Skewness_Removal_using_Scipy.ipynb

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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",
        "import warnings\n",
        "warnings.filterwarnings (\"ignore\")"
      ]
    },
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      "source": [
        "df=pd.read_csv(\"cars.csv\")\n",
        "df.head()"
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          "height": 320
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              "   symboling normalized-losses         make fuel-type   body-style  \\\n",
              "0          3                 ?  alfa-romero       gas  convertible   \n",
              "1          3                 ?  alfa-romero       gas  convertible   \n",
              "2          1                 ?  alfa-romero       gas    hatchback   \n",
              "3          2               164         audi       gas        sedan   \n",
              "4          2               164         audi       gas        sedan   \n",
              "\n",
              "  drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0          rwd           front   64.1    48.8        dohc          130   \n",
              "1          rwd           front   64.1    48.8        dohc          130   \n",
              "2          rwd           front   65.5    52.4        ohcv          152   \n",
              "3          fwd           front   66.2    54.3         ohc          109   \n",
              "4          4wd           front   66.4    54.3         ohc          136   \n",
              "\n",
              "  horsepower  city-mpg  highway-mpg  price  \n",
              "0        111        21           27  13495  \n",
              "1        111        21           27  16500  \n",
              "2        154        19           26  16500  \n",
              "3        102        24           30  13950  \n",
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 205 entries, 0 to 204\n",
            "Data columns (total 15 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   symboling          205 non-null    int64  \n",
            " 1   normalized-losses  205 non-null    object \n",
            " 2   make               205 non-null    object \n",
            " 3   fuel-type          205 non-null    object \n",
            " 4   body-style         205 non-null    object \n",
            " 5   drive-wheels       205 non-null    object \n",
            " 6   engine-location    205 non-null    object \n",
            " 7   width              205 non-null    float64\n",
            " 8   height             205 non-null    float64\n",
            " 9   engine-type        205 non-null    object \n",
            " 10  engine-size        205 non-null    int64  \n",
            " 11  horsepower         205 non-null    object \n",
            " 12  city-mpg           205 non-null    int64  \n",
            " 13  highway-mpg        205 non-null    int64  \n",
            " 14  price              205 non-null    int64  \n",
            "dtypes: float64(2), int64(5), object(8)\n",
            "memory usage: 24.1+ KB\n"
          ]
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        "df[\"normalized-losses\"].replace(\"?\",np.nan,inplace=True)\n",
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              "   symboling normalized-losses         make fuel-type   body-style  \\\n",
              "0          3               NaN  alfa-romero       gas  convertible   \n",
              "1          3               NaN  alfa-romero       gas  convertible   \n",
              "2          1               NaN  alfa-romero       gas    hatchback   \n",
              "3          2               164         audi       gas        sedan   \n",
              "4          2               164         audi       gas        sedan   \n",
              "\n",
              "  drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0          rwd           front   64.1    48.8        dohc          130   \n",
              "1          rwd           front   64.1    48.8        dohc          130   \n",
              "2          rwd           front   65.5    52.4        ohcv          152   \n",
              "3          fwd           front   66.2    54.3         ohc          109   \n",
              "4          4wd           front   66.4    54.3         ohc          136   \n",
              "\n",
              "  horsepower  city-mpg  highway-mpg  price  \n",
              "0        111        21           27  13495  \n",
              "1        111        21           27  16500  \n",
              "2        154        19           26  16500  \n",
              "3        102        24           30  13950  \n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
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              "      background-color: #434B5C;\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-910ff360-b554-4606-b61f-9f858c3ce6e0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"horsepower\"].replace(\"?\",np.nan,inplace=True)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "2MQNv9S4i2k9",
        "outputId": "ddfeaaaa-f864-46ef-ce1f-cfb3e4efe2fe"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   symboling normalized-losses         make fuel-type   body-style  \\\n",
              "0          3               NaN  alfa-romero       gas  convertible   \n",
              "1          3               NaN  alfa-romero       gas  convertible   \n",
              "2          1               NaN  alfa-romero       gas    hatchback   \n",
              "3          2               164         audi       gas        sedan   \n",
              "4          2               164         audi       gas        sedan   \n",
              "\n",
              "  drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0          rwd           front   64.1    48.8        dohc          130   \n",
              "1          rwd           front   64.1    48.8        dohc          130   \n",
              "2          rwd           front   65.5    52.4        ohcv          152   \n",
              "3          fwd           front   66.2    54.3         ohc          109   \n",
              "4          4wd           front   66.4    54.3         ohc          136   \n",
              "\n",
              "  horsepower  city-mpg  highway-mpg  price  \n",
              "0        111        21           27  13495  \n",
              "1        111        21           27  16500  \n",
              "2        154        19           26  16500  \n",
              "3        102        24           30  13950  \n",
              "4        115        18           22  17450  "
            ],
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              "    <tr>\n",
              "      <th>2</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>152</td>\n",
              "      <td>154</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>16500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <td>gas</td>\n",
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              "      <td>front</td>\n",
              "      <td>66.2</td>\n",
              "      <td>54.3</td>\n",
              "      <td>ohc</td>\n",
              "      <td>109</td>\n",
              "      <td>102</td>\n",
              "      <td>24</td>\n",
              "      <td>30</td>\n",
              "      <td>13950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>164</td>\n",
              "      <td>audi</td>\n",
              "      <td>gas</td>\n",
              "      <td>sedan</td>\n",
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              "      <td>front</td>\n",
              "      <td>66.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>ohc</td>\n",
              "      <td>136</td>\n",
              "      <td>115</td>\n",
              "      <td>18</td>\n",
              "      <td>22</td>\n",
              "      <td>17450</td>\n",
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              "</table>\n",
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              "\n",
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              "\n",
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              "  </style>\n",
              "\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-80cd8108-e9b4-4a2d-b25f-4ce38521ddcb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"normalized-losses\"].isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QTIoc-l8jB1h",
        "outputId": "f54c0602-a8fd-4fd8-f882-76f73807b064"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "41"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"horsepower\"].isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sUrTUr55jMBu",
        "outputId": "4415bbbe-e0ed-4f9c-a204-9d03c388eec5"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.impute import SimpleImputer\n",
        "si=SimpleImputer(missing_values=np.nan,strategy=\"mean\")\n",
        "df[[\"normalized-losses\",\"horsepower\"]]=si.fit_transform(df[[\"normalized-losses\",\"horsepower\"]])\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "aei_c70vjVDd",
        "outputId": "8c4bd381-620e-4e33-d07f-438f34741bdc"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   symboling  normalized-losses         make fuel-type   body-style  \\\n",
              "0          3              122.0  alfa-romero       gas  convertible   \n",
              "1          3              122.0  alfa-romero       gas  convertible   \n",
              "2          1              122.0  alfa-romero       gas    hatchback   \n",
              "3          2              164.0         audi       gas        sedan   \n",
              "4          2              164.0         audi       gas        sedan   \n",
              "\n",
              "  drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0          rwd           front   64.1    48.8        dohc          130   \n",
              "1          rwd           front   64.1    48.8        dohc          130   \n",
              "2          rwd           front   65.5    52.4        ohcv          152   \n",
              "3          fwd           front   66.2    54.3         ohc          109   \n",
              "4          4wd           front   66.4    54.3         ohc          136   \n",
              "\n",
              "   horsepower  city-mpg  highway-mpg  price  \n",
              "0       111.0        21           27  13495  \n",
              "1       111.0        21           27  16500  \n",
              "2       154.0        19           26  16500  \n",
              "3       102.0        24           30  13950  \n",
              "4       115.0        18           22  17450  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-45249684-27ac-4d12-9f42-7eb3696af90d\">\n",
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              "      <th>1</th>\n",
              "      <td>3</td>\n",
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              "      <td>16500</td>\n",
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              "      <th>2</th>\n",
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              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
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              "      <td>52.4</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>152</td>\n",
              "      <td>154.0</td>\n",
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              "      <td>26</td>\n",
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              "      <th>3</th>\n",
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              "      <td>30</td>\n",
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              "      <th>4</th>\n",
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              "</div>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=df.iloc[:,:-1]\n",
        "x"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "fCtv5DN1j6hM",
        "outputId": "e36acf80-a906-4333-bc7f-2295142c1b0a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     symboling  normalized-losses         make fuel-type   body-style  \\\n",
              "0            3              122.0  alfa-romero       gas  convertible   \n",
              "1            3              122.0  alfa-romero       gas  convertible   \n",
              "2            1              122.0  alfa-romero       gas    hatchback   \n",
              "3            2              164.0         audi       gas        sedan   \n",
              "4            2              164.0         audi       gas        sedan   \n",
              "..         ...                ...          ...       ...          ...   \n",
              "200         -1               95.0        volvo       gas        sedan   \n",
              "201         -1               95.0        volvo       gas        sedan   \n",
              "202         -1               95.0        volvo       gas        sedan   \n",
              "203         -1               95.0        volvo    diesel        sedan   \n",
              "204         -1               95.0        volvo       gas        sedan   \n",
              "\n",
              "    drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0            rwd           front   64.1    48.8        dohc          130   \n",
              "1            rwd           front   64.1    48.8        dohc          130   \n",
              "2            rwd           front   65.5    52.4        ohcv          152   \n",
              "3            fwd           front   66.2    54.3         ohc          109   \n",
              "4            4wd           front   66.4    54.3         ohc          136   \n",
              "..           ...             ...    ...     ...         ...          ...   \n",
              "200          rwd           front   68.9    55.5         ohc          141   \n",
              "201          rwd           front   68.8    55.5         ohc          141   \n",
              "202          rwd           front   68.9    55.5        ohcv          173   \n",
              "203          rwd           front   68.9    55.5         ohc          145   \n",
              "204          rwd           front   68.9    55.5         ohc          141   \n",
              "\n",
              "     horsepower  city-mpg  highway-mpg  \n",
              "0         111.0        21           27  \n",
              "1         111.0        21           27  \n",
              "2         154.0        19           26  \n",
              "3         102.0        24           30  \n",
              "4         115.0        18           22  \n",
              "..          ...       ...          ...  \n",
              "200       114.0        23           28  \n",
              "201       160.0        19           25  \n",
              "202       134.0        18           23  \n",
              "203       106.0        26           27  \n",
              "204       114.0        19           25  \n",
              "\n",
              "[205 rows x 14 columns]"
            ],
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              "      <th></th>\n",
              "      <th>symboling</th>\n",
              "      <th>normalized-losses</th>\n",
              "      <th>make</th>\n",
              "      <th>fuel-type</th>\n",
              "      <th>body-style</th>\n",
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              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>122.0</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>convertible</td>\n",
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              "      <th>1</th>\n",
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              "      <td>122.0</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>152</td>\n",
              "      <td>154.0</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
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              "      <td>24</td>\n",
              "      <td>30</td>\n",
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              "      <th>4</th>\n",
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              "      <td>sedan</td>\n",
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              "      <td>sedan</td>\n",
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              "      <td>ohc</td>\n",
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              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>ohc</td>\n",
              "      <td>141</td>\n",
              "      <td>114.0</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d1dd03d2-11ce-469c-8fdf-9b65d805aa47')\"\n",
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              "\n",
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              "          document.querySelector('#df-d1dd03d2-11ce-469c-8fdf-9b65d805aa47 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d1dd03d2-11ce-469c-8fdf-9b65d805aa47');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=df.iloc[:,-1]\n",
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4Biyvu3gkBak",
        "outputId": "3675328f-92c9-4f7a-b4ef-b4b648859fa7"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      13495\n",
              "1      16500\n",
              "2      16500\n",
              "3      13950\n",
              "4      17450\n",
              "       ...  \n",
              "200    16845\n",
              "201    19045\n",
              "202    21485\n",
              "203    22470\n",
              "204    22625\n",
              "Name: price, Length: 205, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Skewness Removal**\n",
        "\n",
        "Skewness can be removed for numeric columns only."
      ],
      "metadata": {
        "id": "UcuiWdHKkjvK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.stats import skew\n",
        "skew(x[\"normalized-losses\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eggn8JjFkFoi",
        "outputId": "15866b54-430b-4a30-8908-1e034520a44c"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8485348696008058"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "skew(x[\"horsepower\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M51o1GbXlGWg",
        "outputId": "5a6fc80d-22d8-4ee7-cf49-9611d936e69d"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.3875147343096037"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In the above dataset there are 8 numeric columns.\n",
        "\n",
        "So we can find the skewness of all by using for loop\n",
        "\n",
        "for this we will first select all numeric columns."
