJqa6pvCAfi1TflVkqSJ6dFyhfj3ocFfZObQeI1IjlBjq1v/2nDY7HIAAMAXMHVZ4MKFC/XUU09p2bJlys3N1W233aaCggItWLBAUsdyvWuuucY7fsGCBcrPz9fChQuVm5urZcuWaenSpbr99tu9Y371q1/prbfe0sGDB7VlyxbdeOON2rJli/c9AQxczW1u7SiukSTlZAb2rJXUsdz5upkdhwr/fU2e3BwqDACAXzP1VM358+eroqJC9913n0pKSjRu3DgtX75cWVkdZ7yUlJR0O/MqOztby5cv12233abHHntMaWlpeuSRRzRv3jzvmOrqan3ve99TaWmpoqOjNXnyZH3wwQc644wz+v3zAehf24tq1OY2lBDhVEZcmNnl+MTlk9P0+//uVkFlo97bXaYLxvS8bBoAAJjPYnBC5TFqa2sVHR2tmpoa9l8BJ+Gf63o++Lu/PbHqgAoqGzV3bIrOGZFodjnHuHp6Zq9et2h5rv7ywUHNGhavf9x0po+rAgAAJ3Iq2cD0boEA4AvldS0qqGyURdLkjBizy/Gp78zIktUifbS/QofKG8wuBwAAHAfhCsCAsLGgo5HFiORIRYX23OAmUKXHhnln4l5Yz1ERAAD4K8IVgIDnMQxt7gxXUwK8/frxzJ/WsaTw3xsPq83tMbkaAADQE8IVgIC3v6xetc3tCg2xaXRKpNnl9IkvjU5SQoRT5fUteie3zOxyAABADwhXAALexs6zrSZlxMhuG5h/rYXYrPpaTrok6fn1/tFABAAAdDcwvwsBEDRa2z3aXVorSZqcGWNuMX1s/rQMSdKqvUdVXN1kcjUAAODzCFcAAtqeI3VqcxuKC3doUEyo2eX0qeyEcJ05JE6GIb24gcYWAAD4G8IVgIC2/XC1JGn8oGhZLBZzi+kH3zyjo7HFvzYcltvDMYUAAPgTwhWAgNXS7taeI3WSOsJVMJg7NkXRoSEqqm7S6n1HzS4HAAB8BuEKQMDaXdqxJDA+3KHUaJfZ5fQLV4hNV0weJEn618bDJlcDAAA+i3AFIGBtP1wjKXiWBHbp6hq4ctcR1Ta3mVwNAADoQrgCEJBa2tza27UkMD04lgR2GZsWpeFJEWpt9+jN7SVmlwMAADoRrgAEpNzSOrV7DCVEOJUSFRxLArtYLBZdMaVjaeDLm4pMrgYAAHQhXAEISMHWJfDzLp80SBaLtO5QpQ5XNZpdDgAAEOEKQABqbnNrb1m9pOBbEtglLSZUZ2bHS5Je3czsFQAA/oBwBSDg7Cmtk9tjKDHCqeRIp9nlmMa7NHBzkQyDM68AADAb4QpAwMktrZUkjUmLCsolgV0uHpciV4hVB482aFtn50QAAGAewhWAgNLu8Xi7BI5OiTS5GnNFukI0Z0yKJOkVlgYCAGA6whWAgJJX3qjmNo/CnXalx4WZXY7pupYGvr61WG1uj8nVAAAQ3AhXAAJK15LAUSmRsgbxksAus4clKCHCocqGVn20v9zscgAACGp2swsAgJNlGIZ2l3SEq9EpUSZXc+r+ua6gT953WFKEyusr9cg7+1Rc3XzSr7t6emaf1AMAQLBi5gpAwDhS26KqxjbZrRYNS4owuxy/MWFQjCRpZ3EtSwMBADAR4QpAwOhaEjg0MUIOO399dcmMD1N0aIha2j3a19nsAwAA9D++OwEQMHK7lgSmBt6SwL5ktVg0flDHYcpbackOAIBpCFcAAkJdc5sOVzVJ6mhmge4mpHeEq92ltWptZ2kgAABmIFwBCAi7SzuWu6XHhioqNMTkavzPoJhQxYU71OY2vMsnAQBA/yJcAQgIXUsCRwVgl8D+YLFYvLNX21gaCACAKQhXAPxeu9ujA0frJbEk8EQmpMdIkvYeqVNTq9vcYgAACEKEKwB+L6+iUW1uQxFOu1KiXWaX47dSolxKinTK7TG0q4SlgQAA9DfCFQC/t6+sY7/V8KQIWS0Wk6vxb11LA7cXVZtbCAAAQYhwBcDv7TvSsSRweDJLAr/IuLSOcHWgrIGlgQAA9DPCFQC/VtvcptLaZlkkDUuKMLscv5cU5VJipFNuw9BuugYCANCvCFcA/Nr+zlmrtJhQRTjtJlcTGMaldXRU3FlMuAIAoD8RrgD4tb1d+62SmbU6WWM7lwbuPVKnlnaWBgIA0F8IVwD8lscwtL+sc79VEvutTlZqtEtx4Q61ewzt7Zz5AwAAfY9wBcBvFVc3qbHVLafdqsy4MLPLCRgWi0VjO5cG7ijiQGEAAPoL4QqA3+qadRmaGCGblRbsp6Kra+CeI3Vqc3tMrgYAgOBAuALgt/ax36rXBsWGKjo0RK3tHu/SSgAA0LcIVwD8UnObW4WVjZLYb9UbVotFY1gaCABAvyJcAfBLB4/Wy2NICREOxYU7zC4nIHUtDcwtrVW7h6WBAAD0NcIVAL+0/2iDpI79VuidrPgwhTvtam7z6GDnv08AANB3CFcA/NLBo582s0DvWC0WjU3tOlCYpYEAAPQ1whUAv1PX3KayuhZZJA1JCDe7nIA2dlBHuNpVXCuPYZhcDQAAAxvhCoDfOVjesYQtNdqlMKfd5GoC25CECIWG2NTQ6lZeBUsDAQDoS4QrAH6na0ngEJYEnjab1aLRXUsDi2pNrgYAgIGNcAXA7xzobL4wJJElgb4wLu3TfVcsDQQAoO8QrgD4larGVlU2tMpqkQbHE658YVhShJx2q2qb23W4qsnscgAAGLAIVwD8SlfL8EExoXKF2EyuZmCw26wamdJxEPNODhQGAKDPEK4A+BVasPeNrgOFdxTXyGBpIAAAfYJwBcBvGIahAzSz6BMjkiMVYrOoqrFNJTXNZpcDAMCARLgC4Dcq6ltV29wum9WirPgws8sZUBx2q0YkdywN3MGBwgAA9AnCFQC/caC8Y9YqMy5MITb+evK1sWmfHigMAAB8j+9eAPiNg7Rg71Mjk6NktUhldS0qr2sxuxwAAAYcwhUAv2AYxqeHByew36ovhDps3kYhu0qYvQIAwNcIVwD8wtH6FjW0umW3WpQRG2p2OQPW6NTOpYGEKwAAfI5wBcAv5Jc3SpIy4sJkZ79Vn+kKVwWVjSqrpWsgAAC+xHcwAPzCoYqO/VaD49lv1ZeiQ0O8M4Mrc4+YXA0AAAML4QqAX8gr7wxXCbRg72tjOmevVuwkXAEA4EuEKwCmq2psVXVTm6yWjjbs6FujO1uyrzlQrtrmNpOrAQBg4CBcATBd16xVWkyonHabydUMfEmRLiVGONXmNvT+nqNmlwMAwIBBuAJguryKjmYW7LfqP2PSupYGlppcCQAAAwfhCoDpumaushMIV/2la9/V+3uOqqXdbXI1AAAMDIQrAKaqb2nX0foWSVIW+636zaDYUCVHOVXf0q41ByrMLgcAgAGBcAXAVF2zVslRToU57SZXEzysFosuHJMsia6BAAD4CuEKgKnyOd/KNHPHpkiSVu46IrfHMLkaAAACH+EKgKm8hwez36rfTc+OV6TLrvL6Fm0prDK7HAAAAh7hCoBpmtvcKqlulsTMlRkcdqvOH5UkiaWBAAD4AuEKgGkKKhtlSIoLdyg6NMTscoJS19LAt3aWyjBYGggAwOkgXAEwzaf7regSaJazRyTKYbcqr6JR+8rqzS4HAICARrgCYJr8yo7Dg7PiWBJolginXWcNS5DEgcIAAJwuwhUAU7g9hg5XNkmSMpm5MtXcsR0t2d9i3xUAAKeFcAXAFEdqm9Xq9sgVYlVipNPscoLal0Yny2KRthfVqLi6yexyAAAIWIQrAKboWhKYGRcmq8VicjXBLSHCqalZsZJYGggAwOkgXAEwRVczi8w4lgT6g66ugSt2sTQQAIDeIlwBMEWBd+aKZhb+4MIxHfuu1h2qVHVjq8nVAAAQmAhXAPpdTVObqhvbZJGUERtqdjmQlBUfrlEpkXJ7DL2TW2Z2OQAABCTCFYB+1zVrlRLtkjPEZnI16DLHuzSQfVcAAPQG4QpAvytgv5VfmtO5NHDV3qNqanWbXA0AAIHH9HC1ZMkSZWdny+VyKScnR6tXrz7h+FWrViknJ0cul0tDhgzRE088cdyxzz//vCwWiy6//HIfVw3gdHTNXGVxvpVfGZsWpUExoWpu82j1vqNmlwMAQMAxNVy98MILuvXWW3X33Xdr8+bNmj17ti6++GIVFBT0OP7QoUO65JJLNHv2bG3evFl33XWXfvKTn+ill146Zmx+fr5uv/12zZ49u68/BoBT0Ob2qLi6WRLNLPyNxWLRnM4DhekaCADAqTM1XD300EO68cYbddNNN2n06NFavHixMjIy9Pjjj/c4/oknnlBmZqYWL16s0aNH66abbtINN9ygBx98sNs4t9utb33rW/rVr36lIUOG9MdHAXCSiqqa5DYMRTrtig0LMbscfM6cMR37rt7JPaJ2t8fkagAACCymhavW1lZt3LhRc+bM6XZ9zpw5WrNmTY+vWbt27THj586dqw0bNqitrc177b777lNiYqJuvPHGk6qlpaVFtbW13R4A+oa3BXt8mCwcHux3pg2OVWxYiKoa27Q+r8rscgAACCimhavy8nK53W4lJyd3u56cnKzS0p47VZWWlvY4vr29XeXl5ZKkjz76SEuXLtWTTz550rUsWrRI0dHR3kdGRsYpfhoAJyvfe74V+638kd1m1ZdGdy0NpGsgAACnwvSGFp//ybVhGCf8aXZP47uu19XV6dvf/raefPJJJSQknHQNd955p2pqaryPwsLCU/gEAE6WYRjeToFZhCu/1dU1cMXOI96/YwEAwBezm/WFExISZLPZjpmlKisrO2Z2qktKSkqP4+12u+Lj47Vz507l5eXpK1/5ivd5j6djz4DdbteePXs0dOjQY97X6XTK6XSe7kcC8AWqGtvU0OqWzWpRagyHB/urs0ckKjTEpqLqJu0srtW4QdFmlwQAQEAwbebK4XAoJydHK1eu7HZ95cqVmjlzZo+vmTFjxjHjV6xYoalTpyokJESjRo3S9u3btWXLFu/jq1/9qs477zxt2bKF5X6AyQo7lwSmRrsUYjN94hzH4Qqx6ewRHbP/dA0EAODkmfrdzcKFC/XUU09p2bJlys3N1W233aaCggItWLBAUsdyvWuuucY7fsGCBcrPz9fChQuVm5urZcuWaenSpbr99tslSS6XS+PGjev2iImJUWRkpMaNGyeHw2HK5wTQoaCqI1xlxLIk0N91dQ1csZN9VwAAnCzTlgVK0vz581VRUaH77rtPJSUlGjdunJYvX66srCxJUklJSbczr7Kzs7V8+XLddttteuyxx5SWlqZHHnlE8+bNM+sjADgFhztnrjLiWBLo7740Okk2q0W7S+tUUNGoTA58BgDgC1kMdisfo7a2VtHR0aqpqVFUVJTZ5QB+75/rej74+7Pa3R796j+75PYY+umFIxQfwT5Hs109PfPEzz/5sdYcqNA9Xx6tm2ZzZiAAIDidSjZg0wOAflFS0yy3x1CYw6a4cJboBoKuroFvsTQQAICTQrgC0C8KP7PfisODA8OcsR37rjbkV6m8vsXkagAA8H+EKwD9opD9VgEnLSZU4wdFyzCkd3LpGggAwBchXAHoF4VVTZLoFBhoPl0aSLgCAOCLEK4A9Ln6lnZVNrRKktIJVwFl7riOpYEf7i9XfUu7ydUAAODfCFcA+tzhzv1WCRFOhTpsJleDUzE8KUKD48PU2u7RB3uPml0OAAB+jXAFoM8VVnYsCcxkv1XAsVgs3sYWdA0EAODECFcA+lzXzBVLAgPT3LEd+67e3V2m1naPydUAAOC/CFcA+pTHMD5twx5HuApEkzNilRDhVF1zu9YdqjC7HAAA/BbhCkCfKq9vUXObRyE2i1KiXGaXg16wWi26kAOFAQD4QoQrAH3qcOd+q7SYUNmsHB4cqOZ0Lg1cueuIPB7D5GoAAPBPhCsAfcq7JJD9VgFt5tB4RTjtOlLbom1FNWaXAwCAXyJcAehTRdUdM1fpsXQKDGROu03njkyUxNJAAACOh3AFoM+0ezwqrWmWJA2KIVwFuq6W7CsIVwAA9IhwBaDPHKltUbvHkCvEqrhwh9nl4DSdOzJRITaLDhxt0P6yerPLAQDA7xCuAPSZoqrOJYExYbJYaGYR6KJcIZo5NEGStGIXs1cAAHwe4QpAnymq7mhmMYj9VgNGV9fAFTuPmFwJAAD+h3AFoM90zVyx32rguHB0siwWaUthtXc/HQAA6EC4AtAn2tweldZ2fPNNp8CBIynKpckZMZKklbnMXgEA8FmEKwB9orSmWR5DCnfYFB0aYnY58CG6BgIA0DPCFYA+cdh7vhXNLAaaOWM69l2tPVChmqY2k6sBAMB/EK4A9AnvfiuWBA44QxIjNDwpQu0eQ+/vKTO7HAAA/AbhCkCfOFzV2SmQZhYDEl0DAQA4FuEKgM+1tLt1tK5FEjNXA9Xczn1X7+8pU3Ob2+RqAADwD4QrAD5XUt0sQ1KUy64oF80sBqLxg6KVEuVSQ6tbaw6Um10OAAB+gXAFwOeKqrv2W4WZXAn6isViYWkgAACfQ7gC4HPstwoOXUsDV+46IrfHMLkaAADMR7gC4HNF3jbshKuB7IzsOEW57KpoaNWmgiqzywEAwHR2swsAMLA0t7lVXt8qiZkrf/fPdQWn/R5DEiO0pbBaD7+9T5eMTz3t97t6euZpvwcAAGZh5gqAT3XNWsWGhSjcyc9vBroxqVGSpF0ltTIMlgYCAIIb4QqAT3kPD2bWKiiMSI5UiM2iyoZWFdc0m10OAACmIlwB8KnDdAoMKg67VSNTOmavth+uMbkaAADMRbgC4FNFnZ0CaWYRPMYPipYkbS+qZmkgACCoEa4A+ExjS7uqGtskSWnRhKtgMbJzaWBVY5t3zx0AAMGIcAXAZ7qWBMaHOxTqsJlcDfqLw27VKJYGAgBAuALgO0Xe/VbMWgWbT5cG1rA0EAAQtAhXAHymq1NgOs0sgs7IlEg5bFZVN7XpcBVLAwEAwYlwBcBnDnc2s6ANe/AJsVk1KjVSUsfsFQAAwYhwBcAnapvbVNvcLouktBiX2eXABBM+szTQw9JAAEAQIlwB8InizqVgiZFOOe00swhGw5Mj5bBbVdPUpsOVjWaXAwBAvyNcAfCJrk6BnG8VvEJsVo1J7ewayNJAAEAQIlwB8ImuZhbstwpu41kaCAAIYoQrAKfNMAzvzNUgOgUGtWFJEXLaraptblchSwMBAEGGcAXgtNU0tamhpV1Wi5QaTTOLYPbZpYHbWBoIAAgyhCsAp63r8ODkKJdCbPy1EuzGp3csDdzB0kAAQJDhuyAAp439VvisYUkRcoVYVdfcrvwKlgYCAIIH4QrAaSvy7rciXEGyW60ak9rV2KLa3GIAAOhHhCsAp8UwDBV3hqu0aMIVOnR1DdxRVMvSQABA0CBcATgtpbXNamh1y2qRUmhmgU5Dk8IVGmJTfUu78sobzC4HAIB+QbgCcFp2FNVKkpIiaWaBT9mtVo1J40BhAEBw4TshAKdlR+c3zmkxzFqhu0+XBtbI7WFpIABg4CNcATgtO4u7whX7rdDd0MQIhTlsamh16+DRerPLAQCgzxGuAJyWrmWBNLPA59msFu/s1dbD1eYWAwBAPyBcAei1o3UtKq1tlkVSKs0s0IOJ6TGSpJ3FtWpze8wtBgCAPka4AtBrXUsC4yOccobYTK4G/igzPkwxYSFqafdod2md2eUAANCnCFcAem1nceeSQJpZ4DisFot39mprYbWptQAA0Nd6Fa4OHTrk6zoABKCumatBNLPACXSFqz1H6tTU6ja3GAAA+lCvwtWwYcN03nnn6dlnn1Vzc7OvawIQILzNLAhXOIGUaJeSo5xyewxvIAcAYCDqVbjaunWrJk+erJ/+9KdKSUnR97//fX3yySe+rg2AH6tpbFNBZaMkOgXii03qnL3awtJAAMAA1qtwNW7cOD300EMqKirS008/rdLSUp111lkaO3asHnroIR09etTXdQLwMztLOmYgMuJCFeqgmQVObEJnuDpU3qCapjZziwEAoI+cVkMLu92uK664Qi+++KJ+//vf68CBA7r99tuVnp6ua665RiUlJb6qE4Cf2dm5JHBcWrTJlSAQxIY7lBUXJkPSNs68AgAMUKcVrjZs2KCbb75Zqampeuihh3T77bfrwIEDevfdd1VUVKTLLrvMV3UC8DM7OvfOjBtEuMLJmZgRI4mlgQCAgatX4eqhhx7S+PHjNXPmTBUXF+uZZ55Rfn6+fv3rXys7O1uzZs3SX/7yF23atMnX9QLwEzuKOsLV2LQokytBoJiQHi2bxaKSmmaV1tAMCQAw8PQqXD3++OO6+uqrVVBQoFdffVWXXnqprNbub5WZmamlS5f6pEgA/qWhpV0HyxskSWNZFoiTFOawa2RKpCRpc2GVydUAAOB79t68aOXKlcrMzDwmUBmGocLCQmVmZsrhcOjaa6/1SZEA/EtuSa0MQ0qJcikx0ml2OQggUzJjtKukVlsLqzV3bIqsFovZJQEA4DO9mrkaOnSoysvLj7leWVmp7Ozs0y4KgH/rWhI4bhBLAnFqRqREKjTEptrmdh04Wm92OQAA+FSvwpVhGD1er6+vl8vlOq2CAPi/HcUdnQJZEohTZbdaNSG947+bzQXV5hYDAICPndKywIULF0qSLBaL7r33XoWFhXmfc7vdWrdunSZNmuTTAgH4n09nrghXOHWTM2O17lCldhbXqKU9TU4756QBAAaGUwpXmzdvltQxc7V9+3Y5HA7vcw6HQxMnTtTtt9/u2woB+JXmNrf2lXUs52JZIHojIzZU8eEOVTS0amdxraZkxppdEgAAPnFK4eq9996TJF1//fV6+OGHFRXFN1ZAsNlTWie3x1B8uEMpUSwDxqmzWCyanBmjt3PLtLmginAFABgwerXn6umnnyZYAUGq6/DgsYOiZaHTG3ppUkZHoDp4tEHVja0mVwMAgG+c9MzVlVdeqb/97W+KiorSlVdeecKxL7/88mkXBsA/7fQ2s+AHLOi9uHCHshPCdai8QZsLq3XeyCSzSwIA4LSddLiKjv70p9TR0WxiB4LVzq5mFnQKxGnKyYzVofIGbcqv0rkjEpkJBQAEvJMOV08//XSP/wwgeLS5PcotrZNEMwucvnGDovX6tmJVNLQqr6JR2QnhZpcEAMBp6dWeq6amJjU2Nnp/n5+fr8WLF2vFihU+KwyA/9lfVq/Wdo8iXXZlxoV98QuAE3DYrRrf2c5/U36VydUAAHD6ehWuLrvsMj3zzDOSpOrqap1xxhn64x//qMsuu0yPP/64TwsE4D+6zrcamxbFEi74RE5np8DtRTVqaXebXA0AAKenV+Fq06ZNmj17tiTp3//+t1JSUpSfn69nnnlGjzzyiE8LBOA/uppZsN8KvpIVH6b4cIda3R7tKKo1uxwAAE5Lr8JVY2OjIiMjJUkrVqzQlVdeKavVqjPPPFP5+fk+LRCA/+iauRo3iHAF37BYLMrJ6pi92sjSQABAgOtVuBo2bJheffVVFRYW6q233tKcOXMkSWVlZad8/tWSJUuUnZ0tl8ulnJwcrV69+oTjV61apZycHLlcLg0ZMkRPPPFEt+dffvllTZ06VTExMQoPD9ekSZP0v//7v6f2AQEcw+0xtKukc+aKZhbwocmZsbJIyqtoUH5Fg9nlAADQa70KV/fee69uv/12DR48WNOnT9eMGTMkdcxiTZ48+aTf54UXXtCtt96qu+++W5s3b9bs2bN18cUXq6CgoMfxhw4d0iWXXKLZs2dr8+bNuuuuu/STn/xEL730kndMXFyc7r77bq1du1bbtm3T9ddfr+uvv15vvfVWbz4qgE6HyhvU2OpWaIhN2QkRZpeDASQ6NETDkjr+m/rXhsMmVwMAQO9ZDMMwevPC0tJSlZSUaOLEibJaOzLaJ598oqioKI0aNeqk3mP69OmaMmVKtyYYo0eP1uWXX65FixYdM/6OO+7Q66+/rtzcXO+1BQsWaOvWrVq7du1xv86UKVP05S9/Wffff/9J1VVbW6vo6GjV1NSc8kwcMFC9tqVItzy/RTlZsXrpBzO7PffPdT3/QAQ4WdsOV+v59YVKjnLqozvOl93Wq5/9AQDgc6eSDXr9f6+UlBRNnjzZG6wk6YwzzjjpYNXa2qqNGzd6lxR2mTNnjtasWdPja9auXXvM+Llz52rDhg1qa2s7ZrxhGHrnnXe0Z88enX322cetpaWlRbW1td0eALrz7rdK4wcO8L0xqVEKc9h0pLZF7+85anY5AAD0ykkfIvxZDQ0N+t3vfqd33nlHZWVl8ng83Z4/ePDgF75HeXm53G63kpOTu11PTk5WaWlpj68pLS3tcXx7e7vKy8uVmpoqSaqpqdGgQYPU0tIim82mJUuW6MILLzxuLYsWLdKvfvWrL6wZCGZdndzG0ikQfcBus2pKZqw+3F+u59cX6oIxyV/8IgAA/EyvwtVNN92kVatW6Tvf+Y5SU1NP67ybz7/WMIwTvl9P4z9/PTIyUlu2bFF9fb3eeecdLVy4UEOGDNG5557b43veeeedWrhwoff3tbW1ysjIONWPAgxYhmFoZ3HnGVc0s0AfmZrVEa7e21OmI7XNSo5ymV0SAACnpFfh6s0339Qbb7yhWbNm9foLJyQkyGazHTNLVVZWdszsVJeUlJQex9vtdsXHx3uvWa1WDRs2TJI0adIk5ebmatGiRccNV06nU06ns9efBRjoDlc1qba5XQ6bVcOTIs0uBwNUUpRL0wbHan1elf61oVA/On+42SUBAHBKerXnKjY2VnFxcaf1hR0Oh3JycrRy5cpu11euXKmZM2f2+JoZM2YcM37FihWaOnWqQkJCjvu1DMNQS0vLadULBLOu/VYjUyLlsNNoAH3nqmmZkqQXNhTK4+lVvyUAAEzTq++S7r//ft17771qbGw8rS++cOFCPfXUU1q2bJlyc3N12223qaCgQAsWLJDUsVzvmmuu8Y5fsGCB8vPztXDhQuXm5mrZsmVaunSpbr/9du+YRYsWaeXKlTp48KB2796thx56SM8884y+/e1vn1atQDDbWdy134olgehbl4xPVaTLrsLKJn10oNzscgAAOCW9Whb4xz/+UQcOHFBycrIGDx58zKzRpk2bTup95s+fr4qKCt13330qKSnRuHHjtHz5cmVlZUmSSkpKup15lZ2dreXLl+u2227TY489prS0ND3yyCOaN2+ed0xDQ4NuvvlmHT58WKGhoRo1apSeffZZzZ8/vzcfFYCkHd79VjSzQN8Kddh0xeRBemZtvp7/pFCzhyeaXRIAACetV+dcfVFnvV/84he9LsgfcM4V0N3UX7+t8voWvXLzTE3OjD3mec65gq9cPT1TO4tr9OVHPlSIzaK1d35JCRHsiQUAmOdUskGvZq4CPTwBOHlltc0qr2+R1SKNSuGHDeh7Y9OiNTE9WlsP1+hfGw7rB+cONbskAABOSq93pldXV+upp57SnXfeqcrKSkkdywGLiop8VhwA83UtCRyWFKFQh83kahAsvjW9Y3n4Pz/Jp7EFACBg9Cpcbdu2TSNGjNDvf/97Pfjgg6qurpYkvfLKK7rzzjt9WR8Ak+3k8GCY4CsT0xTV2dhi1b6jZpcDAMBJ6VW4Wrhwoa677jrt27dPLtenhzxefPHF+uCDD3xWHADzeZtZ0CkQ/SjUYdO8nHRJ0j8+zje5GgAATk6vwtX69ev1/e9//5jrgwYNOuaQXwCBbUfnzNU4OgWin3UtDXx3d5mKqptMrgYAgC/Wq3DlcrlUW1t7zPU9e/YoMZG2ucBAUd3Y6v2mdgwzV+hnw5IiNGNIvDyG9PwndKQEAPi/XoWryy67TPfdd5/a2tokSRaLRQUFBfrZz37W7cwpAIGt6/DgrPgwRblCvmA04HvfPrNj9ur59YVqc3tMrgYAgBPrVbh68MEHdfToUSUlJampqUnnnHOOhg0bpsjISP3mN7/xdY0ATLKjqGO/1TiaWcAkc8YmKzHSqaN1LVqx84jZ5QAAcEK9OucqKipKH374od577z1t3LhRHo9HU6ZM0QUXXODr+gCYqGvmiiWBMEuIzaqrpmXoz+/u1/9+nKcvT0g1uyQAAI7rlMOVx+PR3/72N7388svKy8uTxWJRdna2UlJSZBiGLBZLX9QJwARdnQJpZgEzffOMTC15/4A+Plip3aW1HGYNAPBbp7Qs0DAMffWrX9VNN92koqIijR8/XmPHjlV+fr6uu+46XXHFFX1VJ4B+1tDSrkPlDZJoww5zpcWEas6YZEnS39fQlh0A4L9OKVz97W9/0wcffKB33nlHmzdv1nPPPafnn39eW7du1dtvv613331XzzzzTF/VCqAf5ZbUyjCklCiXEiKcZpeDIHftzMGSpFc3F6mmsc3cYgAAOI5TClfPPfec7rrrLp133nnHPHf++efrZz/7mf7xj3/4rDgA5vE2sxjErBXMNz07TqNSItXU5taLGwrNLgcAgB6dUrjatm2bLrroouM+f/HFF2vr1q2nXRQA833azIL9VjCfxWLxzl4983Ge3B7D3IIAAOjBKYWryspKJScnH/f55ORkVVVVnXZRAMy3ozNcjWO/FfzE5ZMGKTo0RIWVTXpvd5nZ5QAAcIxTCldut1t2+/EbDNpsNrW3t592UQDM1dLu1r4jdZLoFAj/Eeqwaf60DEnS39fmmVsMAAA9OKVW7IZh6LrrrpPT2fPm9paWFp8UBcBce0vr1e4xFBsWotRol9nlAF7fOTNLT64+qNX7yrW/rE7DkiLNLgkAAK9TClfXXnvtF4655pprel0MAP/w2fOtOLsO/iQjLkwXjE7Wyl1HtOyjPP32ivFmlwQAgNcphaunn366r+oA4Ee6OgWOYb8V/NCNZ2Vr5a4jennTYd0+Z6Tiwh1mlwQAgKRT3HMFIDjs9DazYL8V/M/07DiNGxSl5jaP/rmOQ4UBAP6DcAWgm3a3R7klneGKZhbwQxaLRTeelS1JemZtvlrbPSZXBABAB8IVgG4Oljeopd2jCKddWXFhZpcD9OjL49OUFOlUWV2L/rOt2OxyAACQRLgC8Dne/VapUbJaaWYB/+SwW72HCj+1+pAMg0OFAQDmI1wB6GZHUceSwLGDaGYB//at6ZlyhVi1q6RWHx+sNLscAAAIVwC629nZhn0szSzg52LCHJo3JV2S9NTqgyZXAwAA4QrAZ3g8hnZ1dQpk5goB4IazsmWxSO/sLtP+sjqzywEABDnCFQCvgspG1bW0y2G3amhihNnlAF9oaGKELhydLEn66wfMXgEAzEW4AuDVdb7V6JRIhdj46wGB4fvnDJUkvbq5WEdqm02uBgAQzPjuCYDXjq79VpxvhQCSkxWraYNj1er26OmP8swuBwAQxAhXALy62rCPTWO/FQLL987umL36x8f5qmtuM7kaAECwIlwBkCQZxmeaWdApEAHmS6OSNDQxXHUt7Xr+k0KzywEABCnCFQBJUmltsyoaWmWzWjQyJdLscoBTYrVa9P3O2aulHx5Sa7vH5IoAAMGIcAVAkrSz8/Dg4UkRcoXYTK4GOHWXTU5TUqRTpbXNenVLkdnlAACCEOEKgKTPNLNgSSAClNNu041nZUuSnlh1QG6PYXJFAIBgQ7gCIEna0TlzRTMLBLJvnZml6NAQHTzaoLd2lppdDgAgyNjNLgCAf9jVOXM1jjbsMNE/1xWc9nvkZMXq3d1l+vV/dqmqoVUWi+W03u/q6ZmnXRMAIDgwcwVAFfUtKq7pOHx1DDNXCHAzh8TLYbOquKZZ+8rqzS4HABBECFcAtLOzBXt2QrginExoI7CFOe06IztOkvTenjKTqwEABBPCFQBvuGK/FQaKs4YlyGa1KL+iUYfKG8wuBwAQJAhXALydAtlvhYEiKjREOZmxkqT3mb0CAPQTwhUA7WLmCgPQ2SMSZbVI+8rqVVjZaHY5AIAgQLgCglxdc5t32RRnXGEgiQt3aFJGx+zVu7uZvQIA9D3CFRDkumat0qJdigt3mFwN4FvnjUyURdKeI3U6XMXsFQCgbxGugCDnbWbBfisMQPERTk3KiJHE7BUAoO8RroAg521mwZJADFDnjUySRdLu0joVVTeZXQ4AYAAjXAFBbmcRzSwwsCVEOjWR2SsAQD8gXAFBrLnNrf1H6yXRhh0D27mde69yS2pVzOwVAKCPEK6AILa7tE5uj6GECIeSo5xmlwP0maRIl8and/wA4Z3cIyZXAwAYqAhXQBDbXtSx32pMWrQsFovJ1QB960ujkjtmr0rpHAgA6BuEKyCIbT9cLUmamM6SQAx8iZGfdg5cuYvZKwCA7xGugCC27XBnp0D2WyFInD8qSVaLtK+sXnmdh2cDAOArhCsgSDW3ubWvrKOZxQRmrhAk4iOcysmKlSStZO8VAMDHCFdAkNpVUtvZzMKplCiX2eUA/ea8kUmyWS06VN6gA53dMgEA8AXCFRCktncuCZyQTjMLBJeYMIemDY6T1LH3yjAMkysCAAwUhCsgSHXttxrPfisEoXNHJirEZlFBZaNyS2rNLgcAMEAQroAgtb2oWhL7rRCcolwhmjU0QZL01s4jcnuYvQIAnD7CFRCEGlratb+zmQUzVwhWZ49IVJjDpqP1LdqUX2V2OQCAAYBwBQShXSW18hhScpRTSTSzQJByhdh03sgkSdLbu4+otd1jckUAgEBHuAKC0HbvfqsYcwsBTDY9O06xYSGqa27XRwfKzS4HABDgCFdAENpe9GmnQCCY2W1WXTgmRZL0wd6jamhpN7kiAEAgI1wBQWjb4WpJ0njCFaAJ6dFKi3appd2j9/aUmV0OACCAEa6AIFPX3KaD5Q2SaGYBSJLVYtHccR2zV+sOVqqyodXkigAAgYpwBQSZncW1MgxpUEyoEiKcZpcD+IXhSZEalhQht2Fo5a5Ss8sBAAQowhUQZLZzeDDQo7ljO2avth6uUVF1k8nVAAACEeEKCDLbOptZsN8K6G5QTKgmdv65eGsHs1cAgFNHuAKCzI4iZq6A47lwTIpsVov2H63XviN1ZpcDAAgwhCsgiNQ0tekQzSyA44oLd+jM7DhJ0n93lspjGCZXBAAIJIQrIIjs7Jy1yogLVWy4w+RqAP907sgkOe1WldQ0a2N+ldnlAAACCOEKCCJd+60mDIoxtxDAj4U77frSqCRJ0oqdpaptbjO5IgBAoCBcAUHE2ymQZhbACZ05NF4JEU41tLr1yNv7zC4HABAgCFdAENlWVC1JmsB+K+CE7FarLp2QKkn625o87S+rN7kiAEAgIFwBQaKqoVWFlR1n94wlXAFfaERypEalRKrdY+j+/+ySQXMLAMAXIFwBQWJHcceSwMHxYYoODTG5GiAwXDI+VSE2i1btPap3d5eZXQ4AwM8RroAgsc273yrG3EKAAJIQ4dQNZ2VLku7/zy61tLtNrggA4M8IV0CQ6GpmwX4r4NT8+PzhSox0Kq+iUU9/lGd2OQAAP0a4AoLE9iI6BQK9EeG0646LRkmS/vzOPpXVNptcEQDAXxGugCBQXt+iouomWSzS2LQos8sBAs6VkwdpYkaMGlrd+v1/95hdDgDATxGugCDQNWuVnRCuSBfNLIBTZbVa9MuvjJEkvbTpsDYXVJlcEQDAH5kerpYsWaLs7Gy5XC7l5ORo9erVJxy/atUq5eTkyOVyaciQIXriiSe6Pf/kk09q9uzZio2NVWxsrC644AJ98sknffkRAL/Hfivg9E3OjNW8KemSpF/+3y55PLRmBwB0Z2q4euGFF3Trrbfq7rvv1ubNmzV79mxdfPHFKigo6HH8oUOHdMkll2j27NnavHmz7rrrLv3kJz/RSy+95B3z/vvv65vf/Kbee+89rV27VpmZmZozZ46Kior662MBfufT/VYx5hYCBLg7LhqpcIdNWwur9cKGQrPLAQD4GYth4qmI06dP15QpU/T44497r40ePVqXX365Fi1adMz4O+64Q6+//rpyc3O91xYsWKCtW7dq7dq1PX4Nt9ut2NhYPfroo7rmmmtOqq7a2lpFR0erpqZGUVHsT0HgO/O376i0tln/WjBD0wbH+fz9/7mu5x+IAAPB1dMzu/1+6YeHdP9/dinKZdc7Pz1XiZFOkyoDAPSHU8kGps1ctba2auPGjZozZ06363PmzNGaNWt6fM3atWuPGT937lxt2LBBbW1tPb6msbFRbW1tios7/jeULS0tqq2t7fYABoqy2maV1jbLapHGpPLDAuB0XTsjS+MGRam2uV2/fmOX2eUAAPyIaeGqvLxcbrdbycnJ3a4nJyertLS0x9eUlpb2OL69vV3l5eU9vuZnP/uZBg0apAsuuOC4tSxatEjR0dHeR0ZGxil+GsB/dS0JHJYUoXCn3eRqgMBnt1n12yvGy2qRXttSrNX7jppdEgDAT5je0MJisXT7vWEYx1z7ovE9XZekP/zhD3ruuef08ssvy+VyHfc977zzTtXU1HgfhYWso8fAsbWwWpI0flCMqXUAA8mE9BhdM2OwJOmeV3eouc1tbkEAAL9gWrhKSEiQzWY7ZpaqrKzsmNmpLikpKT2Ot9vtio+P73b9wQcf1G9/+1utWLFCEyZMOGEtTqdTUVFR3R7AQLG5M1xNyowxtQ5goPnpnBFKiXIpv6JRj7233+xyAAB+wLRw5XA4lJOTo5UrV3a7vnLlSs2cObPH18yYMeOY8StWrNDUqVMVEvLp2T0PPPCA7r//fv33v//V1KlTfV88ECAMw/DOXE2iUyDgU5GuEP3yqx1nXz2x6oD2HakzuSIAgNlMXRa4cOFCPfXUU1q2bJlyc3N12223qaCgQAsWLJDUsVzvsx3+FixYoPz8fC1cuFC5ublatmyZli5dqttvv9075g9/+IPuueceLVu2TIMHD1ZpaalKS0tVX1/f758PMNuh8gbVNrfLabdqVGqk2eUAA87csSm6YHSS2tyG7n5lB2dfAUCQMzVczZ8/X4sXL9Z9992nSZMm6YMPPtDy5cuVlZUlSSopKel25lV2draWL1+u999/X5MmTdL999+vRx55RPPmzfOOWbJkiVpbW/W1r31Nqamp3seDDz7Y758PMNuWzlmrcYOiFWIzfYslMOBYLBb98qtjFRpi0yd5lfr3xsNmlwQAMJGp51z5K865wkDxi9d26O9r83XDrGzd+5UxffZ1OOcKA9nnz7nqyZMfHNRvlucqJixE7yw8R/ERnH0FAANFQJxzBaDvbaGZBdAvrp81WKNTo1Td2KbfLM/94hcAAAYkwhUwQDW3ubWrpONA7MkZMeYWAwxwdptVi64cL4tFenlTkT7Yy9lXABCMCFfAAJVbUqs2t6G4cIfSY0PNLgcY8CZlxOjazrOvfvbSNtU2t5lbEACg3xGugAHKuyQwI+aEB3MD8J3/uWiksuLDVFzTrN++wfJAAAg2hCtggPpsuALQP8Icdv1hXsfB9c+vL9QqlgcCQFAhXAEDVNfhwRMJV0C/mj4kXtfNHCyJ5YEAEGwIV8AAVNXQqryKRknSpPQYc4sBglDX8sCSmmb95j8sDwSAYEG4AgagLYerJUlDEsIVHRZibjFAEPrs8sAXNhTq/T1lJlcEAOgPhCtgAGJJIGC+zy4PvPPl7SwPBIAgQLgCBiCaWQD+4bPLA3/9n11mlwMA6GN2swsA4FuGYTBzBfjQP9cVnNbr54xJ0VOrD+rFDYcVGmLXyJTI03q/q6dnntbrAQB9h5krYIA5VN6gqsY2Oe1WjUmNMrscIOhlJ4RrxtB4SdIrmw+rqdVtckUAgL5CuAIGmI35VZKk8YOi5bDzRxzwB3PGpCg+3KHa5na9trVIhmGYXRIAoA/wnRcwwGwqqJYk5WTFmlsIAC+H3aqv56TLapG2Ha7x7osEAAwshCtggNlc0DFzNTmTcAX4k8z4cJ03KkmS9PrWYlU2tJpcEQDA1whXwABS19ymPUfqJElTsmLMLQbAMc4dkaSsuDC1tHv04oZCuT0sDwSAgYRwBQwgWwqrZRhSemyokiJdZpcD4HNsVou+MTVDTrtVBZWNHC4MAAMM4QoYQDblV0tivxXgz2LDHbps0iBJ0ru7y5Rf0WByRQAAXyFcAQPIps79VlPYbwX4tUkZMZqUESND0osbCtXcRnt2ABgICFfAAOHxGN5mFoQrwP99dWKaYsNCVNXYpv/bWmx2OQAAHyBcAQPEgaP1qm1ulyvEqlGpkWaXA+ALuEJs+sbUDFkkbS6s1tbD1WaXBAA4TXazCwBw6v65ruCYaxvyKiVJKVGh+teGw/1dEoBeyOpsz/7u7jK9tqVImbFhig13mF0WAKCXmLkCBoiCykZJUlZ8mMmVADgV541MUkZsqJrbPHpufYHaPR6zSwIA9BLhChggusJVZhzhCggkNqtFV03LVGiITYermvTWjlKzSwIA9BLhChgAmlrdKqtrkSRlEK6AgBMb7tDXctIlSR8dqNCOohqTKwIA9AbhChgACqs6Zq3iwh2KcLKVEghEo1OjNHt4giTppU2HVVHfYnJFAIBTRbgCBoD8CpYEAgPBnDEpyooLU0u7R899UqA2N/uvACCQEK6AASC/okGSNDg+3ORKAJwOm9Wiq87IVJjDpuKaZi3fXmJ2SQCAU0C4AgJcu8fjXRZIp0Ag8EWHhnjPv1p3qFJbC6vNLgkAcJIIV0CAK6luVpvbUJjDpqRIp9nlAPCBEcmROndkoiTplc1FKqtrNrkiAMDJIFwBAS6vc0lgVlyYLBaLydUA8JUvjU7WkIRwtbo79l+1trP/CgD8HeEKCHB5nc0sBiew3woYSKwWi+ZPy1CE064jtS16dUuRDMMwuywAwAkQroAA5jEMbzOLLJpZAANOpCtEV52RIatF2lJYrTUHKswuCQBwAoQrIICV17WosdWtEJtFaTEus8sB0AeGJETo4nGpkqQ3d5RozYFykysCABwP4QoIYF3nW6XHhslu5Y8zMFDNHBqvyRkx8hjSj/65WYc7O4QCAPwL340BASyP862AoGCxWHT55EFKi3GpsqFV3//fjWpuc5tdFgDgcwhXQAD7NFxxvhUw0IXYrPr29CzFhTu0s7hWd768nQYXAOBnCFdAgKppalNVY5sskjLiCFdAMIgJc+ixq6fIZrXolc1FWvZRntklAQA+g3AFBKiuLoGpMS65QmwmVwOgv8wYGq+7LxktSfrt8lwaXACAHyFcAQEqjxbsQNC6ftZgXTl5kNwegwYXAOBHCFdAgOrqFEgzCyD4WCwW/fbK8Ro3KEqVDa266e8bVN/SbnZZABD0CFdAAGpqdau0plmSlEUzCyAouUJs+st3piohwqndpXW65bnNcntocAEAZiJcAQEor6JBhqSECKeiXCFmlwPAJINiQvXkNTly2K16Z3eZfvdmrtklAUBQI1wBAejg0XpJ0pBElgQCwW5yZqz++PWJkqQnVx/S858UmFwRAAQvwhUQgA6WdzSzGJJAuAIgfWVimm69YLgk6Z5Xd9BBEABMQrgCAkx1Y6t3v1U24QpAp1u+NFxfmZimdo+hHzy7SYc6fwgDAOg/hCsgwKw7VClDUmKkU5HstwLQyWKx6IGvTdCkjBjVNLXpxr+tV01jm9llAUBQIVwBAWbtgQpJLAkEcCxXiE1/vSZHadEuHSxv0M3/3Kg2t8fssgAgaBCugADz8cHOcJUYYXIlAPxRUqRLS6+bpjCHTR/tr9DPX90hw6BFOwD0B8IVEEAqG1q1u7ROEvutABzf6NQoPXLVZFkt0vPrC/Xou/vNLgkAggLhCgggnxzqmLVKinQqwmk3uRoA/uyCMcn61VfHSpL+uHKvXtp42OSKAGDgI1wBAcS734rzrQCchO/MGKzvnzNEknTHS9v04T5atANAXyJcAQHk44OVkqQhCey3AnBy7pg7ytuifcGzG5VbUmt2SQAwYBGugABRUd+iPUfYbwXg1FitFj349Qmanh2n+pZ2Xf/0epXUNJldFgAMSIQrIECsO9QxazUqJVLh7LcCcAqcdpv++p2pGp4UodLaZl23bL1qmzkDCwB8jXAFBIg1Bzr2Spw5JN7kSgAEouiwED19/TQlRjq150idfvDsRrW2cwYWAPgS4QoIEF0b0WcNSzC5EgCBKj02TE9fN03hnWdg/c+/t8rj4QwsAPAVwhUQAAorG5VX0Sib1aIzh8SZXQ6AADZuULSWfDtHdqtFr24p1v1v7OKQYQDwEcIVEABWd85aTc6IUaQrxORqAAS6c0Yk6oGvT5AkPf1Rnpa8f8DkigBgYCBcAQHgw/1HJUlnDWdJIADfuGJyun5+6RhJ0gNv7dHznxSYXBEABD7CFeDn3B5DH+3vODx49vBEk6sBMJDceFa2bj53qCTprle26787SkyuCAACG+EK8HM7impU09SmSJddE9OjzS4HwADz/+aO1FXTMuQxpJ88t8XbmRQAcOoIV4CfW72vY0ngjCHxstv4IwvAtywWi359+TjNHZusVrdH33tmo3YU1ZhdFgAEJL5TA/xcVzOL2ey3AtBH7DarHr5qsqZnx6m+pV3XPf2J8sobzC4LAAIO4QrwYw0t7dpUUCVJOov9VgD6kCvEpievnaoxqVEqr2/Vt55ap+LqJrPLAoCAQrgC/NgnhyrV5jY0KCZUg+PDzC4HwAAX5QrR3284Q9kJ4SqqbtK3n1qno3UtZpcFAAGDcAX4sQ8691udPSJBFovF5GoABIPESKeevWm6BsWE6mB5g76zdJ2qG1vNLgsAAgLhCvBjH3butzprGEsCAfSfQTGh+sdN05UY6dTu0jpd+/R61be0m10WAPg9whXgp0pqmrSvrF4WizRzaLzZ5QAIMoMTwvXsjdMVGxairYXVuuFv69XU6ja7LADwa4QrwE+9t7tjSeCkjBjFhjtMrgZAMBqZEqlnbpiuSKddnxyq1IJnN6qlnYAFAMdDuAL81Lu7yyRJ549MMrkSAMFsfHq0ll0/TaEhNq3ae1S3PLdF7W6P2WUBgF8iXAF+qLnNrY/2d+y3Om8U4QqAuaYNjtOT10yVw2bVf3eW6vZ/bZXbY5hdFgD4HcIV4IfWHapUU5tbyVFOjU2LMrscANBZwxP02LemyG616NUtxfp//yZgAcDnEa4AP/Re55LA80Ym0YIdgN+4cEyyHvnmZNmsFr28qUh3vLRNHgIWAHjZzS4AQHeGYXj3W7EkEMDn/XNdgdkl6Os56XpxQ6H+vfGw8sob9OL3Z8hq5QdBAMDMFeBnDhxtUEFloxw2q84almB2OQBwjAnpMfr61AxZJG3Ir9Jdr2xnBgsARLgC/E7XksDpQ+IU7mRyGYB/mviZgPX8+kLd89oOAhaAoEe4AvzMu5/ZbwUA/mxSRoy+lpMui6VjueK9r++QYRCwAAQv08PVkiVLlJ2dLZfLpZycHK1evfqE41etWqWcnBy5XC4NGTJETzzxRLfnd+7cqXnz5mnw4MGyWCxavHhxH1YP+FZtc5vW51VKks5nvxWAADA5M1YPfm2iLBbp2Y8LdO9rO5nBAhC0TA1XL7zwgm699Vbdfffd2rx5s2bPnq2LL75YBQU9b9Y9dOiQLrnkEs2ePVubN2/WXXfdpZ/85Cd66aWXvGMaGxs1ZMgQ/e53v1NKSkp/fRTAJz7cV652j6EhCeEanBBudjkAcFLm5aTrD/MmyGKR/vfjfN31ynbatAMISqaGq4ceekg33nijbrrpJo0ePVqLFy9WRkaGHn/88R7HP/HEE8rMzNTixYs1evRo3XTTTbrhhhv04IMPesdMmzZNDzzwgK666io5nc7++iiAT7yTS5dAAIHp61Mz9ODXJspq6diD9dMXt6jd7TG7LADoV6aFq9bWVm3cuFFz5szpdn3OnDlas2ZNj69Zu3btMePnzp2rDRs2qK2trde1tLS0qLa2ttsD6G9tbo/e2X1EUsdZMgAQaOblpOuRb072HjT84+c2q7WdgAUgeJgWrsrLy+V2u5Wc3P2byOTkZJWWlvb4mtLS0h7Ht7e3q7y8vNe1LFq0SNHR0d5HRkZGr98L6K1PDlWqurFN8eEOTRscZ3Y5ANArl05I05JvTZHDZtWbO0r1g2c3qrnNbXZZANAvTG9oYbF0P3TQMIxjrn3R+J6un4o777xTNTU13kdhYWGv3wvorf/u6PihwoVjkmXjME4AAWzO2BQ9ee1UOe1WvbO7TN99ZoOaWglYAAY+08JVQkKCbDbbMbNUZWVlx8xOdUlJSelxvN1uV3x8fK9rcTqdioqK6vYA+pPHY+itnR3/bc8dRyMWAIHvnBGJevr6aQpz2LR6X7muffoT1be0m10WAPQp08KVw+FQTk6OVq5c2e36ypUrNXPmzB5fM2PGjGPGr1ixQlOnTlVISEif1Qr0tc2F1Sqra1Gk066ZQ3v/gwIA8Cczhybof288Q5FOuz45VKlvPbVOVQ2tZpcFAH3G1GWBCxcu1FNPPaVly5YpNzdXt912mwoKCrRgwQJJHcv1rrnmGu/4BQsWKD8/XwsXLlRubq6WLVumpUuX6vbbb/eOaW1t1ZYtW7Rlyxa1traqqKhIW7Zs0f79+/v98wEnq2vW6vzRSXLabSZXAwC+k5MVp39+90zFhIVoa2G1vvbEGhVVN5ldFgD0CVPD1fz587V48WLdd999mjRpkj744AMtX75cWVlZkqSSkpJuZ15lZ2dr+fLlev/99zVp0iTdf//9euSRRzRv3jzvmOLiYk2ePFmTJ09WSUmJHnzwQU2ePFk33XRTv38+4GQYhuHdb3XRWJYEAhh4xqdH61/fn6HUaJcOHG3QvCVrtPdIndllAYDPWYyujhDwqq2tVXR0tGpqath/hT63q7hWlzyyWk67VZvvvVBhDvsXvuaf63o+aBsAzHD19MyTGldc3aRrl32ifWX1inLZtey6aZpKd1QAfu5UsoHp3QKBYPffziWB54xIPKlgBQCBKi0mVP9aMEM5WbGqbW7Xt55ap7d3HTG7LADwGcIVYLK3OpcEzmVJIIAgEBPm0LM3Ttf5o5LU0u7R95/dqBfXcwQKgIGBcAWY6MDReu05Uie71aIvjU4yuxwA6BehDpv+8p0cfS0nXW6Pof95aZsee2+/2KkAINARrgATvb6lWJI0a1iCYsIcJlcDAP0nxGbVA1+boB+cO1SS9MBbe3THS9vU2u4xuTIA6D3CFWASwzD0+taOcHX55DSTqwGA/mexWHTHRaP0y6+MkdUivbjhsL6zlLOwAAQuwhVgku1FNTpU3iBXiFUXjmG/FYDgdd2sbC29bpoinHatO1Spy5d8pP1l9WaXBQCnjHAFmOS1ziWBF4xOVoSTLoEAgtt5I5P08s0zlR4bqvyKRl2x5COt3nfU7LIA4JTwHR1gArfH0P91LQmcNMjkagDg9Pjy7L1rZgzWPz7OV35lo65d9okunZCmM4fEn/L7nOzZWwDgS8xcASZYd7BCZXUtig4N0dkjEs0uBwD8RoTTrhvPytbkjBh5DOn1rcV6fWux3B46CQLwf4QrwASvbimSJF0yPlUOO38MAeCz7DarvpaTrjljkiVJHx+s0FOrD6qmqc3kygDgxPiuDuhnzW1uvdl5cPBlk+gSCAA9sVgsOndkkr49PUtOu1X5lY169N19NLoA4NcIV0A/e3/PUdU1tyslyqUzBseZXQ4A+LUxaVH60XnDlBrtUkOrW09/dEjv7j4iDwcOA/BDhCugn726uWNJ4FcnpclqtZhcDQD4v/gIpxacM1RTs2JlSHo7t0zPrM1TQ0u72aUBQDeEK6Aflde36O3cI5KkKybTJRAATlaIzaorp6Rr3pR0hdgs2nukXo++t1+FlY1mlwYAXoQroB+9vOmw2j2GJmbEaHRqlNnlAEDAycmK1YJzhio+3KGapjb95YMDWrWnjGWCAPwC4QroJ4Zh6Pn1hZKkq6ZlmFwNAASu1OhQ/fC8YRo3KFoeQ3pr1xEt/fCQqhtbzS4NQJAjXAH9ZEN+lQ4ebVCYw6avTKRLIACcDleITd+clqErJw+Sw2bVofIGPfLuPm0uqJLBLBYAk9jNLgAIFs9/0jFrdemEVEU4+aMHAKfLYrFo6uA4ZSeE68UNhSqsatK/Nh7WjqIa1bW0K8oVYnaJXldPzzS7BAD9gJkroB/UNrfpje3FkqT50/gfLAD4UnyEU987e6guGJ0sm8Wi3NI6Pfw2s1gA+h/hCugHr28pVnObR8OTIjQlM8bscgBgwLFZLTp/VJJuPm+o0mJcampz618bD+vpNXkqr2sxuzwAQYJwBfSDF7oaWZyRKYuFs60AoK+kRofqB+cM0wWjk2W3WrS/rF4Pv7tPK3cdUZvbY3Z5AAY4whXQx3YU1Wh7UY0cNitnWwFAP+iaxbrlS8M1PClCbo+h9/aU6eF39mlPaZ3Z5QEYwAhXQB9b9tEhSdLF41MUF+4wuRoACB7xEU5dN3Owrj4jU1EuuyobWvX3tXn6x7p82rYD6BO0LAP6UFlds/5va0cji+tnZZtcDQAEH4vFonGDojU8KULv7i7TRwfKtbO4VnuP1Ons4Yk6a3iCnHab2WUCGCCYuQL60LMfF6jNbSgnK1aTMmLMLgcAgpYzxKaLx6fqR+cNV1Z8mNrcht7ZXaY/rtirdYcq5PbQVRDA6SNcAX2kuc2tf3ycL0m6ftZgc4sBAEiSUqJd+t7sIfrmGZmKD3eovqVdr20p1sPv7NXO4hpatwM4LSwLBPrI61uLVdHQqrRoly4am2J2OQCAThaLReMHRWt0aqTWH6rUu7vLVF7fqn+sK1BmXJguHpeirPhws8sEEIAIV0AfMAxDyz7saGRxzczBstuYJAYAf2O3WjVjaIImZ8Zq9b6j+nB/uQoqG/WXDw5qRHKEzh+VrMy4MLPLBBBACFdAH1h7sEK7S+sUGmLTVdMyzC4HAHACrhCbLhyToulD4vVO7hFtzK/S3iP12nukXsOTInT+qCRmsgCcFMIV0Ae6Zq3m5QxSTBjt1wEgEES5QnTF5HSdPTxR7+89qs0FVdpXVq99ZfUakhiuL41KVnYCIQvA8RGuAB/bWVyjt3PLZLHQfh0AAlF8hFPzpqTrvJFJWrW3TBvzq3TwaIMOHj2o7IRwnTsiUcOSImSxWMwuFYCfIVwBPvbou/slSV+ZkKahiREmVwMA6K24cIeumJyuc0cmadXeo9qYV6VD5Q06VN6g1GiXzhqWoAnpMbJZCVkAOrDLHvChPaV1enNHqSwW6UfnDzO7HACAD8SGOXT5pEH66ZwRmjk0Xg6bVSU1zfrXxsN6cMUefbi/XC1tbrPLBOAHmLkCfOjP7+6TJF0yLlUjkiNNrgYA4EsxYQ5dOiFN549K0rpDlVpzoEI1TW1avr1E7+4+ounZ8ZoxJF5RoSFmlwrAJIQrwEf2l9Xpje0lkpi1AoCBLMxh13kjk3TWsARtKajW6v1HVV7fqlV7j2r1vqMamxatmUPjlRkXxr4sIMgQrgAfefTd/TIMae7YZI1OjTK7HABAHwuxWTUtO045g2O1u6RWq/eXK7+iUduLarS9qEZpMS7NGJKgCenRZpcKoJ8QrgAfOHC0Xq9vLZYk/fj84SZXAwDoT1aLRWPSojUmLVrF1U1ae7BCWwurVVzdrJc2HdabO0pUVtesb5+ZpdToULPLBdCHCFeAD/z+zd3yGNIFo5M0bhA/oQSAYJUWE6p5U9J10dgUbcir1MeHKlXT1KbH3jugJ1Yd1EVjU3TtzMGaNjiWJYPAAES4Ak7TxwcrtGLXEdmsFt1x0SizywEA+IFwp13njEzSWcMTlVtSqwNH67XuUKXe2F6iN7aXaHRqlL41PVOXTUpTpIsGGMBAQbgCToPHY+g3b+RKkq6alqHhdAgEAHyGzWrRuEHR+u2V45VbUqu/r8nTq1uKlFtSq3te3aHfvJGrr05M0zenZ2pienTQz2b9c12B2SV0c/X0TLNLQIAhXAGn4fWtxdpeVKMIp123XTjC7HIAAH5sdGqUfjdvgn528Si9tKlIz31SoP1l9XphQ6Fe2FCo0alRuvqMDF02eZCimM0CAhLhCuil5ja3/vDf3ZKkH5w7VAkRTpMrAgAEgpgwh248K1s3zBqsDflVem5dgf6zvUS5JbX6+Ws79ZvluZo7NkVXTknXWcMSZLMG92wWEEgIV0AvLf3wkIprmpUW7dKNZ2WbXQ4AIMBYLBZNGxynaYPjdO9XxuiVzR2zWXuP1Ou1LcV6bUuxkqOcunzSIM3LSedweiAAEK6AXjhc1ajH3tsvSfp/F42UK8RmckUAgEAWE+bQ9bOydd3Mwdp2uEYvbTqs17cW60hti/7ywUH95YODGjcoSvOmpOuS8alKjnKZXTKAHhCugFNkGIbueXWHGlvdmjY4VpdNHGR2SQCAAcJisWhiRowmZsToni+P0Xt7yvTSxsN6b0+ZdhTVakfRLt33n12amhWri8el6uLxKZydBfgRwhVwil7fWqz39xyVw2bVoisnyMpaeABAH3DYrZo7NkVzx6aosqFV/9lWrFc3F2lTQbXW51VpfV6V7vvPLk3JjNEl41N10bgUpceGmV02ENQIV8ApqGpo1X3/t0uS9KPzh2lYUoTJFQEAgkFcuEPXzBisa2YMVklNk/67o1TLt5doQ36VNhVUa1NBtX79Rq5GpUTq7BGJOmdEoqYOjpXTzrJ1oD8RroBT8JvluapoaNWI5AgtOGeo2eUAAIJQanSorp+VretnZetIbbM3aH2SV6ndpXXaXVqnv35wUKEhNs0cGq9zRnaErcy4sKA/Rwvoa4Qr4CR9sPeo/r3xsCwWadGVE+SwW80uCQAQ5JKjXLp25mBdO3OwKhta9eH+cq3ac1Sr9h5VeX2L3tldpnd2l0mSUqJcysmK1ZSsWOVkxWpMahT/LwN8jHAFnISjdS1a+OJWSdI1Z2YpJyvW5IoAAOguLtyhr05M01cnpsnjMZRbWqtVe4/qg71HtSGvSqW1zXpje4ne2F4iSXLarZqYEaOcrFiNTYvSqJQoDY4Pk91G4AJ6i3AFfAGPx9BP/7VV5fUtGpkcqTsvGW12SQAAnJDVatHYtGiNTYvWzecOU1OrW1sPV2tjfpU25VdpY0GVqhvb9MmhSn1yqNL7OofdquFJERqZEqlRKZEamRKlIQnhSosJ5TBj4CQQroAv8NSHB/XB3qNyhVj156snc6YVACDghDpsOnNIvM4cEi+p41iRA0cbtCm/SpsKqpRbWqe9pXVqanNrZ3GtdhbXdnt9iM2i9NgwZcZ1PLLiO35Njw3ToJhQRYXa2c8FiHAFnNDWwmr94b97JEn3XjpWI5IjTa4IAIDTZ7FYNCwpQsOSIvSNaRmSOlZqFFY1andpnfaU1ml3aa32lNapsLJJrW6PDpU36FB5Q4/vF+6wKS0mVINiQzt+jQlVWoxLadEdv0+JdimE5YYIAoQr4Dgq6lv0o+c2qd1j6MvjU/XNMzLMLgkAgD5jtVqUFR+urPhwzR2b4r3u9hgqrW1WfkWDCisblV/RqPzKRhVUNKq4ukkVDa1qaHVrX1m99pXV9/jeFouUHOnqCFze8NX1cGlQTKiiQ0P666MCfYZwBfSgpd2tBc9uVGFlkzLjwvTbK8ez3AEAEJRsVosGdQYi9XAKSVOrWyU1TSqublZxdZMOVzepuNujWa1uj0prm1Va26xNBdU9fp0wh03hTrviwhxKjnIpOcqp5CiXEiOdzHohYBCugM8xDEN3vrxd6/OqFOmya9l1U/lpGgAAxxHqsGlIYoSGJEb0+LzHY6iiodUbtoqqPw1ixTUd18rrW9XY6lZjq1tH61q050id9/UWSfERHYErJdqlzNgwZcSFsQcafolwBXzOkvcP6OVNRbJZLXrs6ikalsQ+KwAAestqtSgx0qnESKcmZsT0OKa5za2Smmb979p8lde36Ehts47Udvza1OZWeX2ryutbvY02LJISI53e5hoZcWFKiHDKyioTmIxwBXzGa1uK9MBbHQ0sfvnVsTp7RKLJFQEAMPC5QmzKTgj3NtnoYhiG6lvavUGrqLpJBZWNqmxoVVldi8rqWrQhv0pSx7LCYUkRGpEUqWHJEYpyseoE/Y9wBXR6Y1uJ96Dg62YO1nfOzDK5IgAAgpvFYlGkK0SRrpBuoauuuU2FlR1Bq6CyUUXVjWpsdWvb4RptO1wjSUqNdml4UqRGJEcoMz5Mdiv7ttD3CFeApLd2luqW5zfL7TH0tZx03XvpGLNLAgAAxxHpCtGYtBCNSYuS1NHR8HBVo/YeqdPeI/Uqrm5SSU2zSmqa9cG+o3LarRqZEqnxg6I1IjmSBhnoMxbDMAyzi/A3tbW1io6OVk1NjaKioswuB33sndwjWvDsRrW5DV0+KU1//MakbqfQ/3NdgYnVAQCAU1Xf0q79ZfXad6ROe8vq1dDS7n3OYesIWuMGRWtkcqQc9uMHraunZ/ZHufBzp5INmLlCUHt502Hd8dI2tbkNfXlCqh78+sRuwQoAAASeCKddkzJiNCkjRh7D0OGqJu0oqtGO4hpVN7Zpe1GNthfVKMRm0cjkSE3KiNWIlAiWDuK0Ea4QlAzD0GPv7deDK/ZKki6dkKo/zZ8kO8sEAAAYUKwWizLjwpQZF6aLx6WoqLojaG0vqlFVY5t2FNdqR3Gtwhw2TUyP0ZTMWKXFuDjfEr1CuELQaXd79PPXdui5TwolSd8/e4juuGiUrMxYAQAwoFksFqXHhik9Nkxzx6aouKZZ2wqrtaWwWnUt7Vp7sEJrD1YoKdKpKZmxOn9UklKiXWaXjQDCnqsesOdq4DpS26yfPLdZ6w5VymKRfvXVsbpmxuATvoY9VwAADGxuj6EDR+u1qaBKu4pr1e7p+PbYapFmDUvQvCnpmjs2RaEODi4ORuy5Anqwet9R3fr8FlU0tCrcYdOf5k/SnLEpZpcFAABMZrNaNCI5UiOSI9Xc5tb2ohptLqhSXkWjVu8r1+p95Qp32PTlCan6Wk6Gpg2OZdkgesTMVQ+YuRpYWts9+vO7+/Toe/tlGNKolEgt+dYUDUmM+OIXi5krAACC1axh8Xp5U5Fe3nxYhZVN3utZ8WGaNyVd83LSNSgm1MQK0R9OJRsQrnpAuBo4NhVU6WcvbdPeI/WSpG+ekalffGWMXCEnP61PuAIAIDh1tWI3DEPr86r0742FemNbiRpa3ZIki0WaOTReX8tJ10VjU1k2OEARrk4T4Srw1be0648r9uhva/JkGFJ8uEO/umysLp2QdsrvRbgCACA49XTOVWNru/67o1T/3nhYaw5UeK9HOO26dEKqvpaTrpwslg0OJOy5QtBqc3v0/PpCPfz2XpXXt0qSrpwySD//8hjFhjtMrg4AAAS6MIddV05J15VT0lVY2aiXNxXp35sKVVjZpOfXF+r59YXKTgjXZZPS9NWJaSe9DQEDAzNXPWDmKvB4PIbe2lmqB97ao4PlDZKkwfFhuu+ycTp7ROJpvTczVwAABKeeZq564vEYWp9XqX9vPKw3tpeosXPZoCSNGxSlr05M06UT0pTG/qyAxLLA00S4Chwt7W69trlYf/nggA4c7QhV8eEO3XLBcH3zjEyF+OBQYMIVAADB6WTD1Wc1tLTrrZ2len1rsT7cV+5t6y5J0wbH6qsT0zR3XIqSIjk/K1AQrk4T4cr/ldY0618bCvXsunwdqW2RJEW67Lpu5mB97+whinSF+OxrEa4AAAhOvQlXn1XZ0Ko3d5To9S3F+iSvUp/9rntSRowuHJOsC8cka3hSBHu0/Bjh6jQRrvxTS7tbq/Yc1QvrC/XenjJ1/SAoOcqpG8/K1jfPyPRpqOpCuAIAIDidbrj6rJKaJr2xrUT/t61EWwuruz2XFR+mC0Yn64LRyZo6ONYnK2/gO4Sr00S48h/NbW59uK9cy7eXaOWuI6prafc+d8bgOF11Roa+PCFVTnvftT4lXAEAEJx8Ga4+60hts97JLdPbuUf04f5ytbZ7vM+FO2w6IztOM4bGa+bQBI1OjZLNyqyWmegWiIBlGIYOljdo9d6jWrX3qNYerFBz26d/4SRHOfXViWmaPy1Tw5LovgMAAAJPcpRLV0/P1NXTM9XQ0q7V+8r1du4Rvbu7TJUNrXpvz1G9t+eoJCk6NETTs+M0c2i8pg6O08iUSGa2/BjhCqZqbnNrd2mdNuVXaX1epdbnVam8vqXbmJQoly4al6IvT0hVTmasrPz0BgAADBDhTrsuGpeii8alyOMxtLu0TmsOlGvtgQqtO1SpmqY2rdh1RCt2HZEkOexWjUmN0sT0aI1Pj9HE9GgNSYxgdstPEK7QLwzDUElNs/YeqdP+snrtKa3TjuJa7TtS162LjiQ5bFZNHRyrc0Yk6pyRiRqZHMkmTwAAMOBZrRaNSYvSmLQo3TR7iNrdHm0vqtHagxVae6BCWwqrVdfcri2F1dpSWC0pX1LHUsKRKZEamhihYUkRGpoYoaFJEcqIDZWdWa5+ZXq4WrJkiR544AGVlJRo7NixWrx4sWbPnn3c8atWrdLChQu1c+dOpaWl6X/+53+0YMGCbmNeeukl/fznP9eBAwc0dOhQ/eY3v9EVV1zR1x8lqLk9hqobW1VS06zCykYVVjXqcFVT5z836XBVY7flfZ8VF+7