Notebook.ipynb

{
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       "      <th></th>\n",
       "      <th>Employee_ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Department</th>\n",
       "      <th>Job_Title</th>\n",
       "      <th>Years_at_Company</th>\n",
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       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Manager</td>\n",
       "      <td>9</td>\n",
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       "      <td>Female</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Analyst</td>\n",
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       "      <td>3</td>\n",
       "      <td>42</td>\n",
       "      <td>Female</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
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       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
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      ],
      "text/plain": [
       "   Employee_ID  Age  Gender   Department Job_Title  Years_at_Company  \\\n",
       "0            0   27    Male    Marketing   Manager                 9   \n",
       "1            1   53  Female        Sales  Engineer                10   \n",
       "2            2   59  Female    Marketing   Analyst                 8   \n",
       "3            3   42  Female  Engineering   Manager                 1   \n",
       "4            4   44  Female        Sales  Engineer                10   \n",
       "\n",
       "   Satisfaction_Level  Average_Monthly_Hours  Promotion_Last_5Years  Salary  \\\n",
       "0            0.586251                    151                      0   60132   \n",
       "1            0.261161                    221                      1   79947   \n",
       "2            0.304382                    184                      0   46958   \n",
       "3            0.480779                    242                      0   40662   \n",
       "4            0.636244                    229                      1   74307   \n",
       "\n",
       "   Attrition  \n",
       "0          0  \n",
       "1          0  \n",
       "2          1  \n",
       "3          0  \n",
       "4          0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv('C:/Users/hp/Downloads/Salary prediction/employee_attrition_data.csv')\n",
    "data.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 11 columns):\n",
      " #   Column                 Non-Null Count  Dtype  \n",
      "---  ------                 --------------  -----  \n",
      " 0   Employee_ID            1000 non-null   int64  \n",
      " 1   Age                    1000 non-null   int64  \n",
      " 2   Gender                 1000 non-null   object \n",
      " 3   Department             1000 non-null   object \n",
      " 4   Job_Title              1000 non-null   object \n",
      " 5   Years_at_Company       1000 non-null   int64  \n",
      " 6   Satisfaction_Level     1000 non-null   float64\n",
      " 7   Average_Monthly_Hours  1000 non-null   int64  \n",
      " 8   Promotion_Last_5Years  1000 non-null   int64  \n",
      " 9   Salary                 1000 non-null   int64  \n",
      " 10  Attrition              1000 non-null   int64  \n",
      "dtypes: float64(1), int64(7), object(3)\n",
      "memory usage: 86.1+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Attrition</th>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <th>998</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "</table>\n",
       "<p>1000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Employee_ID    Age  Gender  Department  Job_Title  Years_at_Company  \\\n",
       "0          False  False   False       False      False             False   \n",
       "1          False  False   False       False      False             False   \n",
       "2          False  False   False       False      False             False   \n",
       "3          False  False   False       False      False             False   \n",
       "4          False  False   False       False      False             False   \n",
       "..           ...    ...     ...         ...        ...               ...   \n",
       "995        False  False   False       False      False             False   \n",
       "996        False  False   False       False      False             False   \n",
       "997        False  False   False       False      False             False   \n",
       "998        False  False   False       False      False             False   \n",
       "999        False  False   False       False      False             False   \n",
       "\n",
       "     Satisfaction_Level  Average_Monthly_Hours  Promotion_Last_5Years  Salary  \\\n",
       "0                 False                  False                  False   False   \n",
       "1                 False                  False                  False   False   \n",
       "2                 False                  False                  False   False   \n",
       "3                 False                  False                  False   False   \n",
       "4                 False                  False                  False   False   \n",
       "..                  ...                    ...                    ...     ...   \n",
       "995               False                  False                  False   False   \n",
       "996               False                  False                  False   False   \n",
       "997               False                  False                  False   False   \n",
       "998               False                  False                  False   False   \n",
       "999               False                  False                  False   False   \n",
       "\n",
       "     Attrition  \n",
       "0        False  \n",
       "1        False  \n",
       "2        False  \n",
       "3        False  \n",
       "4        False  \n",
       "..         ...  \n",
       "995      False  \n",
       "996      False  \n",
       "997      False  \n",
       "998      False  \n",
       "999      False  \n",
       "\n",
       "[1000 rows x 11 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Employee_ID              0\n",
       "Age                      0\n",
       "Gender                   0\n",
       "Department               0\n",
       "Job_Title                0\n",
       "Years_at_Company         0\n",
       "Satisfaction_Level       0\n",
       "Average_Monthly_Hours    0\n",
       "Promotion_Last_5Years    0\n",
       "Salary                   0\n",
       "Attrition                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
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     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
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    {
     "data": {
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       "      <td>Marketing</td>\n",
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       "      <td>Engineering</td>\n",
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       "      <td>4</td>\n",
       "      <td>44</td>\n",
       "      <td>Female</td>\n",
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       "      <td>Engineer</td>\n",
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      ],
      "text/plain": [
       "   Employee_ID  Age  Gender   Department Job_Title  Years_at_Company  \\\n",
       "0            0   27    Male    Marketing   Manager                 9   \n",
       "1            1   53  Female        Sales  Engineer                10   \n",
       "2            2   59  Female    Marketing   Analyst                 8   \n",
       "3            3   42  Female  Engineering   Manager                 1   \n",
       "4            4   44  Female        Sales  Engineer                10   \n",
       "\n",
       "   Satisfaction_Level  Average_Monthly_Hours  Promotion_Last_5Years  Salary  \\\n",
       "0            0.586251                    151                      0   60132   \n",
       "1            0.261161                    221                      1   79947   \n",
       "2            0.304382                    184                      0   46958   \n",
       "3            0.480779                    242                      0   40662   \n",
       "4            0.636244                    229                      1   74307   \n",
       "\n",
       "   Attrition  \n",
       "0          0  \n",
       "1          0  \n",
       "2          1  \n",
       "3          0  \n",
       "4          0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Employee_ID', 'Age', 'Gender', 'Department', 'Job_Title',\n",
       "       'Years_at_Company', 'Satisfaction_Level', 'Average_Monthly_Hours',\n",
       "       'Promotion_Last_5Years', 'Salary', 'Attrition'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(columns= \"Employee_ID\",inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Department</th>\n",
       "      <th>Job_Title</th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Manager</td>\n",
       "      <td>9</td>\n",