      ],
      "metadata": {
        "id": "dnFg7aX4lSrT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x.select_dtypes([\"int64\",\"float64\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "qFQOPap8lNZT",
        "outputId": "41f92d24-998f-4812-b717-4b4190ebabc9"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     symboling  normalized-losses  width  height  engine-size  horsepower  \\\n",
              "0            3              122.0   64.1    48.8          130       111.0   \n",
              "1            3              122.0   64.1    48.8          130       111.0   \n",
              "2            1              122.0   65.5    52.4          152       154.0   \n",
              "3            2              164.0   66.2    54.3          109       102.0   \n",
              "4            2              164.0   66.4    54.3          136       115.0   \n",
              "..         ...                ...    ...     ...          ...         ...   \n",
              "200         -1               95.0   68.9    55.5          141       114.0   \n",
              "201         -1               95.0   68.8    55.5          141       160.0   \n",
              "202         -1               95.0   68.9    55.5          173       134.0   \n",
              "203         -1               95.0   68.9    55.5          145       106.0   \n",
              "204         -1               95.0   68.9    55.5          141       114.0   \n",
              "\n",
              "     city-mpg  highway-mpg  \n",
              "0          21           27  \n",
              "1          21           27  \n",
              "2          19           26  \n",
              "3          24           30  \n",
              "4          18           22  \n",
              "..        ...          ...  \n",
              "200        23           28  \n",
              "201        19           25  \n",
              "202        18           23  \n",
              "203        26           27  \n",
              "204        19           25  \n",
              "\n",
              "[205 rows x 8 columns]"
            ],
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              "      <div>\n",
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              "      <th></th>\n",
              "      <th>symboling</th>\n",
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              "      <th>0</th>\n",
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              "      <td>21</td>\n",
              "      <td>27</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>122.0</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>130</td>\n",
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              "      <td>27</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>122.0</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>152</td>\n",
              "      <td>154.0</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
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              "    <tr>\n",
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              "      <td>2</td>\n",
              "      <td>164.0</td>\n",
              "      <td>66.2</td>\n",
              "      <td>54.3</td>\n",
              "      <td>109</td>\n",
              "      <td>102.0</td>\n",
              "      <td>24</td>\n",
              "      <td>30</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>164.0</td>\n",
              "      <td>66.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>136</td>\n",
              "      <td>115.0</td>\n",
              "      <td>18</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>200</th>\n",
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              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>141</td>\n",
              "      <td>114.0</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>-1</td>\n",
              "      <td>95.0</td>\n",
              "      <td>68.8</td>\n",
              "      <td>55.5</td>\n",
              "      <td>141</td>\n",
              "      <td>160.0</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>-1</td>\n",
              "      <td>95.0</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>173</td>\n",
              "      <td>134.0</td>\n",
              "      <td>18</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>-1</td>\n",
              "      <td>95.0</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>145</td>\n",
              "      <td>106.0</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>-1</td>\n",
              "      <td>95.0</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>141</td>\n",
              "      <td>114.0</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 8 columns</p>\n",
              "</div>\n",
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              "        async function convertToInteractive(key) {\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To get only column names we will use .columns attribute"
      ],
      "metadata": {
        "id": "DEEYWQzhl8vV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x.select_dtypes([\"int64\",\"float64\"]).columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ahq5ml5Llt-F",
        "outputId": "df541edb-450f-432b-8fa3-dc1e8a3ed7ca"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['symboling', 'normalized-losses', 'width', 'height', 'engine-size',\n",
              "       'horsepower', 'city-mpg', 'highway-mpg'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colnames=x.select_dtypes([\"int64\",\"float64\"]).columns\n",
        "colnames"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Btko3maol6WN",
        "outputId": "c858a08b-79ea-4126-9597-25f75eb40603"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['symboling', 'normalized-losses', 'width', 'height', 'engine-size',\n",
              "       'horsepower', 'city-mpg', 'highway-mpg'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in x[colnames]:\n",
        "  print(i)\n",
        "  print(skew(x[i]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X_xC7i7bmS4n",
        "outputId": "f34ae6b8-7f6f-449c-c1e3-ffe68c5c4b91"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "symboling\n",
            "0.20952469094997359\n",
            "normalized-losses\n",
            "0.8485348696008058\n",
            "width\n",
            "0.8973753485201392\n",
            "height\n",
            "0.06265991683394276\n",
            "engine-size\n",
            "1.9333748457840114\n",
            "horsepower\n",
            "1.3875147343096037\n",
            "city-mpg\n",
            "0.6588377533622138\n",
            "highway-mpg\n",
            "0.5360379305163596\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in x[colnames]:\n",
        "  print(i)\n",
        "  print(skew(x[i]))\n",
        "  plt.figure()\n",
        "  sns.distplot(x[i])\n",
        "  plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "4gzTZevUm1DN",
        "outputId": "62f0bc97-4a35-4fc2-c6ce-22ba290b841d"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "symboling\n",
            "0.20952469094997359\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "normalized-losses\n",
            "0.8485348696008058\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "width\n",
            "0.8973753485201392\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "height\n",
            "0.06265991683394276\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "engine-size\n",
            "1.9333748457840114\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "horsepower\n",
            "1.3875147343096037\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "city-mpg\n",