QhPRoTRscp2mD4zQhPVqukL7bQwUAABAI7DarJmfGanJmrG4+d5g8HkP5lY3adrha2w7XaPvhGu0orlFDq1ubCqq1qaC62+tDbBYNjg9XVny40mJcSo0O9f6aGu1SSrSLJYY+Zmq4euGFF3TrrbdqyZIlmjVrlv7yl7/o4osv1q5du5SZeewGwkOHDumSSy7Rd7/7XT377LP66KOPdPPNNysxMVHz5s2TJK1du1bz58/X/fffryuuuEKvvPKKvvGNb+jDDz/U9OnT+/sjBgzDMNTuMdTc5lZzm0eNre2qa25XbXOb6prbVd/crrrOf65qbFN5fYsqGlpUUd+q8voWVTa0yvMFrVHsVosGJ4RrRHKEhiVFamxalMYPilZqtIuZKQAAgC9gtVqUnRCu7IRwXTZpkKSOH3AfOFrvXR104GiDDpTV62B5vZrbPNpXVq99ZfU9vp/FIsWHOxUXHqK4cIfiwh2KDfv015iwEEU47Ypw2hXutCvC9ek/h4XY2KrRA1O7BU6fPl1TpkzR448/7r02evRoXX755Vq0aNEx4++44w69/vrrys3N9V5bsGCBtm7dqrVr10qS5s+fr9raWr355pveMRdddJFiY2P13HPPnVRd/tQt8P09ZVqfVym3R3J7PHJ7JI9hyO0x5DYMud0dv3q6fu/59NE1rr3zn9vchlraPWppc6ul3aPmz/za3Ob+wnB0MhIinMqIC1V6bJgyYkOVERem9NhQZcSGKS0mVA574P10hG6BAAAEp77qFtgfPB5DxTVN2l9Wr8KqJpVUN6mkplnFnb+W1jSr1d3zqqKT5bBZ5bRb5bB/9lebnCHWjuc6f7XbrLJZLLJZLbJaLbJZ1PnrZ691/rPFIpv10+d/cO7QPjlq51QERLfA1tZWbdy4UT/72c+6XZ8zZ47WrFnT42vWrl2rOXPmdLs2d+5cLV26VG1tbQoJCdHatWt12223HTNm8eLFx62lpaVFLS2fNlGoqamR1PEv0mzvbc/X0x/l9fvXDXVYFem0K8IV4v0JRVTnTyyiwxyKDw/p+ElHhENxYQ7FR3T8hOP463rdam6sV3O/fgrfaGyoM7sEAABgAn/4XvB0RNmkKakuTUl1SYrt9pzHY6iyoVVH65tV3diuqsZWVTe2qqqhTdVNrapqaFVNc7saWj591Le2q7Hl0x/IN3c++tK88XEyIl19/FVOrOu/g5OZkzItXJWXl8vtdis5Obnb9eTkZJWWlvb4mtLS0h7Ht7e3q7y8XKmpqccdc7z3lKRFixbpV7/61THXMzIyTvbjAAAAYID5rtkFQMMWm13Bp+rq6hQdHX3CMaY3tPj8XhvDME64/6an8Z+/fqrveeedd2rhwoXe33s8HlVWVio+Pp69QCaqra1VRkaGCgsLTV+eiS/G/Qoc3KvAwv0KHNyrwML9Chxm3yvDMFRXV6e0tLQvHGtauEpISJDNZjtmRqmsrOyYmacuKSkpPY632+2Kj48/4ZjjvackOZ1OOZ3ObtdiYmJO9qOgj0VFRfGXXgDhfgUO7lVg4X4FDu5VYOF+BQ4z79UXzVh1Ma27gMPhUE5OjlauXNnt+sqVKzVz5sweXzNjxoxjxq9YsUJTp05VSEjICccc7z0BAAAAwBdMXRa4cOFCfec739HUqVM1Y8YM/fWvf1VBQYH33Ko777xTRUVFeuaZZyR1dAZ89NFHtXDhQn33u9/V2rVrtXTp0m5dAG+55RadffbZ+v3vf6/LLrtMr732mt5++219+OGHpnxGAAAAAMHB1HA1f/58VVRU6L777lNJSYnGjRun5cuXKysrS5JUUlKigoJP22BnZ2dr+fLluu222/TYY48pLS1NjzzyiPeMK0maOXOmnn/+ed1zzz36+c9/rqFDh+qFF17gjKsA5HQ69Ytf/OKYJZvwT9yvwMG9Cizcr8DBvQos3K/AEUj3ytRzrgAAAABgoAi8E10BAAAAwA8RrgAAAADABwhXAAAAAOADhCsAAAAA8AHCFfzWkiVLlJ2dLZfLpZycHK1evdrskoLeBx98oK985StKS0uTxWLRq6++2u15wzD0y1/+UmlpaQoNDdW5556rnTt3mlNskFu0aJGmTZumyMhIJSUl6fLLL9eePXu6jeF++Y/HH39cEyZM8B6QOWPGDL355pve57lX/mvRokWyWCy69dZbvde4X/7jl7/8pSwWS7dHSkqK93nulX8pKirSt7/9bcXHxyssLEyTJk3Sxo0bvc8Hwv0iXMEvvfDCC7r11lt19913a/PmzZo9e7Yuvvjibq350f8aGho0ceJEPfrooz0+/4c//EEPPfSQHn30Ua1fv14pKSm68MILVVdX18+VYtWqVfrhD3+ojz/+WCtXrlR7e7vmzJmjhoYG7xjul/9IT0/X7373O23YsEEbNmzQ+eefr8suu8z7TQP3yj+tX79ef/3rXzVhwoRu17lf/mXs2LEqKSnxPrZv3+59jnvlP6qqqjRr1iyFhITozTff1K5du/THP/5RMTEx3jEBcb8MwA+dccYZxoIFC7pdGzVqlPGzn/3MpIrweZKMV155xft7j8djpKSkGL/73e+815qbm43o6GjjiSeeMKFCfFZZWZkhyVi1apVhGNyvQBAbG2s89dRT3Cs/VVdXZwwfPtxYuXKlcc455xi33HKLYRj82fI3v/jFL4yJEyf2+Bz3yr/ccccdxllnnXXc5wPlfjFzBb/T2tqqjRs3as6cOd2uz5kzR2vWrDGpKnyRQ4cOqbS0tNt9czqdOuecc7hvfqCmpkaSFBcXJ4n75c/cbreef/55NTQ0aMaMGdwrP/XDH/5QX/7yl3XBBRd0u8798j/79u1TWlqasrOzddVVV+ngwYOSuFf+5vXXX9fUqVP19a9/XUlJSZo8ebKefPJJ7/OBcr8IV/A75eXlcrvdSk5O7nY9OTlZpaWlJlWFL9J1b7hv/scwDC1cuFBnnXWWxo0bJ4n75Y+2b9+uiIgIOZ1OLViwQK+88orGjBnDvfJDzz//vDZt2qRFixYd8xz3y79Mnz5dzzzzjN566y09+eSTKi0t1cyZM1VRUcG98jMHDx7U448/ruHDh+utt97SggUL9JOf/ETPPPOMpMD5s2U3uwDgeCwWS7ffG4ZxzDX4H+6b//nRj36kbdu26cMPPzzmOe6X/xg5cqS2bNmi6upqvfTSS7r22mu1atUq7/PcK/9QWFioW265RStWrJDL5TruOO6Xf7j44ou9/zx+/HjNmDFDQ4cO1d///nedeeaZkrhX/sLj8Wjq1Kn67W9/K0maPHmydu7cqccff1zXXHONd5y/3y9mruB3EhISZLPZjvkpRFlZ2TE/rYD/6Oq+xH3zLz/+8Y/1+uuv67333lN6err3OvfL/zgcDg0bNkxTp07VokWLNHHiRD388MPcKz+zceNGlZWVKScnR3a7XXa7XatWrdIjjzwiu93uvSfcL/8UHh6u8ePHa9++ffzZ8jOpqakaM2ZMt2ujR4/2NjMLlPtFuILfcTgcysnJ0cqVK7tdX7lypWbOnGlSVfgi2dnZSklJ6XbfWltbtWrVKu6bCQzD0I9+9CO9/PLLevfdd5Wdnd3tee6X/zMMQy0tLdwrP/OlL31J27dv15YtW7yPqVOn6lvf+pa2bNmiIUOGcL/8WEtLi3Jzc5WamsqfLT8za9asY44M2bt3r7KysiQF0P+3zOqkAZzI888/b4SEhBhLly41du3aZdx6661GeHi4kZeXZ3ZpQa2urs7YvHmzsXnzZkOS8dBDDxmbN2828vPzDcMwjN/97ndGdHS08fLLLxvbt283vvnNbxqpqalGbW2tyZUHnx/84AdGdHS08f777xslJSXeR2Njo3cM98t/3HnnncYHH3xgHDp0yNi2bZtx1113GVar1VixYoVhGNwrf/fZboGGwf3yJz/96U+N999/3zh48KDx8ccfG5deeqkRGRnp/X6Ce+U/PvnkE8Nutxu/+c1vjH379hn/+Mc/jLCwMOPZZ5/1jgmE+0W4gt967LHHjKysLMPhcBhTpkzxtpCGed577z1D0jGPa6+91jCMjjapv/jFL4yUlBTD6XQaZ599trF9+3Zziw5SPd0nScbTTz/tHcP98h833HCD9++7xMRE40tf+pI3WBkG98rffT5ccb/8x/z5843U1FQjJCTESEtLM6688kpj586d3ue5V/7l//7v/4xx48YZTqfTGDVqlPHXv/612/OBcL8shmEY5syZAQAAAMDAwZ4rAAAAAPABwhUAAAAA+ADhCgAAAAB8gHAFAAAAAD5AuAIAAAAAHyBcAQAAAIAPEK4AAAAAwAcIVwAAAADgA4QrAAB6cN111+nyyy8/qbHnnnuubr311hOOGTx4sBYvXuz9vcVi0auvvipJysvLk8Vi0ZYtW3pVKwDAPxCuAAAB42RCjC9e0xfWr1+v733ve2aXAQDoQ3azCwAAIBgkJiaaXQIAoI8xcwUACAjXXXedVq1apYcfflgWi0UWi0V5eXlatWqVzjjjDDmdTqWmpupnP/uZ2tvbT/gat9utG2+8UdnZ2QoNDdXIkSP18MMPn1Z97e3t+tGPfqSYmBjFx8frnnvukWEY3uc/vywQADDwEK4AAAHh4Ycf1owZM/Td735XJSUlKikpUUhIiC655BJNmzZNW7du1eOPP66lS5fq17/+9XFfk5GRIY/Ho/T0dL344ovatWuX7r33Xt1111168cUXe13f3//+d9ntdq1bt06PPPKI/vSnP+mpp57y1ccHAAQAlgUCAAJCdHS0HA6HwsLClJKSIkm6++67lZGRoUcffVQWi0WjRo1ScXGx7rjjDt177709vkaSbDabfvWrX3l/n52drTVr1ujFF1/UN77xjV7Vl5GRoT/96U+yWCwaOXKktm/frj/96U/67ne/e3ofHAAQMJi5AgAErNzcXM2YMUMWi8V7bdasWaqvr9fhw4dP+NonnnhCU6dOVWJioiIiIvTkk0+qoKCg17WceeaZ3eqYMWOG9u3bJ7fb3ev3BAAEFsIVACBgGYbRLdB0XZN0zPXPevHFF3Xbbbfphhtu0IoVK7RlyxZdf/31am1t7dN6AQADG8sCAQABw+FwdJsJGjNmjF566aVuIWvNmjWKjIzUoEGDenyNJK1evVozZ87UzTff7L124MCB06rt448/Pub3w4cPl81mO633BQAEDmauAAABY/DgwVq3bp3y8vJUXl6um2++WYWFhfrxj3+s3bt367XXXtMvfvELLVy4UFartcfXeDweDRs2TBs2bNBbb72lvXv36uc//7nWr19/WrUVFhZq4cKF2rNnj5577jn9+c9/1i233OKLjw0ACBCEKwBAwLj99ttls9k0ZswYJSYmqq2tTcuXL9cnn3yiiRMnasGCBbrxxht1zz33HPc1BQUFWrBgga688krNnz9f06dPV0VFRbdZrN645ppr1NTUpDPOOEM//OEP9eMf/5hDgwEgyFiMzx7CAQAAAADoFWauAAAAAMAHCFcAAJxAQUGBIiIijvs4nfbtAICBhWWBAACcQHt7u/Ly8o77/ODBg2W303wXAEC4AgAAAACfYFkgAAAAAPgA4QoAAAAAfIBwBQAAAAA+QLgCAAAAAB8gXAEAAACADxCuAAAAAMAHCFcAAAAA4AP/H1ZVvRmcGzvIAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#-->distplot\n",
    "#It will take only one column\n",
    "plt.figure(figsize=(10,7))#size of the graph\n",
    "sns.distplot(tips['total_bill'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b3c172b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_10852\\572135213.py:2: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(tips['total_bill'],bins=100)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='total_bill', ylabel='Density'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))#size of the graph\n",
    "sns.distplot(tips['total_bill'],bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "375060e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_10852\\1710614074.py:2: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(tips['total_bill'],bins=100,kde=False)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='total_bill'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))#size of the graph\n",
    "sns.distplot(tips['total_bill'],bins=100,kde=False)#kde helps to display the graph curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "76297894",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_10852\\3075034415.py:2: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(tips['total_bill'],bins=100,kde=True,hist=False)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='total_bill', ylabel='Density'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))#size of the graph\n",
    "sns.distplot(tips['total_bill'],bins=100,kde=True,hist=False)#hist displays the bar graph in the background"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ed9d88e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_10852\\1505147209.py:2: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(tips['total_bill'],bins=100,kde=True,hist=True,color='purple')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='total_bill', ylabel='Density'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))#size of the graph\n",
    "sns.distplot(tips['total_bill'],bins=100,kde=True,hist=True,color='purple')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "43f9ce94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x25d9d212f90>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#jointplot()\n",
    "sns.jointplot(x='total_bill',y='tip',data=tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "ae6ac97f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x25d9d2ebb50>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#jointplot()\n",
    "sns.jointplot(x='total_bill',y='tip',data=tips,kind='hex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "09f8b54b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x25d9d677850>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#jointplot()\n",
    "sns.jointplot(x='total_bill',y='tip',data=tips,kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0171d953",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x25d9dad4310>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#jointplot()\n",
    "sns.jointplot(x='total_bill',y='tip',data=tips,kind='kde')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "93c51ade",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x25d9ee97090>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#jointplot()\n",
    "sns.jointplot(x='total_bill',y='tip',data=tips,kind='kde',color='purple')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "39d161a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\axisgrid.py:118: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x25da4f36010>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850.25x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Pairpolot\n",
    "import seaborn as sns\n",
    "sns.pairplot(tips,hue=\"sex\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "335367bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\axisgrid.py:118: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x25da6ab6e50>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 850.25x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.pairplot(tips,hue=\"sex\",palette=\"coolwarm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "86c25c13",
   "metadata": {},
   "outputs": [],
   "source": [
    "#logistic regression\n",
    "#logistic regression is a statistical method used to model the relationship between a binary dependent variable and one at more independent variables\n",
    "#in logistic regression ,the dependent variable is binary,meaning it can only take on two values , labelled as 0 or 1\n",
