1) Regression Models/Decision Tree Regressor/Decision_Tree_Regression.ipynb

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            "--2024-11-21 14:19:16--  https://media.githubusercontent.com/media/pradeep-016/ML_Course/refs/heads/main/1)%20Regression%20Models/Decision%20Tree%20Regressor/SECOND%20HAND%20CARS%20DATASET.csv\n",
            "Resolving media.githubusercontent.com (media.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.111.133, ...\n",
            "Connecting to media.githubusercontent.com (media.githubusercontent.com)|185.199.110.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 53212 (52K) [text/plain]\n",
            "Saving to: ‘SECOND HAND CARS DATASET.csv’\n",
            "\n",
            "SECOND HAND CARS DA 100%[===================>]  51.96K  --.-KB/s    in 0.05s   \n",
            "\n",
            "2024-11-21 14:19:17 (997 KB/s) - ‘SECOND HAND CARS DATASET.csv’ saved [53212/53212]\n",
            "\n"
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      "source": [
        "!wget \"https://media.githubusercontent.com/media/pradeep-016/ML_Course/refs/heads/main/1)%20Regression%20Models/Decision%20Tree%20Regressor/SECOND%20HAND%20CARS%20DATASET.csv\""
      ]
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    {
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.metrics import mean_squared_error, r2_score"
      ],
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        "id": "6_GxpX3Z8iRU"
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      "execution_count": 2,
      "outputs": []
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        "df = pd.read_csv('/content/SECOND HAND CARS DATASET.csv')\n",
        "df.head()"
      ],
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      "execution_count": 3,
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              "   v.id  on road old  on road now  years      km  rating  condition  economy  \\\n",
              "0     1       535651       798186      3   78945       1          2       14   \n",
              "1     2       591911       861056      6  117220       5          9        9   \n",
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              "4     5       691388       811335      6   61559       3          9       12   \n",
              "\n",
              "   top speed  hp  torque  current price  \n",
              "0        177  73     123       351318.0  \n",
              "1        148  74      95       285001.5  \n",
              "2        181  53      97       215386.0  \n",
              "3        197  54     116       244295.5  \n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 1000,\n  \"fields\": [\n    {\n      \"column\": \"v.id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 288,\n        \"min\": 1,\n        \"max\": 1000,\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          522,\n          738,\n          741\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road old\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 58407,\n        \"min\": 500265,\n        \"max\": 699859,\n        \"num_unique_values\": 998,\n        \"samples\": [\n          658059,\n          601674,\n          617090\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road now\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 57028,\n        \"min\": 700018,\n        \"max\": 899797,\n        \"num_unique_values\": 998,\n        \"samples\": [\n          755102,\n          863684,\n          734310\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"years\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 2,\n        \"max\": 7,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          3,\n          6,\n          7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"km\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29150,\n        \"min\": 50324,\n        \"max\": 149902,\n        \"num_unique_values\": 997,\n        \"samples\": [\n          61132,\n          62186,\n          137960\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 5,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          5,\n          3,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"condition\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          6,\n          9,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"economy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 8,\n        \"max\": 15,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          9,\n          13,\n          14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"top speed\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19,\n        \"min\": 135,\n        \"max\": 200,\n        \"num_unique_values\": 66,\n        \"samples\": [\n          155,\n          140,\n          177\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 20,\n        \"min\": 50,\n        \"max\": 120,\n        \"num_unique_values\": 71,\n        \"samples\": [\n          77,\n          73,\n          104\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"torque\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 21,\n        \"min\": 68,\n        \"max\": 140,\n        \"num_unique_values\": 73,\n        \"samples\": [\n          105,\n          98,\n          139\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"current price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 126073.25914983764,\n        \"min\": 28226.5,\n        \"max\": 584267.5,\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          383570.5,\n          506854.0,\n          146223.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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      "execution_count": 4,
      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1000 entries, 0 to 999\n",
            "Data columns (total 12 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   v.id           1000 non-null   int64  \n",
            " 1   on road old    1000 non-null   int64  \n",
            " 2   on road now    1000 non-null   int64  \n",
            " 3   years          1000 non-null   int64  \n",