            "0.6588377533622138\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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5Fb9dnWdb7fkPt/beRqf2MjLMDwP7eaHVKuJfXBuIiBwIAxCRE7BaRTz7zwM4Xl6Hfj5qLHtwFBRyx//nKwgC0hNDoZAJOFlRj/wibpNBRI7B8b+DEhGW/PcEth4xQCWXYcXDSdBrHWPKe1cEeauROkQHANh8qAyG2iaJKyIiYgAicnh/33kGb3/dtt7Pq+nDkBThL3FF129CTBAG+HugqcWK//n8ELvCiEhyDhGAli9fjsjISGg0GiQnJ2Pv3r1Xbb9+/XrExcVBo9EgPj4eW7Zs6fD8o48+CkEQOjwmTZrUmx+BqFes2VOERZuPAgCevW0wMsaES1xR98gEAfeOGgC5TED2sQqszz0vdUlE5OYkD0Dr1q1DZmYmFi5ciPz8fCQkJCAtLQ0VFRWdtt+1axemTJmCGTNmYP/+/UhPT0d6ejoOHz7cod2kSZNQVlZme3zyySd98XGI7EIURfx12wnM+/wQAODJiQMx85ZoiavqGZ2vBrdd6gp75d9HUMgFEolIQpIHoLfeegtPPPEEpk+fjqFDh2LFihXw9PTE+++/32n7pUuXYtKkSXj++ecxZMgQvPrqqxg1ahSWLVvWoZ1arYZer7c9/P2dr9uA3JPJ3Io/rivA0uyTAIDfTRyEOZPiJN/nyx4mxAQhOSoApmYLnllXgFaLVeqSiMhNSRqAmpubkZeXh9TUVNsxmUyG1NRU5OTkdHpOTk5Oh/YAkJaWdln77du3o3///oiNjcVTTz2FCxcuXLEOs9kMo9HY4UEkhW9PVOL2v36LjQWlkMsEZN0Tjzl3uEb4Adq6wt7KSISPRoH9RTX4639PSF0SEbkpSQNQVVUVLBYLdDpdh+M6nQ4GQ+ebKBoMhmu2nzRpElavXo3s7Gy88cYb2LFjB+644w5YLJ3vTJ2VlQWtVmt7hIWF9fCTEXWdKIr47mQVHnlvD6a+vxclNY0Y4O+Bf8xIxpSxzjnm52pC/Tzw57vjAQDLvzmNr4+VS1wREbkjhdQF9IYHHnjA9uf4+HiMGDECgwYNwvbt23Hrrbde1n7u3LnIzMy0fW00GhmCqNc0tVhw7oIJJ8vrsfvMBWw/XomSmkYAgEwApqZE4vm0WHipXfKfJwDg1wkh2HeuGqtzCvHHdQewadYEhAV4Sl0WEbkRSb/DBgUFQS6Xo7y842+A5eXl0Ov1nZ6j1+uvqz0ADBw4EEFBQTh16lSnAUitVkOtVnfjExBdrrnVisILJpQbm3DB1IzaxhaYzK0wNVuQteUo6sytl53joZQjY0wYZkyIcpsg8D+Th+DA+VocKK7Bkx/lYf3vUlw69BGRY5H0u41KpUJSUhKys7ORnp4OALBarcjOzsbMmTM7PSclJQXZ2dl45plnbMe2bduGlJSUK77P+fPnceHCBQQHB9uzfCIbqyjih1Ijdp+9gMILDdfc/dxHo0B0f2/Eh2pxU2w/pAwMgodK3kfVOga1Qo6/PTQKdy37Dj+UGfHMugKseDgJcplrjHciIscm+a9bmZmZmDZtGkaPHo2xY8diyZIlMJlMmD59OgBg6tSpCA0NRVZWFgBg9uzZmDhxIhYvXozJkydj7dq1yM3NxcqVKwEA9fX1eOWVV3DvvfdCr9fj9OnTeOGFFxAdHY20tDTJPie5rh9KjfjP4TJc+Mlmn1oPJcICPBHopYKfpxLeagW8VApkjA1DoJcKWg+lywxs7olQPw/8v0dGY8q7u7Hth3K8/p+j+J/JQ6Uui4jcgOQBKCMjA5WVlViwYAEMBgMSExOxdetW20DnoqIiyGQ/jtUeP3481qxZg5deegnz5s1DTEwMNm7ciOHDhwMA5HI5Dh48iA8//BA1NTUICQnB7bffjldffZXdXGRXza1WbDlUhr3nqgG0dWONGxiAkWH+CPRWdRpwBvXz7usyHV5ShD/e/M0IzF5bgHd3nkU/HzV++4tBUpdFRC5OELkm/WWMRiO0Wi1qa2vh6+srdTlkJ2v2FNnttRqaW/H+d2dRemlfqxtjgnBLXH+oFVfvxnowWdpZXfa8Bt11pWvwzvbTeGPrMQDAG/fGO+2q10Qknev5+S35HSAiZ9PYbMH737eFHy+1AhmjwxDdn3d2euqpmwahprEZ/2/HGczdcAhymQy/SRogdVlE5KIkXwmayJm0WKxYtessSmua4KWS4/EJUQw/djRnUhweTA6HVQSeW38A/9hdKHVJROSiGICIrsOWQ2UovtgID6Ucj02Igs5XI3VJLkUQBCy6azgeHR8JAHhp42H8fecZaYsiIpfEAETURYdLarHnbNuA5wfGhCFY6yFxRa5JJhOw8NdD8dRNbQOhF20+imVfn5S4KiJyNQxARF1Q09CMz/eXAAB+EROEGJ2PxBW5NkEQ8EJaLJ69bTAA4H+/OoG/bD0GztkgInthACLqgi2HytDYYsEAfw+kDtVd+wTqMUEQMOvWGLw0eQgA4G/bT+PVTUcZgojILhiAiK7hbJUJh0uNEADcPTIUChn/2fSlx28ciFfT29b5ev/7s/ifjYdhvcZK20RE18Lv5ERXYRVFbD5YCgAYExnAcT8SeWRcBN78zQjIhLa1jJ779ABaLVapyyIiJ8YARHQV+4suorS2CWqFjF1fErtvdBiWPDAScpmADfklmL22AC0MQUTUTQxARFdgsYrIPlYBALglrj+8uVO55O5MCMHyB0dBKRew+VAZXvzsIMcEEVG3MAARXcGhkhrUNLTASyXHuIGBUpdDl0warsc7DyXZ7gS9sfW41CURkRNiACLqhCiK+PZEFQDghuggKOX8p+JIUofqkHVPPABgxY7T+CjnnLQFEZHT4Xd1ok6cKK+Dwdg29ic5ind/HNH9o8PwfFosAOBPm35AXuFFiSsiImfCAETUiR0nKgEAYyMD4KG6+g7vJJ3f3zQIk+OD0WIR8fTH+bhQb5a6JCJyEgxARD9TVtuIcxcaIBOA8dFBUpdDVyEIAt74zQgM6ucFg7EJz6wr4KBoIuoSBiCin9l3rq0rZUiwL7QeSomroWvxViuw4uEkaJQy7DxZhX/mFktdEhE5AQYgop9osVhRUNwWgMZGBkhcDXVVjM4Hz97WNh5o0eajMNQ2SVwRETm6bgWgM2fO2LsOIodwuKQWTS1W+HsqMai/t9Tl0HV4bEIUEsL8UNfUipc2HmJXGBFdVbcCUHR0NG6++Wb84x//QFMTf9Mi17H3XDUAYHRkAGSCIHE1dD3kMgFv/mYElHIB/z1age3HK6UuiYgcWLcCUH5+PkaMGIHMzEzo9Xo8+eST2Lt3r71rI+pTFXVNKLw0+Dkp3F/qcqgbBut88NgNUQCA1/9zDBZumkpEV9CtAJSYmIilS5eitLQU77//PsrKyjBhwgQMHz4cb731Fior+ZsXOZ+D52sBADH9feDLwc9O6/c3RUProcTx8jp8ln9e6nKIyEH1aBC0QqHAPffcg/Xr1+ONN97AqVOn8NxzzyEsLAxTp05FWVmZveok6lWiKOJAcQ0AICFMK20x1CNaTyVm3RINAHjrqxNobLZIXBEROaIeBaDc3Fz8/ve/R3BwMN566y0899xzOH36NLZt24bS0lLcdddd9qqTqFeV1jThgqkZSrmAIcG+UpdDPfRISgQG+HvAYGzCx3sKpS6HiBxQtwLQW2+9hfj4eIwfPx6lpaVYvXo1CgsLsWjRIkRFReHGG2/EqlWrkJ+fb+96iXrFwfM1AIBYvS/UCq787OzUCrntLtB7351Fc6tV4oqIyNF0KwC98847ePDBB1FYWIiNGzfiV7/6FWSyji/Vv39/vPfee3Ypkqg3WUURB0vaxv8kDGD3l6tIHxmK/j5qlNU24YsDpVKXQ0QOplsBaNu2bXjxxRcRHBzc4bgoiigqKgIAqFQqTJs2recVEvWyogsNqG1sgVohw2Cdj9TlkJ2oFXI8NqFtRtjKb0/DyhlhRPQT3QpAgwYNQlVV1WXHq6urERUV1eOiiPrSodK2uz9Dg32hlHNxdFfyYHI4vNUKnCivx/YTFVKXQ0QOpFvf7a+0wmp9fT00Gk2PCiLqS6Io4miZEQAwLITdX67GV6PEQ8nhANrGAhERtVNcT+PMzEwAbTswL1iwAJ6enrbnLBYL9uzZg8TERLsWSNSbDMYm1DS0QCkXEM2tL1zSIykRWLnzDL4/dQGFF0yICPSSuiQicgDXFYD2798PoO235kOHDkGlUtmeU6lUSEhIwHPPPWffCol60Q+X7v5E9/OGSsHuL1c0wN8Tv4jphx0nKrF2XzFenBQndUlE5ACuKwB98803AIDp06dj6dKl8PXleink3Nq7v7j2j2ubMjYMO05UYn3ueWTeNhjrc6VfIfrBS11zRCSN6wpA7T744AN710HU52oamlFa0wQBQBwDkEu7dYgOQd5qVNWbkX20XOpyiMgBdDkA3XPPPVi1ahV8fX1xzz33XLXthg0belwYUW87aqgDAIQHeMJb3a3fBchJKOUy3Dd6AN7Zfhpr9hZj0jC91CURkcS6POhBq9VCEATbn6/2IHIGx9j95VYeGBMGANh5shLGphaJqyEiqXX5196fdnuxC4ycXXOrFWerTACAOD0XP3QHEYFeGBnuh/1FNThcUovxg4KkLomIJNStaS+NjY1oaGiwfV1YWIglS5bgq6++slthRL3pbJUJrVYRfp5K9PNRS10O9ZE7E0IAAAeKa6QthIgk160AdNddd2H16tUAgJqaGowdOxaLFy/GXXfdhXfeeee6X2/58uWIjIyERqNBcnIy9u7de9X269evR1xcHDQaDeLj47Fly5Yrtv3d734HQRCwZMmS666LXNeJirbxP4P7+9i6dsn1TY4PhkwAii82otrULHU5RCShbgWg/Px83HjjjQCATz/9FHq9HoWFhVi9ejXefvvt63qtdevWITMzEwsXLkR+fj4SEhKQlpaGiorOl63ftWsXpkyZghkzZmD//v1IT09Heno6Dh8+fFnbzz//HLt370ZISMj1f0hyaSfLLwUgHRc/dCf9fTUYNzAQAHDwfI20xRCRpLoVgBoaGuDj0zZu4quvvsI999wDmUyGcePGobCw8Lpe66233sITTzyB6dOnY+jQoVixYgU8PT3x/vvvd9p+6dKlmDRpEp5//nkMGTIEr776KkaNGoVly5Z1aFdSUoJZs2bh448/hlKpvGoNZrMZRqOxw4NcV7WpGVX1zZAJwMB+DEDupr0b7OD5WokrISIpdSsARUdHY+PGjSguLsaXX36J22+/HQBQUVFxXYsjNjc3Iy8vD6mpqT8WJJMhNTUVOTk5nZ6Tk5PToT0ApKWldWhvtVrxyCOP4Pnnn8ewYcOuWUdWVlaHWWxhYWFd/gzkfE5cuvsTEegFjVIucTXU1+4YHgy5IMBgbEKFsUnqcohIIt0KQAsWLMBzzz2HyMhIJCcnIyUlBUDb3aCRI0d2+XWqqqpgsVig0+k6HNfpdDAYDJ2eYzAYrtn+jTfegEKhwB/+8Icu1TF37lzU1tbaHsXFxV3+DOR82gPQYO795Za0nkoM6t+2H1j7VihE5H66tfrbb37zG0yYMAFlZWVISEiwHb/11ltx991326247sjLy8PSpUuRn5/f5cGtarUaajVnArmDVqsVZyrbpr/H6Dj93V0NCfbFifJ6HC0z4qbY/lKXQ0QS6Pbuj3q9HiNHjoRM9uNLjB07FnFxXd9oMCgoCHK5HOXlHZemLy8vh17f+Uqter3+qu137tyJiooKhIeHQ6FQQKFQoLCwEM8++ywiIyO7XBu5puLqRjRbrPBSyaHXaqQuhyQyRN/WVV98sRHGRi6KSOSOuhWATCYT5s+fj/HjxyM6OhoDBw7s8OgqlUqFpKQkZGdn245ZrVZkZ2fbutV+LiUlpUN7ANi2bZut/SOPPIKDBw+ioKDA9ggJCcHzzz+PL7/8shufllzJ6cp6AG2Dn2Wc/u62fD2UGODvAQA4amA3GJE76lYX2OOPP44dO3bgkUceQXBwcI/WUcnMzMS0adMwevRojB07FkuWLIHJZML06dMBAFOnTkVoaCiysrIAALNnz8bEiROxePFiTJ48GWvXrkVubi5WrlwJAAgMDERgYGCH91AqldDr9YiNje12neQaTle0BaBozv5ye0ODfXH+YiOOlhmRHBV47ROIyKV0KwD95z//webNm3HDDTf0uICMjAxUVlZiwYIFMBgMSExMxNatW20DnYuKijp0s40fPx5r1qzBSy+9hHnz5iEmJgYbN27E8OHDe1wLuTZzqwXFF9tWMB/EAdBub0iwL776oRynK00wt1ig5oxAIrfSrQDk7++PgIAAuxUxc+ZMzJw5s9Pntm/fftmx++67D/fdd1+XX//cuXPdrIxcybkqE6wi4O+pRICXSupySGL9fdQI8FKh2tSMExX1iA/lRs5E7qRbY4BeffVVLFiwoMN+YESO7vSl2V+D2P1FAARBwJBLG+GeMNRJXA0R9bVu3QFavHgxTp8+DZ1Oh8jIyMtWWs7Pz7dLcUT21D4AmgGI2g3W++D70xdwoqIOoihyXzgiN9KtAJSenm7nMoh6V7WpGWW1bav+DuznJXE15CgiA72glAuoa2qFwdiEYK2H1CURUR/pVgBauHChvesg6lW7z1wAAOh81fDRXH1vOHIfSrkMA4O8cby8DifK6xmAiNxItxdCrKmpwd///nfMnTsX1dXVANq6vkpKSuxWHJG9tAeggUHs/qKOBuva/k60b5FCRO6hW3eADh48iNTUVGi1Wpw7dw5PPPEEAgICsGHDBhQVFWH16tX2rpOoR/acaQvpUUHs/qKOBut8AJSh8AKnwxO5k27dAcrMzMSjjz6KkydPQqP5cTuBX/7yl/j222/tVhyRPVSbmnH80m/3kQxA9DOB3m3T4a3ijzMFicj1dSsA7du3D08++eRlx0NDQ6+4izuRVPaebev+6u+jhre6Wzc9ycUNvrQxLrvBiNxHtwKQWq2G0Xj5/jknTpxAv379elwUkT3tZvcXXcPgSyuDn7q0VAIRub5uBaA777wTf/rTn9DS0raLsiAIKCoqwosvvoh7773XrgUS9VT7AGgGILqSyCAvyIS27tKLpmapyyGiPtCtALR48WLU19ejX79+aGxsxMSJExEdHQ0fHx+89tpr9q6RqNtqGn4c/8MARFeiUcoxwN8TwI8LZhKRa+vWgAitVott27bh+++/x4EDB1BfX49Ro0YhNTXV3vUR9cjes9UQRWBQPy+u/0NXNaifN4qqG3Cqsh6jI+231yEROabrDkBWqxWrVq3Chg0bcO7cOQiCgKioKOj1ei4lTw5nz9m28T/JAwMlroQc3aD+XvjmOHCm0sTvZURu4Lq6wERRxJ133onHH38cJSUliI+Px7Bhw1BYWIhHH30Ud999d2/VSdQtuefaAtBY/kZP1xDu7wmlXEC9uRXldWapyyGiXnZdd4BWrVqFb7/9FtnZ2bj55ps7PPf1118jPT0dq1evxtSpU+1aJFF3NDZbcKS0bbZiUoQ/dp6skrgicmQKuQyRgV44WVGP0xX10Ptqrn0SETmt67oD9Mknn2DevHmXhR8AuOWWWzBnzhx8/PHHdiuOqCcKimvQahWh81VjgD/3eKJrG9SvbTo8B0ITub7rCkAHDx7EpEmTrvj8HXfcgQMHDvS