    "#The independent variables can be either continous or catagorial\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8c4b10f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: scikit-learn in c:\\programdata\\anaconda3\\lib\\site-packages (1.3.0)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from scikit-learn) (1.24.3)\n",
      "Requirement already satisfied: scipy>=1.5.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from scikit-learn) (1.11.1)\n",
      "Requirement already satisfied: joblib>=1.1.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from scikit-learn) (1.2.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from scikit-learn) (2.2.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1184e99e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.metrics import accuracy_score,precision_score,recall_score,f1_score,confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4767c1a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=np.array([0.3,0.6,0.8,0.2,0.4,0.9,0.1,0.7,0.5,0.6])\n",
    "y_true=np.array([0,1,1,0,0,1,0,1,0,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d7847c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Accuracy\n",
    "#Accuracy measure the percentage of currently classified instances out of all instances\n",
    "accuracy=accuracy_score(y_true,np.round(y_pred))\n",
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4fce3066",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Percision\n",
    "#percision measured the proportion of true positive prediction out of all positive predictions\n",
    "#precision=true positive/all positive\n",
    "precision=precision_score(y_true,np.round(y_pred))\n",
    "precision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4aa01021",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Recall\n",
    "#recall=true positive/actual positive\n",
    "#recall measures the proportion of true positive prediction out of all actual positive cases\n",
    "recall=recall_score(y_true,np.round(y_pred))\n",
    "recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "96a16cd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#F1 score\n",
    "#It is the mean of precision and recall\n",
    "f1_score=f1_score(y_true,np.round(y_pred))\n",
    "f1_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4c5e7176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5, 0],\n",
       "       [0, 5]], dtype=int64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#confusion matrix\n",
    "#It is a table that gives the performance of the classification model.\n",
    "#It shows true positive ,true negative ,false position,false negative\n",
    "matrix=confusion_matrix(y_true,np.round((y_pred)))\n",
    "matrix\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "93c13d6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Eg:1\n",
    "#Logisic Expression\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "419147c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        [5.8, 2.7, 4.1, 1. ],\n",
       "        [6.2, 2.2, 4.5, 1.5],\n",
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       "        [6.7, 3. , 5. , 1.7],\n",
       "        [6. , 2.9, 4.5, 1.5],\n",
       "        [5.7, 2.6, 3.5, 1. ],\n",
       "        [5.5, 2.4, 3.8, 1.1],\n",
       "        [5.5, 2.4, 3.7, 1. ],\n",
       "        [5.8, 2.7, 3.9, 1.2],\n",
       "        [6. , 2.7, 5.1, 1.6],\n",
       "        [5.4, 3. , 4.5, 1.5],\n",
       "        [6. , 3.4, 4.5, 1.6],\n",
       "        [6.7, 3.1, 4.7, 1.5],\n",
       "        [6.3, 2.3, 4.4, 1.3],\n",
       "        [5.6, 3. , 4.1, 1.3],\n",
       "        [5.5, 2.5, 4. , 1.3],\n",
       "        [5.5, 2.6, 4.4, 1.2],\n",
       "        [6.1, 3. , 4.6, 1.4],\n",
       "        [5.8, 2.6, 4. , 1.2],\n",
       "        [5. , 2.3, 3.3, 1. ],\n",
       "        [5.6, 2.7, 4.2, 1.3],\n",
       "        [5.7, 3. , 4.2, 1.2],\n",
       "        [5.7, 2.9, 4.2, 1.3],\n",
       "        [6.2, 2.9, 4.3, 1.3],\n",
       "        [5.1, 2.5, 3. , 1.1],\n",
       "        [5.7, 2.8, 4.1, 1.3],\n",
       "        [6.3, 3.3, 6. , 2.5],\n",
       "        [5.8, 2.7, 5.1, 1.9],\n",
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       "        [6.4, 2.7, 5.3, 1.9],\n",
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       "        [6.4, 3.2, 5.3, 2.3],\n",
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       "        [7.7, 2.6, 6.9, 2.3],\n",
       "        [6. , 2.2, 5. , 1.5],\n",
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       "        [7.7, 2.8, 6.7, 2. ],\n",
       "        [6.3, 2.7, 4.9, 1.8],\n",
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       "        [7.4, 2.8, 6.1, 1.9],\n",
       "        [7.9, 3.8, 6.4, 2. ],\n",
       "        [6.4, 2.8, 5.6, 2.2],\n",
       "        [6.3, 2.8, 5.1, 1.5],\n",
       "        [6.1, 2.6, 5.6, 1.4],\n",
       "        [7.7, 3. , 6.1, 2.3],\n",
       "        [6.3, 3.4, 5.6, 2.4],\n",
       "        [6.4, 3.1, 5.5, 1.8],\n",
       "        [6. , 3. , 4.8, 1.8],\n",
       "        [6.9, 3.1, 5.4, 2.1],\n",
       "        [6.7, 3.1, 5.6, 2.4],\n",
       "        [6.9, 3.1, 5.1, 2.3],\n",
       "        [5.8, 2.7, 5.1, 1.9],\n",
       "        [6.8, 3.2, 5.9, 2.3],\n",
       "        [6.7, 3.3, 5.7, 2.5],\n",
       "        [6.7, 3. , 5.2, 2.3],\n",
       "        [6.3, 2.5, 5. , 1.9],\n",
       "        [6.5, 3. , 5.2, 2. ],\n",
       "        [6.2, 3.4, 5.4, 2.3],\n",
       "        [5.9, 3. , 5.1, 1.8]]),\n",
       " 'target': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "        0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "        1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "        1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "        2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "        2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]),\n",
       " 'frame': None,\n",
       " 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='<U10'),\n",
       " 'DESCR': '.. _iris_dataset:\\n\\nIris plants dataset\\n--------------------\\n\\n**Data Set Characteristics:**\\n\\n    :Number of Instances: 150 (50 in each of three classes)\\n    :Number of Attributes: 4 numeric, predictive attributes and the class\\n    :Attribute Information:\\n        - sepal length in cm\\n        - sepal width in cm\\n        - petal length in cm\\n        - petal width in cm\\n        - class:\\n                - Iris-Setosa\\n                - Iris-Versicolour\\n                - Iris-Virginica\\n                \\n    :Summary Statistics:\\n\\n    ============== ==== ==== ======= ===== ====================\\n                    Min  Max   Mean    SD   Class Correlation\\n    ============== ==== ==== ======= ===== ====================\\n    sepal length:   4.3  7.9   5.84   0.83    0.7826\\n    sepal width:    2.0  4.4   3.05   0.43   -0.4194\\n    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\\n    petal width:    0.1  2.5   1.20   0.76    0.9565  (high!)\\n    ============== ==== ==== ======= ===== ====================\\n\\n    :Missing Attribute Values: None\\n    :Class Distribution: 33.3% for each of 3 classes.\\n    :Creator: R.A. Fisher\\n    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\\n    :Date: July, 1988\\n\\nThe famous Iris database, first used by Sir R.A. Fisher. The dataset is taken\\nfrom Fisher\\'s paper. Note that it\\'s the same as in R, but not as in the UCI\\nMachine Learning Repository, which has two wrong data points.\\n\\nThis is perhaps the best known database to be found in the\\npattern recognition literature.  Fisher\\'s paper is a classic in the field and\\nis referenced frequently to this day.  (See Duda & Hart, for example.)  The\\ndata set contains 3 classes of 50 instances each, where each class refers to a\\ntype of iris plant.  One class is linearly separable from the other 2; the\\nlatter are NOT linearly separable from each other.\\n\\n.. topic:: References\\n\\n   - Fisher, R.A. \"The use of multiple measurements in taxonomic problems\"\\n     Annual Eugenics, 7, Part II, 179-188 (1936); also in \"Contributions to\\n     Mathematical Statistics\" (John Wiley, NY, 1950).\\n   - Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.\\n     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\\n   - Dasarathy, B.V. (1980) \"Nosing Around the Neighborhood: A New System\\n     Structure and Classification Rule for Recognition in Partially Exposed\\n     Environments\".  IEEE Transactions on Pattern Analysis and Machine\\n     Intelligence, Vol. PAMI-2, No. 1, 67-71.\\n   - Gates, G.W. (1972) \"The Reduced Nearest Neighbor Rule\".  IEEE Transactions\\n     on Information Theory, May 1972, 431-433.\\n   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al\"s AUTOCLASS II\\n     conceptual clustering system finds 3 classes in the data.\\n   - Many, many more ...',\n",
       " 'feature_names': ['sepal length (cm)',\n",
       "  'sepal width (cm)',\n",
       "  'petal length (cm)',\n",
       "  'petal width (cm)'],\n",
       " 'filename': 'iris.csv',\n",
       " 'data_module': 'sklearn.datasets.data'}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "iris=load_iris()\n",
    "iris"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0423e800",
   "metadata": {},
   "outputs": [
    {
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       "<p>150 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)\n",
       "0                  5.1               3.5                1.4               0.2\n",
       "1                  4.9               3.0                1.4               0.2\n",
       "2                  4.7               3.2                1.3               0.2\n",
       "3                  4.6               3.1                1.5               0.2\n",
       "4                  5.0               3.6                1.4               0.2\n",
       "..                 ...               ...                ...               ...\n",
       "145                6.7               3.0                5.2               2.3\n",