            " 4   km             1000 non-null   int64  \n",
            " 5   rating         1000 non-null   int64  \n",
            " 6   condition      1000 non-null   int64  \n",
            " 7   economy        1000 non-null   int64  \n",
            " 8   top speed      1000 non-null   int64  \n",
            " 9   hp             1000 non-null   int64  \n",
            " 10  torque         1000 non-null   int64  \n",
            " 11  current price  1000 non-null   float64\n",
            "dtypes: float64(1), int64(11)\n",
            "memory usage: 93.9 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "id": "PH4OEkG3FMdk",
        "outputId": "103364eb-65c2-4a26-cc40-f285906dd954"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              v.id    on road old  on road now        years             km  \\\n",
              "count  1000.000000    1000.000000    1000.0000  1000.000000    1000.000000   \n",
              "mean    500.500000  601648.286000  799131.3970     4.561000  100274.430000   \n",
              "std     288.819436   58407.246204   57028.9502     1.719079   29150.463233   \n",
              "min       1.000000  500265.000000  700018.0000     2.000000   50324.000000   \n",
              "25%     250.750000  548860.500000  750997.7500     3.000000   74367.500000   \n",
              "50%     500.500000  601568.000000  798168.0000     5.000000  100139.500000   \n",
              "75%     750.250000  652267.250000  847563.2500     6.000000  125048.000000   \n",
              "max    1000.000000  699859.000000  899797.0000     7.000000  149902.000000   \n",
              "\n",
              "            rating    condition      economy   top speed          hp  \\\n",
              "count  1000.000000  1000.000000  1000.000000  1000.00000  1000.00000   \n",
              "mean      2.988000     5.592000    11.625000   166.89300    84.54600   \n",
              "std       1.402791     2.824449     2.230549    19.28838    20.51694   \n",
              "min       1.000000     1.000000     8.000000   135.00000    50.00000   \n",
              "25%       2.000000     3.000000    10.000000   150.00000    67.00000   \n",
              "50%       3.000000     6.000000    12.000000   166.00000    84.00000   \n",
              "75%       4.000000     8.000000    13.000000   184.00000   102.00000   \n",
              "max       5.000000    10.000000    15.000000   200.00000   120.00000   \n",
              "\n",
              "            torque  current price  \n",
              "count  1000.000000     1000.00000  \n",
              "mean    103.423000   308520.24250  \n",
              "std      21.058716   126073.25915  \n",
              "min      68.000000    28226.50000  \n",
              "25%      85.000000   206871.75000  \n",
              "50%     104.000000   306717.75000  \n",
              "75%     121.000000   414260.87500  \n",
              "max     140.000000   584267.50000  "
            ],
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              "      <th></th>\n",
              "      <th>v.id</th>\n",
              "      <th>on road old</th>\n",
              "      <th>on road now</th>\n",
              "      <th>years</th>\n",
              "      <th>km</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.0000</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>1000.00000</td>\n",
              "      <td>1000.00000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>500.500000</td>\n",
              "      <td>601648.286000</td>\n",
              "      <td>799131.3970</td>\n",
              "      <td>4.561000</td>\n",
              "      <td>100274.430000</td>\n",
              "      <td>2.988000</td>\n",
              "      <td>5.592000</td>\n",
              "      <td>11.625000</td>\n",
              "      <td>166.89300</td>\n",
              "      <td>84.54600</td>\n",
              "      <td>103.423000</td>\n",
              "      <td>308520.24250</td>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>288.819436</td>\n",
              "      <td>58407.246204</td>\n",
              "      <td>57028.9502</td>\n",
              "      <td>1.719079</td>\n",
              "      <td>29150.463233</td>\n",
              "      <td>1.402791</td>\n",
              "      <td>2.824449</td>\n",
              "      <td>2.230549</td>\n",
              "      <td>19.28838</td>\n",
              "      <td>20.51694</td>\n",
              "      <td>21.058716</td>\n",
              "      <td>126073.25915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>500265.000000</td>\n",
              "      <td>700018.0000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>50324.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>135.00000</td>\n",
              "      <td>50.00000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>28226.50000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>250.750000</td>\n",
              "      <td>548860.500000</td>\n",
              "      <td>750997.7500</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>74367.500000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>150.00000</td>\n",
              "      <td>67.00000</td>\n",
              "      <td>85.000000</td>\n",
              "      <td>206871.75000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>500.500000</td>\n",
              "      <td>601568.000000</td>\n",
              "      <td>798168.0000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>100139.500000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>166.00000</td>\n",
              "      <td>84.00000</td>\n",
              "      <td>104.000000</td>\n",
              "      <td>306717.75000</td>\n",
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              "    <tr>\n",
              "      <th>75%</th>\n",
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              "      <td>652267.250000</td>\n",
              "      <td>847563.2500</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>125048.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>184.00000</td>\n",