       "      <td>0.586251</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>60132</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.261161</td>\n",
       "      <td>221</td>\n",
       "      <td>1</td>\n",
       "      <td>79947</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>8</td>\n",
       "      <td>0.304382</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>46958</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42</td>\n",
       "      <td>Female</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
       "      <td>0</td>\n",
       "      <td>40662</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.636244</td>\n",
       "      <td>229</td>\n",
       "      <td>1</td>\n",
       "      <td>74307</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Gender   Department Job_Title  Years_at_Company  Satisfaction_Level  \\\n",
       "0   27    Male    Marketing   Manager                 9            0.586251   \n",
       "1   53  Female        Sales  Engineer                10            0.261161   \n",
       "2   59  Female    Marketing   Analyst                 8            0.304382   \n",
       "3   42  Female  Engineering   Manager                 1            0.480779   \n",
       "4   44  Female        Sales  Engineer                10            0.636244   \n",
       "\n",
       "   Average_Monthly_Hours  Promotion_Last_5Years  Salary  Attrition  \n",
       "0                    151                      0   60132          0  \n",
       "1                    221                      1   79947          0  \n",
       "2                    184                      0   46958          1  \n",
       "3                    242                      0   40662          0  \n",
       "4                    229                      1   74307          0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (3.9.2)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (4.55.0)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (1.4.7)\n",
      "Requirement already satisfied: numpy>=1.23 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (1.23.5)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (23.0)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (11.0.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (3.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from matplotlib) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\hp\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.1.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "!pip install matplotlib\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[\"Gender\"].value_counts().plot(kind=\"pie\")\n",
    "plt.ylabel(\"\")\n",
    "plt.title(\"Gender Count of Employees\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Department</th>\n",
       "      <th>Job_Title</th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Manager</td>\n",
       "      <td>9</td>\n",
       "      <td>0.586251</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>60132</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.261161</td>\n",
       "      <td>221</td>\n",
       "      <td>1</td>\n",
       "      <td>79947</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>8</td>\n",
       "      <td>0.304382</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>46958</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42</td>\n",
       "      <td>Female</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
       "      <td>0</td>\n",
       "      <td>40662</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.636244</td>\n",
       "      <td>229</td>\n",
       "      <td>1</td>\n",
       "      <td>74307</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Gender   Department Job_Title  Years_at_Company  Satisfaction_Level  \\\n",
       "0   27    Male    Marketing   Manager                 9            0.586251   \n",
       "1   53  Female        Sales  Engineer                10            0.261161   \n",
       "2   59  Female    Marketing   Analyst                 8            0.304382   \n",
       "3   42  Female  Engineering   Manager                 1            0.480779   \n",
       "4   44  Female        Sales  Engineer                10            0.636244   \n",
       "\n",
       "   Average_Monthly_Hours  Promotion_Last_5Years  Salary  Attrition  \n",
       "0                    151                      0   60132          0  \n",
       "1                    221                      1   79947          0  \n",
       "2                    184                      0   46958          1  \n",
       "3                    242                      0   40662          0  \n",
       "4                    229                      1   74307          0  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HD2t6dJ7v1Zg9ezYOHjwIPz8/DB06FNWrV8fjx49x9uxZ7N+/v8AtHJ4XGRmJDz/8EG3btkWzZs1gY2ODuLg4rFu3Dvfu3cPixYs1QaBDhw747bffYGlpierVqyM8PBz79+/XuldZYby9vVGlShVMnDgRcXFxsLCwwNatW5GUlPTK6QpjZGSEXr164YcffoChoSF69+5d5GlVKhX27t2LAQMGwM/PD3v27MGuXbvw+eefF+h9at++PWxtbbF582a0bdsWDg4Oxa4VADp27IiWLVti2rRpuHnzJmrXro3//ve/+PvvvzF27FhNr1O+mjVrIjAwEGPGjIFSqdQE8q+++uqNll8U9erVw7Jly/Dtt9+iatWqcHBw0Fyo8jwDAwP8/PPPaNu2LWrUqIFBgwahQoUKiIuLw8GDB2FhYYGdO3eWWJ1EOiPdBZ5E5U/Hjh2FSqUSGRkZL20zcOBAYWRkpLldhFqtFq6uroXepiBfdna2mDNnjqhRo4ZQKpXC2tpa1KtXT3z11VciJSVF0w6AGDVqVKHzWL16tfDw8BBKpVJ4e3uLNWvWiOnTp4sXfyYyMjLEqFGjhI2NjTAzMxOdO3fW3JZh9uzZWm0TEhLEqFGjhKurqzAyMhJOTk6idevWYuXKla/8nBISEsTs2bNFixYthLOzs5DL5cLa2lq0atVKbNmyRattUlKSGDRokLCzsxNmZmYiMDBQXL58Wbi5uYkBAwZo2hV224tLly6JgIAAYWZmJuzs7MTQoUNFZGSkACDWrFmjaTdgwABhamr6yppPnjwpAIg2bdq8st3z8ud77do10aZNG2FiYiIcHR3F9OnTRV5eXqHTfPzxxwKA+P3334u8nIoVK4pOnTppDUtLSxPjxo0TLi4uwsjISHh4eIh58+YVuIVG/ndm/fr1mu+Hr6/va2/p8aLi3vYiPj5etG/fXpibmwsAmltgFLYdhRDi3Llz4oMPPhC2trZCqVQKNzc30aNHDxEaGlqsOomkIhPiJbdlJiIqooiICPj6+mL9+vXo06eP1OVIIjIyEnXq1MGvv/76Rlc+FtW4ceOwevVqxMfHw8TEpEjT5J9/9ttvv5VYXUT07/AcMiIqlhcfKwQ8u7O6gYEBmjdvLkFF+mHVqlUwMzPDBx98UGLLePr0KdavX4+uXbsWOYxdu3YNSUlJhd57joj0B88hI6JimTt3Ls6cOYOWLVtCLpdjz5492LNnD4YNG1bgFhvlwc6dO3Hp0iWsXLkSo0ePLpEHjicmJmL//v3YsmULHj16hE8//fS101y/fh27d+/GsmXLoFAo3vgCACJ6OxjIiKhYGjdujJCQEHzzzTdIT09HxYoVMWPGjFc+a7As++STT5CQkIB27dqV2Enuly5dQp8+feDg4IDvv//+pffbet6RI0cwfvx41KhRA3///fdLbwhMRPqB55ARERERSYznkBERERFJjIGMiIiISGI8h0xH1Go17t27B3Nz8zd+fA0RERG9XUIIpKWlwcXFpdDn1b4tDGQ6cu/evXJ5hRkREVFZcOfOHbzzzjuSLZ+BTEfyH9B7584dWFhYSFwNERERFUVqaipcXV01+3GpMJDpSP5hSgsLCwYyIiKiUkbq0414Uj8RERGRxBjIiIiIiCTGQEZEREQkMQYyIiIiIokxkBERERFJjIGMiIiISGIMZEREREQSYyAjIiIikhgDGREREZHEGMiIiIiIJMZARkRERCQxyQNZXFwc+vbtC1tbWxgbG8PHxwenT5/WahMdHY1OnTrB0tISpqamaNCgAW7fvq0Z//TpU4waNQq2trYwMzND165dkZCQoDWP27dvo3379jAxMYGDgwMmTZqE3NxcrTaHDh1C3bp1oVQqUbVqVaxdu7bE1puIiIgon6SBLCkpCU2aNIGRkRH27NmDS5cuYcGCBbC2tta0uXbtGpo2bQpvb28cOnQI58+fx3/+8x+oVCpNm3HjxmHnzp3YvHkzDh8+jHv37uGDDz7QjM/Ly0P79u2RnZ2NY8eOYd26dVi7di2+/PJLTZsbN26gffv2aNmyJSIiIjB27Fh89NFH2Ldv39v5MF4h7OpDZOXmSV0GERERlRCZEEJItfApU6YgLCwMR48efWmbXr16wcjICL/99luh41NSUmBvb4/ff/8d3bp1AwBcvnwZ1apVQ3h4OBo1aoQ9e/agQ4cOuHfvHhwdHQEAy5cvx+TJk/HgwQMoFApMnjwZu3btwoULF7SWnZycjL179752XVJTU2FpaYmUlBRYWFgU52N4pesP0hGw8DCcLFQY3coD3eq9A4Vc8o5NIiKiMqGk9t/FJemefceOHahfvz66d+8OBwcH+Pr6YtWqVZrxarUau3btgqenJwIDA+Hg4AA/Pz9s375d0+bMmTPIyclBQECAZpi3tzcqVqyI8PBwAEB4eDh8fHw0YQwAAgMDkZqaiosXL2raPD+P/Db583hRVlYWUlNTtV4lIS75CezMlLiX8hSf/xWFlvMP4c9Tt5GTpy6R5REREdHbJ2kgu379OpYtWwYPDw/s27cPI0eOxJgxY7Bu3ToAQGJiItLT0zF79mwEBQXhv//9L7p06YIPPvgAhw8fBgDEx8dDoVDAyspKa96Ojo6Ij4/XtHk+jOWPzx/3qjapqal48uRJgdpnzZoFS0tLzcvV1fXffyCFaOZhjyOftcSXHarD3lyJuOQnmLw1Cq0XHMam03eQy2BGRERU6kkayNRqNerWrYuZM2fC19cXw4YNw9ChQ7F8+XLNeAB4//33MW7cONSpUwdTpkxBhw4dNG2kMnXqVKSkpGhed+7cKbFlqYwMMbhpJRyZ1BJftK8GOzMFbj/OxGdbzqP1wsPYeuYugxkREVEpJmkgc3Z2RvXq1bWGVatWTXMFpZ2dHeRy+SvbODk5ITs7G8nJyVptEhIS4OTkpGnz4lWX+e9f18bCwgLGxsYFalcqlbCwsNB6lTRjhSE+alYZRz5ric/becPGVIFbjzIxYXMk3lt0BNvPxSFPLdkpgURERPSGJA1kTZo0QUxMjNawK1euwM3NDQCgUCjQoEGDV7apV68ejIyMEBoaqhkfExOD27dvw9/fHwDg7++PqKgoJCYmatqEhITAwsJCE/b8/f215pHfJn8e+sREIcew5lVw9LOWmBzkDWsTI9x4mIGxf0agzaLD+DuCwYyIiKhUERI6efKkkMvl4rvvvhOxsbFiw4YNwsTERKxfv17TZtu2bcLIyEisXLlSxMbGiqVLlwpDQ0Nx9OhRTZsRI0aIihUrigMHDojTp08Lf39/4e/vrxmfm5sratasKdq0aSMiIiLE3r17hb29vZg6daqmzfXr14WJiYmYNGmSiI6OFj/++KMwNDQUe/fuLdK6pKSkCAAiJSVFB59M8aQ9zRE/HIgVtWbsE26Tg4Xb5GARsOCQ2BkZJ/Ly1G+9HiIiotJCyv338yQNZEIIsXPnTlGzZk2hVCqFt7e3WLlyZYE2q1evFlWrVhUqlUrUrl1bbN++XWv8kydPxMcffyysra2FiYmJ6NKli7h//75Wm5s3b4q2bdsKY2NjYWdnJyZMmCBycnK02hw8eFDUqVNHKBQKUblyZbFmzZoir4c+bNDUJ9ni+/1XhM/0vZpg1mbhYbH7/D0GMyIiokLow/5bCCEkvQ9ZWaIv9zEBgJQnOVgTdgOr/7mBtKfPnkbg7WSOsQGeCKzhCJlMJml9RERE+kJf9t8MZDqiLxv0eSmZOVj9z3X8EnYT6VnPglkNFwuMDfBEQDUHBjMiIir39GX/zUCmI/qyQQuTnJmNn4/ewJqwG8jIfvYIJp8Klhj3ngdaejGYERFR+aUv+28GMh3Rlw36Ko8zsrHq6HWsO3YTmf8LZrVdrTA2wAPvetozmBERUbmjL/tvBjId0ZcNWhSP0rOw8sh1/Bp+C09yngUz34pWGBfgiWYedgxmRERUbujL/puBTEf0ZYMWx8P0LKw4fA2/ht9CVu6zO/3Xc7PG+Pc80biKLYMZERGVefqy/2Yg0xF92aBvIjHtKZYfuo71J24h+3/BrKG7Dca95wn/KrYSV0dERFRy9GX/zUCmI/qyQf+NhNSnWHboGn4/eVsTzBpVtsG4AE/4VWYwIyKiskdf9t8MZDqiLxtUF+JTnuKnQ1ex8eQdZP/voeVNqtpiXIAn6rvbSFwdERGR7ujL/puBTEf0ZYPq0r3kJ/jx4FVsOn0HOXnPvibNPOwwNsAT9dysJa6OiIjo39OX/TcDmY7oywYtCXeTMvHjwavYfPoucv/30PIWnvYY954n6rhaSVscERHRv6Av+28GMh3Rlw1aku48zsTSA7HYejYOef8LZq28HTAuwBM+71hKXB0REVHx6cv+m4FMR/Rlg74Ntx5lYOmBq9h29i7+l8sQUM0BYwM8UbMCgxkREZUe+rL/ZiDTEX3ZoG/TjYcZWBoai+0RcZpg1qa6I8YGeKK6S