       "146                6.3               2.5                5.0               1.9\n",
       "147                6.5               3.0                5.2               2.0\n",
       "148                6.2               3.4                5.4               2.3\n",
       "149                5.9               3.0                5.1               1.8\n",
       "\n",
       "[150 rows x 4 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "iris_df=pd.DataFrame(data=iris.data,columns=iris.feature_names)\n",
    "iris_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "91fd3cb6",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)  \\\n",
       "0                  5.1               3.5                1.4               0.2   \n",
       "1                  4.9               3.0                1.4               0.2   \n",
       "2                  4.7               3.2                1.3               0.2   \n",
       "3                  4.6               3.1                1.5               0.2   \n",
       "4                  5.0               3.6                1.4               0.2   \n",
       "..                 ...               ...                ...               ...   \n",
       "145                6.7               3.0                5.2               2.3   \n",
       "146                6.3               2.5                5.0               1.9   \n",
       "147                6.5               3.0                5.2               2.0   \n",
       "148                6.2               3.4                5.4               2.3   \n",
       "149                5.9               3.0                5.1               1.8   \n",
       "\n",
       "     Target  \n",
       "0         0  \n",
       "1         0  \n",
       "2         0  \n",
       "3         0  \n",
       "4         0  \n",
       "..      ...  \n",
       "145       2  \n",
       "146       2  \n",
       "147       2  \n",
       "148       2  \n",
       "149       2  \n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_df=pd.DataFrame(data=iris.data,columns=iris.feature_names)\n",
    "iris_df['Target']=iris.target\n",
    "iris_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e6599058",
   "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>sepal length (cm)</th>\n",
       "      <th>sepal width (cm)</th>\n",
       "      <th>petal length (cm)</th>\n",
       "      <th>petal width (cm)</th>\n",
       "      <th>Target</th>\n",
       "      <th>Target.names</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)  \\\n",
       "0                  5.1               3.5                1.4               0.2   \n",
       "1                  4.9               3.0                1.4               0.2   \n",
       "2                  4.7               3.2                1.3               0.2   \n",
       "3                  4.6               3.1                1.5               0.2   \n",
       "4                  5.0               3.6                1.4               0.2   \n",
       "..                 ...               ...                ...               ...   \n",
       "145                6.7               3.0                5.2               2.3   \n",
       "146                6.3               2.5                5.0               1.9   \n",
       "147                6.5               3.0                5.2               2.0   \n",
       "148                6.2               3.4                5.4               2.3   \n",
       "149                5.9               3.0                5.1               1.8   \n",
       "\n",
       "     Target Target.names  \n",
       "0         0       setosa  \n",
       "1         0       setosa  \n",
       "2         0       setosa  \n",
       "3         0       setosa  \n",
       "4         0       setosa  \n",
       "..      ...          ...  \n",
       "145       2    virginica  \n",
       "146       2    virginica  \n",
       "147       2    virginica  \n",
       "148       2    virginica  \n",
       "149       2    virginica  \n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_df=pd.DataFrame(data=iris.data,columns=iris.feature_names)\n",
    "iris_df['Target']=iris.target\n",
    "iris_df['Target.names']=iris.target_names[iris.target]\n",
    "iris_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8e8c7cbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2],\n",
       "       [4.9, 3. , 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.3, 0.2],\n",
       "       [4.6, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.6, 1.4, 0.2],\n",
       "       [5.4, 3.9, 1.7, 0.4],\n",
       "       [4.6, 3.4, 1.4, 0.3],\n",
       "       [5. , 3.4, 1.5, 0.2],\n",
       "       [4.4, 2.9, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.1],\n",
       "       [5.4, 3.7, 1.5, 0.2],\n",
       "       [4.8, 3.4, 1.6, 0.2],\n",
       "       [4.8, 3. , 1.4, 0.1],\n",
       "       [4.3, 3. , 1.1, 0.1],\n",
       "       [5.8, 4. , 1.2, 0.2],\n",
       "       [5.7, 4.4, 1.5, 0.4],\n",
       "       [5.4, 3.9, 1.3, 0.4],\n",
       "       [5.1, 3.5, 1.4, 0.3],\n",
       "       [5.7, 3.8, 1.7, 0.3],\n",
       "       [5.1, 3.8, 1.5, 0.3],\n",
       "       [5.4, 3.4, 1.7, 0.2],\n",
       "       [5.1, 3.7, 1.5, 0.4],\n",
       "       [4.6, 3.6, 1. , 0.2],\n",
       "       [5.1, 3.3, 1.7, 0.5],\n",
       "       [4.8, 3.4, 1.9, 0.2],\n",
       "       [5. , 3. , 1.6, 0.2],\n",
       "       [5. , 3.4, 1.6, 0.4],\n",
       "       [5.2, 3.5, 1.5, 0.2],\n",
       "       [5.2, 3.4, 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.6, 0.2],\n",
       "       [4.8, 3.1, 1.6, 0.2],\n",
       "       [5.4, 3.4, 1.5, 0.4],\n",
       "       [5.2, 4.1, 1.5, 0.1],\n",
       "       [5.5, 4.2, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.2, 1.2, 0.2],\n",
       "       [5.5, 3.5, 1.3, 0.2],\n",
       "       [4.9, 3.6, 1.4, 0.1],\n",
       "       [4.4, 3. , 1.3, 0.2],\n",
       "       [5.1, 3.4, 1.5, 0.2],\n",
       "       [5. , 3.5, 1.3, 0.3],\n",
       "       [4.5, 2.3, 1.3, 0.3],\n",
       "       [4.4, 3.2, 1.3, 0.2],\n",
       "       [5. , 3.5, 1.6, 0.6],\n",
       "       [5.1, 3.8, 1.9, 0.4],\n",
       "       [4.8, 3. , 1.4, 0.3],\n",
       "       [5.1, 3.8, 1.6, 0.2],\n",
       "       [4.6, 3.2, 1.4, 0.2],\n",
       "       [5.3, 3.7, 1.5, 0.2],\n",
       "       [5. , 3.3, 1.4, 0.2],\n",
       "       [7. , 3.2, 4.7, 1.4],\n",
       "       [6.4, 3.2, 4.5, 1.5],\n",
       "       [6.9, 3.1, 4.9, 1.5],\n",
       "       [5.5, 2.3, 4. , 1.3],\n",
       "       [6.5, 2.8, 4.6, 1.5],\n",
       "       [5.7, 2.8, 4.5, 1.3],\n",
       "       [6.3, 3.3, 4.7, 1.6],\n",
       "       [4.9, 2.4, 3.3, 1. ],\n",
       "       [6.6, 2.9, 4.6, 1.3],\n",
       "       [5.2, 2.7, 3.9, 1.4],\n",
       "       [5. , 2. , 3.5, 1. ],\n",
       "       [5.9, 3. , 4.2, 1.5],\n",
       "       [6. , 2.2, 4. , 1. ],\n",
       "       [6.1, 2.9, 4.7, 1.4],\n",
       "       [5.6, 2.9, 3.6, 1.3],\n",
       "       [6.7, 3.1, 4.4, 1.4],\n",
       "       [5.6, 3. , 4.5, 1.5],\n",
       "       [5.8, 2.7, 4.1, 1. ],\n",
       "       [6.2, 2.2, 4.5, 1.5],\n",
       "       [5.6, 2.5, 3.9, 1.1],\n",
       "       [5.9, 3.2, 4.8, 1.8],\n",
       "       [6.1, 2.8, 4. , 1.3],\n",
       "       [6.3, 2.5, 4.9, 1.5],\n",
       "       [6.1, 2.8, 4.7, 1.2],\n",
       "       [6.4, 2.9, 4.3, 1.3],\n",
       "       [6.6, 3. , 4.4, 1.4],\n",
       "       [6.8, 2.8, 4.8, 1.4],\n",
       "       [6.7, 3. , 5. , 1.7],\n",
       "       [6. , 2.9, 4.5, 1.5],\n",
       "       [5.7, 2.6, 3.5, 1. ],\n",
       "       [5.5, 2.4, 3.8, 1.1],\n",
       "       [5.5, 2.4, 3.7, 1. ],\n",
       "       [5.8, 2.7, 3.9, 1.2],\n",
       "       [6. , 2.7, 5.1, 1.6],\n",
       "       [5.4, 3. , 4.5, 1.5],\n",
       "       [6. , 3.4, 4.5, 1.6],\n",
       "       [6.7, 3.1, 4.7, 1.5],\n",
       "       [6.3, 2.3, 4.4, 1.3],\n",
       "       [5.6, 3. , 4.1, 1.3],\n",
       "       [5.5, 2.5, 4. , 1.3],\n",
       "       [5.5, 2.6, 4.4, 1.2],\n",
       "       [6.1, 3. , 4.6, 1.4],\n",
       "       [5.8, 2.6, 4. , 1.2],\n",
       "       [5. , 2.3, 3.3, 1. ],\n",
       "       [5.6, 2.7, 4.2, 1.3],\n",
       "       [5.7, 3. , 4.2, 1.2],\n",
       "       [5.7, 2.9, 4.2, 1.3],\n",
       "       [6.2, 2.9, 4.3, 1.3],\n",
       "       [5.1, 2.5, 3. , 1.1],\n",
       "       [5.7, 2.8, 4.1, 1.3],\n",
       "       [6.3, 3.3, 6. , 2.5],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [7.1, 3. , 5.9, 2.1],\n",
       "       [6.3, 2.9, 5.6, 1.8],\n",
       "       [6.5, 3. , 5.8, 2.2],\n",
       "       [7.6, 3. , 6.6, 2.1],\n",
       "       [4.9, 2.5, 4.5, 1.7],\n",
       "       [7.3, 2.9, 6.3, 1.8],\n",
       "       [6.7, 2.5, 5.8, 1.8],\n",
       "       [7.2, 3.6, 6.1, 2.5],\n",
       "       [6.5, 3.2, 5.1, 2. ],\n",
       "       [6.4, 2.7, 5.3, 1.9],\n",
       "       [6.8, 3. , 5.5, 2.1],\n",
       "       [5.7, 2.5, 5. , 2. ],\n",
       "       [5.8, 2.8, 5.1, 2.4],\n",
       "       [6.4, 3.2, 5.3, 2.3],\n",
       "       [6.5, 3. , 5.5, 1.8],\n",
       "       [7.7, 3.8, 6.7, 2.2],\n",
       "       [7.7, 2.6, 6.9, 2.3],\n",
       "       [6. , 2.2, 5. , 1.5],\n",
       "       [6.9, 3.2, 5.7, 2.3],\n",
       "       [5.6, 2.8, 4.9, 2. ],\n",
       "       [7.7, 2.8, 6.7, 2. ],\n",
       "       [6.3, 2.7, 4.9, 1.8],\n",
       "       [6.7, 3.3, 5.7, 2.1],\n",
       "       [7.2, 3.2, 6. , 1.8],\n",
       "       [6.2, 2.8, 4.8, 1.8],\n",
       "       [6.1, 3. , 4.9, 1.8],\n",
       "       [6.4, 2.8, 5.6, 2.1],\n",
       "       [7.2, 3. , 5.8, 1.6],\n",
       "       [7.4, 2.8, 6.1, 1.9],\n",
       "       [7.9, 3.8, 6.4, 2. ],\n",
       "       [6.4, 2.8, 5.6, 2.2],\n",
       "       [6.3, 2.8, 5.1, 1.5],\n",
       "       [6.1, 2.6, 5.6, 1.4],\n",
       "       [7.7, 3. , 6.1, 2.3],\n",
       "       [6.3, 3.4, 5.6, 2.4],\n",
       "       [6.4, 3.1, 5.5, 1.8],\n",
       "       [6. , 3. , 4.8, 1.8],\n",
       "       [6.9, 3.1, 5.4, 2.1],\n",
       "       [6.7, 3.1, 5.6, 2.4],\n",