              "      <td>102.00000</td>\n",
              "      <td>121.000000</td>\n",
              "      <td>414260.87500</td>\n",
              "    </tr>\n",
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              "      <th>max</th>\n",
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              "      <td>699859.000000</td>\n",
              "      <td>899797.0000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>149902.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>200.00000</td>\n",
              "      <td>120.00000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>584267.50000</td>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"v.id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 360.1000917722167,\n        \"min\": 1.0,\n        \"max\": 1000.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          1000.0,\n          500.5,\n          750.25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road old\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271516.2369850819,\n        \"min\": 1000.0,\n        \"max\": 699859.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          601648.286,\n          601568.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road now\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 361771.7582737073,\n        \"min\": 1000.0,\n        \"max\": 899797.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          799131.397,\n          798168.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"years\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 352.0794497807197,\n        \"min\": 1.7190794729256267,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          4.561,\n          5.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"km\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 49941.87869887283,\n        \"min\": 1000.0,\n        \"max\": 149902.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          100274.43,\n          100139.5,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 352.5764755459382,\n        \"min\": 1.0,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          2.988,\n          3.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"condition\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 351.7262259090189,\n        \"min\": 1.0,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          5.592,\n          6.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"economy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 349.9454704755444,\n        \"min\": 2.2305493382461528,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          11.625,\n          12.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"top speed\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 306.99361180438143,\n        \"min\": 19.28837972958314,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          166.893,\n          166.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 328.31733937768274,\n        \"min\": 20.516940045455808,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          84.546,\n          84.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"torque\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 323.1159705211535,\n        \"min\": 21.058716497938363,\n        \"max\": 1000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          103.423,\n          104.0,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"current price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 197732.83334730723,\n        \"min\": 1000.0,\n        \"max\": 584267.5,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          308520.2425,\n          306717.75,\n          1000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "numeric_columns = [\"v.id\",\"on road old\",\"on road now\",\"years\",\"km\",\"rating\",\"condition\",\"economy\",\"top speed\",\"hp\",\"torque\",\"current price\"]"
      ],
      "metadata": {
        "id": "bhHsNOBL-SNc"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for col in numeric_columns:\n",
        "  plt.figure(figsize=(8,5))\n",
        "  sns.histplot(df[col], kde=True, bins = 30)\n",
        "  plt.title(f\"Distribution of {col}\")\n",
        "  plt.xlabel(col)\n",
        "  plt.ylabel('Frequency')\n",
        "  plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "w7m3YRPy-vkV",
        "outputId": "a3155e5b-1a4a-4d49-c65b-0c9020c98dc4"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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AUyC4AgAAwBQIrgAAADAFm7sLAAAAgGtkZWWpqKjIJW1FRUUpMTHRJW25CsEVAACgA8jKylLv1FTVVFe7pD3/gABty8jwqPBKcAUAAOgAioqKVFNdrXEPPaeYxO5tais/a5fefOYBFRUVEVwBAABwasQkdldCSl93l3FKMDgLAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYgs3dBQAAcDrKyspSUVFRm9uJiopSYmKiCyoCPB/BFQCAdpaVlaXeqamqqa5uc1v+AQHalpFBeMVpgeAKAEA7KyoqUk11tcY99JxiEru3up38rF1685kHVFRURHDFacGtwfXxxx/XE0880Wxbr169tG3bNkmS3W7X/fffr0WLFqm2tlYjR47Uyy+/rJiYGHeUCwCAS8UkdldCSl93lwGYhtsHZ/Xt21e5ubnOx6pVq5z77rvvPn300UdavHixVq5cqZycHI0ZM8aN1QIAAMBd3N5VwGazKTY29ojtZWVlmjt3rt566y1dfPHFkqR58+YpNTVVa9as0dlnn93epQIAAMCN3B5cMzMzFR8fLz8/P6WlpWn69OlKTEzUxo0bVV9fr/T0dOexvXv3VmJiolavXn3M4FpbW6va2lrn8/Ly8lP+GdDxuGq0r8SIXwAAXMWtwXXYsGGaP3++evXqpdzcXD3xxBM677zz9MMPPygvL08+Pj4KCwtr9pqYmBjl5eUds83p06cf0W8WOBmuHO0rMeIXAABXcWtwHTVqlPPvAwYM0LBhw5SUlKR33nlH/v7+rWpz6tSpmjJlivN5eXm5unTp0uZacfpw1WhfiRG/AAC4ktu7CvxSWFiYevbsqZ07d+qSSy5RXV2dSktLm911zc/PP2qf2MN8fX3l6+vbDtWio2O0LwAAnsXtswr8UmVlpXbt2qW4uDgNGTJE3t7eWr58uXP/9u3blZWVpbS0NDdWCQAAAHdw6x3XP//5z7rqqquUlJSknJwcPfbYY/Ly8tJNN92k0NBQTZo0SVOmTFFERIRCQkL0pz/9SWlpacwoAAAAcBpya3Ddv3+/brrpJhUXF6tTp04aPny41qxZo06dOkmSXnjhBVmtVo0dO7bZAgQA2oZZEwAAZuTW4Lpo0aLj7vfz89OsWbM0a9asdqoI6PiYNQEAYFYeNTgLwKnHrAkAALMiuAKnKWZNAACYjUfNKgAAAAAcC8EVAAAApkBXgVOAEdsAAACuR3B1MUZsAwAAnBoEVxdjxDYAAMCpQXA9RRixDQAA4FoMzgIAAIApEFwBAABgCgRXAAAAmALBFQAAAKZAcAUAAIApEFwBAABgCgRXAAAAmALBFQAAAKZAcAUAAIApEFwBAABgCgRXAAAAmALBFQAAAKZAcAUAAIApEFwBAABgCjZ3FwAAOHlZWVkqKipySVtRUVFKTEx0SVsAcCoRXAHAZLKystQ7NVU11dUuac8/IEDbMjIIrwA8HsEVAEymqKhINdXVGvfQc4pJ7N6mtvKzdunNZx5QUVERwRWAxyO4AoBJxSR2V0JKX3eXAQDthsFZAAAAMAWCKwAAAEyB4AoAAABTILgCAADAFAiuAAAAMAWCKwAAAEyB4AoAAABTILgCAADAFAiuAAAAMAWCKwAAAEyB4AoAAABTILgCAADAFAiuAAAAMAWCKwAAAEyB4AoAAABTILgCAADAFAiuAAAAMAWCKwAAAEyB4AoAAABTILgCAADAFAiuAAAAMAWCKwAAAEzBY4LrP/7xD1ksFk2ePNm5zW6366677lJkZKSCgoI0duxY5efnu69IAAAAuI1HBNf169frf//3fzVgwIBm2++77z599NFHWrx4sVauXKmcnByNGTPGTVUCAADAndweXCsrKzVu3Di9+uqrCg8Pd24vKyvT3LlzNWPGDF188cUaMmSI5s2bp2+//VZr1qxxY8UAAABwB7cH17vuuktXXHGF0tPTm23fuHGj6uvrm23v3bu3EhMTtXr16mO2V1tbq/Ly8mYPAAAAmJ/NnW++aNEibdq0SevXrz9iX15ennx8fBQWFtZse0xMjPLy8o7Z5vTp0/XEE0+4ulQAAAC4mdvuuGZnZ+vee+/Vm2++KT8/P5e1O3XqVJWVlTkf2dnZLmsbAAAA7uO24Lpx40YVFBRo8ODBstlsstlsWrlypV566SXZbDbFxMSorq5OpaWlzV6Xn5+v2NjYY7br6+urkJCQZg8AAACYn9u6CowYMULff/99s20TJ05U79699dBDD6lLly7y9vbW8uXLNXbsWEnS9u3blZWVpbS0NHeUDAAAADdyW3ANDg5Wv379mm0LDAxUZGSkc/ukSZM0ZcoURUREKCQkRH/605+Ulpams88+2x0lAwAAwI3cOjjrRF544QVZrVaNHTtWtbW1GjlypF5++WV3l9XuMjIyXNJOVFSUEhMTXdIWAABAe/Oo4Prll182e+7n56dZs2Zp1qxZ7inIzcpLCiVJ48ePd0l7/gEB2paRQXgFAACm5FHBFc3VVDbNQXvF7x9WrwFD2tRWftYuvfnMAyoqKiK4AgAAUyK4mkBkfJISUvq6uwwAAAC3cvvKWQAAAEBLEFwBAABgCgRXAAAAmEKrguvu3btdXQcAAABwXK0Krj169NBFF12khQsXym63u7omAAAA4AitCq6bNm3SgAEDNGXKFMXGxur3v/+91q1b5+raAAAAAKdWBdczzjhDL774onJycvTaa68pNzdXw4cPV79+/TRjxgwVFha6uk4AAACc5to0OMtms2nMmDFavHixnnnmGe3cuVN//vOf1aVLF91yyy3Kzc11VZ0AAAA4zbVpAYINGzbotdde06JFixQYGKg///nPmjRpkvbv368nnnhCV199NV0IALRYVlaWioqKXNJWVFQUq8SZGNcCgKNpVXCdMWOG5s2bp+3bt+vyyy/X66+/rssvv1xWa9MN3OTkZM2fP19du3Z1Za0AOrCsrCz1Tk1VTXW1S9rzDwjQtowMAosJcS0AOJZWBdfZs2frtttu06233qq4uLijHhMdHa25c+e2qTgAp4+ioiLVVFdr3EPPKSaxe5vays/apTefeUBFRUWEFRPiWgBwLK0KrpmZmSc8xsfHRxMmTGhN8wBOYzGJ3ZWQ0tfdZcADcC0A+LVWDc6aN2+eFi9efMT2xYsXa8GCBW0uCgAAAPi1VgXX6dOnKyoq6ojt0dHRevrpp9tcFAAAAPBrreoqkJWVpeTk5CO2JyUlKSsrq81FAYArZGRktLkNRqQDgOdoVXCNjo7W1q1bj5g1YMuWLYqMjHRFXQDQauUlTYugjB8/vs1tMSIdADxHq4LrTTfdpHvuuUfBwcE6//zzJUkrV67UvffeqxtvvNGlBQLAyaqpLJckXfH7h9VrwJBWt8OIdADwLK0Krk8++aT27t2rESNGyGZrasLhcOiWW26hjysAjxEZn8SodADoQFoVXH18fPT222/rySef1JYtW+Tv76/+/fsrKSnJ1fUBAAAAktq45GvPnj3Vs2dPV9UCoAOpqWtUUWWtKuwNqqprUGVtg6oOPWobHDIMyTAMGZIchrR/f5WCBl2hvZVWVedXyGa1yOZllc1qkZ+3l/y8rfK1ecnLanH3RwMAuEmrgmtjY6Pmz5+v5cuXq6CgQA6Ho9n+FStWuKQ4AJ7JMAxV1zWqyG5R0IBL9MbWcr2+Y7Pyy2tVUGFXQXmtKmobTrrdyEvv1MYSSSV5xzzGx8sqP2+r/H28FOhjU5CvTYG+h//0UpCvTQ2tm+kPAODhWhVc7733Xs2fP19XXHGF+vXrJ4uFOyBAR1Xb0KiiijoVVNhVWFGr4qo6lVbXq67RIclbkaPu1fvbqiRVHfFaH5tVIX7eCvL1UuAvAqaft1UWWXTof7JYLDpYUqKlny9Xt4Fp8vYLVL3DoYZGQ/WNDtU2ND0kqa7RobpGh8rtDZJqj1F1L3W5712tr/HSvu8OKMTfW6F+3k1/+nsrxN8mX5vXKTpjAIBTpVXBddGiRXrnnXd0+eWXu7oeAG7U6DBUWFGrnLIa5ZXZVVBRq7Ka+mMeH+BlqDhzk8Zcep4G9UxUdLCfooN9FR3ip+gQXwX72lr8g+2mTZv05t3Tdcsl7ykhJeGI/Q7DUG2DQ/b6RtnrG1VT13io+0HTn4e7IlQe6opg9fFTtSHtLa4+6vv52qyHQuzhUGtTWICPwvy9FeRnk5UfyAHA47R6cFaPHj1cXQuAdlbf6FBOaY0OlNYot9SuvHK7GhzGEccF+9nUKchXnYJ9FRXkq/CApjuXebszNOPpx/S7v2zU4MHdT2mtVotF/t5e8vc+8Z3Sdcs/0ruvzNCoPz2tqOQ+Kq+pV3lNvcrs9SqvaVBNfaNqGxwqqKhVQcWRd229LJamu7IOm8Ivvl1LdlapMqhQXSMDFR/mJ5sXXREAwB1aFVzvv/9+vfjii/rXv/5FNwHARBwOQ7tK6hUy7Df6Kt+mkuzdajSaB1U/m1VxYf6KC/VTTIifOgX7tigsehIvGWo4mKNwrzr17xx6xP66BofK7YfCbE1TmC2tqVPZoeeNhqGD1fWSrAo58xq9uqlcr25aJ0myWS3qEhGgpMgAdY0MVNfIACVFBaprZKASwv3lTagFgFOmVcF11apV+uKLL7RkyRL17dtX3t7ezfa/9957LikOQNvtP1itVZlF+npnkb7dWaSD1fUKv/BWFdZKkqFgP5sSwv0VH+qv+DB/hQd4d/gfSH1sVkUFNd09/jWHYajS3qDSmnrt3btPK5d+pBHX3KjSBm/tK6lWXYNDe4qqtKeoSlJhs9d6WS3qHOb/c6iNOhRsIwPVJcKffrUA0EatCq5hYWG69tprXV0LABdwOAx9t79Un/+Ur88z8rUjv7LZfn+bRcUZq3XOWUM1oHd3hfl3/KB6MqwWi0IO9X21Fjv0wRdzNfV//qjBgwfL4TCUV27X3uIq7S2q1r7iKu0trtK+4mrtLa6Svd6hrJJqZZVU6+vMombtWixSfKi/unUKVPdOQereKVDdOgWpe6cgxYT48m8AAC3QquA6b948V9cBoA1q6hq1ameRPv8pX8u3Faio8ud+m15WiwYmhOq8lE46LyVKjqI9GvbU39V9xHsKD/BxY9XmY7VaFB/WdGf6nF916TUMQwUVtdpb1BRm9xYfCraHAm5VXaMOHOpP/OtQG+jjpeRDgbZbVJAz3HbrFCg/k3XTAIBTqdULEDQ0NOjLL7/Url27dPPNNys4OFg5OTkKCQlRUFCQK2sEcBQFFXatyCjQ5xn5+jqzyDldlCQF+9p0Qa9OuqRPjC7sGa3QgJ+782wq2euGajs+i8WimJCmfsHDukU222cYhooq67SnqEq7Cyu1+9CfuwqrlFVSraq6Rv1woFw/HChv9jqrReoaGahescHqGROs3rHB6hUbrMajDKADgNNBq4Lrvn37dNlllykrK0u1tbW65JJLFBwcrGeeeUa1tbWaM2eOq+sETnuGYWhHfqU+z8jXsp/y9V12abP9ncP8dUmfGKWnxuis5Aj52Bgk5CksFos6BTfNynBWckSzfXUNDmWVVGlXYZV2FVZqd2FTqN1ZUKlye0NTyC2q0pIffl6UwcdLip0wU+uLvZTvc1CRQT6KCvRVoK8XXQ4AdGitXoBg6NCh2rJliyIjf76zcO211+p3v/udy4oDTnf1jQ6t31OiZRlN/VWzS2qa7R+YEKr01Bil94lR79hgQosJ+dis6hEdrB7Rwc22G0bTnLrb8iq0I7/C+eeO/ArZ6x3yje2hrCopa+fP3Q78vb0UHeKr6GBfdQpqmk83xK/lc+miY7DXN6rw0FRvhRVN8zEfrKpXZW29KmsbmpZhPjTn8eHp7345uYjVIgX62hTi561gP5uC/Zr+Hh7oo4Rwf3WJCFDnMH+6scAtWhVcv/76a3377bfy8WneP65r1646cOCASwoDTlel1XVauaNQn2cU6MvtBaqw/7x0qo/NquE9opSeGqMRqdGKCfFzY6U4lSwWy6GFHPx0fs9Ozu2NDkOffr1e1/1usi6c+JDqfcNUVFmr0up61dQ3al9xtfb9YtEFX5vVebc3OthX0cF+CgvwZoEFE3M4DFXUNqispl57K60Ku+BWPfvtQVWs+lrZJdWHVpU79ToF+6pLuL9SooPVLyFU/TuHqndsMIEWp1SrgqvD4VBjY+MR2/fv36/g4OCjvAIdSVZWloqKik58YAtERUUpMTHRJW2Z2a7CSi3PyNfnGQXauO9gsz6MkYE+urh3tNL7xOi8lCgF+LS6azo6AC+rRXHBNtVkrlZqqEMJKXGSmu7OF1c2Lc3bdKetVsWVdaptcGj/wRrtP/jz3Xqb1eIMsrZqq7yjkjp8v9mMjAyXtNOe31l1DQ6VVNWpuKr20J9Nyy1X2Ov18z+XTaFn/0Zr9tsl2Z2v9bVZD91991OnIF9FBPko+NCSy0F+h/70tTVbTOPwjzKNh6aEq7DXq8LeoIrapr8XVtRq/8EaZR/ql1146DrblFWqtzdkS2q6PlOig9TZv0GBfS6U/cioALRJq/4LeOmll2rmzJl65ZVXJDXdGaisrNRjjz3GMrAdXFZWlnqnpqqm+ujLaJ4s/4AAbcvIOO3Ca32jQxv2HtTyjKZZAJrmBP1Zz5ggjUiNUXpqtM7oEi4vK3fHcHzeXlbFhvopNvTnu/CNDkMlVU1h9udfHdeqwWEot8yu3DK7JJviJ83SuPfz1GftN+rXOUT9O4eqb3yoesYEm76vdHlJ01y748ePd0l7p+I7q76xKaAeDqfFlbUqrqpr9tuWX/OyWhTiZ5Ovo1Y7Vn2s+24fr3MG9lRiRMAp7yJiGIZKq+u1/2CN9pVUaVtuhb4/UKYfDpSpuKpO2/IqtE1S1FV/1icHpKiyfUqMCFBiRIDiw1ikA23TquD6/PPPa+TIkerTp4/sdrtuvvlmZWZmKioqSv/+979dXSM8SFFRkWqqqzXuoecUk9i2JT7zs3bpzWceUFFR0WkRXIsra/V1ZpFWbGvqAvDLX+d5e1k0LDlSI1KjlZ4aoy4RAW6sFB2Fl/XnQWGHOQ6FjoIKuwrKa5VdUKKCcrvqfAP0XXZps0F/Pl5W9Y4LVt/4pl8D9+scol6xwaZaSKGmsmmmhit+/7B6DRjSprba+p1lr2/UzoJKZRZU6Out5eo05hF9muOtqqxdx3xNgI+XIgJ9FBnoo8hAX4UHNi23HOTbFEz3Z/6otctf0RXP/l6DU2Pa8vFazGKxKDzQR+GBPuqfEKorBzRtN4ymeY6/31+mJeu3adGXW+Qb211FlXUqqqzTpqxS2awWdYsKVM/YYCVFBLB8Mk5aq4JrQkKCtmzZokWLFmnr1q2qrKzUpEmTNG7cOPn7+7u6RnigmMTuSkjp6+4yPFqjw1Ch3aKw836rB5YVadc7nzfbHx7grYt6RWtEaozO7xmlYD/vY7QEuI7VYlFEoI8iAn3UO1babynQjGk36KMv18gRlqAfDt05++FAmcrtDdq6v0xb95fp8C0Jm9WinjHBTUE2IVT94kOUGhfi8f0aI+OT2u07q8Jer12FVcrMr9DOwkrtKmiaJSKrpFq/7JERkDJMVYd+fvX39lJkoI8ign4OqRFBPqZabtlisSgu1F9xof6Kqs3RzImTdddL76kxPFH7ipsW5qisbdCOgkrtKKiUj5dV3ToFqmdMsBIjAvjNElqk1Z3lbDaby371AnQUZTX12ndoJaX9B2tU1+it0HNu0K6D9ZKk3rHBuqBXJ6WnxmhwIl0A4CkMxQfbNHhgvEYPjG/aYhjKKqnWDwfK9f2BMv2YU6bvD5SptLpeP+WW66fccme/RqtFSooMVI/oIPWMCVJKdLB6RAepR3SQxwfa1jIMQ8VVddpVUKnMQ8F0V2GlMvMrlVduP+brwgK81TM6WOFedv17zgxdPW6Sevfq2WH7rvt6SQkxTfMQH16ko2l2jEpV1jY0dSvIq1CAj5f6xoeoX+dQhfBDPI6jVf9Pef3114+7/5ZbbmlVMYCZGIahcnuD9h+s1oGDNdpfWnNEnzQfq6GDP6zUX269Wr9NH6roDjoLgCsGvrhq8Axcw2KxKCkyUEmRgbpiQNMAMMMwdKC05tAd2fJm/Rr3FFVpT1GVlv2U/4s2pMSIAKVEByk5KlCJEQHqcqivY+dwf4/vctDQ6FCFvWn0fllNvQ4c9FKnax/WfUsLVfTBUlXVHXvkUadgX/XoFOQM8CmH/uwU3LS876ZNm/TKpo8VPem2Dhtaf+2Xi3QM7xGl3DK7duRXKLOgUtV1jVq/96A27D2orlGB6t85VEmRAR49+wUDld2j1fO4/lJ9fb2qq6vl4+OjgIAAgis6pF8G1f0Hm5bu/HVQtVqk2FA/JUUEKikyQHV5u/TC9P/RRY/f1CFDq6sHvkhSZWWly9qCa1ksFiWEByghPECX9fs5zBZW1CqzoFKZh0JIZn6ldhRUqLS6/ojpuX5uS4oNaRpMFnsozESH+Com2E9l+bXyiU1RZX1Tv1Afm9VlAaah0SF7vUM19Y2qbWhUTX2j7HUOVdX9PLdpVV2jqmobVH1EMPVSQM807Sv7+f/3CeH+zlDqfHQKbrZaHY5ksfy8fPJ5KZ20u7BS3x8oU/bBGucPQcF+Ng3qEqZwx4nba28MVHafVgXXgwcPHrEtMzNTd955px544IE2FwV4ggaHdOBgjXLLa5RXZldeuV1Vtc3/Q2a1SDEhfuoc5q+E8Ka+Xb8chb0//9etdiyuHPiSsW6llix4UXb7sX/NCs/zy/lmz+0R5dx++FfpmflNg5EO93HMLmkKsjX1jb+Y2eBIcRNe0NJcSbm7JTVN7+TtZZWX1SKb1eL80/rL7jaGdLgLqcMwVN/oUKW6qfMf5+ub6gitWrFTjcbJTfvl7WVRqH/TgCirvVxr/u8VvfDkX3XRWQOYhN9FvKwWpcQEKyUmWAer6vT9gTL9lFuuCnuDvsosko/VW6Hn3qSKWs9JsAxUdh+X/X4iJSVF//jHPzR+/Hht27bNVc0C7aLRYWhPUZW+yy7Vsk1lirv1RX2431vG/v3NjjscVBPC/dX50N0CpnZxzcCX/OOMrIb5WCwWRQX5KirIV2ndI5vtMwxDRZV1yj5YrYJyu/LLa5V/6M+CCruyCkq1KztHfqGd1GA0BdPaBodqG1oTXHxlC/ZVQ9MbH6pN8rN5yc/bKj9vL/l5eynQ10tBPjYF+jY9Ds9z6udtdU4rtT/zoD7f/IkGx01T905BbTg7OJbwQB+d37OTzukeqYzcCm3MOqiymnqFDR+nOz4u0M1FP+r287qpc5hnDARnoHL7c2nHGpvNppycHFc2Cbhcub1e23IrtC2vXBm55fopt0I78ipUU//z3VSfmO4yJAX6ejl/nRkX4q/oEF+CKtBGFsuR03T90qZNmzRkyGWaMus9xXXvo9qGRtnrHWpodKjBYajRYajBYajB4XAunGCRRYd7E1gOvYe3l0W7vvtWn81/QaP/8LD6DT5Lvt5W+XhZWQbXw9m8rOqfEKq+nUO0bss2ffXjXim2h+Z9s1cL1+zTTWcl6u6LenTILlg4vlYF1w8//LDZc8MwlJubq3/9618699xzXVIY0FZl1fXaXVSp3YVN/aW251coI7e82QpCv+TnbVX/zqGK963T/3vmb7rlj/erZyo/SQPu5GW1KMDHpgCfEx97NEWqUV3+LgVYGxTiT79Ts7FaLEoIdChvwWTN/eRbfbZfWrO7RK+v3qd3NmRrwjld9Yfzuys8sJUXCEynVcH1mmuuafbcYrGoU6dOuvjii/X888+7oi7ghAzDUHlNg/aXViu75HCH/p+DanFV3TFfGxfqp9S4EKXGBR/6M0RdIwPlZW0a7fvS9m8UYLu/HT8NPJkZlws9Wa74jJ78+WB+Z8T66rbLB+vbnUV67rPt2pxVqv9duVtvrcnSpPOSNWl4MvNhnwZaFVwdDs/pII2O63A/uP0Hq3WgtEYHDo3k33/w579X1h57SURJignxVXJUoLp1ClL3TkFNQTU2hJ/O0SJmWC60rVz5GT3x86HjOadHlN7rHqkV2wr0P5/tUEZuuWZ+nqmFa/ZpyiW9dP3QBFbk6sBOj8nj4JEMQ7L6hyizpE4HtuQoq6T656mmDgXTlgzGiAryUecwf3WNClS3qCAldwpUt6hAdY0KVJAvlzhaz5OWCz1VXPUZPfXzoWOyWCwakRqji3pF678/5GrGZzu0u6hKf33/ey34dq8eviJV5/fs5O4ycQq06r/qU6ZMafGxM2bMOOa+2bNna/bs2dq7d68kqW/fvnr00Uc1atQoSZLdbtf999+vRYsWqba2ViNHjtTLL7+smJj2WY8ZrlFb36iiqjoVV9Y6J/Iuq6lXaZW3utzzlh76vFhS8VFfa7FIMcGHRvEfGsmfEB7g/HvnMH/5+zAdDU6t9lwu1F1Oh8+IjsdqtejKAfEa2TdWC9fs08zPM7U9v0K3vLZOF/bqpIcvT1VKTLC7y4QLtSq4bt68WZs3b1Z9fb169eolSdqxY4e8vLw0ePBg53EnGrWZkJCgf/zjH0pJSZFhGFqwYIGuvvpqbd68WX379tV9992nTz75RIsXL1ZoaKjuvvtujRkzRt98801rykY7qLDXK7fMrvxyu4qr6lRcWXecX+c3XR8R/lZ1iw5VYkSAEiIClBDur4RDATU21K/ZvKgAAPyat5dVE89N1rWDOuufK3Zqwbd79eX2Qn2dWaRb0pJ03yU9WUq2g2hVcL3qqqsUHBysBQsWKDw8XFLTogQTJ07Ueeedp/vvb9mglquuuqrZ86eeekqzZ8/WmjVrlJCQoLlz5+qtt97SxRdfLEmaN2+eUlNTtWbNGp199tmtKR0udHiC8ZzSGuWU2pVTduRKUocF+9kUGeij8AAfhfp7K8TfWzUFezX3zzfqvbWrm/3AAwBAa4QF+OiRK/to/NlJmv7fDH32U77mfbNXH23J1dRRvTVmcGemQjO5VgXX559/Xp999pkztEpSeHi4/v73v+vSSy9tcXD9pcbGRi1evFhVVVVKS0vTxo0bVV9fr/T0dOcxvXv3VmJiolavXn3M4FpbW6va2lrn8/Ly8pOuBcdW12jIv8dZ2ljspU/z9xyxkpRFTWt0x4b4KSrYV5GBPooM8jnqmuT7D0pGw7FH/gMdkStG77tqlgOgo0qOCtQrtwzV15mFeuzDH7W7sEr3L96iReuz9MTofuoTH+LuEtFKrQqu5eXlKiwsPGJ7YWGhKioqTqqt77//XmlpabLb7QoKCtL777+vPn366LvvvpOPj4/CwsKaHR8TE6O8vLxjtjd9+nQ98cQTJ1UDjq/RYWjVziJ9+F2Olnyfr+ixj2pvlSQ1yma1KC7Uz7nmdGwIv9oHjsbVMxRIUmVlpcvaAjqi81I66dN7z9fcVXv00vJMrd97UFf+82vdktZVfx7ZiwG8JtSqf7Frr71WEydO1PPPP6+zzjpLkrR27Vo98MADGjNmzEm11atXL3333XcqKyvTu+++qwkTJmjlypWtKUuSNHXq1GaDx8rLy9WlS5dWt3c6Kyi3650N2fr3umwdKP150v6GiiL1igtXvx5dlBDmz7QjQAu4coaCjHUrtWTBi7Lb7a4oDejQfGxW3Xlhd119Rrye+iRDn3yfq/nf7tVnP+bpyWv6aUQqA77NpFXBdc6cOfrzn/+sm2++WfX19U0N2WyaNGmSnnvuuZNqy8fHRz169JAkDRkyROvXr9eLL76oG264QXV1dSotLW121zU/P1+xsbHHbM/X11e+vkdfRhAts7OgUq9+tVvvbz6gusam6ahC/Gy6+ozO6u1fqfGXXaUbZv2fEiID3VwpYD6uGL2fn7XLRdUAp4/4MH/NGjdYN2YW6uH3f1BWSbUmLdigKwfE6bGr+h5zCWJ4llYF14CAAL388st67rnntGtX0xdo9+7dFRjY9iDjcDhUW1urIUOGyNvbW8uXL9fYsWMlSdu3b1dWVpbS0tLa/D440u7CSj2/bIf++32ujKblvzU4MUzjz07S5f3j5OftpU2bNkky3FonAACtdV5KJy2dfL5mfr5Dr369Wx9vzdXXmUV6+IpUXTckgcFbHq5NnTtyc3OVm5ur888/X/7+/jIM46T+wadOnapRo0YpMTFRFRUVeuutt/Tll19q6dKlCg0N1aRJkzRlyhRFREQoJCREf/rTn5SWlsaMAi5WUGHXC8sy9c6GbDU6mkJpemqM7rywm4YkRbi5OgAAXMvfx0tTL0/VVQPj9dD/bdWPOeV68N2t+s93B/T0tf2VxG8UPVargmtxcbGuv/56ffHFF7JYLMrMzFS3bt00adIkhYeH6/nnn29ROwUFBbrllluUm5ur0NBQDRgwQEuXLtUll1wiSXrhhRdktVo1duzYZgsQwDUaGh1auGafnv9shyoOzbU6one0/jyyl1LjGHEJAOjY+nUO1X/uOldzV+3RjGU79M3OYo2c+ZUmp/fU7cOTGcPhgVoVXO+77z55e3srKytLqampzu033HCDpkyZ0uLgOnfu3OPu9/Pz06xZszRr1qzWlInj+OFAmfOnTEkakBCqR67sozO7cocVAHD6sHlZ9fsLuuuyfrH66/vf65udxfrHkm1a8n2unr9+oHpEs/KWJ2lVcP3ss8+0dOlSJSQkNNuekpKiffv2uaQwnBqNDkOzvtipmZ/vUH2joRA/mx68rLduOitRXlb69QAATk9JkYFaOGmY3t24X09+/JO27C/T5S+t0gOX9tJtw5P5b6SHaFVwraqqUkBAwBHbS0pKGNHvwbxCOulvXxRre3HTPLgj+8boqWv7KyqIfzMAACwWi64b2kXnpXTSX97bqi+3F+qp/2bos5/y9D/XDaTvqwdoVeeN8847T6+//rrzucVikcPh0LPPPquLLrrIZcXBdfJqLIq79UVtL65XsK9Nz183UHPGDyG0AgDwK7Ghfpp365l6Zmx/Bfp4af3eg7ps5td6Y/VeGQYz67hTq+64PvvssxoxYoQ2bNiguro6Pfjgg/rxxx9VUlKib775xtU1og0Mw9C6vSVaU2iTl3+Iuod7a/7vhqtLxJF3zAEAQBOLxaIbzkzUOd2j9OC7W7V6d7Ee+c+PWrGtQL/tRbcBd2nVHdd+/fppx44dGj58uK6++mpVVVVpzJgx2rx5s7p37+7qGtFKDQ6Hlv6YrzW7SyRZVPHdEj11cSShFQCAFuoSEaA3bx+mx67qIx+bVV9sL9R9S4vk161tK+ChdU76jmt9fb0uu+wyzZkzRw8//PCpqAkuYK9v1Mdbc3WgtEZWi3RGeIPeXzpLPk/f5u7SAAAwFavVoonnJuuc7lG659+btT2/QjHXPaHvShoV2+hg2qx2dNJn2tvbW1u3bj0VtcBFKmsbtHjDfh0orZGPl1WjB8YrOcjh7rIAADC1XrHB+s/d5+qKlKbfXO6q9NKiDdkqqqx1c2Wnj1b9iDB+/PgTzsEK9yivqde7G/erpLpOQb42XTc0gVGQAAC4iJ+3lyYNClX+4sflazVUXFmnt9dn66fccneXdlpo1eCshoYGvfbaa/r88881ZMgQBQY2D0YzZsxwSXE4OaXVdfq/TQdUWdugUH9vjRnUWSH+3u4uCwCADse+e4PS4+r1fU2YskqqteynfOWU1ujCnp3oOnAKnVRw3b17t7p27aoffvhBgwcPliTt2LGj2TEWCyPt3KG8pt4ZWsMDvDVmUIKC/Fr1cwkAAGgBPy/pmjPim2bv2V2iH3PKlV9u1+X94xQe4OPu8jqkk0o2KSkpys3N1RdffCGpaYnXl156STExMaekOLRMZW2D3tvcFFojAnw0ZnBnBfoSWgEAONUsFouGJUcqLtRfn/6Qp6LKOi1al630PtFKYblYlzupe9m/nnR3yZIlqqqqcmlBODk1dY16f/MBldXUK9TfW9cSWgEAaHeJEQG6+axExYf6qa7Rof9+n6evMwvlYMECl2pTJwxWj3CvhkaHPtySo5KqpoFY1w7qrCBCKwAAbhHkZ9OYwQkakhguSdqUVaoPt+SotqHRzZV1HCcVXC0WyxF9WOnT6h6GYWjpj/nKK7fL12bVtYM6K5SBWAAAuJWX1aLhKVEa1S9WNqtF+4qr9fb6bB2srnN3aR3CSd2eMwxDt956q3x9m9a3t9vt+sMf/nDErALvvfee6yrEUa3aWaSdhZXyslh01YB4RQTSCRwAAE/RMyZYof7e+nhrrg5W1+vt9dka1S+WKSrb6KSC64QJE5o9Hz9+vEuLQct8f6BMm7JKJUnpfaLVOdzfvQUBAIAjxIT46cYzu+jjrbnKK7frP1tydH5KJw1MCOU31q10UsF13rx5p6oOtFBOaY2+3F4gSUrrFqnesSEn9fqMjIw2vX9bXw8AwOkk0NemsUM6a8W2AmXkVmjljkKVVdfr/J5RhNdWYCSPiVTaG/TJ97lyGFJKdJDO7Bre4teWlxRKct1d8srKSpe0AwBAR2ezWnVJaowiA321ameRvttfqqq6Bl3ah+lETxbB1SQaHA598n2uqusaFRnko/TUmJP6Sa2msmkpuit+/7B6DRjS6joy1q3UkgUvym63t7oNAABONxaLRUOSwhXka9NnP+Ups6BSNXWNGhzk7srMheBqEqsyi5wzCFzZP04+ttbNZBYZn6SElL6triM/a1erXwsAwOmuV2yw/H289MnWXO0vrVF5lU1eQZHuLss0WEzXBAob/LRlf5kkaWTfWIWxjBwAAKaVGBGg3wxJUICPl8rrrYod/5z2l9e7uyxTILh6OFtojLbXhUmShiSGKzmKaTQAADC7TsG+umFoFwXZDNlCo/XwimL9mFPm7rI8Hl0FPJhDUtToB9Uoq2JD/JTWvWP+KsFVMxVERUUpMTHRJW0BAHCqhfh768KYev3f+r1SfE/d/OpavXn7MPXrHOru0jwWwdWDZauTfOOjZJNDo/rFysvasabNcPVMB/4BAdqWkUF4BQCYhq+XlP/235T+9/e1o7heN7+6Rm9MGqaBXcLcXZpHIrh6qJzSGmWr6Q5rik+pQjrgcq6umulAaho09uYzD6ioqIjgCgAwFaOuWo+eH6GZm+q0Yd9Bjf9/a7Vg0lkanNjyaS9PFwRXD1TX4NBnP+VLsqjyhxWKPqu3u0s6pdo60wEAAGYX4G3VgtvO0sT567VuT4lumbtOC247U0OSItxdmkdhcJYH+iqzUGU19fJVvUqWzXF3OQAAoB0E+to0f+KZSusWqcraBt0yd5027C1xd1keheDqYfYVV+nHnKZfofdUjoy6ajdXBAAA2kuAj02v3XqmhveIUlVdoybOX6+fDuUC0FXAo9Q2NOrzjAJJ0hldwhSU7ZrR9ugYsrKyVFRU1OZ2XDWLA4COh+8Zz+Dv46X/N2Gobpm7Tuv2luiW19bp3T+kqStTYhJcPck3O4tVWdugUH9vndM9Uluz3V0RPEVWVpZ6p6aqptp1d+ArKytd1hYA8+N7xrP4eXvp1QlDdeMra5SRW67xc9fq/+48RzEhfu4uza0Irh4iu6Ra3x9omnh4RO9oeXvRiwM/KyoqUk11tcY99JxiEru3qa2MdSu1ZMGLstvtLqoOQEfA94znCfX31uu3naXr5nyrvcXVumXuOr3z+zSFBnS8mYZaiuDqARoaHVq+ramLQP/OoeoSEeDmiuCpYhK7t3kGhvysXS6qBkBHxPeMZ+kU7Ks3Jg3T2Nnfant+hW5bsF5vTDpLAT6nZ4Tjtp4HWLe3RGU19QrytencHh1zdSwAANA6XSIC9MakYQr199bGfQd158JNqm90uLsstyC4ullxZa027jsoSbqgZyf52rzcXBEAAPA0vWKD9dqtZ8rf20srdxTq0f/8KMMw3F1Wuzs97zN7CMMwtGJbgRyG1C0qUN07MVqwrVwxkvVUjIZta5uM0AUA13DFzAnu+k4ekhSuf908SLe/vkH/XpelHtFBmjQ82S21uAvB1Y1+zClXTpld3l4WXdCrkywWi7tLMq3ykkJJ0vjx413WpitGw7q6LkboAkDruXrmBHd8J49IjdHDl6fq759k6KlPflK3qEBd1Du63etwF4Krm9jrG/XtrmJJ0tndIhXid/qOEHSFmsqmyZmv+P3D6jVgSJvacuVoWFfVxQhdAGg7V82c4O7v5EnDk7WzoFKL1mfrT//erP+78xz1ig12Sy3tjeDqJmt3l6imvlERgT4amBDm7nI6jMj4JI8cDdvWuhihCwCu09aZE9z9nWyxWDTt6n7aW1ylNbtLNGnBen1w17luram9MDjLDYoqa7XlQKmkpgFZXla6CAAAgJbzsVk1e9wQdY0M0P6DNfrDGxtV39jxB2sRXNuZYRj6akehDEPq3ilQiczZCgAAWiE80Ef/b8KZCvazacO+g5qzsczdJZ1ydBVoZ7sKq5R9sEZeVovOS+nk7nIAwKU8dWaPjo7zfvrqER2k2eOGaMK8dfpib42Czhjl7pJOKYJrO2podOirzKZR5kMSwxXqz4AsAB2Dp87s0dFx3iFJw1Oi9ODIXpq+ZJsiRtyhg7VSgruLOkUIru1o476DqrA3KMjXpqFdw91dDgC4jKfO7NHRcd5x2B3nd9PyrXu07oC0pshQSn2j/Lw73qJGBNd2Um6v14ZDK2SdlxIlby+6FwPoeDx1Zo+OjvMOi8WiP50Zpht/2Kzq8Hgt/TFPowfGd7g54klP7WRVZpEaHIY6h/krJTrI3eUAAIAOJtDHqsIPpssqQ3uLq7X+0A2zjoTg2g4OHKxRZkGlLGqa/qqj/fQDAAA8Q33BHp0R0ShJWrOrWNklrlklzFPQVeAUMwxDX+9s6jzft3OIOgX7urkiAADMh5kTWi45yCG7b4h+yi3Xkh/ydPNZiQry6xiRr2N8Cg+WWVCp/PJaeXtZdHZypLvLAQDAVJg5oXUu7NVJBRV2FVXWaelPeRozqHOH+I0vwfUUanQY+nZXsaSm6a8CfTndAACcDGZOaB1vL6su7x+nf6/L0v6DNdqUVaohSeaf0citSWr69Ol67733tG3bNvn7++ucc87RM888o169ejmPsdvtuv/++7Vo0SLV1tZq5MiRevnllxUTE+PGylvm+wNlKqupV4CPlwYlmv9iAQDAXZg54eSFB/jo/J6dtDyjQN/uKlKXcH9Fh/i5u6w2cevgrJUrV+quu+7SmjVrtGzZMtXX1+vSSy9VVVWV85j77rtPH330kRYvXqyVK1cqJydHY8aMcWPVLVPvkNbuabrbena3SPnYGAcHAADaV9+4EHXvFCiHIX36Y57qGx3uLqlN3HrH9dNPP232fP78+YqOjtbGjRt1/vnnq6ysTHPnztVbb72liy++WJI0b948paamas2aNTr77LOPaLO2tla1tbXO5+Xl5af2QxzD9nIv2esdigjwUd+4ELfUAAAATm8Wi0UjUmOUV75PB6vr9XVmkS7uHe3uslrNo24DlpWVSZIiIiIkSRs3blR9fb3S09Odx/Tu3VuJiYlavXr1UduYPn26QkNDnY8uXbqc+sJ/xSs4SpkVTaf23B6RslrN3xkaAACYk7+3ly7tEyupqRvj7kLzDk7zmODqcDg0efJknXvuuerXr58kKS8vTz4+PgoLC2t2bExMjPLy8o7aztSpU1VWVuZ8ZGdnn+rSjxB23jg5DIs6h/krOSqw3d8fAADglxIjAjQ4MUyS9HlGgapqG9xbUCt5zDD3u+66Sz/88INWrVrVpnZ8fX3l6+u+uVL3ltYrsN8ISdLwHlEdYuoJAABgfmndI5VVUq2iyjoty8jX1SZcEtYj7rjefffd+vjjj/XFF18oISHBuT02NlZ1dXUqLS1tdnx+fr5iY2PbucqWeWNrhSwWqxICGhUbau6RewAAoOOwWa26rG+svKwW7Suu1vcHytxd0klza3A1DEN333233n//fa1YsULJycnN9g8ZMkTe3t5avny5c9v27duVlZWltLS09i73hLJLqvVjYa2Mxnr1DW10dzkAAADNRAb56tzuTQsirdpZpPKaejdXdHLcGlzvuusuLVy4UG+99ZaCg4OVl5envLw81dTUSJJCQ0M1adIkTZkyRV988YU2btyoiRMnKi0t7agzCrhbl4gA/WtUtIo+eUFB3u6uBgAA4EhndAlTfJif6hsNfZ6RL8Mw3F1Si7k1uM6ePVtlZWW68MILFRcX53y8/fbbzmNeeOEFXXnllRo7dqzOP/98xcbG6r333nNj1ccXFeCl6oyv3F0GAADAUVksFqWnxshmtSj7YI1+OOCeqUNbw62Ds1qS8P38/DRr1izNmjWrHSoCAADo+MIDfHRO90h9lVmkr3cWKikyQCH+nv/rYo8YnAUAAID2dUaXMMWHHuoysM0cXQYIrgAAAKchi8Wi9D4x8rJalF1Sox9yPL/LAMEVAADgNHW4y4AkfZ1Z6PGzDHjMAgQAAJhBRkaGR7SBjsWd19UZXcK0s6BSuWV2Ld9WoGvOiG9zLacKwRUAgBYoLymUJI0fP95lbVZWmnfNeLiGJ1xXVotFl/SJ0Ztrs5RVUq2MvAqFuKwa1yK4AgDQAjWVTf3/rvj9w+o1YEib2spYt1JLFrwou93uitJgYp5yXYUH+Ojs5Ah9s6tYX+0oVHpMm0o5ZQiuAACchMj4JCWk9G1TG/lZu1xUDToKT7iuBiWGa0d+pQora7XloFeb2jpVGJwFAAAAeVktGpEaLYuk/dVe8u821N0lHYHgCgAAAElSTIifBiWGSZIiRv5RdY2eNbcrwRUAAABOZ3eLVCdfh4o//Zd8vCzuLqcZgisAAACcvL2sOj+mQfY9m9xdyhEIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFtwbXr776SldddZXi4+NlsVj0wQcfNNtvGIYeffRRxcXFyd/fX+np6crMzHRPsQAAAHArtwbXqqoqDRw4ULNmzTrq/meffVYvvfSS5syZo7Vr1yowMFAjR46U3W5v50oBAADgbjZ3vvmoUaM0atSoo+4zDEMzZ87U3/72N1199dWSpNdff10xMTH64IMPdOONN7ZnqQAAAHAzj+3jumfPHuXl5Sk9Pd25LTQ0VMOGDdPq1auP+bra2lqVl5c3ewAAAMD8PDa45uXlSZJiYmKabY+JiXHuO5rp06crNDTU+ejSpcsprRMAAADtw2ODa2tNnTpVZWVlzkd2dra7SwIAAIALeGxwjY2NlSTl5+c3256fn+/cdzS+vr4KCQlp9gAAAID5eWxwTU5OVmxsrJYvX+7cVl5errVr1yotLc2NlQEAAMAd3DqrQGVlpXbu3Ol8vmfPHn333XeKiIhQYmKiJk+erL///e9KSUlRcnKyHnnkEcXHx+uaa65xX9EAAABwC7cG1w0bNuiiiy5yPp8yZYokacKECZo/f74efPBBVVVV6Y477lBpaamGDx+uTz/9VH5+fu4qGQAAAG7i1uB64YUXyjCMY+63WCyaNm2apk2b1o5VAQAAwBN5bB9XAAAA4JcIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUyC4AgAAwBQIrgAAADAFgisAAABMgeAKAAAAUzBFcJ01a5a6du0qPz8/DRs2TOvWrXN3SQAAAGhnHh9c3377bU2ZMkWPPfaYNm3apIEDB2rkyJEqKChwd2kAAABoRx4fXGfMmKHf/e53mjhxovr06aM5c+YoICBAr732mrtLAwAAQDuyubuA46mrq9PGjRs1depU5zar1ar09HStXr36qK+pra1VbW2t83lZWZkkqby8/NQWe0hlZaUkaX/mj6qtqW5TW/lZuyRJeXt3aFdggEe05Yk1nQ5teWJNp0NbnliTp7bliTWdDm15Yk2nQ1ueWJOr2yrcv0dSU65pjwx1+D0Mwzj+gYYHO3DggCHJ+Pbbb5ttf+CBB4yzzjrrqK957LHHDEk8ePDgwYMHDx48TPbIzs4+bjb06