4KCJ7yCts6/4aHRnA8RzUJe0B6GyVCRarKHE1RNSbrisAVVdXQ6fTXfF5nU6Hixcv9rgoInvILWz7uzg6wl/iSshZBPtpoFHKYG61oqy2UepyiKgXXVcAslgsUCiuPGxILpejtbW1x0UR9ZTVKiLfFoA4AJq6RiYIiAxsWy/qbBX3BSNyZdc1CFoURTz66KNQq9WdPm82c+YEOYaTFfUwNrXCUyXHkGAfqcshJxIV5IVjhjqcrTLhxhhu7UPkqq4rAE2bNu2abTgDjBzBvkvT3xPD/KCQd2vBc3JT7SuGn7tgglUUIeP4MSKXdF0B6IMPPuitOojsKo/jf6ibgrUeUCtkaGqxwlDbhBA/ziAkckX81ZhcUu6lGWBJXACRrpNcJiAisG1fMI4DInJdDEDkciqMTSiuboQgACPD/aQuh5xQFAdCE7k8BiByOe3T32N1PvDlBqjUDT8fB0RErocBiFxO7rm2ADSG3V/UTSH+HlDKBTQ0W1DBfcGIXBIDELmcH1eA5gBo6h6FTIbwAI4DInJl1zULjMjR/XwDVEezZk+R1CVQF0UFeeF0pQlnq0xIGRgodTlEZGe8A0QupX0DVL2vBqGcvkw9EBX0475gIscBEbkcBiByKbnn2qe/+3MDVOqRAf4eUMgEmMytqKpvlrocIrIzBiByKdwAlexFKZchjOOAiFwWAxC5DKtVRH4RN0Al+2mfDn+2ql7iSojI3hiAyGWcqKhDHTdAJTv66c7wHAdE5FoYgMhltK//ww1QyV7CAzwhFwQYm1pRbeI4ICJXwp8S5DK4ASrZm0ohQ6h/22xCjgMici0OEYCWL1+OyMhIaDQaJCcnY+/evVdtv379esTFxUGj0SA+Ph5btmzp8PzLL7+MuLg4eHl5wd/fH6mpqdizZ09vfgRyALm2BRA5/ofs56fbYhCR65A8AK1btw6ZmZlYuHAh8vPzkZCQgLS0NFRUVHTafteuXZgyZQpmzJiB/fv3Iz09Henp6Th8+LCtzeDBg7Fs2TIcOnQI3333HSIjI3H77bejsrKyrz4W9bHySxugyrgBKtnZjwOhGYCIXInkAeitt97CE088genTp2Po0KFYsWIFPD098f7773fafunSpZg0aRKef/55DBkyBK+++ipGjRqFZcuW2do8+OCDSE1NxcCBAzFs2DC89dZbMBqNOHjwYF99LOpj7eN/YvW+8OEGqGRH4QGeEABcbGhBbWOL1OUQkZ1IGoCam5uRl5eH1NRU2zGZTIbU1FTk5OR0ek5OTk6H9gCQlpZ2xfbNzc1YuXIltFotEhISOm1jNpthNBo7PMi52Lq/OP6H7EyjlCPk0qri53gXiMhlSBqAqqqqYLFYoNPpOhzX6XQwGAydnmMwGLrUftOmTfD29oZGo8Ff//pXbNu2DUFBQZ2+ZlZWFrRare0RFhbWg09FUrANgOYGqNQLIgMvLYjIcUBELkPyLrDecvPNN6OgoAC7du3CpEmTcP/9919xXNHcuXNRW1trexQXF/dxtdQTDc2tDr0BKjk/20Bo3gEichmSBqCgoCDI5XKUl5d3OF5eXg69Xt/pOXq9vkvtvby8EB0djXHjxuG9996DQqHAe++91+lrqtVq+Pr6dniQ8ygoroGFG6BSL4q4tCBiRZ0Z9eZWiashInuQNACpVCokJSUhOzvbdsxqtSI7OxspKSmdnpOSktKhPQBs27btiu1/+rpms7nnRZPDybs0AJoboFJv8VIr0N9HDQAoZDcYkUuQvAssMzMT7777Lj788EMcPXoUTz31FEwmE6ZPnw4AmDp1KubOnWtrP3v2bGzduhWLFy/GsWPH8PLLLyM3NxczZ84EAJhMJsybNw+7d+9GYWEh8vLy8Nhjj6GkpAT33XefJJ+Rehc3QKW+wG4wIteikLqAjIwMVFZWYsGCBTAYDEhMTMTWrVttA52Lioogk/2Y08aPH481a9bgpZdewrx58xATE4ONGzdi+PDhAAC5XI5jx47hww8/RFVVFQIDAzFmzBjs3LkTw4YNk+QzUu/56QaoY7gAIvWiyEAv7DlbjXMXGqQuhYjsQPIABAAzZ8603cH5ue3bt1927L777rvi3RyNRoMNGzbYszxyYD/dADVOzw1QqfdEXroDVFrTiKYWCzRKucQVEVFPSN4FRtQT+y6N/xkZzg1QqXdpPZQI8FJBBFBUzbtARM6OPzHIqeWda1sAMSmC3V/U+yIDuS0GkatgACKnxgHQ1JeigtoWRORAaCLnxwBETqvc2ITzF7kBKvWd9jtA52sa0WKxSlwNEfUEAxA5LW6ASn0twEsFX40CFquI4oscB0TkzBiAyGlxA1Tqa4Ig2GaDsRuMyLkxAJHT4gaoJIX2brBzVbwDROTMGIDIKf10A9TRXACR+lD7itCF1SZYrKLE1RBRdzEAkVNq3wA1WMsNUKlv9fNRw1MlR4tFRAnHARE5LQYgckrtA6CTOP6H+phMEGx3gc5wHBCR02IAIqfE9X9ISgMZgIicHgMQOR2LVcR+2wBojv+hvhfVzxsAUHjBhFYr1wMickYMQOR0TpTXoc7MDVBJOroO44AapS6HiLqBAYicTnv3FzdAJakIgsBuMCInx58e5HS4ASo5goGXusHOVNZLXAkRdQcDEDkdDoAmR9A+E6yougGt3BeMyOkwAJFTKatt5Aao5BD6+6jhpVagxSKimOOAiJwOAxA5lb1n27q/hoZwA1SS1k/HAZ1mNxiR02EAIqfSvgDiGE5/JwcQ3b9tHNDpCgYgImejkLoAouux79IA6LEMQE5rzZ4iqUuwm/YAVHyxAU0tFmiUcokrIqKu4h0gchq1DS04Xl4HgAsgkmPw91Qh0EsFqwic5XR4IqfCAEROI7ewGqLYNvumn49a6nKIAACDLt0FOsVxQEROhQGInMbeS91fYyI5/Z0cR3Q/jgMickYMQOQ0OACaHNHAfl4QAFTUmWFsbJG6HCLqIgYgcgpNLRYcPF8DABgbxQBEjsNTpUCInwcATocnciYMQOQUCopr0GIR0c9HjfAAT6nLIeqgfTbYSXaDETkNBiByCvvO/jj9XRAEiash6miwzgcAcKK8DlZRlLgaIuoKBiByCvsK28f/cAA0OZ7wAE9olDI0NFtQwm0xiJwCAxA5PItVRH57AOL4H3JAcplgmw3WvlYVETk2BiByeEfLjKg3t8JHrUCc3lfqcog6Fav/sRuMiBwfAxA5vPYNUEdF+EMu4/gfckwxl8YBnb/YiLomTocncnQMQOTwcgsvDYBm9xc5MF+NEiF+GgCcDUbkDBiAyKGJooi9Z7kAIjmH2Et3gY4b2A1G5OgYgMihnbvQgKp6M1RyGUYM0EpdDtFVtQegkxV1aLVaJa6GiK6GAYgcWvv6PyMGaKFRyiWuhujqBgR4wketQFOLFWcquTs8kSNziAC0fPlyREZGQqPRIDk5GXv37r1q+/Xr1yMuLg4ajQbx8fHYsmWL7bmWlha8+OKLiI+Ph5eXF0JCQjB16lSUlpb29segXpBz5gIAIHkgu7/I8ckEAUNC2mYqHik1SlwNEV2N5AFo3bp1yMzMxMKFC5Gfn4+EhASkpaWhoqKi0/a7du3ClClTMGPGDOzfvx/p6elIT0/H4cOHAQANDQ3Iz8/H/PnzkZ+fjw0bNuD48eO48847+/JjkR2Iooic020BaPygIImrIeqaYcFtAehomZGrQhM5MEEUpf0XmpycjDFjxmDZsmUAAKvVirCwMMyaNQtz5sy5rH1GRgZMJhM2bdpkOzZu3DgkJiZixYoVnb7Hvn37MHbsWBQWFiI8PPyaNRmNRmi1WtTW1sLXl+vOSOVMZT1uWbwDKrkMB1++vcddYGv2FNmpMqIra7Va8ectR9HUYsVvbxyIyCAvqUu6ogeTr/39kMiZXM/Pb0nvADU3NyMvLw+pqam2YzKZDKmpqcjJyen0nJycnA7tASAtLe2K7QGgtrYWgiDAz8+v0+fNZjOMRmOHB0mvvftrZLgfx/+Q01DIZBiib+8Gq5W4GiK6EkkDUFVVFSwWC3Q6XYfjOp0OBoOh03MMBsN1tW9qasKLL76IKVOmXDENZmVlQavV2h5hYWHd+DRkb7sudX+lDAqUuBKi6zOsfRxQmRES32QnoiuQfAxQb2ppacH9998PURTxzjvvXLHd3LlzUVtba3sUFxf3YZXUGVEUsZvjf8hJRff3gVIuoKahBee5OSqRQ1JI+eZBQUGQy+UoLy/vcLy8vBx6vb7Tc/R6fZfat4efwsJCfP3111ftC1Sr1VCr1d38FNQbTpTX44KpGRqlDAlhXP+HnItKIcPQYF8cOF+L/cU1CAvwlLokIvoZSe8AqVQqJCUlITs723bMarUiOzsbKSkpnZ6TkpLSoT0AbNu2rUP79vBz8uRJ/Pe//0VgILtQnE3O6SoAbas/qxUc/0POZ2S4PwDg4PkaLopI5IAkvQMEAJmZmZg2bRpGjx6NsWPHYsmSJTCZTJg+fToAYOrUqQgNDUVWVhYAYPbs2Zg4cSIWL16MyZMnY+3atcjNzcXKlSsBtIWf3/zmN8jPz8emTZtgsVhs44MCAgKgUqmk+aB0XdoHQI8byPBKzmlQP294qxWoN7fiZHk9hgRzRimRI5E8AGVkZKCyshILFiyAwWBAYmIitm7dahvoXFRUBJnsxxtV48ePx5o1a/DSSy9h3rx5iImJwcaNGzF8+HAAQElJCb744gsAQGJiYof3+uabb3DTTTf1yeei7rNaRew+07YC9HgOgCYnJZcJSAzzw3enqrC/6CIDEJGDkXwdIEfEdYCkdbikFr/6v+/grVagYMFtUMjt01PLdYCor5XWNGLZN6egkAmYe8cQeKgcqzuX6wCRq3GadYCIOtO++vOYSH+7hR8iKQRrNdD5qtFqFXHgfI3U5RDRT/CnCzmc9vE/nP5Ozk4QBIyOaNvHbveZC1wTiMiBMACRQ2m1WLH30g7wXACRXEFShD9Uchkq6sw4U8Ud4okcBQMQOZRDJbWoN7dC66HkoFFyCRqlHCPD/QD82L1LRNJjACKH0r79RXJUAOQyQeJqiOyjfTmHo2VGXGxolrgaIgIYgMjB7LaN/2H3F7kOna8Gg/p5QQTvAhE5CgYgchhNLRbsO9c+/ocDoMm13BDd9nd6z9kLqGtqkbgaImIAIoeRe+4imlqs6O+jxmCdt9TlENlVrM4HA/w90GIR8e2JSqnLIXJ7DEDkML492fZD4caYfhAEjv8h1yIIAlKHtK1wv+dsNWobeReISEoMQOQw2n8r/sVgdn+Ra4rp742IAE+0WkVsP14hdTlEbk3yvcDIPVxrGwpjUwuOGeogAKgwmrltBbkkQRBw21Ad/v7dWew7V40xkQEI8fOQuiwit8Q7QOQQTpXXAwBC/DzgpWYuJ9c1sJ83hof4wioCn+8vgcXK1aGJpMAARA7hREUdgLYuAiJX96uEEGiUMpTUNCLndJXU5RC5JQYgkpxVFHGqou0OUIzOR+JqiHqfr0aJO4YHAwC2HS2HwdgkcUVE7ocBiCRXVtOEhmYL1AoZwgM8pS6HqE+MjvBHdD9vtFhEfJRzDiZzq9QlEbkVBiCS3LFyIwBgUD9vbn9BbkMQBDwwJgwBXipcbGjBx3uK0Gq1Sl0WkdtgACLJHTe0jf+J07P7i9yLp1qBR8ZFQK2Q4dwFE/6xuxDmVovUZRG5BQYgklRdUwvOX2wEAAxmACI3pPPV4MGx4VDKBZwor8ffd57lVhlEfYABiCR1wjb9XQNfjVLiaoikEaPzweMTBsJTJUdJTSOWZp/E/qKLEEVOkSfqLQxAJKnjhrbxP3F6X4krIZJWWIAnfveLQdD5qtHQbMH6vPNY+e0ZHC6p5VpBRL2AK86RZFqtVpy8NP09ltPfiRDko8bMm2Pw3clKZB+rQGF1Awr3FsFHo0CszgeDdT6ICPSED++WEvUYAxBJpvBCA8ytVnipFQj153YARAAglwmYGNsfieH+2HP2AvadrUZdUytyCy8it/AiAEDrocQAfw+E+XtiQIAHQv08oFbIJa6cyLkwAJFkjpW1dX/F6rwh4+7vRB1oPZS4faget8T2x5kqE06U1+F0ZT0qjGbUNragtrEFR0rb/g0JAPRaDeL0vhgW4otgrQYC/00RXRUDEElCFEX8cCkADQnm+B+iK1HIZRh8qfsLAMwtFpTUNOL8xUYUX2zA+YuNqG1sQVltE8pqm/DN8QqE+nlgQnQQhodqubYW0RUwAJEkymqbcLGhBUq5gJj+HP9D1FVqpRwD+3ljYL8f980zNrXgdEU9jpQacaK8DiU1jViXW4zsY+X41YgQW3gioh8xAJEk2u/+xPT3gUrByYhEPeGrUWJkuD9Ghvuj3tyKvWcvIOf0BVTVN2PVrnMYHuKLu0cOgIeK44SI2vEnD0nih0tjF4aGsPuLyJ681QrcEqfDs7fH4oZBgZAJwOFSI5Z9cxIllxYdJSIGIJLAhXozDMYmyARuf0HUWzRKOSaPCMFTN0Xb9htb8e1pHCqplbo0IofAAER9rr37KzLIC54q9sIS9aZQPw88fVM0huh9YLGKWLu3CLnnqqUui0hyDEDU59qn7g7j7C+iPuGhkuOhcREYHeEPEcCG/SXYfeaC1GURSYoBiPpUTUMziqobIAAYFqKVuhwityETBNw9MhQTooMAAP8+UIpNB0slropIOgxA1Kfaxx9EBHrB14PL+RP1JUEQcMdwPZKjAiACyFx3ALtOVUldFpEkGICoTx083xaARgzg3R8iKQiCgF8nhGBYiC+aLVY8+Y88nKsySV0WUZ9jAKI+c6HejJKaxkvdXxz/QyQVmSDg/tFhGBnuh7qmVjz5UR5M5lapyyLqUwxA1Gfau78G9fPmbtZEElPKZVjxcBKCvNU4Xl6HFz47CFEUpS6LqM8wAFGfaQ9A8ez+InIIOl8N3nl4FBQyAZsPluHjPUVSl0TUZyQPQMuXL0dkZCQ0Gg2Sk5Oxd+/eq7Zfv3494uLioNFoEB8fjy1btnR4fsOGDbj99tsRGBgIQRBQUFDQi9VTVxmMbRs1ygROfydyJGMiAzDnjjgAwKubfsDJ8jqJKyLqG5IGoHXr1iEzMxMLFy5Efn4+EhISkJaWhoqKik7b79q1C1OmTMGMGTOwf/9+pKenIz09HYcPH7a1MZlMmDBhAt54442++hjUBfuLLgIAYvW+8FRz8UMiR/LYDVG4MSYI5lYr/rC2AE0tFqlLIup1gihhp29ycjLGjBmDZcuWAQCsVivCwsIwa9YszJkz57L2GRkZMJlM2LRpk+3YuHHjkJiYiBUrVnRoe+7cOURFRWH//v1ITEy8ah1msxlms9n2tdFoRFhYGGpra+Hry7sVPdVqsWLkq9tQ19SKh5LDuf4PkYN4MDnc9ueKuibcsWQnLpia8eTEgZh7xxAJKyPqHqPRCK1W26Wf35LdAWpubkZeXh5SU1N/LEYmQ2pqKnJycjo9Jycnp0N7AEhLS7ti+67KysqCVqu1PcLCwnr0etTRd6eqUNfUCk+VHLHc+4vIIfX30eD1e0cAAN799gwOFNdIWxBRL5MsAFVVVcFisUCn03U4rtPpYDAYOj3HYDBcV/uumjt3Lmpra22P4uLiHr0edbQhvwQAMGKAHxQyyYedEdEV3DZUhzsTQmAVgRc+PYjmVqvUJRH1Gv40AqBWq+Hr69vhQfZhbGrBl0faAuqocD9piyGia3r5zmEI9FLheHkdln9zSupyiHqNZAEoKCgIcrkc5eXlHY6Xl5dDr9d3eo5er7+u9iS9LwpKYW61or+PGqF