       "       [6.9, 3.1, 5.1, 2.3],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [6.8, 3.2, 5.9, 2.3],\n",
       "       [6.7, 3.3, 5.7, 2.5],\n",
       "       [6.7, 3. , 5.2, 2.3],\n",
       "       [6.3, 2.5, 5. , 1.9],\n",
       "       [6.5, 3. , 5.2, 2. ],\n",
       "       [6.2, 3.4, 5.4, 2.3],\n",
       "       [5.9, 3. , 5.1, 1.8]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#separate dependent variable and independent variable\n",
    "x=iris.data\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "012b16a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y=iris.target\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6be17f10",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "689359cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(120, 4)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3ddd0811",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 4)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2e8019a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "clf=LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cd8fc381",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To train the Algorithm\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "clf.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5d08bad2",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=clf.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "43f9fe3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 2, 1, 2, 1, 1, 2, 0, 2, 0, 0, 2, 2, 1, 1, 1, 0, 2, 1, 0,\n",
       "       1, 1, 1, 1, 1, 2, 0, 0])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "89146155",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy=accuracy_score(y_test,y_pred)\n",
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1300c802",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>174</td>\n",
       "      <td>96</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>189</td>\n",
       "      <td>87</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>185</td>\n",
       "      <td>110</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>195</td>\n",
       "      <td>104</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>149</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>Female</td>\n",
       "      <td>150</td>\n",
       "      <td>153</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>Female</td>\n",
       "      <td>184</td>\n",
       "      <td>121</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>Female</td>\n",
       "      <td>141</td>\n",
       "      <td>136</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>Male</td>\n",
       "      <td>150</td>\n",
       "      <td>95</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Male</td>\n",
       "      <td>173</td>\n",
       "      <td>131</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Gender  Height  Weight  Index\n",
       "0      Male     174      96      4\n",
       "1      Male     189      87      2\n",
       "2    Female     185     110      4\n",
       "3    Female     195     104      3\n",
       "4      Male     149      61      3\n",
       "..      ...     ...     ...    ...\n",
       "495  Female     150     153      5\n",
       "496  Female     184     121      4\n",
       "497  Female     141     136      5\n",
       "498    Male     150      95      5\n",
       "499    Male     173     131      5\n",
       "\n",
       "[500 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "bmi=pd.read_csv(\"D:\\\\New folder\\\\bmi.csv\")\n",
    "bmi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a7466382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>174</td>\n",
       "      <td>96</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>189</td>\n",
       "      <td>87</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>185</td>\n",
       "      <td>110</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>195</td>\n",
       "      <td>104</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>149</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Height  Weight  Index\n",
       "0    Male     174      96      4\n",
       "1    Male     189      87      2\n",
       "2  Female     185     110      4\n",
       "3  Female     195     104      3\n",
       "4    Male     149      61      3"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bmi.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "e1458193",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender\n",
       "Female    255\n",
       "Male      245\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bmi['Gender'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "f1639bf5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "245"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(bmi['Gender']==\"Male\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "febf1fa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     NaN\n",
       "1     NaN\n",
       "2     NaN\n",
       "3     NaN\n",
       "4     NaN\n",
       "       ..\n",
       "495   NaN\n",
       "496   NaN\n",
       "497   NaN\n",
       "498   NaN\n",
       "499   NaN\n",
       "Name: Gender, Length: 500, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bmi['Gender']=bmi['Gender'].map({'male':0,'female':1})\n",
    "bmi['Gender']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fc0566cd",
   "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>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Index</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>174</td>\n",
       "      <td>96</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>189</td>\n",
       "      <td>87</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>185</td>\n",
       "      <td>110</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>195</td>\n",
       "      <td>104</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>149</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>150</td>\n",
       "      <td>153</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>184</td>\n",
       "      <td>121</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>141</td>\n",
       "      <td>136</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>150</td>\n",
       "      <td>95</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>173</td>\n",
       "      <td>131</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Height  Weight  Index\n",
       "0       174      96      4\n",
       "1       189      87      2\n",
       "2       185     110      4\n",
       "3       195     104      3\n",
       "4       149      61      3\n",
       "..      ...     ...    ...\n",
       "495     150     153      5\n",
       "496     184     121      4\n",
       "497     141     136      5\n",
       "498     150      95      5\n",
       "499     173     131      5\n",
       "\n",
       "[500 rows x 3 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bmi=pd.get_dummies(bmi,columns=['Gender'],dtype=int)\n",
    "bmi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d7068f68",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\saray\\AppData\\Local\\Temp\\ipykernel_16840\\1809008969.py:2: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(bmi['Height'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Height', ylabel='Density'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.distplot(bmi['Height'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "ec0a1aa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Index', ylabel='Height'>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(y=\"Height\",x='Index',data=bmi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0fe2ed83",
   "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>male</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>currentSmoker</th>\n",
       "      <th>cigsPerDay</th>\n",
       "      <th>BPMeds</th>\n",
       "      <th>prevalentStroke</th>\n",
       "      <th>prevalentHyp</th>\n",
       "      <th>diabetes</th>\n",
       "      <th>totChol</th>\n",
       "      <th>sysBP</th>\n",
       "      <th>diaBP</th>\n",
       "      <th>BMI</th>\n",
       "      <th>heartRate</th>\n",
       "      <th>glucose</th>\n",
       "      <th>TenYearCHD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>26.97</td>\n",
       "      <td>80.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>28.73</td>\n",
       "      <td>95.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>245.0</td>\n",
       "      <td>127.5</td>\n",
       "      <td>80.0</td>\n",
       "      <td>25.34</td>\n",
       "      <td>75.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.58</td>\n",
       "      <td>65.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>23.10</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4233</th>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>25.97</td>\n",
       "      <td>66.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4234</th>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>126.5</td>\n",
       "      <td>80.0</td>\n",
       "      <td>19.71</td>\n",
       "      <td>65.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4235</th>\n",
       "      <td>0</td>\n",
       "      <td>48</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>248.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>84.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4236</th>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>126.5</td>\n",
       "      <td>87.0</td>\n",
       "      <td>19.16</td>\n",
       "      <td>86.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4237</th>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>133.5</td>\n",
       "      <td>83.0</td>\n",
       "      <td>21.47</td>\n",
       "      <td>80.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4238 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      male  age  education  currentSmoker  cigsPerDay  BPMeds  \\\n",
       "0        1   39        4.0              0         0.0     0.0   \n",
       "1        0   46        2.0              0         0.0     0.0   \n",