DuurTF16lRNmTLF+dzhcKikpESRkZGyWCyn/P3Ly8vVpUsXZWdnKyQk5JS/X0fEOWwbzl/bcQ7bhvPXdpzDtuH8tV17n0PDMFRRUaH4+PjjHufRwTUqKkpeXl7Kz89vtj0/P1+xsbFHfY2vr698fX2bbQsLCztVJR5TSEgI/2dpI85h23D+2o5z2Dacv7bjHLYN56/t2vMchoaGnvAYjx6c5ePjoyFDhmj58uXObQ6HQ8uXL1daWpobKwMAAEB78+g7rpI0ZcoUTZgwQUOHDtVZZ52lmTNnqqqqShMnTnR3aQAAAGhHHh9cb7jhBhUWFurRRx9VXl6ezjjjDH366aeKiYlxd2lH5evrq8cee+yI7gpoOc5h23D+2o5z2Dacv7bjHLYN56/tPPUcWgzjRPMOAAAAAO7n0X1cAQAAgMMIrgAAADAFgisAAABMgeAKAAAAUyC4tsLjjz8ui8XS7NG7d2/nfrvdrrvuukuRkZEKCgrS2LFjj1hEAdKBAwc0fvx4RUZGyt/fX/3799eGDRuc+w3D0KOPPqq4uDj5+/srPT1dmZmZbqzYc3Tt2vWIa9Biseiuu+6SxDXYEo2NjXrkkUeUnJwsf39/de/eXU8++WSzdbK5Bo+voqJCkydPVlJSkvz9/XXOOedo/fr1zv2cv+a++uorXXXVVYqPj5fFYtEHH3zQbH9LzldJSYnGjRunkJAQhYWFadKkSaqsrGzHT+FeJzqH7733ni699FLnapnffffdEW2czt+Pxzt/9fX1euihh9S/f38FBgYqPj5et9xyi3Jycpq14e5rkODaSn379lVubq7zsWrVKue+++67Tx999JEWL16slStXKicnR2PGjHFjtZ7n4MGDOvfcc+Xt7a0lS5bop59+0vPPP6/w8HDnMc8++6xeeuklzZkzR2vXrlVgYKBGjhwpu93uxso9w/r165tdf8uWLZMkXXfddZK4BlvimWee0ezZs/Wvf/1LGRkZeuaZZ/Tss8/qn//8p/MYrsHju/3227Vs2TK98cYb+v7773XppZcqPT1dBw4ckMT5+7WqqioNHDhQs2bNOur+lpyvcePG6ccff9SyZcv08ccf66uvvtIdd9zRXh/B7U50DquqqjR8+HA988wzx2zjdP5+PN75q66u1qZNm/TII49o06ZNeu+997R9+3aNHj262XFuvwYNnLTHHnvMGDhw4FH3lZaWGt7e3sbixYud2zIyMgxJxurVq9upQs/30EMPGcOHDz/mfofDYcTGxhrPPfecc1tpaanh6+tr/Pvf/26PEk3l3nvvNbp37244HA6uwRa64oorjNtuu63ZtjFjxhjjxo0zDINr8ESqq6sNLy8v4+OPP262ffDgwcbDDz/M+TsBScb777/vfN6S8/XTTz8Zkoz169c7j1myZIlhsViMAwcOtFvtnuLX5/CX9uzZY0gyNm/e3Gw7348/O975O2zdunWGJGPfvn2GYXjGNcgd11bKzMxUfHy8unXrpnHjxikrK0uStHHjRtXX1ys9Pd15bO/evZWYmKjVq1e7q1yP8+GHH2ro0KG67rrrFB0drUGDBunVV1917t+zZ4/y8vKancfQ0FANGzaM8/grdXV1WrhwoW677TZZLBauwRY655xztHz5cu3YsUOStGXLFq1atUqjRo2SxDV4Ig0NDWpsbJSfn1+z7f7+/lq1ahXn7yS15HytXr1aYWFhGjp0qPOY9PR0Wa1WrV27tt1rNiO+H09OWVmZLBaLwsLCJHnGNUhwbYVhw4Zp/vz5+vTTTzV79mzt2bNH5513nioqKpSXlycfHx/nP/JhMTExysvLc0/BHmj37t2aPXu2UlJStHTpUt1555265557tGDBAklynqtfr5DGeTzSBx98oNLSUt16662SxDXYQn/5y1904403qnfv3vL29tagQYM0efJkjRs3ThLX4IkEBwcrLS1NTz75pHJyctTY2KiFCxdq9erVys3N5fydpJacr7y8PEVHRzfbb7PZFBERwTltIb4fW85ut+uhhx7STTfdpJCQEEmecQ16/JKvnujwHRlJGjBggIYNG6akpCS988478vf3d2Nl5uFwODR06FA9/fTTkqRBgwbphx9+0Jw5czRhwgQ3V2cuc+fO1ahRoxQfH+/uUkzlnXfe0Ztvvqm33npLffv21XfffafJkycrPj6ea7CF3njjDd12223q3LmzvLy8NHjwYN10003auHGju0sD0Ab19fW6/vrrZRiGZs+e7e5ymuGOqwuEhYWpZ8+e2rlzp2JjY1VXV6fS0tJmx+Tn5ys2NtY9BXqguLg49enTp9m21NRUZ5eLw+fq1yM9OY/N7du3T59//rluv/125zauwZZ54IEHnHdd+/fvr9/+9re67777NH36dElcgy3RvXt3rVy5UpWVlcrOzta6detUX1+vbt26cf5OUkvOV2xsrAoKCprtb2hoUElJCee0hfh+PLHDoXXfvn1atmyZ826r5BnXIMHVBSorK7Vr1y7FxcVpyJAh8vb21vLly537t2/frqysLKWlpbmxSs9y7rnnavv27c227dixQ0lJSZKk5ORkxcbGNjuP5eXlWrt2LefxF+bNm6fo6GhdccUVzm1cgy1TXV0tq7X5V6CXl5ccDockrsGTERgYqLi4OB08eFBLly7V1Vdfzfk7SS05X2lpaSotLW12R3vFihVyOBwaNmxYu9dsRnw/Ht/h0JqZmanPP/9ckZGRzfZ7xDXYLkPAOpj777/f+PLLL409e/YY33zzjZGenm5ERUUZBQUFhmEYxh/+8AcjMTHRWLFihbFhwwYjLS3NSEtLc3PVnmXdunWGzWYznnrqKSMzM9N48803jYCAAGPhwoXOY/7xj38YYWFhxn/+8x9j69atxtVXX20kJycbNTU1bqzcczQ2NhqJiYnGQw89dMQ+rsETmzBhgtG5c2fj448/Nvbs2WO89957RlRUlPHggw86j+EaPL5PP/3UWLJkibF7927js88+MwYOHGgMGzbMqKurMwyD8/drFRUVxubNm43NmzcbkowZM2YYmzdvdo7Ybsn5uuyyy4xBgwYZa9euNVatWmWkpKQYN910k7s+Urs70TksLi42Nm/ebHzyySeGJGPRokXG5s2bjdzcXGcbp/P34/HOX11dnTF69GgjISHB+O6774zc3Fzno7a21tmGu69Bgmsr3HDDDUZcXJzh4+NjdO7c2bjhhhuMnTt3OvfX1NQYf/zjH43w8HAjICDAuPbaa5v9nwZNPvroI6Nfv36Gr6+v0bt3b+OVV15ptt/hcBiPPPKIERMTY/j6+hojRowwtm/f7qZqPc/SpUsNSUc9J1yDJ1ZeXm7ce++9RmJiouHn52d069bNePjhh5t9QXMNHt/bb79tdOvWzfDx8TFiY2ONu+66yygtLXXu5/w198UXXxiSjnhMmDDBMIyWna/i4mLjpptuMoKCgoyQkBBj4sSJRkVFhRs+jXuc6BzOmzfvqPsfe+wxZxun8/fj8c7f4SnEjvb44osvnG24+xq0GMYvlokBAAAAPBR9XAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAEAAGAKBFcAAACYAsEVAAAApkBwBQAAgCkQXAHAA1144YWaPHmyu8sAAI9CcAUAAIApEFwBAABgCgRXAPBQDodDDz74oCIiIhQbG6vHH3/cuc9isWj27NkaNWqU/P391a1bN7377rvuKxYA2gHBFQA81IIFCxQYGKi1a9fq2Wef1bRp07Rs2TLn/kceeURjx47Vli1bNG7cON14443KyMhwY8UAcGpZDMMw3F0EAKC5Cy+8UI2Njfr666+d28466yxdfPHF+sc//iGLxaI//OEPmj17tnP/2WefrcGDB+vll192R8kAcMpxxxUAPNSAAQOaPY+Li1NBQYHzeVpaWrP9aWlp3HEF0KERXAHAQ3l7ezd7brFY5HA43FQNALgfwRUATGrNmjVHPE9NTXVTNQBw6tncXQAAoHUWL16soUOHavjw4XrzzTe1bt06zZ07191lAcApQ3AFAJN64okntGjRIv3xj39UXFyc/v3vf6tPnz7uLgsAThlmFQAAE7JYLHr//fd1zTXXuLsUAGg39HEFAACAKRBcAQAAYAr0cQUAE6KXF4DTEXdcAQAAYAoEVwAAAJgCwRUAAACmQHAFAACAKRBcAQAAYAoEVwAAAJgCwRUAAACmQHAFAACAKfx/vL6A3sJF6mgAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def outlier_detection(df, column):\n",
        "  Q1 = df[column].quantile(0.25)\n",
        "  Q3 = df[column].quantile(0.75)\n",
        "  IQR = Q3 - Q1\n",
        "  lb = Q1 - 1.5 * IQR\n",
        "  ub = Q3 + 1.5 * IQR\n",
        "  return df[(df[column] >= lb) & (df[column] <= ub)]"
      ],
      "metadata": {
        "id": "unc_du59_QX9"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_df = df.copy()\n",
        "for col in numeric_columns:\n",
        "  new_df = outlier_detection(new_df, col)"
      ],
      "metadata": {
        "id": "G_s3m1ovAOT-"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "6cKVzAHyAqv-",
        "outputId": "e0706a6d-3d4d-46d0-e34e-f10a21a7bac0"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   v.id  on road old  on road now  years      km  rating  condition  economy  \\\n",
              "0     1       535651       798186      3   78945       1          2       14   \n",
              "1     2       591911       861056      6  117220       5          9        9   \n",
              "2     3       686990       770762      2  132538       2          8       15   \n",
              "3     4       573999       722381      4  101065       4          3       11   \n",
              "4     5       691388       811335      6   61559       3          9       12   \n",
              "\n",
              "   top speed  hp  torque  current price  \n",
              "0        177  73     123       351318.0  \n",
              "1        148  74      95       285001.5  \n",
              "2        181  53      97       215386.0  \n",
              "3        197  54     116       244295.5  \n",
              "4        160  53     105       531114.5  "
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    })();\n",