/n4DIiIqHTTl/03A5mO6MsGlcK1B+n4PjQWOyLvIf/b1LamEz4N8IC3U/n6LIiIqHTRl/03A5mO6MsGlVJsQhqWhMZiV9R9TTBr7+OMTwM84OloLm1xREREhdCX/TcDmY7oywbVB1cS0rBk/7NgBgAyGdChlgs+bV0VVR0YzIiISH/oy/6bgUxH9GWD6pPo+6lYsj8Wey/GA3gWzN6v7YIxrT1Q2d5M4uqIiIj0Z//NQKYj+rJB9dHFeylYvD8WIZcSAAAGMqCzbwWMaeUBdztTiasjIqLyTF/23wxkOqIvG1SfXYhLweL9V7A/OhEAYGggQ5f/BbOKtiYSV0dEROWRvuy/Gch0RF82aGkQeScZi/dfwcGYBwCeBbNudd/B6FZV4WrDYEZERG+Pvuy/Gch0RF82aGly7nYSFu2PxZErz4KZ3ECG7vVdMbpVVVSwMpa4OiIiKg/0Zf/NQKYj+rJBS6Mzt5KweP8VHI19CAAwMpShR31XjGpZFS4MZkREVIL0Zf/NQKYj+rJBS7NTNx9jUcgVHLv2CACgMDRAr4au+PjdqnCyVElcHRERlUX6sv9mINMRfdmgZcHx64+wKOQKTtx4DABQyA3wYcOK+PjdKnCwYDAjIiLd0Zf9NwOZjujLBi1Ljl17iMUhsTh581kwU8oN0MfPDSPerQwHcwYzIiL69/Rl/81ApiP6skHLGiEEwq4+wqL9V3DmVhIAQGVkgH6N3DC8RRXYmSklrpCIiEozfdl/M5DpiL5s0LJKCIEjsQ+xKOQKIu4kAwCMjQzRv7EbhjevAhtThbQFEhFRqaQv+28GMh3Rlw1a1gkhcOjKAywOuYLIuykAABOFIQY0dsewZpVhzWBGRETFoC/7bwYyHdGXDVpeCCFw4HIiFu2/ggtxqQAAU4UhBjWphI+aVYKVCYMZERG9nr7svxnIdERfNmh5I4RAyKUELN4fi0v3nwUzc6Ucg5pWwpCmlWBpbCRxhUREpM/0Zf/NQKYj+rJByyu1WuC/lxKweP8VXI5PAwCYq+QY0rQSBjetBAsVgxkRERWkL/tvBjId0ZcNWt6p1QJ7L8Zj8f4ruJKQDgCwUMkxtFllDGziDnMGMyIieo6+7L8ZyHREXzYoPaNWC+yKuo8lobG4mvgsmFmZGGFos8oY0NgdZkq5xBUSEZE+0Jf9NwOZjujLBiVteWqB4PP3sCQ0FtcfZAAArE2MMKx5FfT3d4MpgxkRUbmmL/tvBjId0ZcNSoXLUwvsiIzDkv2xuPkoEwBga6rA8BaV0a+RO4wVhhJXSEREUtCX/TcDmY7oywalV8vNU2N7xD0sPRCLW/8LZnZmCoxoUQV9G7lBZcRgRkRUnujL/puBTEf0ZYNS0eTkqfHXuTh8HxqLu0lPAAD25kp8/G4V9G5YkcGMiKic0Jf9NwOZjujLBqXiyclTY+uZu1h64Crikp8FM0cLJT5+typ6NnBlMCMiKuP0Zf/NQKYj+rJB6c1k56qx+cwd/HjgKu6lPAUAOFuq8HHLquhR/x0o5QxmRERlkb7svxnIdERfNij9O1m5edh0+i5+PHAV8anPgpmLpQqjW3mgW713oJAbSFwhERHpkr7svyXfu8TFxaFv376wtbWFsbExfHx8cPr0ac34gQMHQiaTab2CgoK05uHu7l6gzezZs7XanD9/Hs2aNYNKpYKrqyvmzp1boJbNmzfD29sbKpUKPj4+2L17d8msNOktpdwQ/Rq54dCkd/FVpxpwMFfiXspTfP5XFFrOP4SNJ28jJ08tdZlERFTGSBrIkpKS0KRJExgZGWHPnj24dOkSFixYAGtra612QUFBuH//vub1xx9/FJjX119/rdXmk08+0YxLTU1FmzZt4ObmhjNnzmDevHmYMWMGVq5cqWlz7Ngx9O7dG0OGDMG5c+fQuXNndO7cGRcuXCi5D4D0lsrIEAMau+PIZy3xZYfqsDdXIi75CaZsi0KrBYew6fQd5DKYERGRjkh6yHLKlCkICwvD0aNHX9pm4MCBSE5Oxvbt21/axt3dHWPHjsXYsWMLHb9s2TJMmzYN8fHxUCgUmmVv374dly9fBgD07NkTGRkZCA4O1kzXqFEj1KlTB8uXL3/tuuhLlyeVjCfZedhw4haWH76Gh+nZAAA3WxOMaeWB9+u4QG4oeWczERG9AX3Zf0u6F9mxYwfq16+P7t27w8HBAb6+vli1alWBdocOHYKDgwO8vLwwcuRIPHr0qECb2bNnw9bWFr6+vpg3bx5yc3M148LDw9G8eXNNGAOAwMBAxMTEICkpSdMmICBAa56BgYEIDw8vtPasrCykpqZqvajsMlYY4qNmlXHks5aY2tYbNqYK3HqUiQmbI/HeoiP469xd5Kl5OiYREb0ZSQPZ9evXsWzZMnh4eGDfvn0YOXIkxowZg3Xr1mnaBAUF4ddff0VoaCjmzJmDw4cPo23btsjLy9O0GTNmDDZu3IiDBw9i+PDhmDlzJj777DPN+Pj4eDg6OmotO/99fHz8K9vkj3/RrFmzYGlpqXm5urr+uw+DSgUThRzDW1TB0c9aYnKQN6xNjHDjYQbG/RmJNosO4++IOAYzIiIqNkkPWSoUCtSvXx/Hjh3TDBszZgxOnTr10p6p69evo0qVKti/fz9at25daJtffvkFw4cPR3p6OpRKJdq0aYNKlSphxYoVmjaXLl1CjRo1cOnSJVSrVg0KhQLr1q1D7969NW1++uknfPXVV0hISCiwjKysLGRlZWnep6amwtXVVfIuT3q70rNyse7YTaw8ch0pT3IAAB4OZvg0wAPtajrDwEAmcYVERPQqPGQJwNnZGdWrV9caVq1aNdy+fful01SuXBl2dna4evXqS9v4+fkhNzcXN2/eBAA4OTkVCFX5752cnF7ZJn/8i5RKJSwsLLReVP6YKeUY1bIq/pncEuPf84SFSo7YxHSM/v0c2i45it1R96FmjxkREb2GpIGsSZMmiImJ0Rp25coVuLm5vXSau3fv4tGjR3B2dn5pm4iICBgYGMDBwQEA4O/vjyNHjiAnJ0fTJiQkBF5eXporOv39/REaGqo1n5CQEPj7+xd7vaj8MVcZYUxrDxyd3ApjAzxgrpIjJiENH284i3bfH8XeC/HgLf+IiOilhIROnjwp5HK5+O6770RsbKzYsGGDMDExEevXrxdCCJGWliYmTpwowsPDxY0bN8T+/ftF3bp1hYeHh3j69KkQQohjx46JRYsWiYiICHHt2jWxfv16YW9vL/r3769ZTnJysnB0dBT9+vUTFy5cEBs3bhQmJiZixYoVmjZhYWFCLpeL+fPni+joaDF9+nRhZGQkoqKiirQuKSkpAoBISUnR4SdEpVVyRrZYsO+yqPHlXuE2OVi4TQ4Wo38/K7Jy8qQujYiInqMv+29JA5kQQuzcuVPUrFlTKJVK4e3tLVauXKkZl5mZKdq0aSPs7e2FkZGRcHNzE0OHDhXx8fGaNmfOnBF+fn7C0tJSqFQqUa1aNTFz5kxNYMsXGRkpmjZtKpRKpahQoYKYPXt2gVo2bdokPD09hUKhEDVq1BC7du0q8nroywYl/ZKUkSXm7o0WVT/fJdwmB4u+Px8XGVk5UpdFRET/oy/7bz46SUf05aRA0k9HrjzA8N/O4ElOHuq4WmHNwAawNlW8fkIiIipR+rL/5t0sid6C5p72+H2oH6xMjBBxJxndV4TjfsoTqcsiIiI9wUBG9Jb4VrTG5uH+cLJQ4WpiOrotC8e1B+lSl0VERHqAgYzoLfJwNMeWkf6obGeKuOQn6L48HOfvJktdFhERSYyBjOgte8faBJtH+KPWO5Z4nJGN3iuPI+zqQ6nLIiIiCTGQEUnA1kyJ34c2QuMqtsjIzsOgNaewO+q+1GUREZFEGMiIJGKmlGPNoAZoW9MJ2XlqjPr9LH4/8fKnVBARUdnFQEYkIaXcED98WBe9G1aEEMDnf0Xhx4NXeVd/IqJyhoGMSGKGBjLM7FITo1tWBQDM2xeDb4Kj+QxMIqJyhIGMSA/IZDJMDPTCfzpUBwD8EnYDEzZHIidPLXFlRET0NjCQEemRIU0rYWGP2jA0kOGvc3HP7u6fnSd1WUREVMIYyIj0zAd138Gq/vWgMjLAgcuJ6Lf6BFIyc6Qui4iIShADGZEeauXtiPVD/GChkuP0rST0XBmOxNSnUpdFREQlhIGMSE/Vd7fBn8P94WCuxOX4NHRdfgw3H2ZIXRYREZUABjIiPVbN2QJbRzaGm60J7jx+gm7Lw3HxXorUZRERkY4xkBHpOVcbE2wZ0RjVnC3wMD0LvVYcx4nrj6Qui4iIdIiBjKgUsDdX4s/hjdCwkg3SsnLR/5eTCLmUIHVZRESkIwxkRKWEhcoIvw5uiIBqjsjKVWPE+jPYfPqO1GUREZEOMJARlSIqI0Ms71sX3eu9gzy1wKQt57Hi8DWpyyIion+JgYyolJEbGmBut1oY3rwyAGDWnsuYtSeaz78kIirFGMiISiGZTIap7aphaltvAMCKw9cxeet55PJRS0REpRIDGVEpNrxFFcztVgsGMmDT6bv4eMNZPM3ho5aIiEobBjKiUq5HfVcs61sPCrkB/nspAQN+OYnUp3zUEhFRacJARlQGBNZwwrpBDWGmlOPEjcfovfI4HqRlSV0WEREVEQMZURnhX8UWG4c1gp2ZAhfvpaL78mO48zhT6rKIiKgIGMiIypCaFSyxeURjvGNtjJuPMtF12THExKdJXRYREb0GAxlRGVPJzhRbRzaGl6M5EtOy0H35MZy59VjqsoiI6BUYyIjKIEcLFTYN90c9N2ukPs1Fn59P4ODlRKnLIiKil2AgIyqjLE2MsH6IH971ssfTHDWG/noa28/FSV0WEREVgoGMqAwzVhhiVf/66FzHBblqgbF/RmBN2A2pyyIiohcwkBGVcUaGBljYow4GNXEHAHy18xIW/DeGj1oiItIjDGRE5YCBgQxfdqiOiW08AQBLD1zFtO0XkKdmKCMi0gcMZETlhEwmw+hWHviuS03IZMDvJ27jkz/OIiuXj1oiIpIaAxlROdPHzw0/9K4LI0MZdkfFY8ja00jPypW6LCKico2BjKgcal/LGWsGNoSJwhD/XH2IPquO43FGttRlERGVWwxkROVUUw87/DG0EaxNjBB5NwXdlh9DXPITqcsiIiqXGMiIyrHarlbYPKIxXCxVuP4gA92WHcPVRD5qiYjobWMgIyrnqjqYYcvIxqjqYIb7KU/RfXk4Iu4kS10WEVG5wkBGRHCxMsbm4f6o7WqFpMwcfLjqOI7GPpC6LCKicoOBjIgAANamCvz+kR+aedghMzsPg9eeQvD5e1KXRURULjCQEZGGqVKOnwfUR/tazsjJE/jkj3P47fgtqcsiIirzJA9kcXFx6Nu3L2xtbWFsbAwfHx+cPn1aM37gwIGQyWRar6CgIK15PH78GH369IGFhQWsrKwwZMgQpKena7U5f/48mjVrBpVKBVdXV8ydO7dALZs3b4a3tzdUKhV8fHywe/fukllpIj2mlBvi+16+6NuoIoQA/rP9Apbsj+WjloiISpCkgSwpKQlNmjSBkZER9uzZg0uXLmHBggWwtrbWahcUFIT79+9rXn/88YfW+D59+uDixYsICQlBcHAwjhw5gmHDhmnGp6amok2bNnBzc8OZM2cwb948zJgxAytXrtS0OXbsGHr37o0hQ4bg3Llz6Ny5Mzp37owLFy6U7IdApIcMDWT45v2aGNPaAwCwaP8VfLXzEtR81BIRUYmQCQn/2TtlyhSEhYXh6NGjL20zcOBAJCcnY/v27YWOj46ORvXq1XHq1CnUr18fALB37160a9cOd+/ehYuLC5YtW4Zp06YhPj4eCoVCs+zt27fj8uXLAICePXsiIyMDwcHBmnk3atQIderUwfLly1+7LqmpqbC0tERKSgosLCyK+hEQ6b21YTcwY+clAMD7dVwwr1ttKOSSd64TEemEvuy/Jf1V3bFjB+rXr4/u3bvDwcEBvr6+WLVqVYF2hw4dgoODA7y8vDBy5Eg8evRIMy48PBxWVlaaMAYAAQEBMDAwwIkTJzRtmjdvrgljABAYGIiYmBgkJSVp2gQEBGgtNzAwEOHh4YXWnpWVhdTUVK0XUVk0sEklLOlVB3IDGf6OuIehv55GZjYftUREpEuSBrLr169j2bJl8PDwwL59+zBy5EiMGTMG69at07QJCgrCr7/+itDQUMyZMweHDx9G27ZtkZf37IHI8fHxcHBw0JqvXC6HjY0N4uPjNW0cHR212uS/f12b/PEvmjVrFiwtLTUvV1fXf/FJEOm39+tUwM8D6kNlZIDDVx6g788nkJzJRy0REemKpIFMrVajbt26mDlzJnx9fTFs2DAMHTpU6xBhr1690KlTJ/j4+KBz584IDg7GqVOncOjQIekKBzB16lSkpKRoXnfu3JG0HqKS9q6XAzZ81AiWxkY4ezsZPVaEIz7lqdRlERGVCZIGMmdnZ1SvXl1rWLVq1XD79u2XTlO5cmXY2dnh6tWrAAAnJyckJiZqtcnNzcXjx4/h5OSkaZOQkKDVJv/969rkj3+RUqmEhYWF1ouorKvnZo3NI/zhaKHElYR0dF12DNcfpL9+QiIieiVJA1mTJk0QExOjNezKlStwc3N76TR3797Fo0eP4OzsDADw9/dHcnIyzpw5o2lz4MABqNVq+Pn5adocOXIEOTk5mjYhISHw8vLSXNHp7++P0NBQrWWFhITA39//360kURnj6WiOLSMao5KdKeKSn6D78nBE3U2RuiwiotJNSOjkyZNCLpeL7777TsTGxooNGzYIExMTsX79eiGEEGlpaWLixIkiPDxc3LhxQ+zfv1/UrVtXeHh4iKdPn2rmExQUJHx9fcWJEyfEP//8Izw8PETv3r0145OTk4Wjo6Po16+fuHDhgti4caMwMTERK1as0LQJCwsTcrlczJ8/X0RHR4vp06cLIyMjERUVVaR1SUlJEQBESkqKjj4dIv32IO2paP/9EeE2OVjU+HKvCLv6QOqSiIiKTV/235IGMiGE2Llzp6hZs6ZQKpXC29tbrFy5UjMuMzNTtGnTRtjb2wsjIyPh5uYmhg4dKuLj47Xm8ejRI9G7d29hZmYmLCwsxKBBg0RaWppWm8jISNG0aVOhVCpFhQoVxOzZswvUsmnTJuHp6SkUCoWoUaOG2LVrV5HXQ182KNHblPokW/RaES7cJgcLj893iz1R96UuiYioWPRl/y3pfcjKEn25jwnR2/Y0Jw9jN0Zg78V4GMiAmV180KthRanLIiIqEn3Zf/PujkT0r6iMDPFjn7ro1cAVagFM2RaFZYeu8VFLRETFwEBGRP+aoYEMsz7wwch3qwAA5uy9jJm7o/moJSKiImIgIyKdkMlkmBzkjS/aVwMArDp6A5O2nEdOnlriyoiI9B8DGRHp1EfNKmNB99owNJBh69m7GLn+DJ7m5EldFhGRXmMgIyKd61rvHazoWw9KuQH2Ryei/+qTSHmS8/oJiYjKKQYyIioRAdUd8dsQP5ir5Dh58zF6rTyOxDQ+aomIqDAMZERUYhpWssGfw/xhZ6ZE9P1UdFsWjluPMqQui4hI7xQ7kLm7u+Prr79+5fMmiYjyVXexwNaR/qhoY4LbjzPRdVk4Lt1LlbosIiK9UuxANnbsWGzbtg2VK1fGe++9h40bNyIrK6skaiOiMsLN1hRbRvjD28kcD9Oz0HNlOE7eeCx1WUREeuONAllERAROnjyJatWq4ZNPPoGzszNGjx6Ns2fPlkSNRFQGOFio8OdwfzRwt0ba01z0W30C+y8lSF0WEZFe+NePTsrJycFPP/2EyZMnIycnBz4+PhgzZgwGDRoEmUymqzr1nr48eoFI3z3JzsPo388i9HIiDA1kmNu1FrrWe0fqsoionNKX/fcbn9Sfk5ODTZs2oVOnTpgwYQLq16+Pn3/+GV27dsXnn3+OPn366LJOIiojjBWGWN6vHj6oWwF5aoEJmyPx89HrUpdFRCQpeXEnOHv2LNasWYM//vgDBgYG6N+/PxYtWgRvb29Nmy5duqBBgwY6LZSIyg4jQwPM71YbtqYKrDp6A9/uisajjGx8FuhVrnrWiYjyFTuQNWjQAO+99x6WLVuGzp07w8jIqECbSpUqoVevXjopkIjKJgMDGT5vVw02pkrM2XsZyw5dQ1JGNr7r4gNDA4YyIipfinUOWV5eHtavX49OnTrB2tq6JOsqdfTlGDRRabTx5G18/lcU1AIIquGExb3qQGVkKHVZRFQO6Mv+u1jnkBkaGmL48OFITk4uoXKIqDzq1bAifupTFwpDA+y9GI9Ba04h7SkftURE5UexT+qvWbMmrl/nCbhEpFtBNZ2xdnADmCnlCL/+CL1XHcfDdN7jkIjKh2IHsm+//RYTJ05EcHAw7t+/j9TUVK0XEdGbalzFDn8MbQRbUwUuxKWix/Jw3E3KlLosIqISV+z7kBkY/H+Ge/5qKCEEZDIZ8vLydFddKaIvx6CJyoLrD9LRb/VJxCU/gaOFEr8N8YOno7nUZRFRGaQv++9iX2V58ODBkqiDiEijsr0Zto5sjH6rTyA2MR3dl4fjl4ENUM+NFxMRUdn0r+/UT8/oS8ImKkuSM7MxaO0pnLudDGMjQyzrWxfvejlIXRYRlSH6sv9+40CWmZmJ27dvIzs7W2t4rVq1dFJYaaMvG5SorMnMzsXI9Wdx+MoDyA1kWNCjNt6vU0HqsoiojNCX/XexD1k+ePAAgwYNwp49ewodX17PISOikmGikGNV//qYuDkSOyLvYeyfEUjOzMGAxu5Sl0ZEpDPFvspy7NixSE5OxokTJ2BsbIy9e/di3bp18PDwwI4dO0qiRiIq5xRyAyzuWQcD/N0gBDB9x0UsDLkCnnFBRGVFsXvIDhw4gL///hv169eHgYEB3Nzc8N5778HCwgKzZs1C+/btS6JOIirnDAxkmNGpBmxMlVi0/wq+D41FUkY2ZnSqwUctEVGpV+wesoyMDDg4PDup1traGg8ePAAA+Pj44OzZs7qtjojoOTKZDJ8GeOCbzjUhkwG/Hb+FTzeeQ3auWurSiIj+lWIHMi8vL8TExAAAateujRUrViAuLg7Lly+Hs7OzzgskInpRv0ZuWNrbF0aGMgSfv48h604hIytX6rKIiN5YsQPZp59+ivv37wMApk+fjj179qBixYr4/vvvMXPmTJ0XSERUmA61XLB6QAOYKAxxNPYh+vx8AkkZ2a+fkIhID/3r+5BlZmbi8uXLqFixIuzs7HRVV6mjL5fNEpU3524nYdDaU0jOzEFVBzP8OrghXKyMpS6LiEoJfdl/F7uH7EUmJiaoW7duuQ5jRCQd34rW2DLCH86WKlxNTEe3ZcdwNTFd6rKIiIqlSD1k48ePL/IMFy5c+K8KKq30JWETlVdxyU/Qb/UJXH+QAWsTI6wd1BC1Xa2kLouI9Jy+7L+LdNuLc+fOFWlmzz9snIjobapgZYzNw/0xaO0pnL+bgg9XHceKfvXR1IO990Sk//gsSx3Rl4RNVN6lZ+Vi+G+nEXb1ERSGBljcqw7a+fAKcCIqnL7sv//1OWRERPrETCnHLwMboJ2PE7Lz1Bj1+1lsOHFL6rKIiF6p2HfqB4DTp09j06ZNhT5cfNu2bTopjIjoTSnlhljauy6sTC7g9xO3Me2vC0jKyMaollV5agUR6aVi95Bt3LgRjRs3RnR0NP766y/k5OTg4sWLOHDgACwtLUuiRiKiYjM0kOG7zjXxSauqAID5/72Cr4MvQa3mWRpEpH+KHchmzpyJRYsWYefOnVAoFFiyZAkuX76MHj16oGLFiiVRIxHRG5HJZJjQxgtfdqgOAFgTdhMTNkciJ4+PWiIi/VLsQHbt2jXNA8QVCgUyMjIgk8kwbtw4rFy5UucFEhH9W4ObVsKinrUhN5Dhr3NxGP7bGTzJzpO6LCIijWIHMmtra6SlpQEAKlSogAsXLgAAkpOTkZmZqdvqiIh0pIvvO1jVvz5URgY4cDkRfVefQEpmjtRlEREBeINA1rx5c4SEhAAAunfvjk8//RRDhw5F79690bp1a50XSESkKy29HbB+iB8sVHKcuZWEHivCkZD6VOqyiIiKH8h++OEH9OrVCwAwbdo0jB8/HgkJCejatStWr15d7ALi4uLQt29f2NrawtjYGD4+Pjh9+nShbUeMGAGZTIbFixdrDXd3d4dMJtN6zZ49W6vN+fPn0axZM6hUKri6umLu3LkF5r9582Z4e3tDpVLBx8cHu3fvLvb6EJF+q+9ug00j/OFgrkRMQhq6LjuGmw8zpC6LiMq5Yt/2wsbGRvP/BgYGmDJlyhsvPCkpCU2aNEHLli2xZ88e2NvbIzY2FtbW1gXa/vXXXzh+/DhcXFwKndfXX3+NoUOHat6bm5tr/j81NRVt2rRBQEAAli9fjqioKAwePBhWVlYYNmwYAODYsWPo3bs3Zs2ahQ4dOuD3339H586dcfbsWdSsWfON15GI9I+3kwW2jmyMfqtP4OajTHRbfgxrBzVEzQq8UpyIpFHkO/Xn5uYiLy8PSqVSMywhIQHLly9HRkYGOnXqhKZNmxZr4VOmTEFYWBiOHj36ynZxcXHw8/PDvn370L59e4wdOxZjx47VjHd3dy8w7HnLli3DtGnTEB8fD4VCoVn29u3bcfnyZQBAz549kZGRgeDgYM10jRo1Qp06dbB8+fLXrou+3OmXiIruQVoWBvxyEpfup8JcKceqAfXRqLKt1GUR0VukL/vvIh+yHDp0KMaMGaN5n5aWhgYNGuDHH3/Evn370LJly2If4tuxYwfq16+P7t27w8HBAb6+vli1apVWG7VajX79+mHSpEmoUaPGS+c1e/Zs2NrawtfXF/PmzUNubq5mXHh4OJo3b64JYwAQGBiImJgYJCUladoEBARozTMwMBDh4eGFLi8rKwupqalaLyIqXezNldg4vBH8KtkgLSsX/X85if9ejJe6LCIqh4ocyMLCwtC1a1fN+19//RV5eXmIjY1FZGQkxo8fj3nz5hVr4devX8eyZcvg4eGBffv2YeTIkRgzZgzWrVunaTNnzhzI5XKtMPiiMWPGYOPGjTh48CCGDx+OmTNn4rPPPtOMj4+Ph6Ojo9Y0+e/j4+Nf2SZ//ItmzZoFS0tLzcvV1bVY605E+sFCZYR1gxviveqOyM5VY8T6M9h0+o7UZRFROVPkc8ji4uLg4eGheR8aGoquXbtq7s4/YMAArFmzplgLV6vVqF+/PmbOnAkA8PX1xYULF7B8+XIMGDAAZ86cwZIlS3D27NlXPu5k/Pjxmv+vVasWFAoFhg8fjlmzZmkdYtWlqVOnai03NTWVoYyolFIZGWJZn7r4/K8obDp9F59tOY+kjGwMb1FF6tKIqJwocg+ZSqXCkydPNO+PHz8OPz8/rfHp6enFWrizszOqV6+uNaxatWq4ffs2AODo0aNITExExYoVIZfLIZfLcevWLUyYMAHu7u4vna+fnx9yc3Nx8+ZNAICTkxMSEhK02uS/d3JyemWb/PEvUiqVsLCw0HoRUeklNzTAnK61MLxFZQDArD2XMWt3NIp4mi0R0b9S5EBWp04d/PbbbwCeBaWEhAS0atVKM/7atWsvvQLyZZo0aYKYmBitYVeuXIGbmxsAoF+/fjh//jwiIiI0LxcXF0yaNAn79u176XwjIiJgYGAABwcHAIC/vz+OHDmCnJz/vwlkSEgIvLy8NFd0+vv7IzQ0VGs+ISEh8Pf3L9Y6EVHpJZPJMLVtNUxt6w0AWHHkOj7bch65fNQSEZU0UUSHDh0SxsbGonLlysLY2FgMHjxYa/zIkSNF//79izo7IYQQJ0+eFHK5XHz33XciNjZWbNiwQZiYmIj169e/dBo3NzexaNEizftjx46JRYsWiYiICHHt2jWxfv16YW9vr1VLcnKycHR0FP369RMXLlwQGzduFCYmJmLFihWaNmFhYUIul4v58+eL6OhoMX36dGFkZCSioqKKtC4pKSkCgEhJSSnWZ0BE+unPU7dF5am7hNvkYPHRulPiSXau1CURUQnQl/13kW97AQDR0dH473//CycnJ3Tv3h0GBv/fwbZy5Uo0bNgQderUKVYgDA4OxtSpUxEbG4tKlSph/PjxWvcTe9GLt7g4e/YsPv74Y1y+fBlZWVmoVKkS+vXrh/Hjx2udP3b+/HmMGjUKp06dgp2dHT755BNMnjxZa96bN2/GF198gZs3b8LDwwNz585Fu3btirQe+nLZLBHpzn8vxmP0H+eQnatGbVcrvOtpDwcLJRzNVc/+a6GCrakCcsNi32ObiPSEvuy/ixXI6OX0ZYMSkW4dv/4IQ9edRlpWbqHjDWSArZkSDubPApqDuRIO//uv43P/tTNjcCPSR/qy/2Yg0xF92aBEpHs3HmZgR8Q9xKc+xYO0p0hIzUJi2lM8SMuCuoi/oDIZYGuaH9yUcDBXwdFCCXsLFRz/F+IcLZSwM1PCiMGN6K3Rl/03A5mO6MsGJaK3J08t8CgjC4n/C2iJqVmasJaQmqUJbw/Ss5BXxOT2LLgpYP+/wPaynjd7cwY3Il3Ql/13sZ9lSUREzxgayOBgroKDuQrAy5+DmacWeJyRrQltic/1sj37bxYSU5/1uOWqBR6mZ+Nhejai7796+c+Cm/ahUYf/9b7ln+Nmb6aEQs7gRqTvGMiIiEqYoYEM9uZK2JsrUeMVdwdSqwUeZ2Y/62lLe4oHqVlISH2KxLT//29i6lM8SM9CTp7Ao4xsPMrIxuX4tFcu38ZU8UIP23OHTDX/VUIpN9TxmhNRUb1RIEtOTsaWLVtw7do1TJo0CTY2Njh79iwcHR1RoUIFXddIRFQuGBjIYGf27Dyy6nj5oRO1WiApM7tAUNN+/6wHLifvWe/c4yIEN2sTI03vmsOLh0z/N8zeXAmVEYMbka4VO5CdP38eAQEBsLS0xM2bNzF06FDY2Nhg27ZtuH37Nn799deSqJOIiP7HwEAGWzMlbM2UqOb88uAmhEBSZs7/Hxp9LrzlHzLND2/ZeWokZeYgKTMHMQmvDm5WJkZa57I5vnBVaX6oY3AjKrpiB7Lx48dj4MCBmDt3LszNzTXD27Vrhw8//FCnxRER0ZuTyWSwMVXAxlQB78KfAgfgWXBLeZLzwnlthZ/vlp2rRnJmDpIzc3Al4dWPy7NQyTW9a47mKti/cA+3/PBmrGBwIyp2IDt16hRWrFhRYHiFChUQHx+vk6KIiOjtkclksDJRwMpEAS8n85e2E0Ig9UkuEjRXlP7/YdIHadrvs3LVSH2ai9Sn6YhNfHVwM88Pbq+5lxuDG5VlxQ5kSqUSqampBYZfuXIF9vb2OimKiIj0j0wmg6WJESxNjODp+Jrg9jS3wHlthZ3v9jRHjbSnuUh7mo6rrwtuSrn2+W3Phbfn7+VmouD1alT6FPtb26lTJ3z99dfYtGkTgGd/oLdv38bkyZPRtWtXnRdIRESli0wmg6WxESyNjeDxmuCWlvW/4Pa/K0ufv5fb84dMn+TkIS0rF2kPcnHtQcYrl2+mCW7aPWzNPe1fGSSJpFTsG8OmpKSgW7duOH36NNLS0uDi4oL4+Hj4+/tj9+7dMDU1Lala9Zq+3FiOiKisEUIgPSu34OHR1CwkvNDjlpmd99L5GBnKsH1UE9Rwefk946j80Zf99xvfqf+ff/7B+fPnkZ6ejrp16yIgIEDXtZUq+rJBiYjKs/T/9bi92Mt2/PpjRMWlwMvRHDs+acJ7rpGGvuy/+egkHdGXDUpERAU9Ss9C4OIjeJiejREtqmBKW2+pSyI9oS/772KfQ/b9998XOlwmk0GlUqFq1apo3rw5DA35rw8iItIPtmZKzOzig2G/ncGKI9fQupoDGrjbSF0WkUaxe8gqVaqEBw8eIDMzE9bW1gCApKQkmJiYwMzMDImJiahcuTIOHjwIV1fXEilaH+lLwiYiopebtDkSm8/cRUUbE+z5tBlMlbwis7zTl/13sZ84O3PmTDRo0ACxsbF49OgRHj16hCtXrsDPzw9LlizB7du34eTkhHHjxpVEvURERG/sy47VUcHKGLcfZ2Lm7mipyyHSKHYPWZUqVbB161bUqVNHa/i5c+fQtWtXXL9+HceOHUPXrl1x//59Xdaq1/QlYRMR0asdu/YQH646AQBYM6gBWno5SFwRSUlf9t/F7iG7f/8+cnNzCwzPzc3V3KnfxcUFaWmvfhYaERGRFBpXscPgJpUAAJO3nEdyZrbEFRG9QSBr2bIlhg8fjnPnzmmGnTt3DiNHjkSrVq0AAFFRUahUqZLuqiQiItKhz4K8UMXeFIlpWfjy74tSl0NU/EC2evVq2NjYoF69elAqlVAqlahfvz5sbGywevVqAICZmRkWLFig82KJiIh0QWVkiIU96sDQQIYdkfewM/Ke1CVROffG9yG7fPkyrly5AgDw8vKCl5eXTgsrbfTlGDQRERXdopArWBIaCysTI/x3bHM4WKikLoneMn3Zf/PGsDqiLxuUiIiKLidPjQ9+OoaouBS09LLHLwMbQCaTSV0WvUX6sv9+oxuw3L17Fzt27MDt27eRna19MuTChQt1UhgREVFJMzI0wMIetdF+6T84GPMAG0/dQe+GFaUui8qhYgey0NBQdOrUCZUrV8bly5dRs2ZN3Lx5E0II1K1btyRqJCIiKjEejub4LNAL3+6KxjfBl9Ckih0q2ppIXRaVM8U+qX/q1KmYOHEioqKioFKpsHXrVty5cwctWrRA9+7dS6JGIiKiEjW4SSX4VbJBZnYeJm6ORJ6aZ/PQ21XsQBYdHY3+/fsDAORyOZ48eQIzMzN8/fXXmDNnjs4LJCIiKmkGBjLM714bpgpDnLz5GKv/uS51SVTOFDuQmZqaas4bc3Z2xrVr1zTjHj58qLvKiIiI3iJXGxNM71gDADB/3xXExPMG5/T2FDuQNWrUCP/88w8AoF27dpgwYQK+++47DB48GI0aNdJ5gURERG9L9/rvoLW3A7Lz1Bi/KQLZuWqpS6JyotiBbOHChfDz8wMAfPXVV2jdujX+/PNPuLu7a24MS0REVBrJZDLM6uoDaxMjXLyXiqUHYqUuicqJYt2HLC8vD2FhYahVqxasrKxKsKzSR1/uY0JERP/enqj7GLnhLAxkwNaRjeFb0VrqkqiE6Mv+u1g9ZIaGhmjTpg2SkpJKqh4iIiLJtfVxRuc6LlALYMKmSDzJzpO6JCrjin3IsmbNmrh+nVefEBFR2fZVp5pwslDh+sMMzNl7WepyqIwrdiD79ttvMXHiRAQHB+P+/ftITU3VehEREZUFliZGmNe9FgBg7bGbCLvKOwlQySn2sywNDP4/wz3/vC8hBGQyGfLyyme3rr4cgyYiIt36z/YL+O34LThbqrB3bHNYGhtJXRLpkL7sv4v96KSDBw+WRB1ERER6aWo7bxyNfYCbjzLx1c6LWNijjtQlURlU7B4yKpy+JGwiItK9M7eS0H35MagFsLxvPQTVdJK6JNIRfdl/F/scMgA4evQo+vbti8aNGyMuLg4A8Ntvv2luGEtERFSW1HOzxogWVQAA0/6KwsP0LIkrorKm2IFs69atCAwMhLGxMc6ePYusrGdfypSUFMycOVPnBRIREemDsQGeqOZsgUcZ2Zi6LQo8wES69EZXWS5fvhyrVq2CkdH/n9jYpEkTnD17VqfFERER6QuF3AALe9SGwtAAIZcSsOXMXalLojKk2IEsJiYGzZs3LzDc0tISycnJuqiJiIhIL1VztsC49zwBAF/tvIS7SZkSV0RlRbEDmZOTE65evVpg+D///IPKlSsXu4C4uDj07dsXtra2MDY2ho+PD06fPl1o2xEjRkAmk2Hx4sVawx8/fow+ffrAwsICVlZWGDJkCNLT07XanD9/Hs2aNYNKpYKrqyvmzp1bYP6bN2+Gt7c3VCoVfHx8sHv37mKvDxERlW3DmldGPTdrpGflYtLm81CreeiS/r1iB7KhQ4fi008/xYkTJyCTyXDv3j1s2LABEydOxMiRI4s1r6SkJDRp0gRGRkbYs2cPLl26hAULFsDauuAzw/766y8cP34cLi4uBcb16dMHFy9eREhICIKDg3HkyBEMGzZMMz41NRVt2rSBm5sbzpw5g3nz5mHGjBlYuXKlps2xY8fQu3dvDBkyBOfOnUPnzp3RuXNnXLhwoVjrREREZZuhgQwLe9SGicIQ4dcfYe2xm1KXRGWBKCa1Wi2+/fZbYWpqKmQymZDJZEKlUokvvviiuLMSkydPFk2bNn1tu7t374oKFSqICxcuCDc3N7Fo0SLNuEuXLgkA4tSpU5phe/bsETKZTMTFxQkhhPjpp5+EtbW1yMrK0lq2l5eX5n2PHj1E+/bttZbr5+cnhg8fXqR1SUlJEQBESkpKkdoTEVHp9lv4TeE2OVh4TtstYhPSpC6H3pC+7L+L3UMmk8kwbdo0PH78GBcuXMDx48fx4MEDfPPNN8UOgzt27ED9+vXRvXt3ODg4wNfXF6tWrdJqo1ar0a9fP0yaNAk1atQoMI/w8HBYWVmhfv36mmEBAQEwMDDAiRMnNG2aN28OhUKhaRMYGIiYmBjNg9LDw8MREBCgNe/AwECEh4cXWntWVhYfG0VEVI718auI5p72yMpVY/ymCOTkqaUuiUqxYgey9evXIzMzEwqFAtWrV0fDhg1hZmb2Rgu/fv06li1bBg8PD+zbtw8jR47EmDFjsG7dOk2bOXPmQC6XY8yYMYXOIz4+Hg4ODlrD5HI5bGxsEB8fr2nj6Oio1Sb//eva5I9/0axZs2Bpaal5ubq6FmPNiYiotJPJZJjbtRYsjY1w/m4Kfjp4TeqSqBQrdiAbN24cHBwc8OGHH2L37t3/6tmVarUadevWxcyZM+Hr64thw4Zh6NChWL58OQDgzJkzWLJkCdauXav13Ex9MHXqVKSkpGhed+7ckbokIiJ6y5wsVfj6/WdHb5YeiEXU3RSJK6LSqtiB7P79+9i4cSNkMhl69OgBZ2dnjBo1CseOHSv2wp2dnVG9enWtYdWqVcPt27cBPHsiQGJiIipWrAi5XA65XI5bt25hwoQJcHd3B/Dsqs/ExESteeTm5uLx48dwcnLStElISNBqk//+dW3yx79IqVTCwsJC60VEROVPp9ouaF/LGblqgXGbIvA05807Kqj8KnYgk8vl6NChAzZs2IDExEQsWrQIN2/eRMuWLVGlSpVizatJkyaIiYnRGnblyhW4ubkBAPr164fz588jIiJC83JxccGkSZOwb98+AIC/vz+Sk5Nx5swZzTwOHDgAtVoNPz8/TZsjR44gJydH0yYkJAReXl6aKzr9/f0RGhqqVUtISAj8/f2LtU5ERFS+yGQyfPt+TdibK3E1MR3z98W8fiKiF/3bqwIePHggli5dKmrUqCEMDAyKNe3JkyeFXC4X3333nYiNjRUbNmwQJiYmYv369S+d5sWrLIUQIigoSPj6+ooTJ06If/75R3h4eIjevXtrxicnJwtHR0fRr18/ceHCBbFx40ZhYmIiVqxYoWkTFhYm5HK5mD9/voiOjhbTp08XRkZGIioqqkjroi9XaRARkTQORCcIt8nBwn1KsAi/9lDqcqiI9GX//UaBLCMjQ6xfv160bdtWKBQKUaVKFfHFF1+I6OjoYs9r586dombNmkKpVApvb2+xcuXKV7YvLJA9evRI9O7dW5iZmQkLCwsxaNAgkZamfQlyZGSkaNq0qVAqlaJChQpi9uzZBea9adMm4enpKRQKhahRo4bYtWtXkddDXzYoERFJZ8rWSOE2OVg0mR0qUp9kS10OFYG+7L9lQhTv6ai9evVCcHAwTExM0KNHD/Tp04eH9fDs5rOWlpZISUnh+WREROVUelYu2i45gjuPn6BnfVfM6VZL6pLoNfRl/13sc8gMDQ2xadMm3L9/Hz/88INWGONd7YmIqDwzU8qxoHsdyGTAn6fvYP+lhNdPRIQ3CGQbNmxAu3btYGhoCABIS0vDypUr0bBhQ9SuXVvnBRIREZUmDSvZYGizZ892nrItCo8zsiWuiEqDYgeyfEeOHMGAAQPg7OyM+fPno1WrVjh+/LguayMiIiqVxr/nCU9HMzxMz8K0v6JQzLODqBwqViCLj4/H7Nmz4eHhge7du8PCwgJZWVnYvn07Zs+ejQYNGpRUnURERKWGysgQC3vUgdxAhj0X4vF3xD2pSyI9V+RA1rFjR3h5eeH8+fNYvHgx7t27h6VLl5ZkbURERKVWzQqW+LS1BwDgy78v4H7KE4krIn1W5EC2Z88eDBkyBF999RXat2+vOYeMiIiICjfy3Sqo7WqF1Ke5+GzLeR66pJcqciD7559/kJaWhnr16sHPzw8//PADHj58WJK1ERERlWpyQwMs7FEbKiMDHI19iPXHb0ldEumpIgeyRo0aYdWqVbh//z6GDx+OjRs3wsXFBWq1GiEhIUhLSyvJOomIiEqlKvZmmBLkDQCYufsybjzMkLgi0kfFvsrS1NQUgwcPxj///IOoqChMmDABs2fPhoODAzp16lQSNRIREZVq/f3d0aSqLZ7k5GHCpgjk5qmlLon0zBvf9gIAvLy8MHfuXNy9exd//PGHrmoiIiIqUwwMZJjXrTbMlXKcvZ2MFUeuS10S6Zl/FcjyGRoaonPnztixY4cuZkdERFTmuFgZY0anGgCAxfuv4NK9VIkrIn2ik0BGREREr/dB3QoIrOGInDyB8ZsikJWbJ3VJpCcYyIiIiN4SmUyGmV18YGuqwOX4NCwKiZW6JNITDGRERERvka2ZErM+8AEArDhyDadvPpa4ItIHDGRERERvWZsaTuhW7x0IAUzYHImMrFypSyKJMZARERFJ4MuO1VHByhi3HmVi5u5oqcshiTGQERERScBCZYR53WoBADacuI1DMYkSV0RSYiAjIiKSSOOqdhjUxB0AMHnreSRnZktbEEmGgYyIiEhCk4O8UdneFAmpWfjy74tSl0MSYSAjIiKSkMrIEAt71IGhgQw7Iu8h+Pw9qUsiCTCQERERSayOqxVGtawKAPhi+wUkpj6VuCJ62xjIiIiI9MAnraqiZgULJGfmYPLW8xBCSF0SvUUMZERERHrAyNAAC3vUgUJugIMxD7Dx1B2pS6K3iIGMiIhIT3g6muOzQC8AwLfBl3D7UabEFdHbwkBGRESkRwY3qYSGlWyQkZ2HiZsjkafmocvygIGMiIhIjxgYyLCge22YKgxx8uZjrP7nutQl0VvAQEZERKRnXG1M8GXH6gCA+fuuICY+TeKKqKQxkBEREemhHvVd0crbAdl5aozfFIHsXLXUJVEJYiAjIiLSQzKZDLO7+sDaxAgX76Vi6YFYqUuiEsRARkREpKcczFX4rosPAOCnQ9dw7naSxBVRSWEgIyIi0mPtfJzxfh0X5KkFJmyKxJPsPKlLohLAQEZERKTnvu5UE44WSlx/mIE5ey9LXQ6VAAYyIiIiPWdpYoR53WoDANYeu4mwqw8lroh0jYGMiIioFGjuaY++jSoCACZujkTKkxyJKyJdYiAjIiIqJT5vVw1utia4n/IUX+28KHU5pEMMZERERKWEiUKOhT1qw0AGbDsbh70X4qUuiXSEgYyIiKgUqedmg+EtqgAApv0VhYfpWRJXRLrAQEZERFTKjA3wgLeTOR5lZGPqtigIwQeQl3YMZERERKWMUm6IRT3rwMhQhpBLCdh6Nk7qkuhfYiAjIiIqhao5W2Dce54AgK92XMTdpEyJK6J/Q/JAFhcXh759+8LW1hbGxsbw8fHB6dOnNeNnzJgBb29vmJqawtraGgEBAThx4oTWPNzd3SGTybRes2fP1mpz/vx5NGvWDCqVCq6urpg7d26BWjZv3gxvb2+oVCr4+Phg9+7dJbPSREREOjC8eRXUc7NGWlYuJm0+D7Wahy5LK0kDWVJSEpo0aQIjIyPs2bMHly5dwoIFC2Btba1p4+npiR9++AFRUVH4559/4O7ujjZt2uDBgwda8/r6669x//59zeuTTz7RjEtNTUWbNm3g5uaGM2fOYN68eZgxYwZWrlypaXPs2DH07t0bQ4YMwblz59C5c2d07twZFy5cKPkPgoiI6A0YGsiwoHttGBsZIvz6I6w9dlPqkugNyYSEZwJOmTIFYWFhOHr0aJGnSU1NhaWlJfbv34/WrVsDeNZDNnbsWIwdO7bQaZYtW4Zp06YhPj4eCoVCs+zt27fj8uVnj6Do2bMnMjIyEBwcrJmuUaNGqFOnDpYvX17kulJSUmBhYVHk9SEiIvq3fjt+C//ZfgFKuQF2jWmGqg5mUpdUaujL/lvSHrIdO3agfv366N69OxwcHODr64tVq1a9tH12djZWrlwJS0tL1K5dW2vc7NmzYWtrC19fX8ybNw+5ubmaceHh4WjevLkmjAFAYGAgYmJikJSUpGkTEBCgNc/AwECEh4frYlWJiIhKTF+/imjuaY+sXDXGb4pATp5a6pKomCQNZNevX8eyZcvg4eGBffv2YeTIkRgzZgzWrVun1S44OBhmZmZQqVRYtGgRQkJCYGdnpxk/ZswYbNy4EQcPHsTw4cMxc+ZMfPbZZ5rx8fHxcHR01Jpn/vv4+PhXtskf/6KsrCykpqZqvYiIiKQgk8kwt2stWKjkOH83BT8dvCZ1SVRMkgYytVqNunXrYubMmfD19cWwYcMwdOjQAocIW7ZsiYiICBw7dgxBQUHo0aMHEhMTNePHjx+Pd999F7Vq1cKIESOwYMECLF26FFlZJXezvFmzZsHS0lLzcnV1LbFlERERvY6TpQrfdK4JAFh6IBZRd1MkroiKQ9JA5uzsjOrVq2sNq1atGm7fvq01zNTUFFWrVkWjRo2wevVqyOVyrF69+qXz9fPzQ25uLm7evAkAcHJyQkJCglab/PdOTk6vbJM//kVTp05FSkqK5nXnzp3XrzAREVEJ6lTbBe19nJGrFhi3KQJPc/KkLomKSNJA1qRJE8TExGgNu3LlCtzc3F45nVqtfmXvV0REBAwMDODg4AAA8Pf3x5EjR5CTk6NpExISAi8vL80Vnf7+/ggNDdWaT0hICPz9/QtdhlKphIWFhdaLiIhISjKZDN90rgl7cyWuJqZj/r6Y109EekHSQDZu3DgcP34cM2fOxNWrV/H7779j5cqVGDVqFAAgIyMDn3/+OY4fP45bt27hzJkzGDx4MOLi4tC9e3cAz07GX7x4MSIjI3H9+nVs2LAB48aNQ9++fTVh68MPP4RCocCQIUNw8eJF/Pnnn1iyZAnGjx+vqeXTTz/F3r17sWDBAly+fBkzZszA6dOnMXr06Lf/wRAREb0hG1MF5nT1AQCsDruB49cfSVwRFYmQ2M6dO0XNmjWFUqkU3t7eYuXKlZpxT548EV26dBEuLi5CoVAIZ2dn0alTJ3Hy5ElNmzNnzgg/Pz9haWkpVCqVqFatmpg5c6Z4+vSp1nIiIyNF06ZNhVKpFBUqVBCzZ88uUMumTZuEp6enUCgUokaNGmLXrl1FXo+UlBQBQKSkpLzBp0BERKRbk7dECrfJwaLJ7FCR+iRb6nL0lr7svyW9D1lZoi/3MSEiIgKA9KxcBC0+grtJT9CzvivmdKsldUl6SV/235I/OomIiIh0z0wpx4LutSGTAX+evoPQ6ITXT0SSYSAjIiIqo/wq2+KjppUAAJO3RuFxRrbEFdHLMJARERGVYRPaeMHDwQwP07PwxfYo8Ewl/cRARkREVIapjAyxqGcdyA1k2B0Vjx2R96QuiQrBQEZERFTG1axgiTGtPQAA/9l+AfdTnkhcEb2IgYyIiKgc+PjdKqjtaoXUp7n4bMt5HrrUMwxkRERE5YDc0AALe9SGUm6Ao7EPsf7E7ddPRG8NAxkREVE5UcXeDFPaegMAZu6Kxo2HGRJXRPkYyIiIiMqRAf7uaFzFFk9y8jBhUwTy1Dx0qQ8YyIiIiMoRAwMZ5nWvDXOlHGdvJ2PFkWtSl0RgICMiIip3KlgZY3qnGgCARSFXcOleqsQVEQMZERFROdS1bgW0qe6InDyB8ZsikJWbJ3VJ5RoDGRERUTkkk8kw8wMf2JoqcDk+DYv3x0pdUrnGQEZERFRO2ZkpMfMDHwDAisPXcPrmY4krKr8YyIiIiMqxwBpO6Fr3HagFMGFzJDKycqUuqVxiICMiIirnpneqDhdLFW49ysSsPdFSl1MuMZARERGVcxYqI8zvXhsAsP74bRy+8kDiisofBjIiIiJC46p2GNjYHQDw2ZZIJGdmS1tQOcNARkRERACAyUHeqGxvioTULHz590WpyylXGMiIiIgIAGCsMMTCHnVgaCDDjsh7CD5/T+qSyg0GMiIiItKo42qFUe9WAQB8sf0CElOfSlxR+cBARkRERFpGt/JAzQoWSM7MweSt5yEEH0Be0hjIiIiISItCboCFPepAITfAwZgH+PPUHalLKvMYyIiIiKgAT0dzTGrjBQD4JvgSbj/KlLiiso2BjIiIiAo1uGklNKxkg4zsPEzcHIk8NQ9dlhQGMiIiIiqUoYEMC7rXhqnCECdvPsYv/9yQuqQyi4GMiIiIXsrVxgT/6VAdADBvXwxi4tMkrqhsYiAjIiKiV+rZwBWtvB2QnafG+E0RyM5VS11SmcNARkRERK8kk8kw+wMfWJkY4eK9VPxwIFbqksocBjIiIiJ6LQcLFb7r7AMA+PHQNZy7nSRxRWULAxkREREVSftazni/jgvy1AITNkXiSXae1CWVGQxkREREVGRfd6oJRwslrj/MwJy9l6Uup8xgICMiIqIiszQxwtxutQEAa4/dRNjVhxJXVDYwkBEREVGxtPC0R99GFQEAkzZHIvVpjsQVlX4MZERERFRsn7erBjdbE9xLeYqvdlySupxSj4GMiIiIis1EIceC7rVhIAO2nr2LvRfipS6pVGMgIyIiojdS390Gw1tUAQBM+ysKD9OzJK6o9GIgIyIiojc2NsAD3k7meJSRjanboiAEH0D+JhjIiIiI6I0p5YZY2KMOjAxlCLmUgK1n46QuqVRiICMiIqJ/pbqLBca95wkA+GrHRcQlP5G4otJH8kAWFxeHvn37wtbWFsbGxvDx8cHp06c142fMmAFvb2+YmprC2toaAQEBOHHihNY8Hj9+jD59+sDCwgJWVlYYMmQI0tPTtdqcP38ezZo1g0qlgqurK+bOnVugls2bN8Pb2xsqlQo+Pj7YvXt3yaw0ERFRGTO8eRXUrWiFtKxcTNocCbWahy6LQ9JAlpSUhCZNmsDIyAh79uzBpUuXsGDBAlhbW2vaeHp64ocffkBUVBT++ecfuLu7o02bNnjw4IGmTZ8+fXDx4kWEhIQgODgYR44cwbBhwzTjU1NT0aZNG7i5ueHMmTOYN28eZsyYgZUrV2raHDt2DL1798aQIUNw7tw5dO7cGZ07d8aFCxfezodBRERUihkayLCgRx0YGxni2LVHWBd+U+qSShWZkPDsuylTpiAsLAxHjx4t8jSpqamwtLTE/v370bp1a0RHR6N69eo4deoU6tevDwDYu3cv2rVrh7t378LFxQXLli3DtGnTEB8fD4VCoVn29u3bcfnys8c+9OzZExkZGQgODtYsq1GjRqhTpw6WL19e5LpSUlJgYWFRnI+BiIiozPjt+C38Z/sFKOUG2DWmGao6mEld0ivpy/5b0h6yHTt2oH79+ujevTscHBzg6+uLVatWvbR9dnY2Vq5cCUtLS9Su/eyxDeHh4bCystKEMQAICAiAgYGB5tBmeHg4mjdvrgljABAYGIiYmBgkJSVp2gQEBGgtLzAwEOHh4TpbXyIiorKur19FNPOwQ1auGhM2RSA3Ty11SaWCpIHs+vXrWLZsGTw8PLBv3z6MHDkSY8aMwbp167TaBQcHw8zMDCqVCosWLUJISAjs7OwAAPHx8XBwcNBqL5fLYWNjg/j4eE0bR0dHrTb571/XJn/8i7KyspCamqr1IiIiKu9kMhnmdqsFC5UckXdT8NOha1KXVCpIGsjUajXq1q2LmTNnwtfXF8OGDcPQoUMLHCJs2bIlIiIicOzYMQQFBaFHjx5ITEyUqOpnZs2aBUtLS83L1dVV0nqIiIj0hbOlMb7pXBMA8H1oLKLupkhckf6TNJA5OzujevXqWsOqVauG27dvaw0zNTVF1apV0ahRI6xevRpyuRyrV68GADg5ORUIZ7m5uXj8+DGcnJw0bRISErTa5L9/XZv88S+aOnUqUlJSNK87d+4UZ9WJiIjKtE61XdDOxwm5aoHxmyLwNCdP6pL0mqSBrEmTJoiJidEaduXKFbi5ub1yOrVajaysZ49n8Pf3R3JyMs6cOaMZf+DAAajVavj5+WnaHDlyBDk5//80+pCQEHh5eWmu6PT390doaKjWckJCQuDv719oDUqlEhYWFlovIiIiekYmk+Hbzj6wM1MiNjEdC/4b8/qJyjFJA9m4ceNw/PhxzJw5E1evXsXvv/+OlStXYtSoUQCAjIwMfP755zh+/Dhu3bqFM2fOYPDgwYiLi0P37t0BPOtRCwoKwtChQ3Hy5EmEhYVh9OjR6NWrF1xcXAAAH374IRQKBYYMGYKLFy/izz//xJIlSzB+/HhNLZ9++in27t2LBQsW4PLly5gxYwZOnz6N0aNHv/0PhoiIqAywMVVgTlcfAMDP/9zA8euPJK5IjwmJ7dy5U9SsWVMolUrh7e0tVq5cqRn35MkT0aVLF+Hi4iIUCoVwdnYWnTp1EidPntSax6NHj0Tv3r2FmZmZsLCwEIMGDRJpaWlabSIjI0XTpk2FUqkUFSpUELNnzy5Qy6ZNm4Snp6dQKBSiRo0aYteuXUVej5SUFAFApKSkFPMTICIiKts+2xwp3CYHiyazQ0Xa0xypy9GiL/tvSe9DVpboy31MiIiI9E3a0xy0XXIUd5OeoFcDV8zuWkvqkjT0Zf8t+aOTiIiIqGwzVxlhfvfakMmAjafuIDQ64fUTlTMMZERERFTiGlW2xZAmlQAAk7dG4XFGtsQV6RcGMiIiInorJgZ6wcPBDA/Ts/DF9ijwrKn/x0BGREREb4XKyBALe9SB3ECG3VHx2BF5T+qS9AYDGREREb01Pu9Y4pNWHgCA/2y/gPiUpxJXpB8YyIiIiOit+rhlFdR+xxKpT3MxaUskD12CgYyIiIjeMiNDAyzoUQdKuQGOxj7E+hO3Xz9RGcdARkRERG9dVQczTA7yBgDM3BWNmw8zJK5IWgxkREREJImBjd3hX9kWT3LyMH5TBPLU5ffQJQMZERERScLAQIb5PWrDXCnH2dvJWHHkmtQlSYaBjIiIiCRTwcoYX3asDgBYFHIFl+6lSlyRNBjIiIiISFLd6r2D96o7IidPYPymCGTl5kld0lvHQEZERESSkslkmPWBD2xNFbgcn4bF+2OlLumtYyAjIiIiydmZKfFdFx8AwIrD13Dm1mOJK3q7GMiIiIhILwTVdMIHdStALYDxmyKRkZUrdUlvDQMZERER6Y3pHWvAxVKFW48yMWtPtNTlvDUMZERERKQ3LI2NMK97bQDA+uO3cfjKA4krejsYyIiIiEivNKlqh4GN3QEAn22JREpmjrQFvQUMZERERKR3Jgd5o7KdKRJSs/DljgtSl1PiGMiIiIhI7xgrDLGgR20YyIC/I+4h+Pw9qUsqUQxkREREpJd8K1pjVMuqAIAvtl9AYupTiSsqOQxkREREpLc+aeWBGi4WSM7MwZRtURCibD6AnIGMiIiI9JZCboCFPepAYWgAE4UhsnLVUpdUIuRSF0BERET0Kl5O5tg7thkq25tJXUqJYQ8ZERER6b2yHMYABjIiIiIiyTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGREREJDEGMiIiIiKJMZARERERSYyBjIiIiEhiDGREREREEmMgIyIiIpKYXOoCygohBAAgNTVV4kqIiIioqPL32/n7cakwkOlIWloaAMDV1VXiSoiIiKi40tLSYGlpKdnyZULqSFhGqNVq3Lt3D+bm5pDJZDqdd2pqKlxdXXHnzh1YWFjodN76oKyvH1D215HrV/qV9XXk+pV+JbWOQgikpaXBxcUFBgbSncnFHjIdMTAwwDvvvFOiy7CwsCizf2hA2V8/oOyvI9ev9Cvr68j1K/1KYh2l7BnLx5P6iYiIiCTGQEZEREQkMQayUkCpVGL69OlQKpVSl1Iiyvr6AWV/Hbl+pV9ZX0euX+lX1teRJ/UTERERSYw9ZEREREQSYyAjIiIikhgDGREREZHEGMhKEXd3dyxevFjqMojKhbVr18LKykrqMojoXxo4cCA6d+5c5PY3b96ETCZDREQEAODQoUOQyWRITk4ukfryMZDpUHh4OAwNDdG+fXupS3mt4n5By5KBAwdCJpNhxIgRBcaNGjUKMpkMAwcOfPuFUZHlb8MXX0FBQTpbRs+ePXHlyhWdza88Kk2/iS8qyZ2wvoT9l+0HXlz3/Pf5L3t7e7Rr1w5RUVGvXcaqVatQu3ZtmJmZwcrKCr6+vpg1a5aO1+TVlixZgrVr177x9I0bN8b9+/eLdPPYf/O9YSDTodWrV+OTTz7BkSNHcO/ePanLoVdwdXXFxo0b8eTJE82wp0+f4vfff0fFihUlrEx38vLyoFarpS6jxAQFBeH+/ftarz/++ENn8zc2NoaDg4PO5vemsrOzpS7hjfE3sWyJiYnB/fv3sW/fPmRlZaF9+/av/H7+8ssvGDt2LMaMGYOIiAiEhYXhs88+Q3p6+lus+tld+P9NAFYoFHByctL5YxFfxECmI+np6fjzzz8xcuRItG/fXiuN5yfm0NBQ1K9fHyYmJmjcuDFiYmI0ba5du4b3338fjo6OMDMzQ4MGDbB///6XLm/w4MHo0KGD1rCcnBw4ODhg9erVAIAtW7bAx8cHxsbGsLW1RUBAADIyMjBjxgysW7cOf//9t+ZfPIcOHdLp56Hv6tatC1dXV2zbtk0zbNu2bahYsSJ8fX01w/bu3YumTZvCysoKtra26NChA65du6YZn9+1vW3bNrRs2RImJiaoXbs2wsPDNW0ePXqE3r17o0KFCjAxMYGPj0+B4JCWloY+ffrA1NQUzs7OWLRoEd59912MHTtW0yYrKwsTJ05EhQoVYGpqCj8/P63tlv+v7h07dqB69epQKpW4ffu2Dj81/aJUKuHk5KT1sra2BgDIZDL8/PPP6NKlC0xMTODh4YEdO3ZoTb9jxw54eHhApVKhZcuWWLdunda/bF/sxZgxYwbq1KmD3377De7u7rC0tESvXr2QlpamaaNWqzFr1ixUqlQJxsbGqF27NrZs2aK13AsXLqBt27YwMzODo6Mj+vXrh4cPH2rGv/vuuxg9ejTGjh0LOzs7BAYG6viTezte9ZsIADt37kSDBg2gUqlgZ2eHLl26aMZlZWVh8uTJcHV1hVKpRNWqVTW/awBw+PBhNGzYEEqlEs7OzpgyZQpyc3M14ws7vaNOnTqYMWOG5v2rviM3b95Ey5YtAQDW1tZaveb/9jfh0KFDGDRoEFJSUjS/v8/Xpc8cHBzg5OSEunXrYuzYsbhz5w4uX7780vY7duxAjx49MGTIEFStWhU1atRA79698d1332na5PfSffXVV7C3t4eFhQVGjBihFfSK8nd18eJFdOjQARYWFjA3N0ezZs002+XFnsDXbcMXvdjrdevWLXTs2BHW1tYwNTVFjRo1sHv37ld+b4qCgUxHNm3aBG9vb3h5eaFv37745Zdf8OIt3qZNm4YFCxbg9OnTkMvlGDx4sGZceno62rVrh9DQUJw7dw5BQUHo2LHjS3eoH330Efbu3Yv79+9rhgUHByMzMxM9e/bE/fv30bt3bwwePBjR0dE4dOgQPvjgAwghMHHiRPTo0UOrh6Fx48Yl88HoscGDB2PNmjWa97/88gsGDRqk1SYjIwPjx4/H6dOnERoaCgMDA3Tp0qVAz9O0adMwceJEREREwNPTE71799bsIJ4+fYp69eph165duHDhAoYNG4Z+/frh5MmTmunHjx+PsLAw7NixAyEhITh69CjOnj2rtYzRo0cjPDwcGzduxPnz59G9e3cEBQUhNjZW0yYzMxNz5szBzz//jIsXL+pFD49UvvrqK/To0QPnz59Hu3bt0KdPHzx+/BgAcOPGDXTr1g2dO3dGZGQkhg8fjmnTpr12nteuXcP27dsRHByM4OBgHD58GLNnz9aMnzVrFn799VcsX74cFy9exLhx49C3b18cPnwYAJCcnIxWrVrB19cXp0+fxt69e5GQkIAePXpoLWfdunVQKBQICwvD8uXLdfipvD2v+k3ctWsXunTpgnbt2uHcuXMIDQ1Fw4YNNdP2798ff/zxB77//ntER0djxYoVMDMzAwDExcWhXbt2aNCgASIjI7Fs2TKsXr0a3377bbFrfNl3xNXVFVu3bgXw/71CS5YsAfDvfxMaN26MxYsXw8LCQvP7O3HixDf6jKWSkpKCjRs3AnjWe/QyTk5OOH78OG7duvXK+YWGhmr2U3/88Qe2bduGr776SjP+dX9XcXFxaN68OZRKJQ4cOIAzZ85g8ODBWiH9eUXdhi8zatQoZGVl4ciRI4iKisKcOXNgZmb2yu9NkQjSicaNG4vFixcLIYTIyckRdnZ24uDBg0IIIQ4ePCgAiP3792va79q1SwAQT548eek8a9SoIZYuXap57+bmJhYtWqR5X716dTFnzhzN+44dO4qBAwcKIYQ4c+aMACBu3rxZ6LwHDBgg3n///eKuZpmQv+6JiYlCqVSKmzdvips3bwqVSiUePHgg3n//fTFgwIBCp33w4IEAIKKiooQQQty4cUMAED///LOmzcWLFwUAER0d/dIa2rdvLyZMmCCEECI1NVUYGRmJzZs3a8YnJycLExMT8emnnwohhLh165YwNDQUcXFxWvNp3bq1mDp1qhBCiDVr1ggAIiIiotifSWkzYMAAYWhoKExNTbVe3333nRBCCADiiy++0LRPT08XAMSePXuEEEJMnjxZ1KxZU2ue06ZNEwBEUlKSEOLZ52lpaakZP336dGFiYiJSU1M1wyZNmiT8/PyEEEI8ffpUmJiYiGPHjmnNd8iQIaJ3795CCCG++eYb0aZNG63xd+7cEQBETEyMEEKIFi1aCF9f3zf9aPTGq34T/f39RZ8+fQqdLiYmRgAQISEhhY7//PPPhZeXl1Cr1ZphP/74ozAzMxN5eXlCiIK/lUIIUbt2bTF9+nTN+9d9R/J/t/O/Dy/zJr8JL363pPKyvyOVSqW17vmfRf54AAKA6NSp0yvnf+/ePdGoUSMBQHh6eooBAwaIP//8U7Od8muwsbERGRkZmmHLli3TbM+i/F1NnTpVVKpUSWRnZ790PV+1v3vZNjx37pzW+ud/Hj4+PmLGjBmFzquo35vCsIdMB2JiYnDy5En07t0bACCXy9GzZ0+tLnYAqFWrlub/nZ2dAQCJiYkAnvWQTZw4EdWqVYOVlRXMzMwQHR39ykNOH330kaaHJyEhAXv27NH0utWuXRutW7eGj48PunfvjlWrViEpKUl3K10G2Nvbaw6lrFmzBu3bt4ednZ1Wm9jYWPTu3RuVK1eGhYUF3N3dAaDAdnnVts3Ly8M333wDHx8f2NjYwMzMDPv27dPM4/r168jJydHqIbC0tISXl5fmfVRUFPLy8uDp6QkzMzPN6/Dhw1pd7QqFQquWsqxly5aIiIjQej1/ocbzn4OpqSksLCw02yQmJgYNGjTQmt/zn//LuLu7w9zcXPPe2dlZM8+rV68iMzMT7733ntY2+vXXXzXbKDIyEgcPHtQa7+3tDQBa27FevXrF/Tj0yut+EyMiItC6detCp42IiIChoSFatGhR6Pjo6Gj4+/trnc/TpEkTpKen4+7du8Wq81XfkZfRxW+CPins7+jnn38utO3Ro0dx5swZrF27Fp6enq/tvXV2dkZ4eDiioqLw6aefIjc3FwMGDEBQUJBWb1Tt2rVhYmKiee/v74/09HTcuXOnSH9XERERaNasGYyMjIq0zkXdhi8zZswYfPvtt2jSpAmmT5+O8+fPF2m615HrZC7l3OrVq5GbmwsXFxfNMCEElEolfvjhB82w578s+T8m+V/KiRMnIiQkBPPnz0fVqlVhbGyMbt26vfKEyf79+2PKlCkIDw/HsWPHUKlSJTRr1gwAYGhoiJCQEBw7dgz//e9/sXTpUkybNg0nTpxApUqVdLr+pdngwYMxevRoAMCPP/5YYHzHjh3h5uaGVatWwcXFBWq1GjVr1iywXV61befNm4clS5Zg8eLF8PHxgampKcaOHVusk7XT09NhaGiIM2fOwNDQUGtc/qEc4NmJ6CV94qm+MDU1RdWqVV86/sUfZ5lM9q8vcnjVPPNPVN61axcqVKig1S7/2Xvp6eno2LEj5syZU2De+Ttt4Nm6lWav+000NjZ+6bSvGldUBgYGBU4ZycnJKdDuTb4juvhN0CeF/R29LNhWqlQJVlZW8PLyQmJiInr27IkjR468dhk1a9ZEzZo18fHHH2PEiBFo1qwZDh8+rDnf6lWK8ndV3O9MUbfhy3z00UcIDAzErl278N///hezZs3CggUL8MknnxSrjhexh+xfys3Nxa+//ooFCxZo/QsjMjISLi4uRb7qKywsDAMHDkSXLl3g4+MDJycn3Lx585XT2NraonPnzlizZg3Wrl1b4PwnmUyGJk2a4KuvvsK5c+egUCjw119/AXjWk5KXl/dG61yWBAUFITs7Gzk5OQVOnn706BFiYmLwxRdfoHXr1qhWrdob9TKGhYXh/fffR9++fVG7dm1UrlxZ63YKlStXhpGREU6dOqUZlpKSotXG19cXeXl5SExMRNWqVbVeTk5Ob7Dm5ZuXlxdOnz6tNez5z/9NPH8hxYvbyNXVFcCzi0kuXrwId3f3Am1KewjLV5TfxFq1aiE0NLTQ6X18fKBWqzXnB72oWrVqCA8P1wpcYWFhMDc3xzvvvAPgWe/38+fXpqam4saNG8Vaj/xzo57/ndTVb0JZ+P0dNWoULly4oNmnFFX16tUBPDuPK19kZKTWFe/Hjx/XnJNVlL+rWrVq4ejRo4WG7hfpahu6urpixIgR2LZtGyZMmIBVq1YBKPx7U1TsIfuXgoODkZSUhCFDhhS4R0nXrl2xevVqzJs377Xz8fDwwLZt29CxY0fIZDL85z//KdK/pj766CN06NABeXl5GDBggGb4iRMnEBoaijZt2sDBwQEnTpzAgwcPUK1aNQDPDr3s27cPMTExsLW1haWlZZG7e8sSQ0NDREdHa/7/edbW1rC1tcXKlSvh7OyM27dvY8qUKcVehoeHB7Zs2YJjx47B2toaCxcuREJCguaHydzcHAMGDMCkSZNgY2MDBwcHTJ8+HQYGBpp/WXt6eqJPnz7o378/FixYAF9fXzx48AChoaGoVatWqbzP07+VlZWF+Ph4rWFyubzAYefCDB8+HAsXLsTkyZMxZMgQREREaK4CfNMeRnNzc0ycOBHjxo2DWq1G06ZNkZKSgrCwMFhYWGDAgAEYNWoUVq1ahd69e+Ozzz6DjY0Nrl69io0bN+Lnn38u8B0sjYr6m9i6dWtUqVIFvXr1Qm5uLnbv3o3JkyfD3d0dAwYMwODBg/H999+jdu3auHXrFhITE9GjRw98/PHHWLx4MT755BOMHj0aMTExmD59OsaPHw8Dg2d9DK1atcLatWvRsWNHWFlZ4csvvyz2Z+vm5gaZTIbg4GC0a9cOxsbGOvtNcHd3R3p6OkJDQzWH654/ZFcamJiYYOjQoZg+fTo6d+5c6N/NyJEj4eLiglatWuGdd97B/fv38e2338Le3h7+/v6adtnZ2RgyZAi++OIL3Lx5E9OnT8fo0aNhYGBQpL+r0aNHY+nSpejVqxemTp0KS0tLHD9+HA0bNtQ69QPQze/62LFj0bZtW3h6eiIpKQkHDx7U7FsL+948fxTjVdhD9i+tXr0aAQEBhd4wrmvXrjh9+nSRji8vXLgQ1tbWaNy4MTp27IjAwEDUrVv3tdMFBATA2dkZgYGBWocHLCwscOTIEbRr1w6enp744osvsGDBArRt2xYAMHToUHh5eaF+/fqwt7dHWFhYMda6bLGwsICFhUWB4QYGBti4cSPOnDmDmjVrYty4cUUK1y/64osvULduXQQGBuLdd9+Fk5NTgZsxLly4EP7+/ujQoQMCAgLQpEkTVKtWDSqVStNmzZo16N+/PyZMmAAvLy907twZp06dKjP3TSuuvXv3wtnZWevVtGnTIk1bqVIlbNmyBdu2bUOtWrWwbNkyzVWW+YdB3sQ333yD//znP5g1axaqVauGoKAg7Nq1S3OagIuLC8LCwpCXl4c2bdrAx8cHY8eOhZWVlSZMlHZF+U20sbHB5s2bsWPHDtSpUwetWrXSuup42bJl6NatGz7++GN4e3tj6NChmh6VChUqYPfu3Th58iRq166NESNGaHbm+aZOnYoWLVqgQ4cOaN++PTp37owqVaoUaz0qVKiAr776ClOmTIGjo6MmIOjiN6Fx48YYMWIEevbsCXt7e8ydO7fY89AHo0ePRnR0NDZv3lzo+ICAABw/fhzdu3eHp6cnunbtCpVKhdDQUNja2mratW7dGh4eHmjevDl69uyJTp06ad0K5HV/V7a2tjhw4ADS09PRokUL1KtXD6tWrSq0k0EX2zAvLw+jRo3S1OLp6YmffvoJQOHfm6KSiRcPtFOpkp6ejgoVKmDNmjX44IMPpC6HdCQjIwMVKlTAggULMGTIEKnLKRe+++47LF++HHfu3JG6FKJyY+DAgUhOTsb27dulLkVyPGRZSqnVajx8+BALFiyAlZUVOnXqJHVJ9C+cO3cOly9fRsOGDZGSkoKvv/4aAPD+++9LXFnZ9dNPP6FBgwawtbVFWFgY5s2bV6x/zRIR6RIDWSl1+/ZtVKpUCe+88w7Wrl0LuZybsrSbP38+YmJioFAoUK9ePRw9erRI50PRm4mNjcW3336Lx48fo2LFipgwYQKmTp0qdVlEVE7xkCURERGRxMrGWaREREREpRgDGREREZHEGMiIiIiIJMZARkRERCQxBjIiKjcOHToEmUyG5ORknc7X3d0dixcvfmWbGTNmoE6dOjpdLhGVHQxkRFSqDRw4sMCTD3QlP8C96nXo0CGcOnUKw4YN00wnk8l4o0siKhbevIqI6CUaN26s9ZDqTz/9FKmpqVizZo1mmI2NjeaBwkREb4o9ZERUZmRlZWHMmDFwcHCASqVC06ZNcerUqQLtwsLCUKtWLahUKjRq1AgXLlwodH4KhQJOTk6al7GxMZRKpdYwhUKhdcjS3d0dANClSxfIZDLN+8L8/PPPmmeWent7a56HR0TlDwMZEZUZn332GbZu3Yp169bh7NmzqFq1KgIDA/H48WOtdpMmTcKCBQtw6tQp2Nvbo2PHjsjJydFJDfkBcM2aNbh//36hgRAANmzYgC+//BLfffcdoqOjMXPmTPznP//BunXrdFIHEZUuDGREVCZkZGRg2bJlmDdvHtq2bYvq1atj1apVMDY2xurVq7XaTp8+He+99x58fHywbt06JCQk4K+//tJJHfb29gAAKysrODk5ad6/aPr06ViwYAE++OADVKpUCR988AHGjRuHFStW6KQOIipdeA4ZEZUJ165dQ05ODpo0aaIZZmRkhIYNGyI6Olqrrb+/v+b/bWxs4OXlVaBNScrIyMC1a9cwZMgQDB06VDM8NzcXlpaWb60OItIfDGRERG9Zeno6AGDVqlXw8/PTGmdoaChFSUQkMR6yJKIyoUqVKlAoFAgLC9MMy8nJwalTp1C9enWttsePH9f8f1JSEq5cuYJq1arprBYjIyPk5eW9dLyjoyNcXFxw/fp1VK1aVetVqVIlndVBRKUHe8iIqEwwNTXFyJEjMWnSJNjY2KBixYqYO3cuMjMzMWTIEK22X3/9NWxtbeHo6Ihp06bBzs5Op/cyc3d3R2hoKJo0aQKlUglra+sCbb766iuMGTMGlpaWCAoKQlZWFk6fPo2kpCSMHz9eZ7UQUenAHjIiKtXUajXk8mf/tpw9eza6du2Kfv36oW7durh69Sr27dtXIBDNnj0bn376KerVq4f4+Hjs3LlTp/cSW7BgAUJCQuDq6gpfX99C23z00Uf4+eefsWbNGvj4+KBFixZYu3Yte8iIyimZEEJIXQQR0ZsKCgpC1apV8cMPP0hdChHRG2MPGRGVSklJSQgODsahQ4cQEBAgdTlERP8KzyEjolJp8ODBOHXqFCZMmID3339f6nKIiP4VHrIkIiIikhgPWRIRERFJjIGMiIiISGIMZEREREQSYyAjIiIikhgDGREREZHEGMiIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUns/wDAh9rEEbYYnAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.groupby(\"Job_Title\")[\"Salary\"].mean().sort_values(ascending=False).plot(kind=\"line\")\n",
    "plt.title(\"Average Salary by Job Title\")\n",
    "plt.xlabel(\"Job Title\")\n",
    "plt.ylabel(\"Average Salary\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Department</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Engineering</td>\n",
       "      <td>0</td>\n",
       "      <td>65541.063636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Engineering</td>\n",
       "      <td>1</td>\n",
       "      <td>62424.127660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Finance</td>\n",
       "      <td>0</td>\n",
       "      <td>63390.145299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Finance</td>\n",
       "      <td>1</td>\n",
       "      <td>62041.269663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HR</td>\n",
       "      <td>0</td>\n",
       "      <td>63012.556701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HR</td>\n",
       "      <td>1</td>\n",
       "      <td>65882.861702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Marketing</td>\n",
       "      <td>0</td>\n",
       "      <td>65251.597826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>66018.632653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sales</td>\n",
       "      <td>0</td>\n",
       "      <td>64295.846939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sales</td>\n",
       "      <td>1</td>\n",
       "      <td>67838.756757</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Department  Promotion_Last_5Years        Salary\n",
       "0  Engineering                      0  65541.063636\n",
       "1  Engineering                      1  62424.127660\n",
       "2      Finance                      0  63390.145299\n",
       "3      Finance                      1  62041.269663\n",
       "4           HR                      0  63012.556701\n",
       "5           HR                      1  65882.861702\n",
       "6    Marketing                      0  65251.597826\n",
       "7    Marketing                      1  66018.632653\n",
       "8        Sales                      0  64295.846939\n",
       "9        Sales                      1  67838.756757"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby([\"Department\",\"Promotion_Last_5Years\"])[\"Salary\"].mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Department</th>\n",