       "2        1   48        1.0              1        20.0     0.0   \n",
       "3        0   61        3.0              1        30.0     0.0   \n",
       "4        0   46        3.0              1        23.0     0.0   \n",
       "...    ...  ...        ...            ...         ...     ...   \n",
       "4233     1   50        1.0              1         1.0     0.0   \n",
       "4234     1   51        3.0              1        43.0     0.0   \n",
       "4235     0   48        2.0              1        20.0     NaN   \n",
       "4236     0   44        1.0              1        15.0     0.0   \n",
       "4237     0   52        2.0              0         0.0     0.0   \n",
       "\n",
       "      prevalentStroke  prevalentHyp  diabetes  totChol  sysBP  diaBP    BMI  \\\n",
       "0                   0             0         0    195.0  106.0   70.0  26.97   \n",
       "1                   0             0         0    250.0  121.0   81.0  28.73   \n",
       "2                   0             0         0    245.0  127.5   80.0  25.34   \n",
       "3                   0             1         0    225.0  150.0   95.0  28.58   \n",
       "4                   0             0         0    285.0  130.0   84.0  23.10   \n",
       "...               ...           ...       ...      ...    ...    ...    ...   \n",
       "4233                0             1         0    313.0  179.0   92.0  25.97   \n",
       "4234                0             0         0    207.0  126.5   80.0  19.71   \n",
       "4235                0             0         0    248.0  131.0   72.0  22.00   \n",
       "4236                0             0         0    210.0  126.5   87.0  19.16   \n",
       "4237                0             0         0    269.0  133.5   83.0  21.47   \n",
       "\n",
       "      heartRate  glucose  TenYearCHD  \n",
       "0          80.0     77.0           0  \n",
       "1          95.0     76.0           0  \n",
       "2          75.0     70.0           0  \n",
       "3          65.0    103.0           1  \n",
       "4          85.0     85.0           0  \n",
       "...         ...      ...         ...  \n",
       "4233       66.0     86.0           1  \n",
       "4234       65.0     68.0           0  \n",
       "4235       84.0     86.0           0  \n",
       "4236       86.0      NaN           0  \n",
       "4237       80.0    107.0           0  \n",
       "\n",
       "[4238 rows x 16 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Assignment\n",
    "import pandas as pd\n",
    "framin=pd.read_csv(\"D:\\\\New folder\\\\framingham.csv\")\n",
    "framin\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "258d7c89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4238, 16)\n"
     ]
    }
   ],
   "source": [
    "print(framin.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30155ecc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7e50a9f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['male', 'age', 'education', 'currentSmoker', 'cigsPerDay', 'BPMeds', 'prevalentStroke', 'prevalentHyp', 'diabetes', 'totChol', 'sysBP', 'diaBP', 'BMI', 'heartRate', 'glucose', 'TenYearCHD']\n"
     ]
    }
   ],
   "source": [
    "print(list(framin.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "d3e3020e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping columns education and glucose\n",
    "df = framin.drop(['education'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "4c10eba1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "male                 0\n",
       "age                  0\n",
       "currentSmoker        0\n",
       "cigsPerDay          29\n",
       "BPMeds              53\n",
       "prevalentStroke      0\n",
       "prevalentHyp         0\n",
       "diabetes             0\n",
       "totChol             50\n",
       "sysBP                0\n",
       "diaBP                0\n",
       "BMI                 19\n",
       "heartRate            1\n",
       "glucose            388\n",
       "TenYearCHD           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for more missing data \n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "f7a04d75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['male', 'age', 'currentSmoker', 'cigsPerDay', 'BPMeds',\n",
       "       'prevalentStroke', 'prevalentHyp', 'diabetes', 'totChol', 'sysBP',\n",
       "       'diaBP', 'BMI', 'heartRate', 'glucose', 'TenYearCHD'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dropping all rows with missing data\n",
    "df = df.dropna()\n",
    "df.isna().sum()\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "aaafea4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "98187859",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# clarify what is y and what is x label\n",
    "y = df['TenYearCHD']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "14e0b74a",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop(['TenYearCHD'], axis = 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a8924998",
   "metadata": {},
   "outputs": [],
   "source": [
    "#x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=101)\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state=29)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "3d0197e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2999"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "33f4b64e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "750"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "9e3de56e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2999"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "c1578673",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "750"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "c131024c",
   "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>male</th>\n",
       "      <th>age</th>\n",
       "      <th>currentSmoker</th>\n",
       "      <th>cigsPerDay</th>\n",
       "      <th>BPMeds</th>\n",
       "      <th>prevalentStroke</th>\n",
       "      <th>prevalentHyp</th>\n",
       "      <th>diabetes</th>\n",
       "      <th>totChol</th>\n",
       "      <th>sysBP</th>\n",
       "      <th>diaBP</th>\n",
       "      <th>BMI</th>\n",
       "      <th>heartRate</th>\n",
       "      <th>glucose</th>\n",
       "      <th>TenYearCHD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [male, age, currentSmoker, cigsPerDay, BPMeds, prevalentStroke, prevalentHyp, diabetes, totChol, sysBP, diaBP, BMI, heartRate, glucose, TenYearCHD]\n",
       "Index: []"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check for dupicates\n",
    "duplicate_df = df[df.duplicated()]\n",
    "duplicate_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "701331a1",
   "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>male</th>\n",
       "      <th>age</th>\n",
       "      <th>currentSmoker</th>\n",
       "      <th>cigsPerDay</th>\n",
       "      <th>BPMeds</th>\n",
       "      <th>prevalentStroke</th>\n",
       "      <th>prevalentHyp</th>\n",
       "      <th>diabetes</th>\n",
       "      <th>totChol</th>\n",
       "      <th>sysBP</th>\n",
       "      <th>diaBP</th>\n",
       "      <th>BMI</th>\n",
       "      <th>heartRate</th>\n",
       "      <th>glucose</th>\n",
       "      <th>TenYearCHD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [male, age, currentSmoker, cigsPerDay, BPMeds, prevalentStroke, prevalentHyp, diabetes, totChol, sysBP, diaBP, BMI, heartRate, glucose, TenYearCHD]\n",
       "Index: []"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking for missing values\n",
    "df.isna().sum()\n",
    "null = df[df.isna().any(axis=1)]\n",
    "null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a8a0307",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ecf78ee8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1137de29",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a75cd14e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy score for LogReg is: 84.39999999999999%\n",
      "The f1 score for LogReg is: 6.4%\n",
      "The precision score for LogReg is: 50.0%\n",
      "The recall score for LogReg is: 3.4000000000000004%\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_logistic.py:460: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    }
   ],
   "source": [
    "#Eg:1\n",
    "#Logisic Expression\n",
    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score,precision_score,recall_score,f1_score,confusion_matrix\n",
    "# logistic regression again with the balanced dataset\n",
    "normalized_df_reg = LogisticRegression().fit(X_train, y_train)\n",
    "normalized_df_reg_pred = normalized_df_reg.predict(X_test)\n",
    "# check accuracy: Accuracy: Overall, how often is the classifier correct? Accuracy = (True Pos + True Negative)/total\n",
    "acc = accuracy_score(y_test, normalized_df_reg_pred)\n",
    "print(f\"The accuracy score for LogReg is: {round(acc,3)*100}%\")\n",
    "# f1 score: The F1 score can be interpreted as a weighted average of the precision and recall, where an F1 score reaches its best value at 1 and worst score at 0.\n",
    "f1 = f1_score(y_test, normalized_df_reg_pred)\n",
    "print(f\"The f1 score for LogReg is: {round(f1,3)*100}%\")\n",
    "# Precision score: When it predicts yes, how often is it correct? Precision=True Positive/predicted yes\n",
    "precision = precision_score(y_test, normalized_df_reg_pred)\n",
    "print(f\"The precision score for LogReg is: {round(precision,3)*100}%\")\n",
    "# recall score: True Positive Rate(Sensitivity or Recall): When it’s actually yes, how often does it predict yes? True Positive Rate = True Positive/actual yes\n",
    "recall = recall_score(y_test, normalized_df_reg_pred)\n",
    "print(f\"The recall score for LogReg is: {round(recall,3)*100}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd063fe5",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c67556a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ee67366",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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