+HlKXQ0TXEOClwit3DQMALP/mFI6WGSWuiKh3SBaAVCoVkpKSkJ2dbTtmtVqRnZ2NlJSUTs9JSUnp0B4Atm3bdsX2JC1RFG3rioyJDIAgCBJXRERdMTk+GLcP1aHVKuKFTw+i1cKuMHI9knaBZWZm4t1338WHH36Io0eP4qmnnoLJZML06dMBAFOnTsXcuXNt7WfPno2tW7di8eLFOHbsGF5++WXk5uZi5syZtjbV1dUoKCjADz/8AAA4fvw4CgoKejxOiK7f/uIaHC0zQq2QYSS7v4ichiAIWJQ+HL4aBQ6V1OLdnWelLonI7iQNQBkZGfjf//1fLFiwAImJiSgoKMDWrVttA52LiopQVlZmaz9+/HisWbMGK1euREJCAj799FNs3LgRw4cPt7X54osvMHLkSEyePBkA8MADD2DkyJGXTZOn3rfm0t2fX40IgaeKa/8QOZP+vhos+HVbV9hf/3sCZ7lhKrkYSdcBclTXs44Ada62oQVj//xfmFut2PD78ThWxtVliRzNT9cB6owoipj6/l7sPFmFlIGBWPNEMruyyaE5xTpA5No+zT8Pc6sVcXofjAzzk7ocIuoGQRDwWno8NEoZcs5cwGeXlrQgcgUMQGR3FquID75vGzPwSEoEf2MkcmLhgZ54JnUwAGDR5h9wod58jTOInAMDENndl0cMOH+xEf6eStwzcoDU5RBRD82YEIUhwb6oaWjBos1HpS6HyC4YgMju3t15BgDw8LgIeKjkEldDRD2llMuQdU88BAH4fH8Jdp6slLokoh5jACK7yiu8iP1FNVDJZXgkJULqcojIThLD/DAtJRIA8D+fH0ZjM3eMJ+fGAER29e63bXd/7koMQX8fjcTVEJE9PZcWi2CtBkXVDViafVLqcoh6hAGI7Oa4oQ5bL+379fiNAyWuhojszVutwJ/ualt37d2dZ7hNBjk1BiCym7e/bvuN8I7hesTqfSSuhoh6w21DdbhjuB4Wq4g5Gw7BYuVScuScGIDILk6U12HLobZVu/9wa4zE1RBRb3r5zmHwUStwoLgGq3POSV0OUbcwAJFdvJ19EqIITBqmx5Bgrp5N5Mp0vhq8cEccAODNL4+juLpB4oqIrh8DEPXYD6VGbObdHyK38tDYcCRHBaCh2YLnPz0AK7vCyMkwAFGPiKKIP285ClEEJo8IxtAQ3v0hcgcymYA3f5MAD6Ucu89U4x97CqUuiei6MABRj2w/UYnvTlVBJZdhzqQ4qcshoj4UHuiJOZe6wrK2HMOZynqJKyLqOgYg6rZWixV/vrQs/qM3RCIswFPiioiorz0yLgIpAwPR2GLBM+sK0GKxSl0SUZcwAFG3fbynCCcr6uHnqcTTN0VLXQ4RSUAmE7D4/gRoPZQ4eL4WS/57QuqSiLqEAYi6xVDbhDe/PA4AePb2WGg9lRJXRERSCfHzwJ/vjgcA/G37aew6VSVxRUTXxgBE3bLwi8OoN7diZLgfHhobLnU5RCSxySOCcf/oARBF4A9r98NQ2yR1SURXxQBE1+2rIwZ8eaQcCpmArHviIZMJUpdERA7glTuHI07vg6r6Zsxck8/xQOTQGIDoulTWmTHv80MA2vb7itNz2jsRtfFQyfHOw0nwUSuQW3gRizb9IHVJRFfEAERdJooiXvj0AKrqmxGn98EzqVz0kIg6igrywv/enwAA+DCnEKu+PytxRUSdYwCiLludU4hvjldCpZBh6QMjoVHKpS6JiBxQ2jA9Xry0LtifNv2Ar4+VS1wR0eUYgKhL8gqrsWhz2+3seXfEcbd3Irqq300ciIzRYbCKwO8/zseeMxekLomoAwYguqay2kY8+VE+WiwiJg3TY9r4SKlLIiIHJwgCFt09HDfH9kNTixWPrdqH/KKLUpdFZMMARFfV0NyKJz/KQ1W9GXF6Hyy+PwGCwFlfRHRtSrkM7zychPGDAmFqtmDae3uxm3eCyEEwANEVmVstePKjPBw8Xwt/TyXenToaXmqF1GURkRPRKOX4+7TRGBsVgDpzK6a+vxf/OVQmdVlEDEDUuVaLFc+sLcDOk1XwVMnx3qNjuNcXEXWLp0qB1Y+NRdowHZpbrfj9mny8nX0SVqsodWnkxvjrPF2mqcWCZ9YWYOsRA1RyGVY+Mhqjwv2lLouInJhGKcffHkrCy18cwUe7C/HWthPILbyIt+5PQJC3WrK61uwpkuy92z2YzNX0pcA7QNRBvbkVj63aZws/yx4ciQkxQVKXRUQuQC4T8Gr6cPzvfQnQKGX49kQlbl28A2v3FvFuEPU53gEim7NVJjz5US5OlNfDSyXHu1NHY3w0ww8R2ddvkgYgPlSLP64rwA9lRszZcAif7C3CM6mDcVNsP0kmWoiiiMYWC4yNrag3t6KuqQX15lY0NFtgbrWipdWKZosVza1WiBAhQIAgAALaZrxplHJ4KGXQKOXQKOXwUiug9VBC66GEr4cCChnvNzgaBiAC0La/17P/PIA6cyv6+ajx3rTRGDHAT+qyiMhFxep98MXMG7Bq1zm8te0EDpyvxfRV+zAsxBcZY8JwZ0II/DxVdn1Pq1VEmbEJhRdMKLrQgMLqBuw8WYVqkxnVpmY0tfTe3mU+agUCvdXo53Pp4a2GzlcNrYey196Trk4QRZH3HX/GaDRCq9WitrYWvr6uvddVbWML/vTvH/BZ/nkAwOgIf/ztoVHo76ux6/s4Qj87EXXkKGNPKuvMeHfnGXyUU4jGFgsAQCkXMDLcHxOigzBigBaxeh/ofTVXvTtktYq4YGpGSU0jSmsaUXKxESU1jSi8YEJhdQPOVzei+RobtHqq5PBWK+CtUcBbrYCXWgG1Qga1XAalQgaVXAaZTIAott01EkXAIoowt1jQ1GpFY4sFTS0W1DW1wtjYgtrGFrRepXvPUyVHUoQ/hodqMTxEi+GhvggP8ORyI910PT+/GYA64Q4ByGoVsWF/Cf6y9Rgq6swQBOCJGwfiudtjoVLY/1YtAxCR43GUANSu2tSMfxWU4NO88zhSarzseZVchkBvFbQeSqgUMsgEASZzW5dVfVMr6ptbca2faEq5gAH+nggP8EREoCeq6psR6KVCgJcK/p4qu3//E0URpmYLahqaUVVvRmXdpcelP3eWjXw0CowYoEVimB8Sw/yRGOaHfj7SDRR3Jtfz85tdYG7GahXx9bEKLMk+gcMlbd9gBgZ54c37RiApIkDi6ojInXT2i5FaIcdDyRG4UG/Gqcp6nKk0odzYhKp6M5otVpTVNqGstumKrymgLUD4earg56mEn0dbuAnwUiHQSwWtpxKyPry7IghC2x0ltQID/DsuJdJqscJgbMIAf08cKqnFkdJaHCurQ11TK74/dQHfn/px0chQP49LgcgPieF+GB6ihYeK+zH2BAOQmzCZW/HvA6X44PtzOF5eB6CtT3rmLdGYNj6SG5sSkUMJ9FYj0FuN5KhAAECr1dp2l8fcisZmCyyiCKsVUCtlUCtk0CjkUCtl8FDJnWbAsUIuwwB/zw534ppbrThRXocD52tQUFSDguIanKqsR0lNW3fe5kuLSMplAuL0Pki4FIpGhvlhUD9vyGTsOusqBiAX1tRiwXcnq/CfwwZsPVwGU3Nb37qXSo6Hx0XgiV8MlHT9DSKirlLIZJfu6th3YLSjUSlkbeOBQrV4KDkCAFDX1IJD52uxv7gtEBUU16CyzowjpUYcKTXa7qT5qBUYEaZFwgA/DA3xRazOB5FBXlDKnSMQ9jWHCEDLly/Hm2++CYPBgISEBPzf//0fxo4de8X269evx/z583Hu3DnExMTgjTfewC9/+Uvb86IoYuHChXj33XdRU1ODG264Ae+88w5iYmL64uNIpqahGT+UGnHgfC12na7CvnPVHWY1RAV5IWNMGKaMCYfWkzMPiIicgY9GifHRQbZlSURRRFltky0MFRTV4FBJLerMl3edKeUCooK8EKPzQazOBzH9vREe6IkBfp7w9VC49WBryQPQunXrkJmZiRUrViA5ORlLlixBWloajh8/jv79+1/WfteuXZgyZQqysrLwq1/9CmvWrEF6ejry8/MxfPhwAMBf/vIXvP322/jwww8RFRWF+fPnIy0tDT/88AM0GvvObupLoiii3tyK0pqmthkOlx4ny+txtMyIkprGy84J1mqQNkyPX8YHY0ykv1v/ZScicgWCICDEzwMhfh74ZXwwgLbxRCfK61FQXIMDxTU4Xl6Hk+V1MDVbcKK8HifK67EZHfdg81ErEOrvgQH+Hhjg74kQPw0CvNQI8FIiwEuNQC8V/L1U8FLJXfJnh+SzwJKTkzFmzBgsW7YMAGC1WhEWFoZZs2Zhzpw5l7XPyMiAyWTCpk2bbMfGjRuHxMRErFixAqIoIiQkBM8++yyee+45AEBtbS10Oh1WrVqFBx544Jo19dYssCOltThQXIsWixUtlrZFtVpaxY5fX1poq97cCmNjK4xNLTA2tsB4aUrl1aZTAkB4gCeGBvtibFQAxkcHIlbn4xB/cTkLjMjxSD0LjN8X2vTW/wdRFG2/JJ8or8OJ8vq28UQXG1BV39zl11EpZNB6KOGlksNTpYCX+sf/eigVUCvblgdQyAQoFTIoZQIUchmUchmUcgFKuQxymQCZIEAuawtwckFArN4Hw0O1dv3MTjMLrLm5GXl5eZg7d67tmEwmQ2pqKnJycjo9JycnB5mZmR2OpaWlYePGjQCAs2fPwmAwIDU11fa8VqtFcnIycnJyOg1AZrMZZrPZ9nVtbS2AtgtpT//JP4O3s0/1+HW0HgrotR4I1moQotUgPNATcXpfDNb7wFfTsWurrq6ux+9nDw0mx6iDiH5k7+9x14vfF9r05v8HXzmQFKJBUogGQD/b8cZmC0prG37So9CE8tpGVDe0oKahGRdNzahuaEFzqxVNZqDJZP/aHp8QhfDbBtv1NduvZVfu7UgagKqqqmCxWKDT6Toc1+l0OHbsWKfnGAyGTtsbDAbb8+3HrtTm57KysvDKK69cdjwsLKxrH6SPFQM4LHURROT0npC6AALgvv8fFi4BFvbSa9fV1UGrvfrdJcnHADmCuXPndrirZLVaUV1djcDAQIfoPuoNRqMRYWFhKC4udtnFHh0Fr3Xf4bXuO7zWfYfXuutEUURdXR1CQkKu2VbSABQUFAS5XI7y8vIOx8vLy6HX6zs9R6/XX7V9+3/Ly8sRHBzcoU1iYmKnr6lWq6FWd5wO7ufndz0fxWn5+vryH1Qf4bXuO7zWfYfXuu/wWnfNte78tJN0cQCVSoWkpCRkZ2fbjlmtVmRnZyMlJaXTc1JSUjq0B4Bt27bZ2kdFRUGv13doYzQasWfPniu+JhEREbkXybvAMjMzMW3aNIwePRpjx47FkiVLYDKZMH36dADA1KlTERoaiqysLADA7NmzMXHiRCxevBiTJ0/G2rVrkZubi5UrVwJoG13+zDPPYNGiRYiJibFNgw8JCUF6erpUH5OIiIgciOQBKCMjA5WVlViwYAEMBgMSExOxdetW2yDmoqIiyH6yrPn48eOxZs0avPTSS5g3bx5iYmKwceNG2xpAAPDCCy/AZDLht7/9LWpqajBhwgRs3brVqdcAsje1Wo2FCxde1vVH9sdr3Xd4rfsOr3Xf4bXuHZKvA0RERETU17hBCBEREbkdBiAiIiJyOwxARERE5HYYgIiIiMjtMAC5uG+//Ra//vWvERISAkEQbHumtRNFEQsWLEBwcDA8PDyQmpqKkydPSlOsE8vKysKYMWPg4+OD/v37Iz09HcePH+/QpqmpCU8//TQCAwPh7e2Ne++997JFPena3nnnHYwYMcK2KFxKSgr+85//2J7nde49r7/+um2pkXa83vbx8ssvQxCEDo+4uDjb87zO9scA5OJMJhMSEhKwfPnyTp//y1/+grfffhsrVqzAnj174OXlhbS0NDQ1NfVxpc5tx44dePrpp7F7925s27YNLS0tuP3222Ey/biD4B//+Ef8+9//xvr167Fjxw6UlpbinnvukbBq5zRgwAC8/vrryMvLQ25uLm655RbcddddOHLkCABe596yb98+/L//9/8wYsSIDsd5ve1n2LBhKCsrsz2+++4723O8zr1AJLcBQPz8889tX1utVlGv14tvvvmm7VhNTY2oVqvFTz75RIIKXUdFRYUIQNyxY4coim3XValUiuvXr7e1OXr0qAhAzMnJkapMl+Hv7y/+/e9/53XuJXV1dWJMTIy4bds2ceLEieLs2bNFUeTfa3tauHChmJCQ0OlzvM69g3eA3NjZs2dhMBiQmppqO6bVapGcnIycnBwJK3N+tbW1AICAgAAAQF5eHlpaWjpc67i4OISHh/Na94DFYsHatWthMpmQkpLC69xLnn76aUyePLnDdQX499reTp48iZCQEAwcOBAPPfQQioqKAPA69xbJV4Im6RgMBgCwrbrdTqfT2Z6j62e1WvHMM8/ghhtusK1QbjAYoFKpLttkl9e6ew4dOoSUlBQ0NTXB29sbn3/+OYYOHYqCggJeZztbu3Yt8vPzsW/fvsue499r+0lOTsaqVasQGxuLsrIyvPLKK7jxxhtx+PBhXudewgBEZGdPP/00Dh8+3KH/nuwrNjYWBQUFqK2txaeffopp06Zhx44dUpflcoqLizF79mxs27aNWwn1sjvuuMP25xEjRiA5ORkRERH45z//CQ8PDwkrc13sAnNjer0eAC6bSVBeXm57jq7PzJkzsWnTJnzzzTcYMGCA7bher0dzczNqamo6tOe17h6VSoXo6GgkJSUhKysLCQkJWLp0Ka+zneXl5aGiogKjRo2CQqGAQqHAjh078Pbbb0OhUECn0/F69xI/Pz8MHjwYp06d4t/rXsIA5MaioqKg1+uRnZ1tO2Y0GrFnzx6kpKRIWJnzEUURM2fOxOeff46vv/4aUVFRHZ5PSkqCUqnscK2PHz+OoqIiXms7sFqtMJvNvM52duutt+LQoUMoKCiwPUaPHo2HHnrI9mde795RX1+P06dPIzg4mH+vewm7wFxcfX09Tp06Zfv67NmzKCgoQEBAAMLDw/HMM89g0aJFiImJQVRUFObPn4+QkBCkp6dLV7QTevrpp7FmzRr861//go+Pj61fXqvVwsPDA1qtFjNmzEBmZiYCAgLg6+uLWbNmISUlBePGjZO4eucyd+5c3HHHHQgPD0ddXR3WrFmD7du348svv+R1tjMfHx/bOLZ2Xl5eCAwMtB3n9baP5557Dr/+9a8RERGB0tJSLFy4EHK5HFOmTOHf694i9TQ06l3ffPONCOCyx7Rp00RRbJsKP3/+fFGn04lqtVq89dZbxePHj0tbtBPq7BoDED/44ANbm8bGRvH3v/+96O/vL3p6eop33323WFZWJl3RTuqxxx4TIyIiRJVKJfbr10+89dZbxa+++sr2PK9z7/rpNHhR5PW2l4yMDDE4OFhUqVRiaGiomJGRIZ46dcr2PK+z/QmiKIoSZS8iIiIiSXAMEBEREbkdBiAiIiJyOwxARERE5HYYgIiIiMjtMAARERGR22EAIiIiIrfDAERERERuhwGIiIiI3A4DEBE5pHPnzkEQBBQUFEhdChG5IAYgInJIYWFhKCsrs+05tX37dgiCcNmO2ERE3cHNUInIIcnlcuj1eqnLICIXxTtARCQpq9WKv/zlL4iOjoZarUZ4eDhee+21Dl1g586dw8033wwA8Pf3hyAIePTRR7F69WoEBgbCbDZ3eM309HQ88sgjV3zPyMhILFq0CFOnToW3tzciIiLwxRdfoLKyEnfddRe8vb0xYsQI5Obm2s5ZtWoV/Pz