       "      <th>Job_Title</th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Manager</td>\n",
       "      <td>9</td>\n",
       "      <td>0.586251</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>60132</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.261161</td>\n",
       "      <td>221</td>\n",
       "      <td>1</td>\n",
       "      <td>79947</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>8</td>\n",
       "      <td>0.304382</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>46958</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42</td>\n",
       "      <td>Female</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
       "      <td>0</td>\n",
       "      <td>40662</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.636244</td>\n",
       "      <td>229</td>\n",
       "      <td>1</td>\n",
       "      <td>74307</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Gender   Department Job_Title  Years_at_Company  Satisfaction_Level  \\\n",
       "0   27    Male    Marketing   Manager                 9            0.586251   \n",
       "1   53  Female        Sales  Engineer                10            0.261161   \n",
       "2   59  Female    Marketing   Analyst                 8            0.304382   \n",
       "3   42  Female  Engineering   Manager                 1            0.480779   \n",
       "4   44  Female        Sales  Engineer                10            0.636244   \n",
       "\n",
       "   Average_Monthly_Hours  Promotion_Last_5Years  Salary  Attrition  \n",
       "0                    151                      0   60132          0  \n",
       "1                    221                      1   79947          0  \n",
       "2                    184                      0   46958          1  \n",
       "3                    242                      0   40662          0  \n",
       "4                    229                      1   74307          0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>42.205000</td>\n",
       "      <td>5.605000</td>\n",
       "      <td>0.505995</td>\n",
       "      <td>199.493000</td>\n",
       "      <td>0.486000</td>\n",
       "      <td>64624.980000</td>\n",
       "      <td>0.495000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.016452</td>\n",
       "      <td>2.822223</td>\n",
       "      <td>0.289797</td>\n",
       "      <td>29.631908</td>\n",
       "      <td>0.500054</td>\n",
       "      <td>20262.984333</td>\n",
       "      <td>0.500225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>25.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001376</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30099.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.258866</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47613.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>43.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.505675</td>\n",
       "      <td>201.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>64525.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.761135</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>81921.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.999979</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>99991.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Age  Years_at_Company  Satisfaction_Level  \\\n",
       "count  1000.000000       1000.000000         1000.000000   \n",
       "mean     42.205000          5.605000            0.505995   \n",
       "std      10.016452          2.822223            0.289797   \n",
       "min      25.000000          1.000000            0.001376   \n",
       "25%      33.000000          3.000000            0.258866   \n",
       "50%      43.000000          6.000000            0.505675   \n",
       "75%      51.000000          8.000000            0.761135   \n",
       "max      59.000000         10.000000            0.999979   \n",
       "\n",
       "       Average_Monthly_Hours  Promotion_Last_5Years        Salary    Attrition  \n",
       "count            1000.000000            1000.000000   1000.000000  1000.000000  \n",
       "mean              199.493000               0.486000  64624.980000     0.495000  \n",
       "std                29.631908               0.500054  20262.984333     0.500225  \n",
       "min               150.000000               0.000000  30099.000000     0.000000  \n",
       "25%               173.000000               0.000000  47613.500000     0.000000  \n",
       "50%               201.000000               0.000000  64525.000000     0.000000  \n",
       "75%               225.000000               1.000000  81921.000000     1.000000  \n",
       "max               249.000000               1.000000  99991.000000     1.000000  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Age', 'Gender', 'Department', 'Job_Title', 'Years_at_Company',\n",
       "       'Satisfaction_Level', 'Average_Monthly_Hours', 'Promotion_Last_5Years',\n",
       "       'Salary', 'Attrition'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Department</th>\n",
       "      <th>Job_Title</th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "      <th>Promotion_Last_5Years</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Manager</td>\n",
       "      <td>9</td>\n",
       "      <td>0.586251</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>60132</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.261161</td>\n",
       "      <td>221</td>\n",
       "      <td>1</td>\n",
       "      <td>79947</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>8</td>\n",
       "      <td>0.304382</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>46958</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42</td>\n",
       "      <td>Female</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
       "      <td>0</td>\n",
       "      <td>40662</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44</td>\n",
       "      <td>Female</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>10</td>\n",
       "      <td>0.636244</td>\n",
       "      <td>229</td>\n",
       "      <td>1</td>\n",
       "      <td>74307</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Gender   Department Job_Title  Years_at_Company  Satisfaction_Level  \\\n",
       "0   27    Male    Marketing   Manager                 9            0.586251   \n",
       "1   53  Female        Sales  Engineer                10            0.261161   \n",
       "2   59  Female    Marketing   Analyst                 8            0.304382   \n",
       "3   42  Female  Engineering   Manager                 1            0.480779   \n",
       "4   44  Female        Sales  Engineer                10            0.636244   \n",
       "\n",
       "   Average_Monthly_Hours  Promotion_Last_5Years  Salary  Attrition  \n",
       "0                    151                      0   60132          0  \n",
       "1                    221                      1   79947          0  \n",
       "2                    184                      0   46958          1  \n",
       "3                    242                      0   40662          0  \n",
       "4                    229                      1   74307          0  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data[[\"Years_at_Company\",\"Satisfaction_Level\",\"Average_Monthly_Hours\"]]\n",
    "y = data[\"Salary\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "^C\n"
     ]
    }
   ],
   "source": [
    "!pip install scikit-learn\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Years_at_Company</th>\n",
       "      <th>Satisfaction_Level</th>\n",
       "      <th>Average_Monthly_Hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9</td>\n",
       "      <td>0.586251</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>0.261161</td>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>0.304382</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0.480779</td>\n",
       "      <td>242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>0.636244</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>3</td>\n",
       "      <td>0.377435</td>\n",
       "      <td>239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1</td>\n",
       "      <td>0.431152</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>3</td>\n",
       "      <td>0.647102</td>\n",
       "      <td>206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>2</td>\n",
       "      <td>0.304813</td>\n",
       "      <td>241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1</td>\n",
       "      <td>0.940510</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Years_at_Company  Satisfaction_Level  Average_Monthly_Hours\n",
       "0                   9            0.586251                    151\n",
       "1                  10            0.261161                    221\n",
       "2                   8            0.304382                    184\n",
       "3                   1            0.480779                    242\n",
       "4                  10            0.636244                    229\n",
       "..                ...                 ...                    ...\n",