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              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "new_df",
              "summary": "{\n  \"name\": \"new_df\",\n  \"rows\": 1000,\n  \"fields\": [\n    {\n      \"column\": \"v.id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 288,\n        \"min\": 1,\n        \"max\": 1000,\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          522,\n          738,\n          741\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road old\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 58407,\n        \"min\": 500265,\n        \"max\": 699859,\n        \"num_unique_values\": 998,\n        \"samples\": [\n          658059,\n          601674,\n          617090\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"on road now\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 57028,\n        \"min\": 700018,\n        \"max\": 899797,\n        \"num_unique_values\": 998,\n        \"samples\": [\n          755102,\n          863684,\n          734310\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"years\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 2,\n        \"max\": 7,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          3,\n          6,\n          7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"km\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29150,\n        \"min\": 50324,\n        \"max\": 149902,\n        \"num_unique_values\": 997,\n        \"samples\": [\n          61132,\n          62186,\n          137960\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 5,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          5,\n          3,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"condition\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          6,\n          9,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"economy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 8,\n        \"max\": 15,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          9,\n          13,\n          14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"top speed\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19,\n        \"min\": 135,\n        \"max\": 200,\n        \"num_unique_values\": 66,\n        \"samples\": [\n          155,\n          140,\n          177\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 20,\n        \"min\": 50,\n        \"max\": 120,\n        \"num_unique_values\": 71,\n        \"samples\": [\n          77,\n          73,\n          104\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"torque\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 21,\n        \"min\": 68,\n        \"max\": 140,\n        \"num_unique_values\": 73,\n        \"samples\": [\n          105,\n          98,\n          139\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"current price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 126073.25914983764,\n        \"min\": 28226.5,\n        \"max\": 584267.5,\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          383570.5,\n          506854.0,\n          146223.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = new_df.drop(columns = ['current price','v.id'])\n",
        "y = new_df['current price']"
      ],
      "metadata": {
        "id": "oSbOFODIAv-Z"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 42)"
      ],
      "metadata": {
        "id": "3kbkab91BT_W"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pipeline = Pipeline(steps = [\n",
        "    ('scaler', StandardScaler()),\n",
        "    ('model',DecisionTreeRegressor(random_state = 42))\n",
        "])"
      ],
      "metadata": {
        "id": "Ft7QMTlsBf48"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pipeline.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "huXBIDOMB70o",
        "outputId": "8d0ef82c-498e-4048-af8a-bc26c2e4917c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(steps=[('scaler', StandardScaler()),\n",
              "                ('model', DecisionTreeRegressor(random_state=42))])"
            ],
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              "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
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              "    --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>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()),\n",
              "                (&#x27;model&#x27;, DecisionTreeRegressor(random_state=42))])</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-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;scaler&#x27;, StandardScaler()),\n",
              "                (&#x27;model&#x27;, DecisionTreeRegressor(random_state=42))])</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-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;DecisionTreeRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeRegressor.html\">?<span>Documentation for DecisionTreeRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeRegressor(random_state=42)</pre></div> </div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = pipeline.predict(X_test)"
      ],
      "metadata": {
        "id": "xo5tYa-rC9_x"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mse = mean_squared_error(y_test, y_pred)\n",
        "r2 = r2_score(y_test, y_pred)\n",
        "\n",
        "print(\"Mean Squared Error:\",mse)\n",
        "print(\"R2 Score:\",r2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e_7BFOqsD0fB",
        "outputId": "445f6b61-65d0-4f67-f81c-b96e4d9696c7"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean Squared Error: 947947254.60625\n",
            "R2 Score: 0.9436113983294042\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(8,5))\n",
        "plt.scatter(y_test, y_pred)\n",
        "plt.xlabel(\"Actual Prices\")\n",
        "plt.ylabel(\"Predicted Prices\")\n",
        "plt.title(\"Actual vs Predicted Prices\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "_t_PeoS8EZWC",
        "outputId": "f7710dfc-479f-454e-9d62-55784ba81b14"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "5OiZLUPdGyb_"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}