       "995                 3            0.377435                    239\n",
       "996                 1            0.431152                    154\n",
       "997                 3            0.647102                    206\n",
       "998                 2            0.304813                    241\n",
       "999                 1            0.940510                    159\n",
       "\n",
       "[1000 rows x 3 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler \n",
    "scaler = StandardScaler()\n",
    "X_train = scaler.fit_transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.86965991, -1.44535355, -0.13704082],\n",
       "       [ 0.16690443, -1.75096798,  1.21394692],\n",
       "       [-0.53585105,  0.35320807, -0.10326613],\n",
       "       ...,\n",
       "       [ 1.57241539, -1.13589445,  1.48414447],\n",
       "       [-0.53585105,  1.60933934,  0.2682555 ],\n",
       "       [ 1.22103765,  0.41477896, -0.84630938]])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['scaler.pkl']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import joblib\n",
    "joblib.dump(scaler,\"scaler.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = scaler.fit_transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [ 1.14128867, -1.03680044,  0.30276026],\n",
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       "       [-0.34331448,  1.41437157, -0.35353694],\n",
       "       [-1.82791762,  1.11633012,  0.54455397],\n",
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       "       [-1.45676683,  0.78409056, -1.42433765],\n",
       "       [ 0.77013788,  0.97681098,  0.95905747],\n",
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       "       [-1.45676683, -1.56614612,  0.54455397],\n",
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       "       [ 1.14128867,  1.16641765,  1.51172881],\n",
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       "       [-1.08561605,  0.4968566 , -0.3880789 ],\n",
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       "       [ 0.02783631,  0.88930457, -1.73521528],\n",
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       "       [-0.34331448,  0.19530191,  0.30276026],\n",
       "       [-0.71446526, -1.3095154 , -1.59704744],\n",
       "       [-1.08561605, -0.84541984,  1.13176727],\n",
       "       [ 0.77013788,  1.71687727, -1.28616982],\n",
       "       [-0.71446526,  0.60554719, -1.14800199],\n",
       "       [ 0.77013788, -0.2354487 , -0.59533065],\n",
       "       [-0.34331448, -1.6440537 ,  1.47718685],\n",
       "       [ 0.02783631, -0.59199465,  0.78634768],\n",
       "       [ 0.39898709,  1.31606917, -0.14628519],\n",
       "       [ 1.51243945, -1.33924331, -1.49342157],\n",
       "       [-1.08561605, -0.32366609,  0.57909593],\n",
       "       [-1.45676683, -0.53396705, -0.97529219],\n",
       "       [ 0.02783631, -0.19929124, -0.45716282],\n",
       "       [-1.08561605, -0.34426385,  1.02814139],\n",
       "       [ 0.39898709, -0.06259642,  0.30276026],\n",
       "       [ 1.14128867,  0.65594337,  1.47718685],\n",
       "       [-1.45676683, -0.08913712, -0.14628519],\n",
       "       [-1.08561605, -0.30040483, -0.31899499],\n",
       "       [-0.34331448,  0.01668009, -0.18082715],\n",
       "       [ 0.02783631, -1.04400537,  0.19913439],\n",
       "       [-0.71446526,  0.3167095 ,  1.40810293]])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "\n",
    "def results(predictions):\n",
    "  print(\"Mean absolute error on model is {}\",format(mean_absolute_error(y_test,predictions)))\n",
    "  print(\"Root maen squared error on model is {}\",format(np.sqrt(mean_squared_error(y_test,predictions))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "lr = LinearRegression()\n",
    "lr.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictionlr = lr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error on model is {} 17581.654428973823\n",
      "Root maen squared error on model is {} 20243.734293954476\n"
     ]
    }
   ],
   "source": [
    "results(predictionlr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.svm import SVR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "svrmodel = SVR()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_gridsvr = {\n",
    "    'C': [0.1, 1, 10],\n",
    "    'epsilon': [0.1, 0.2, 0.5],\n",
    "    'kernel': ['linear', 'poly', 'rbf'],  # Ensure valid kernel types\n",
    "    'degree': [2, 3, 4],  # Only applicable if 'poly' kernel is used\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "gridsvr = GridSearchCV(svrmodel, param_gridsvr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(estimator=SVR(),\n",
       "             param_grid={&#x27;C&#x27;: [0.1, 1, 10], &#x27;degree&#x27;: [2, 3, 4],\n",
       "                         &#x27;epsilon&#x27;: [0.1, 0.2, 0.5],\n",
       "                         &#x27;kernel&#x27;: [&#x27;linear&#x27;, &#x27;poly&#x27;, &#x27;rbf&#x27;]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;GridSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>GridSearchCV(estimator=SVR(),\n",
       "             param_grid={&#x27;C&#x27;: [0.1, 1, 10], &#x27;degree&#x27;: [2, 3, 4],\n",
       "                         &#x27;epsilon&#x27;: [0.1, 0.2, 0.5],\n",
       "                         &#x27;kernel&#x27;: [&#x27;linear&#x27;, &#x27;poly&#x27;, &#x27;rbf&#x27;]})</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">best_estimator_: SVR</label><div class=\"sk-toggleable__content fitted\"><pre>SVR(C=10, degree=2, kernel=&#x27;linear&#x27;)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SVR<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.SVR.html\">?<span>Documentation for SVR</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SVR(C=10, degree=2, kernel=&#x27;linear&#x27;)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(estimator=SVR(),\n",
       "             param_grid={'C': [0.1, 1, 10], 'degree': [2, 3, 4],\n",
       "                         'epsilon': [0.1, 0.2, 0.5],\n",
       "                         'kernel': ['linear', 'poly', 'rbf']})"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridsvr.fit(X_train, y_train.values.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'C': 10, 'degree': 2, 'epsilon': 0.1, 'kernel': 'linear'}"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridsvr.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictionssvr = gridsvr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error on model is {} 17724.203088248818\n",
      "Root maen squared error on model is {} 20297.90509729604\n"
     ]
    }
   ],
   "source": [
    "results(predictionssvr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "rfmodel = RandomForestRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_gridrfr = {\n",
    "    \"n_estimators\": [2, 3, 4, 5, 6],  # Use a list instead of a set\n",
    "    \"max_depth\": [5, 10, 15]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "gridrfr = GridSearchCV(estimator=rfmodel, param_grid=param_gridrfr, cv=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15],\n",
       "                         &#x27;n_estimators&#x27;: [2, 3, 4, 5, 6]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;GridSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15],\n",
       "                         &#x27;n_estimators&#x27;: [2, 3, 4, 5, 6]})</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">best_estimator_: RandomForestRegressor</label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestRegressor(max_depth=5, n_estimators=5)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;RandomForestRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestRegressor(max_depth=5, n_estimators=5)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={'max_depth': [5, 10, 15],\n",
       "                         'n_estimators': [2, 3, 4, 5, 6]})"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridrfr.fit(X_train, y_train.values.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 5, 'n_estimators': 5}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridrfr.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictionofrfr = gridrfr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error on model is {} 17616.48885308515\n",
      "Root maen squared error on model is {} 20274.70258217988\n"
     ]
    }
   ],
   "source": [
    "results(predictionofrfr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-5 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-5 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-5 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-5 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-5 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" checked><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['model.pkl']"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joblib.dump(lr, \"model.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Years_at_Company', 'Satisfaction_Level', 'Average_Monthly_Hours'], dtype='object')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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