8sHHjRsTExECj0SAtLQ3FxcUdXnvRokXo378/fHx88Pjjj2POnDlITEy03wUjIrtgACIiSc2dOxevv/465s+fjx9++AFr1qyBTqfr0CYsLAyfffYZAOD48eMoKyvD0qVLcd9998FiseCLL76wta2oqMDmzZvx2GOPXfV9//rXv+KGG27A/v37MXnyZDzyyCOYOnUqHn74YeTn52PQoEGYOnUqfrpfdENDA1577TWsXr0a33//PWpqavDAAw/Ynv/444/x2muv4Y033kBeXh7Cw8Pxzjvv2OMyEZG9SbwbPRG5MaPRKKrVavHdd9+97LmzZ8+KAMT9+/eLoiiK33zzjQhAvHjxYod2Tz31lHjHHXfYvl68eLE4cOBA0Wq1XvF9IyIixIcfftj2dVlZmQhAnD9/vu1YTk6OCEAsKysTRVEUP/jgAxGAuHv3blubo0ePigDEPXv2iKIoisnJyeLTTz/d4b1uuOEGMSEh4eoXgoj6HO8AEZFkjh49CrPZjFtvvbXbr/HEE0/gq6++QklJCYC2rqpHH30UgiDg448/hre3t+2xc+dO23kjRoyw/bn9jlN8fPxlxyoqKmzHFAoFxowZY/s6Li4Ofn5+OHr0KIC2u1Njx47tUN/PvyYix8BB0EQkGQ8Pjx6/xsiRI5GQkIDVq1fj9ttvx5EjR7B582YAwJ133onk5GRb29DQUNuflUql7c+CIFzxmNVq7XGNROR4eAeIiCQTExMDDw8PZGdnX7OtSqUCAFgslsuee/zxx7Fq1Sp88MEHSE1NRVhYGADAx8cH0dHRtkdPA1dra2uHgdHHjx9HTU0NhgwZAgCIjY3Fvn37Opzz86+JyDEwABGRZDQaDV588UW88MILWL16NU6fPo3du3fjvffeu6xtREQEBEHApk2bUFlZifr6ettzDz74IM6fP4933333moOfe0KpVGLWrFnYs2cP8vLy8Oijj2LcuHG2bq5Zs2bhvffew4cffoiTJ09i0aJFOHjwoO1uEhE5DgYgIpLU/Pnz8eyzz2LBggUYMmQIMjIyOoy7aRcaGopXXnkFc+bMgU6nw8yZM23PabVa3HvvvfD29kZ6enqv1erp6YkXX3wRDz74IG644QZ4e3tj3bp1tucfeughzJ07F8899xxGjRqFs2fP4tFHH4VGo+m1moioewRR/MkcTyIiJ3Xrrbdi2LBhePvtt3vl9VetWoVnnnnmuleivu2226DX6/HRRx/1Sl1E1D0cBE1ETu3ixYvYvn07tm/fjr/97W+S1tLQ0IAVK1YgLS0Ncrkcn3zyCf773/9i27ZtktZFRJdjACIipzZy5EhcvHgRb7zxBmJjYyWtRRAEbNmyBa+99hqampoQGxuLzz77DKmpqZLWRUSXYxcYERERuR0OgiYiIiK3wwBEREREbocBiIiIiNwOAxARERG5HQYgIiIicjsMQEREROR2GICIiIjI7TAAERERkdv5//mDzjnl5j1HAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "highway-mpg\n",
            "0.5360379305163596\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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3ddsDwJUrV3D16lWEhob2TOFEdnSqRI9XPzsDAHgqJRa/mxbr1JOZb5ZUIsGofi37gx0tqBa5GiJyFaL3Jaenp+Ptt9/Gpk2bcObMGTz22GMwGo22u8LmzZvXbpL0woULsWvXLqxYsQJnz57FSy+9hKNHj+KJJ54AANTV1eHZZ5/FoUOHcPnyZWRkZGDWrFmIiYlBamqqKOdI1FmGhiZ8lF0MAFgwIQoLp8WKXJFjGBnpBwla9jG7Wsf9wYjo5ok+B2jOnDmoqKjA0qVLodPpkJiYiF27dtkmOhcWFkL6g00ax48fj82bN+OFF17Ac889h9jYWOzYscO2BpBMJsPx48exadMm1NTUICwsDNOnT8fLL7/MeT7k0KyCgA+zrqChyYL4cDWW3DrYrXt+fsjXU4HYEG+cK6tDVkE1pg/t3BIXRETXIxEEgUus/ojBYIBGo4Fer4darRa7HHIwmw8X2uV9D126io+PlcBDJsHnC3+GmGBvu3xOG3udh72cKNbjgyOFUKvkeDY1DrLWhR3vT4rslc/vjevVW+dC5Kq68v0t+hAYEbXs1P7VmZbJ/alDtXYPP85osNYHngoZDI3NOF9eK3Y5ROTkGICIHMA35ytQb7Yg0FuBpOiOF+x0d3KZFCMifAEARy9zMjQR3RwGICKRGRqbcOBCJQBg+hCtbWiHrjUqyh8AcFZnQG1jk8jVEJEzYwAiEtmes+VosgiI8OuDoWGcc3YjWrUKff36wCoAuUU1YpdDRE6MAYhIREZTM7Jb17ZJHarlXV+dMLpfSy/Q0YJq8B4OIuouBiAiEX13uQrNVgHhvn0QHegldjlOYXhfDTxkElTUmlBUVS92OUTkpBiAiERisQo4dOkqACB5QAB7fzpJ5SFDfJgGAFeGJqLuYwAiEsmpEj0Mjc3wUsoxPFwjdjlOZVRUy9YYJ4r1qDc3i1wNETkjBiAikRy82NL7kxTtD7mMfxW7IjrAC/5eCpiardh1Uid2OUTkhPhTl0gEZYZGFFbVQyoBxkb7i12O05FIJBgZ2dIL9O+jRSJXQ0TOiAGISATHWm/hHhjiA7XKQ9xinNTISF9IABy6VIXCq5wMTURdwwBE1MsEQcCxKzUAgITWlY2p63w9FRjQumXIh1nsBSKirmEAIuplhVX1qK5vgkIuxWAtFz68GaP6tQyD/Se7GFYr1wQios5jACLqZW0rGA8NVUMh51/BmzEkVA21So7imgbbpHIios7gT1+iXmSxCjhRrAcAJHL466Z5yKSYlRgOgJOhiahrGICIetGF8jrUmy3wVsrRP8hb7HJcwj2j+wIAdp3SQV/PDVKJqHMYgIh60ZlSAwBgaJiau773kGHhGgwK8YG52YqPj5eIXQ4ROQkGIKJeIggCzupaAtDgUE5+7ikSicTWC/Qhh8GIqJMYgIh6SUlNIwyNzVDIpejPjU971F0jwiGXSnDsih55ulqxyyEiJyAXuwAid3GmtfcnNtj7J7e+2Hy4sDdKchkB3kpMGxyML06VYdvRIrxw+xCxSyIiB8ceIKJe0jb/h2v/2Mc9oyIAANtzitFksYpcDRE5OgYgol5QU29Gqb4REgADtT5il+OSpgwKQqC3EleNZuw5Wy52OUTk4BiAiHrB2dZ5KZH+nvBWcuTZHuQyKX4+smVNoG1Hr4hcDRE5OgYgol5wrqwlAMWx98eu2u4G25tXjvLaRpGrISJHxgBEZGcWq4D8SiMAICaEAcieYoJ9MKqfHyxWAf/+jrfEE9H1MQAR2dmV6nqYmq3o4yFDqEYldjku74GkSADAB0eKYOEGqUR0HQxARHZ2oaIOADAg2BtSCVd/trfbhoXC19MDxTUN2JfHydBE1DEGICI7u1jeEoBiuPdXr1B5yHDPqJa5QO9zPSUiug4GICI7MjVbUFhVDwCICWYA6i1zx7YMg+3NK0dR6/UnIvohBiAiO7pcaYRVAPw8PeDvpRC7HLfRP8gbE2ICIAjAe4cLxC6HiBwQAxCRHV1oG/5i70+ve3B8NABgy5Ei1JubRa6GiBwNAxCRHV2saLn9fQDn//S6W+KCEenvCX1DEz7KLha7HCJyMAxARHbSYLagzNCyGF80d3/vdTKpBA+OjwIAbPg2H1beEk9EP8AARGQnBVeNEAAEeivgo/IQuxy3dM/ovvBWynGxwohvLlSKXQ4RORAGICI7uXy1ZfgrKoC9P2LxUXnYtsf4xzeXRK6GiBwJAxCRnVy+2nL7NQOQuH41IRoyqQTfnK/EiSt6scshIgfBAERkB+ZmK65UtwYgzv8RVYS/J+4YHgoAWLf/osjVEJGjYAAisoOi6npYBUCtksPPk/N/xPbYlBgAwGcnS3GpdWsSInJvDEBEdmCb/xPoBQn3/xLdIK0PUgYHQxCA/9vPuUBExABEZBcFlZz/42gemzIAAPCf7CvcHoOIGICIeprFKtj2/2IAchyj+vljUmwgmq0CVmWcF7scIhIZAxBRD9MZGmG2WKHykCJYrRS7HPqBp6cPAgB8lH0FFzkXiMitMQAR9bC23p8IP09IOf/HoSRG+CJlcAisAvC33efELoeIROQQAWjNmjWIioqCSqVCUlISjhw5csP227ZtQ1xcHFQqFYYNG4bPPvvsum0fffRRSCQSrFy5soerJupY2/ySCH9PkSuhjqT/z0AAwM7jpThZzHWBiNyV6AFo69atSE9Px7Jly5CdnY2EhASkpqaivLy8w/YHDx7E3Llz8dBDDyEnJwdpaWlIS0vDyZMnr2m7fft2HDp0CGFhYfY+DSKbtgAUyQDkkIaEqTErseVnwss7T0MQuEcYkTsSPQC9+eab+PWvf40FCxZgyJAhWLduHTw9PfHOO+902H7VqlWYMWMGnn32WQwePBgvv/wyRo4cidWrV7drV1xcjCeffBLvv/8+PDxuvA6LyWSCwWBo9yDqDqOpGVeNZgAtQ2DkmP4wIw5KuRSH86vwxakyscshIhGIGoDMZjOysrKQkpJiOyaVSpGSkoLMzMwOX5OZmdmuPQCkpqa2a2+1WvHLX/4Szz77LIYOHfqTdSxfvhwajcb2iIiI6OYZkbsral39OchbiT4KmcjV0PWE+/bBryf1BwAs//wMTM0WkSsiot4magCqrKyExWJBSEhIu+MhISHQ6XQdvkan0/1k+9dffx1yuRy/+93vOlXHkiVLoNfrbY+ioqIunglRC87/cR6PTRmAIB8lCq7W450Dl8Uuh4h6mehDYD0tKysLq1atwsaNGzu9Aq9SqYRarW73IOoO2x1g/n1EroR+ipdSjsUz4gAAqzLOcXFEIjcjagAKDAyETCZDWVn7MfiysjJotdoOX6PVam/Y/ptvvkF5eTkiIyMhl8shl8tRUFCAp59+GlFRUXY5DyIAsAoCrlQ3AOAEaGcxe2Q4xvX3R2OTFUv/e5IToonciKgBSKFQYNSoUcjIyLAds1qtyMjIQHJycoevSU5ObtceAHbv3m1r/8tf/hLHjx9Hbm6u7REWFoZnn30WX3zxhf1Ohtxeea0JpmYrFDIpgn1UYpdDnSCRSPBK2jB4yCTYm1eBz050PPRORK5HLnYB6enpmD9/PkaPHo2xY8di5cqVMBqNWLBgAQBg3rx5CA8Px/LlywEACxcuxOTJk7FixQrMnDkTW7ZswdGjR7F+/XoAQEBAAAICAtp9hoeHB7RaLQYNGtS7J0dupW0IJdyvD2RSLoDoLGKCvfHY5AF4a88FLPv4JMb190eAN1fwJnJ1os8BmjNnDv76179i6dKlSExMRG5uLnbt2mWb6FxYWIjS0lJb+/Hjx2Pz5s1Yv349EhIS8OGHH2LHjh2Ij48X6xSIAADFrcNfEX6c/+NsHr8lBoNCfFBZZ8Zz209wKIzIDUgE/k2/hsFggEajgV6v54Rousbmw4UdHl+99zxKahoxd2wkhoVrerkq93V/UmSPvM/JYj3S1nyLZquAN+9NwOyRfds9f73/7z2pp86FyF115ftb9B4gIlfQZLFCp28EAPT1ZQ+QM4oP1+CplFgAwLKPT6GkpkHkiojInroVgC5dutTTdRA5NZ2+EVYB8FTI4Ot545XHyXE9OnkAEiN8UdvYjD98eBxWKzvIiVxVtwJQTEwMpk6divfeew+NjY09XROR07nS2lvQ169Pp9efIscjl0mx4t4EqDykOHChEu8dLhC7JCKyk24FoOzsbAwfPhzp6enQarV45JFHfnIHdyJXVty6BUa4L9f/cXYDgrxtCyT++bMzuFRRJ3JFRGQP3QpAiYmJWLVqFUpKSvDOO++gtLQUEydORHx8PN58801UVFT0dJ1EDq1tAcS+vAPMJcxLjsKEmAA0Nlnx+38fQ5PFKnZJRNTDbmoStFwux+zZs7Ft2za8/vrruHDhAp555hlERERg3rx57W5fJ3JVpmYLKmpNAFrWACLnJ5VK8Nd7EqBWyXGsqAZr9l4QuyQi6mE3FYCOHj2K3/72twgNDcWbb76JZ555BhcvXsTu3btRUlKCWbNm9VSdRA6rpKYRAgC1Sg61ihOgXUWopg9eTmtZX+x/91zgXmFELqZbAejNN9/EsGHDMH78eJSUlODdd99FQUEBXnnlFURHR2PSpEnYuHEjsrOze7peIofTNv+nrx/n/7iaWYnhuDMhDBargH8fLYK5mUNhRK6iWwFo7dq1uP/++1FQUIAdO3bg9ttvh1Ta/q2Cg4Pxz3/+s0eKJHJkbXeAcfjLNb08Kx6hGhWuGs347CSH9YlcRbcC0O7du7Fo0SKEhoa2Oy4IAgoLW1ZLVSgUmD9//s1XSOTgSmpaloII5wKILknj6YG/3pMAADiSX4WzOoPIFRFRT+hWABowYAAqKyuvOV5VVYXo6OibLorIWZiaLbha1zIBOlTDHeBd1YSYQEwY0LLJ8vacYjSYLSJXREQ3q1sB6Hrbh9XV1UGl4pcAuQ+d/vsJ0D6cAO3Spg/VItBbgdrGZuw6pRO7HCK6SfKuNE5PTwcASCQSLF26FJ6e30/6tFgsOHz4MBITE3u0QCJHVtw6/yeMw18uz0MmxV0j+uLtby7hu8tVSIjQoH+gt9hlEVE3dSkA5eTkAGjpATpx4gQUCoXtOYVCgYSEBDzzzDM9WyGRA2ub/8MA5B6iA70wNsofRy5XYXt2MRZOi4Vcxj2liZxRlwLQ3r17AQALFizAqlWrfnKreSJX17ZjeJiGAchdzIjX4ozOgKtGM769UInJg4LFLomIuqFb/3TZsGEDww+5vSaLFeW1bT1AnPvmLlQeMswYqgUA7M2rgKGhSeSKiKg7Ot0DNHv2bGzcuBFqtRqzZ8++YduPPvropgsjcnRlhkZYBcBTIYOmDydAu5OECF8czq9CYVU9dp3S4d7REWKXRERd1OkApNFoIJFIbL8mcnc/nP/T9neD3INUIsHtw0Oxdt9F5BbVYFz/AET6cyVwImfS6QC0YcOGDn9N5K44/8e99fXzxMhIP2QVVuOLUzo8PDGaQZjIiXRrDlBDQwPq67/fGLCgoAArV67El19+2WOFETm6En3bLfCc/+Oupg0OhkwqQX6lERcrjGKXQ0Rd0K0ANGvWLLz77rsAgJqaGowdOxYrVqzArFmzsHbt2h4tkMgRWawCdHreAu/ufD0VSIr2BwB8eVp33UViicjxdCsAZWdnY9KkSQCADz/8EFqtFgUFBXj33Xfx1ltv9WiBRI6ootaEZqsApVwKfy/FT7+AXNbkgUFQyKS4Ut2A06XcJ4zIWXQrANXX18PHxwcA8OWXX2L27NmQSqUYN24cCgoKerRAIkfUNv8nVNMHUs77cGs+Kg+Mj2nZJ2xvXjl7gYicRLcCUExMDHbs2IGioiJ88cUXmD59OgCgvLyc6wORW2ib/xPO+T8EYMKAQHjIJCipaeRcICIn0a0AtHTpUjzzzDOIiopCUlISkpOTAbT0Bo0YMaJHCyRyRLYeIM7/IQBeSjlGR7XMBdp/rlzkaoioM7q0FUabu+++GxMnTkRpaSkSEhJsx6dNm4a77rqrx4ojckRWQUAJJ0DTj0yMCcThS1dxscKIK9X16OvHdYGIHFm3d/HTarUYMWIEpNLv32Ls2LGIi4vrkcKIHFVVnRnmZivkUgmCvJVil0MOws9TgYS+vgCA/ecqxC2GiH5St3qAjEYjXnvtNWRkZKC8vBxWq7Xd85cuXeqR4ogcUdv8n1CNCjIpJ0DT9yYNDEJOUQ1OlxhQU2+GryfvECRyVN0KQA8//DD279+PX/7ylwgNDeXqp+RWOP+HrkerVqF/oBcuVRpxJL8K01s3TSUix9OtAPT555/j008/xYQJE3q6HiKH17YHWDi3wKAOjOsfgEuVRnx3uQq3xAVDLuv2TAMisqNu/c308/ODv79/T9dC5PAEQUBx2x5g7AGiDgwOVUPTxwNGswUnivVil0NE19GtAPTyyy9j6dKl7fYDI3IHxTUNaGiyQCoBQtScAE3XkkklGNN6S/yhS1dFroaIrqdbQ2ArVqzAxYsXERISgqioKHh4eLR7Pjs7u0eKI3I0p0patjoIUas4tEHXNSbKD3vPlqOougGl+gaEcriUyOF0KwClpaX1cBlEzqEtAPELjW7ER+WBwaE+OFliQFZBNW4fzj8vRI6mWwFo2bJlPV0HkVM4XdIypyOMW2DQTxjVzw8nSwzILarBjHgt5FL2GBI5km7/jaypqcE//vEPLFmyBFVVVQBahr6Ki4t7rDgiR3OymD1A1DkxwT5Qq+SoN1twtrRW7HKI6Ee6FYCOHz+OgQMH4vXXX8df//pX1NTUAAA++ugjLFmypCfrI3IYV+tM0Blat8DQsAeIbkwmlWBEpB8AIKugWuRqiOjHuhWA0tPT8eCDD+L8+fNQqb7/Irjtttvw9ddf91hxRI6kbf5PgJcCSg+ZyNWQMxjVGoDOldXC0NAkcjVE9EPdCkDfffcdHnnkkWuOh4eHQ6fT3XRRRI6oLQBx/R/qrEAfJfr5e0IAkFtUI3Y5RPQD3QpASqUSBoPhmuPnzp1DUFDQTRdF5IhOtU2A5vAXdUFipC8A4PiVGlHrIKL2uhWA7rzzTvzpT39CU1NLl65EIkFhYSEWLVqEn//85z1aIJGjsN0Czx4g6oL4MA2kEqBE34jy2kaxyyGiVt0KQCtWrEBdXR2CgoLQ0NCAyZMnIyYmBj4+Pnj11Vd7ukYi0dWZmpFfaQTAITDqGi+lHLHBPgCA41e4NQaRo+jWOkAajQa7d+/Gt99+i2PHjqGurg4jR45ESkpKT9dH5BDOlLb0/mjVKngru/XXhtxYQoQGeWW1OFZUg2lxwZBIJGKXROT2utwDZLVa8c477+D222/HI488grVr1+LAgQMoKSmBIAjdKmLNmjWIioqCSqVCUlISjhw5csP227ZtQ1xcHFQqFYYNG4bPPvus3fMvvfQS4uLi4OXlBT8/P6SkpODw4cPdqo0IAE61bmo5NEwtciXkjAaHquEhk+Cq0WzbTJeIxNWlACQIAu688048/PDDKC4uxrBhwzB06FAUFBTgwQcfxF133dXlArZu3Yr09HQsW7YM2dnZSEhIQGpqKsrLyztsf/DgQcydOxcPPfQQcnJykJaWhrS0NJw8edLWZuDAgVi9ejVOnDiBAwcOICoqCtOnT0dFRUWX6yMCvp//wwBE3aGUyxCnbfmzc4x3gxE5BInQhW6bDRs2YOHChfjvf/+LqVOntntuz549SEtLw+rVqzFv3rxOF5CUlIQxY8Zg9erVAFp6mCIiIvDkk09i8eLF17SfM2cOjEYjdu7caTs2btw4JCYmYt26dR1+hsFggEajwVdffYVp06Zd87zJZILJZGrXPiIiAnq9Hmo1v/AIuG3VNzhdasC6X4xCldEsdjn0A/cnRfbK52w+XHhTrz9dosd7hwuh6eOBP6QO6nAYrLfOhchVtX3fd+b7u0s9QB988AGee+65a8IPANxyyy1YvHgx3n///U6/n9lsRlZWVru5Q1KpFCkpKcjMzOzwNZmZmdfMNUpNTb1ue7PZjPXr10Oj0SAhIaHDNsuXL4dGo7E9IiIiOn0O5PpMzRacK2vZyiA+nIGYuic2xAcKmRT6hiZcqeYwGJHYuhSAjh8/jhkzZlz3+VtvvRXHjh3r9PtVVlbCYrEgJCSk3fGQkJDrLqio0+k61X7nzp3w9vaGSqXC3/72N+zevRuBgYEdvueSJUug1+ttj6Kiok6fA7m+82V1aLYK0PTxQDjvAKNu8pBJMUjbcjfYyRLeDUYkti4FoKqqqmvCxw+FhISgutox9ryZOnUqcnNzcfDgQcyYMQP33nvvdecVKZVKqNXqdg+iNm0LIA4NU/PuHbop8eEaAC1zyrp70wgR9YwuBSCLxQK5/Pq3AMtkMjQ3N3f6/QIDAyGTyVBWVtbueFlZGbRabYev0Wq1nWrv5eWFmJgYjBs3Dv/85z8hl8vxz3/+s9O1EbXhBGjqKYNCfOAhk6DKaEapnosiEompSwuaCIKABx98EEqlssPnfziRuDMUCgVGjRqFjIwMpKWlAWiZBJ2RkYEnnniiw9ckJycjIyMDTz31lO3Y7t27kZycfMPPslqtXa6PCPhhANKIXAk5O4VcioEhPjhVYsDJEj0X1SQSUZcC0Pz583+yTVfuAANadpafP38+Ro8ejbFjx2LlypUwGo1YsGCB7f3Cw8OxfPlyAMDChQsxefJkrFixAjNnzsSWLVtw9OhRrF+/HgBgNBrx6quv4s4770RoaCgqKyuxZs0aFBcX45577ulSbUQWq4DTrQGIE6CpJ8SHaVoCULEB04d03NNNRPbXpQC0YcOGHi9gzpw5qKiowNKlS6HT6ZCYmIhdu3bZ5hoVFhZCKv1+pG78+PHYvHkzXnjhBTz33HOIjY3Fjh07EB8fD6BlGO7s2bPYtGkTKisrERAQgDFjxuCbb77B0KFDe7x+cm35lUY0NFnQx0OG6EBvscshFzBI6wOZRILKOhMqak0I8um4R52I7Msh1vR/4oknrjvktW/fvmuO3XPPPdftzVGpVPjoo496sjxyY20ToONCfSCTcgI03TyVhwz9g7xwvrwOZ3UGBPkEiV0SkVvq1maoRO7iNCdAkx3Ehbb8eWrbY46Ieh8DENENcAI02cPg1vWACq7Ww2jq/J2zRNRzGICIrkMQBNsQWDwDEPUgX08FQjUqCADyWlcZJ6LexQBEdB0l+kZU1zdBLpVgoJYToKlnDeYwGJGoGICIruNUcUvvT0ywN5RymcjVkKsZ3Lo7/PmyOjRZrCJXQ+R+GICIroPzf8iewnxVUKvkMFusuFRhFLscIrfDAER0HdwCg+xJIpF8fzeYjsNgRL2NAYjoOk63TYAOZw8Q2UfbMNjZUm6OStTbGICIOlBlNKOkdbPKwaE+IldDrqp/kBcUMikMjc0oqeHmqES9iQGIqANtt79HBXjCR+UhcjXkqjxkUsSGtNxhyGEwot7lEFthEDkaToB2HpsPF4pdwk0ZrFXjVImBt8MT9TL2ABF1oC0ADeEEaLKzgVofSACU6htRXNMgdjlEboMBiKgDbUNgvAOM7M1bKUdkgCcA4KvTZSJXQ+Q+GICIfqTO1Iz8ypZ1WXgHGPWGtrvB9pwtF7kSIvfBAET0Iyeu6CEIQLhvHwR6K8Uuh9xAXOvmqJkXr3JzVKJewgBE9CPHr9QAAIb3Ze8P9Y4gHyX8vRQwW6z49kKl2OUQuQUGIKIfOX6lZf7P8L6+4hZCbkMikWBQay9QxhkOgxH1BgYgoh851toDlMAeIOpFbcNge/LKYbVyVWgie2MAIvqBq3UmXKluuRU5ngGIelF0gBe8FDJU1JpwsvUuRCKyHwYgoh84XtzyxdM/yAtqrgBNvUguk2JSbBAADoMR9QYGIKIfOF7UEoASOP+HRDBtcDAA3g5P1BsYgIh+gHeAkZimDAqGRAKcKNajzMDNUYnsiQGIqJUgCDjGO8BIREE+Slvv4172AhHZFQMQUatSfSMq60yQSyXcAoNEMy2uZRjsK84DIrIrBiCiVm3DXwNDfKDykIlbDLmtW1rnAX17oRKNTRaRqyFyXQxARK3ahr8SIjj/h8QzJFSNUI0KDU0WZF66KnY5RC6LAYio1fcToH1FrYPcm0QiwS2tw2B7OAxGZDcMQEQArFbhB1tgsAeIxPXD2+EFgatCE9kDAxARgMtXjahtbIZSLsXAEB+xyyE3N35AIFQeUhTXNCCvrFbscohcEgMQEb7fAHVomBoeMv61IHGpPGSYMCAQAFeFJrIX/qQnApBbVAOA83/IcbTdDZZxpkzkSohcEwMQEb6fAM07wMhRtE2EzimqwdU6k8jVELkeBiBye00WK06VGACwB4gcR6imD4aGqSEIwL68CrHLIXI5DEDk9s6V1cLUbIWPUo7oAC+xyyGyaVsVmpujEvU8BiBye20ToIf11UAqlYhcDdH3bhkcAgD4+lwFzM1Wkashci0MQOT2cgtrAAAJEb6i1kH0Y8PDNQj0VqDW1Iyjl6vELofIpTAAkdvLKqwGAIyK9BO5EqL2pFIJpg5qvRuMw2BEPYoBiNyavr4JF8rrAAAj+zEAkeOZ9oPb4bkqNFHPYQAit5Zd1NL7Ex3oBX8vhcjVEF1rYmwQFDIpLl+tx6VKo9jlELkMBiBya9kFLQFoJIe/yEF5K+VI6u8PgJujEvUkBiBya1mtAWgUh7/IgbXdDp9xlqtCE/UUBiByW80WK461boHBAESO7Ja4ltvhv7tcDX1Dk8jVELkGBiByW3lltTCaLfBRyhEb7C12OUTXFRngidhgb1isAvaf46rQRD3BIQLQmjVrEBUVBZVKhaSkJBw5cuSG7bdt24a4uDioVCoMGzYMn332me25pqYmLFq0CMOGDYOXlxfCwsIwb948lJSU2Ps0yMm0zf9JjPTlAojk8Ka1Lor45SmdyJUQuQbRA9DWrVuRnp6OZcuWITs7GwkJCUhNTUV5eceT/Q4ePIi5c+fioYceQk5ODtLS0pCWloaTJ08CAOrr65GdnY0XX3wR2dnZ+Oijj5CXl4c777yzN0+LnADn/5AzmRGvBQDsPVuOxiaLyNUQOT+JIPLCEklJSRgzZgxWr14NALBarYiIiMCTTz6JxYsXX9N+zpw5MBqN2Llzp+3YuHHjkJiYiHXr1nX4Gd999x3Gjh2LgoICREZG/mRNBoMBGo0Ger0earW6m2dGjm7Ca3tQXNOAfz00FpNigzr9us2HC+1YFbmz+5Ou//NJEARMeG0PSvSNWP/LUZg+VNuLlRE5h658f4vaA2Q2m5GVlYWUlBTbMalUipSUFGRmZnb4mszMzHbtASA1NfW67QFAr9dDIpHA19e3w+dNJhMMBkO7B7m2K9X1KK5pgEwq4S3w5BQkEglmxIcCAHad5DAY0c0SNQBVVlbCYrEgJCSk3fGQkBDodB3/BdfpdF1q39jYiEWLFmHu3LnXTYPLly+HRqOxPSIiIrpxNuRMvmvdVyk+XAMvpVzkaog657ZhLb0+u8+UcXNUopsk+hwge2pqasK9994LQRCwdu3a67ZbsmQJ9Hq97VFUVNSLVZIYjuS3BKCkaH+RKyHqvJGRfgj2UaK2sRnfXqwUuxwipyZqAAoMDIRMJkNZWfvFvcrKyqDVdjy+rdVqO9W+LfwUFBRg9+7dNxwLVCqVUKvV7R7k2g63BqCxUQxA5DykUglSW+f+fH6iVORqiJybqAFIoVBg1KhRyMjIsB2zWq3IyMhAcnJyh69JTk5u1x4Adu/e3a59W/g5f/48vvrqKwQEBNjnBMgpVdSacKnCCIkEGMMARE7m1tZhsC9Pl6HJwmEwou4SffJDeno65s+fj9GjR2Ps2LFYuXIljEYjFixYAACYN28ewsPDsXz5cgDAwoULMXnyZKxYsQIzZ87Eli1bcPToUaxfvx5AS/i5++67kZ2djZ07d8JisdjmB/n7+0Oh4IaX7q5t/k+cVg2Np4fI1RB1zdgof/h7KVBlNOPwpSpMjA0UuyQipyR6AJozZw4qKiqwdOlS6HQ6JCYmYteuXbaJzoWFhZBKv++oGj9+PDZv3owXXngBzz33HGJjY7Fjxw7Ex8cDAIqLi/Hxxx8DABITE9t91t69ezFlypReOS9yXJz/Q85MLpMidWgIPjhShM9PljIAEXWT6OsAOSKuA+TaZqz8Gmd1tfj7AyNx27DQLr+e6wCRvdxoHaAf2n+uAvPfOYJAbwUOP5cCGVcyJwLgROsAEfW2mnoz8spqAXD+Dzmv8QMCoOnjgco6M462DukSUdcwAJFbybx4FYIAxAZ7I8hHKXY5RN3iIZMipXVvsM+5KCJRtzAAkVs5cKFl7ZQJMZw3Qc6tbVHEXSd1sFo5k4GoqxiAyK0cvHgVAAMQOb+JsYHwUcqhMzTa7mwkos5jACK3UVzTgPxKI6QSIKk/5/+Qc1PKZbYd4nfklohcDZHzYQAit/Ft6/BXQoQv1Cqu/0POL21EOADg0+MlMDVbRK6GyLkwAJHbaAtAEwZw+Itcw7j+AQhRK2FobMa+vAqxyyFyKgxA5BYEQcC3F1rm/4yP4dYo5BpkUgnuTAgDAPw3t1jkaoicCwMQuYVzZXWorDNB5SHFyEg/scsh6jGzEluGwb46Uw5DY5PI1RA5DwYgcgtfn2sZHhgT5Q+Vh0zkaoh6ztAwNWKCvWFutuKz49whnqizGIDILezNKwcATB0ULHIlRD1LIpHg7lF9AQDbsq6IXA2R82AAIpdX29hkWydlahwDELme2SPCIZNKkFVQjQvldWKXQ+QUGIDI5X174SqaLAKiAjwRHegldjlEPS5YrcKUgUEAgG1ZRSJXQ+QcGIDI5e1rHf6awuEvcmH3jI4AAHyUXYxmi1XkaogcHwMQuTRBEGzro3D4i1zZLXHBCPBSoKLWhP3nuCYQ0U9hACKXdlZXC52hESoPKZKiuf0FuS6FXIq7WleG/uBIocjVEDk+BiByaXvOtgx/TRgQyNvfyeXNTYoE0PLn/kp1vcjVEDk2BiByaV+eLgPA4S9yDwOCvDEhJgBWgb1ARD+FAYhcVqm+AceKaiCRANOHhIhdDlGv+EVSPwDA1u+KYG7mZGii62EAIpf15amW3p+RkX4IVqtEroaod6QMCUGIWonKOjN2ndKJXQ6Rw2IAIpf1ResP/xlDtSJXQtR7PGRS3DemZS7QvzIvi1sMkQNjACKXVG0043B+y+rPqQxA5GbuT4qEXCrBd5ercfxKjdjlEDkkBiBySV+dKYPFKmBIqBqRAZ5il0PUq0LUKtyZEAYA+Mc3+SJXQ+SYGIDIJbUNf7H3h9zVryZGAwA+PVGK4poGkashcjwMQORyaurNtpVwbx3GAETuKT5cg+T+AbBYBWw6eFnscogcDgMQuZzPTujQZBEQp/XBwBAfscshEs2vf9bSC/TB4UIYGptErobIsTAAkcv5b24xACCtdVsAInc1ZWAwYoK9UWtqxr8yC8Quh8ihMACRSympabDd/dU2CZTIXUmlEjw+dQAA4J8H8lFvbha5IiLHwQBELuXjYyUAgLHR/gjz7SNyNUTiu2N4GPoFeKLKaMbmw9weg6gNAxC5lB05rcNfiRz+IgIAuUyK305p6QX6v68vobHJInJFRI6BAYhcxqkSPc7qauEhk+A23v1FZHPXiL4I06hQUWtiLxBRKwYgchlbjhQBAKYP0cLXUyFyNUSOQyGX4vFbYgAAa/ZeQJ2Jc4GIGIDIJTSYLdjRevfXfWMjRK6GyPHcOzoCUQGeuGo0450DXB2aiAGIXMKnJ0pR29iMCP8+mDAgUOxyiByOh0yK9OmDAABvf30J1UazyBURiYsBiFzCliMt8xruGxMJqVQicjVEjun2YaEYEqpGrakZa/ZeELscIlExAJHTO19Wi6MF1ZBJJbhnVF+xyyFyWFKpBItujQMAbMq8jEsVdSJXRCQeBiByehtb9zmaFheMYLVK3GKIHNzkgUGYOigITRYBr356RuxyiETDAEROrdpoxn+yrwAAFkyIFrkaIufwwu1DIJdKkHG23LZxMJG7YQAip7b5SCEam6wYEqrGuP7+YpdD5BQGBHljXnIUAOBPn5yCudkqbkFEImAAIqdlbrbi3czLAICHJkZDIuHkZ6LOWpgSi0BvBS5WGLH+64til0PU6xiAyGl9eqIEZQYTgnyUuIMbnxJ1iaaPB168fQgA4K09F3C50ihyRUS9iwGInJLVKmDdvksAgHnj+kEh5x9loq66MyEMk2IDYW624oUdJyEIgtglEfUafmuQU/rilA55ZbXwUcptcxmIqGskEglenhUPhVyKAxcqse3oFbFLIuo1ogegNWvWICoqCiqVCklJSThy5MgN22/btg1xcXFQqVQYNmwYPvvss3bPf/TRR5g+fToCAgIgkUiQm5trx+pJDFargFUZ5wEAD06IgsbTQ+SKiJxXVKAXnv6fgQCAP+08jeKaBpErIuodogagrVu3Ij09HcuWLUN2djYSEhKQmpqK8vLyDtsfPHgQc+fOxUMPPYScnBykpaUhLS0NJ0+etLUxGo2YOHEiXn/99d46DeplX50pw1ldLbwUMvyKt74T3bSHJ/XHqH5+qDM1Y9GHx2G1ciiMXJ9EEHHQNykpCWPGjMHq1asBAFarFREREXjyySexePHia9rPmTMHRqMRO3futB0bN24cEhMTsW7dunZtL1++jOjoaOTk5CAxMbFLdRkMBmg0Guj1eqjV6q6fGNmN1SrgjtUHcKrEgN9OGYA/zIjr9Ro2Hy7s9c8k93B/UqRon51facStq75GY5MVy+4YwnW1yCl15ftbtB4gs9mMrKwspKSkfF+MVIqUlBRkZmZ2+JrMzMx27QEgNTX1uu07y2QywWAwtHuQY/r4WAlOlRjgrZTj4Un9xS6HyGVEB3phya2DAQDLPzuLUyV6kSsisi+5WB9cWVkJi8WCkJCQdsdDQkJw9uzZDl+j0+k6bK/T6W6qluXLl+OPf/zjTb0H2V9jkwVvfJEHAHhsygD4eylEroioZ/VG7+KNepnmJffDN+cr8dWZMjz5QQ4+eWIivJSifU0Q2ZXok6AdwZIlS6DX622PoqIisUuiDvwrswDFNQ3QqlWc+0NkBxKJBG/cPRxatQqXKox4kbfGkwsTLQAFBgZCJpOhrKys3fGysjJotdoOX6PVarvUvrOUSiXUanW7BzmWaqMZq/deAACkTx+IPgqZyBURuSY/LwVW3ZcImVSCj3KK8d6hArFLIrIL0QKQQqHAqFGjkJGRYTtmtVqRkZGB5OTkDl+TnJzcrj0A7N69+7rtyXX85Yuz0Dc0IU7rg5+P7Ct2OUQuLal/ABa33mDwx09OI6ugSuSKiHqeqENg6enpePvtt7Fp0yacOXMGjz32GIxGIxYsWAAAmDdvHpYsWWJrv3DhQuzatQsrVqzA2bNn8dJLL+Ho0aN44oknbG2qqqqQm5uL06dPAwDy8vKQm5t70/OESDzZhdX44EjLsOTLafGQSbnnF5G9PTwpGjOHh6LZKuDR97JRwvWByMWIGoDmzJmDv/71r1i6dCkSExORm5uLXbt22SY6FxYWorS01NZ+/Pjx2Lx5M9avX4+EhAR8+OGH2LFjB+Lj421tPv74Y4wYMQIzZ84EANx3330YMWLENbfJk3OwWAW8uKNlnae7R/XFmCju+E7UGyQSCf7y8+GI0/qgotaEhzYdhdHULHZZRD1G1HWAHBXXAXIc/zyQj5d3noZaJceeZ6Yg0FspdklcB4icWlfXGrpSXY+0NQdRWWfCtLhgrJ83mr2w5LCcYh0gop+SX2nEG1+0LImw+NbBDhF+iNxNXz9PvD1vFBRyKTLOlnPTVHIZDEDkkKxWAX/48Bgam6yYGBOIuWMjxC6JyG2NiPTDqjmJkEiAD44U4m9fnRe7JKKbxhWuqFd0ddjo2wuV+O5yNRRyKZL7B9gmQd+ImNsIELm6W4eF4uVZ8Xhhx0m8lXEeahVXYyfnxh4gcjil+gZ8carlrr1b47Xw44rPRA7hF+P64fcpLTvHv/LpGbz99SWRKyLqPgYgcijmZiu2fFeEZquAOK0PxvKuLyKH8rtpMfjdLTEAgFc/O4P/239R5IqIuocBiBzKZydKUVFrgo9Kjtkj+0Ii4d0mRI5EIpEgffogPJUSCwBY/vlZ/H3fBZGrIuo6BiByGFkF1ThyuWXF2XtGRcCbmzASOaynUgbahsP+sisP/5txnneHkVNhACKHcKW6Hv/NLQYATIsLRkywt8gVEdFPWZgSi6f/pyUErdh9Di/+9ySaLVaRqyLqHAYgEl2dqRnvHy5Es1XAYK0PpsYFi10SEXXSk9Ni8cLMwZBIgPcOFeLX73LFaHIODEAkKotVwAdHCqFvaEKgtxL3jI6AlPN+iJzKw5P6Y+0DI6GUS7E3rwL3/l8mygyNYpdFdEMMQCSqz0+WIr/SCKVcil+Mi4TKQyZ2SUTUDTPiQ/HBb8YhwEuBUyUG3LXmW5wq0YtdFtF1cS+wDnAvsJ7X0UKIWQVV+E92y7yfXyRFYkiYprfLIqIeVmU0Y+PBy6isM0EuleDOhDCMttNyFlz8lH6Me4GRwztXVovtOS3hZ+qgYIYfIhfh76XAo5P7Y1CID5qtAj7KKcZ/sq7A3MzJ0eRYGICo15XUNGDzkUJYBSAxwhcpgznpmciVeCrk+GVyP0wfEgIJgKzCaqzbfxGVdSaxSyOyYQCiXlVdb8amg5dhbrZiQJAXZo8M52KHRC5IKpFgyqBg/GpiNLyUcugMjVi99wKOXq7iekHkEBiAqNfUm5ux8eBl1JqaoVWr8EBSP8il/CNI5MoGBHnjyakxiArwgrnZio9yivGvQwWobWwSuzRyc/z2oV5hbrbiX4cKUFFrgqaPB+aPj+IdX0RuQt3HAw9PisaMoVrIpBKc1dViVcZ5nCzmXWIkHgYgsjtTswXvHy5AwdV6KOVSzE+OgqaPh9hlEVEvkkok+NnAIDw+JQahGhXqzRZsPlKID44UsjeIRMEARHbVZLHiyc05OF9eBw+ZBA+Oj4JWoxK7LCISiVajwmNTBmDKoCBIAJwo1uNvX53D4fyrsHJuEPUiBiCyG4tVwDPbjuHL02WQSyX45bgo9AvwErssIhKZXCrF9CFa/HZqDMJ9+6CxyYr/5pZg/deXoOMK0tRLGIDILgRBwAs7TuC/uSWQSyWYOzaSG5wSUTvhvn3w2JQBmDksFAq5FIVV9Vi95zw+PV6CBrNF7PLIxcnFLoBcjyAIeOnjU/jgSBGkEuBvcxJR28jNEYnoWlKJBBNiAjE0TI2dx0txutSAby9eRW5RDaYP0WJUlB/3ByS7YA8Q9SirVcDzO05iU2YBJBLgtZ8Pxx0JYWKXRUQOztdTgV+M64cHx0chyFsJo9mC7bnF+PveC7hUWSd2eeSC2ANEPcZiFbD4P8exLesKJBLgjbsTcPeovmKXRUROZGCIDwZM88ahS1fx1ZkylOgb8Y9v8jEoxAepQ7W8iYJ6DAMQ9YhmixXPfngc23OKbcNesxLDxS6LiJyQTNoyLJYQ4YuvzpTh6OUq5JXV4lxZLUZE+iFlcDB8PRVil0lOjgGIbpq52Yr0f+di5/FSyKQSvHXfCMwcHip2WUTk5LyVcqQlhmPigEB8eaYMJ4v1yC6sxrErNRjdzw+TBwUh3LeP2GWSk+IcILopdaZmPLTpO+w8XgoPmQRr7h/J8ENEPSrQR4n7x0bisckDEB3oBYtVwOH8Kkx5Yy+WfHQcRVX1YpdITkgicFe6axgMBmg0Guj1eqjVarHLcVgVtSYs2HgEJ4sN8FTI8PcHRmLKoI53dt98uLCXqyMiV3Wpsg57zpbjUoURQMuQ2R3DQ7FgQjQSInzFLY5E1ZXvbw6BUbfkVxox/50jKKyqR4CXAu88OIY/eIioV/QP9Eb/id4YGOKNt/ZcwNfnKrAjtwQ7ckswItIXD46Pwm3DQuEh4yAHXR97gDrAHqAbyymsxsObjuKq0YwI/z5491dJiA688QrP7AEiop52f1IkAODEFT02HMzHzmOlMFusAIAgHyXSEsOQNiIcQ0LVkHRzLaHe+NnVdh5089gDRHaz7WgRnt9+EmaLFUPD1NiwYAyCfXhbKhGJZ1hfDd68NxFLbh2MzYcL8d7hAlTUmvD2N/l4+5t8xAZ7I21EOG4bFoqoAM9uhyFyLQxA1ClNFite/fQMNh68DABIGRyClfclwlvJP0JE5BiCfJRYmBKLx6YMwL68cuzILcZXZ8pxvrwOb3yRhze+yEOEfx9MHhiEyQODkTwggD/D3Bj/z9NPulpnwuObs3HoUhUAYOG0WCycFguplP+KIiLHo5BLMX2oFtOHaqFvaMKuk6X4+FgJjuRXoaiqAe8dKsR7hwohk0oQG+yN+HANhoVrEB+uwSCtD0ORm+D/ZbqhQ5euIn1rLkr0jfBSyPDmnESkDtWKXRYRUado+nhgzphIzBkTCaOpGZkXr+Lr8xXYf64CBVfrcVZXi7O6WnyYdcX2Gn8vBSL8PdHP3xP6hiZ4K+XwUsrgqZDDSymHl0IGL6Wck6ydHAMQdcjUbMGbX57D+m8uQRCA6EAvrP/lKMSG+IhdGhFRt3gp5UgZEoKUISEAAJ2+ESeK9S2PKzU4WWJARa0JVUYzqoxmHCuqueH7ecgk8FTI4amQtT7kP/qvDN5KOXw9FfD19GBgcjAMQHSNM6UG/H5rLs7qagEA942JwAu3D2G3MBG5FK1GBa1Ghf9pDUQAUNvYhKKqBhRWGVFYVY89ZytgNDXDaG5Gvcli+69FENBkEaBvaIK+oalTn9cShjwQ5K1EiFqFELUSwWoVBEHgxGwR8BuNbEzNFrz99SW8lXEBZosVAV4KvPbz4e1+OBARuTIflQeGhHlgSFjLLdTeSo9r2giCAFOzFUZTM+rNltZHR79uRm1jM2oammButqLO1Iw6UzOuVDe0e791+y4iIcIXIyN9MSLSD4kRvvDz4l5n9sYARACAb85XYNl/T+FSZcvKqimDg7F89nAE+ShFroyIyLFIJBKoPGRQecgQ0In2giCgocmCmvomVNebUVFrgs7QiHKDCRW1JtSamnHgQiUOXKi0vSY22BsTYgIxfkAAxg0IgFp1bRCjm8OFEDvgTgshnik1YPnnZ/H1uQoAQKC3Ei/MHIxZiWE92iXLhRCJiK5lsQoY2c8XuUU1yCmsQU5hNS62bvHRRioBhvf1xYSYAEwYEIiR/fyg8pCJVLFj68r3NwNQB9whAJ0q0WP1ngv4/KQOQMtkvl+M64ff/89Au/xLgwGIiKhjP14JutpoxuH8qzhwoRIHL1y19cy3UXlIMTY6AJNiAjExNhBxWh/OIWrFlaCpQ1argL155djw7eV2Xa0zh4fiD6mD0C/gxttZEBGR/fl5KTAjPhQz4kMBACU1Dfj2QmXL4+JVVNSa8PW5inY99xNjAjAxNgiTYgMRoubq/J3BHqAOuFoP0MWKOmzPLsZH2VdQom8E0NKlOnN4GJ6YGoNBWvvf2s4eICKijnVlLzBBEJBXVosD5yvxzflKHM6/isYma7s2A0O8MTGmJQyNjfaHlxvdwcseIDfX2GRBTmENDl6sxBendDhXVmd7Tq2S476xkfjluH6I8PcUsUoiIuoqiUSCOK0acVo1Hp7UH6ZmC7IKqnHgfMsk6hPFepwrq8O5sjq8820+pBIgTqvGqH5+GNnPFyMj/RDpz/3QAAcJQGvWrMEbb7wBnU6HhIQE/O///i/Gjh173fbbtm3Diy++iMuXLyM2Nhavv/46brvtNtvzgiBg2bJlePvtt1FTU4MJEyZg7dq1iI2N7Y3T6VWCIKC81oSzulocK6pB5sWryC6shqn5+38RyKUSTIwNxN2j+iJlcAgnzxERuQilXIbxAwIxfkAg/oCW+UMHL17FgQsV+OZ8Ja5UN+B0qQGnSw3416ECAICPSo7BWjWGhKkxONQHA0N8EB3oBV9P97r1XvQAtHXrVqSnp2PdunVISkrCypUrkZqairy8PAQHB1/T/uDBg5g7dy6WL1+O22+/HZs3b0ZaWhqys7MRHx8PAPjLX/6Ct956C5s2bUJ0dDRefPFFpKam4vTp01CpnG9stLHJgqtGM0pqGlofjSiuqcf5sjrkldWipv7aRbiCfJRI7h+AyQODkDI4BBpP3kJJROTq/LwUmDk8FDOHt8wfKtU3ILugBtmF1cgqqMapEj1qG5tx5HIVjlyuavdaTR8PRAV4ol+AF0J9VdCqVa0LNqoQ5K2Epo8HfFRyl9kHUvQ5QElJSRgzZgxWr14NALBarYiIiMCTTz6JxYsXX9N+zpw5MBqN2Llzp+3YuHHjkJiYiHXr1kEQBISFheHpp5/GM888AwDQ6/UICQnBxo0bcd999/1kTfaaA3SsqAZHC6pharbA3GyFudkKk+2/FjQ2WWFobFlV1NDQBENjM/StC2jdiFTSslXF4FA1kvoHILl/AAYEeTlUFyfnABERdawrc4BulrnZiosVdThdYsCZUgPO6Ay4WG6EztDYqddLJICPUg51Hw9oWh+eCjmUcmnLw0MKhUwKpYes5b+tx+RSKWRSCaRSCeRSCWQSCQaHqjGsr6ZHz89p5gCZzWZkZWVhyZIltmNSqRQpKSnIzMzs8DWZmZlIT09vdyw1NRU7duwAAOTn50On0yElJcX2vEajQVJSEjIzMzsMQCaTCSaTyfZ7vV4PoOVC9qTdx/LxVsaFbr3WQyZBsFqJUHWfluXb1SpEB3ohNsQb/YO8fzSsZUVtbW3PFN1D6o2OVQ8RkaPo6e+anxLuBYTHqvE/sd8HhHpzM65U16Pgaj2KqupRVmtChaERZQYTymtNqKo3w9Q62bqmEajR33wdD02MRj/1wJt/ox9ou5ad6dsRNQBVVlbCYrEgJKT9VgshISE4e/Zsh6/R6XQdttfpdLbn245dr82PLV++HH/84x+vOR4REdG5E+kll8QugIiIetyvxS5AJC+tBF6y03vX1tZCo7lx75Loc4AcwZIlS9r1KlmtVlRVVSEgIECUYSSDwYCIiAgUFRW5xG34joTX1j54Xe2D19U+eF3tR+xrKwgCamtrERYW9pNtRQ1AgYGBkMlkKCsra3e8rKwMWq22w9dotdobtm/7b1lZGUJDQ9u1SUxM7PA9lUollMr2e175+vp25VTsQq1W8y+nnfDa2gevq33wutoHr6v9iHltf6rnp43UznXckEKhwKhRo5CRkWE7ZrVakZGRgeTk5A5fk5yc3K49AOzevdvWPjo6Glqttl0bg8GAw4cPX/c9iYiIyL2IPgSWnp6O+fPnY/To0Rg7dixWrlwJo9GIBQsWAADmzZuH8PBwLF++HACwcOFCTJ48GStWrMDMmTOxZcsWHD16FOvXrwfQskjUU089hVdeeQWxsbG22+DDwsKQlpYm1mkSERGRAxE9AM2ZMwcVFRVYunQpdDodEhMTsWvXLtsk5sLCQkil33dUjR8/Hps3b8YLL7yA5557DrGxsdixY4dtDSAA+MMf/gCj0Yjf/OY3qKmpwcSJE7Fr1y6nWQNIqVRi2bJl1wzL0c3jtbUPXlf74HW1D15X+3Gmayv6OkBEREREvU3UOUBEREREYmAAIiIiIrfDAERERERuhwGIiIiI3A4DkIi+/vpr3HHHHQgLC4NEIrHtZ9ZGEAQsXboUoaGh6NOnD1JSUnD+/HlxinUiy5cvx5gxY+Dj44Pg4GCkpaUhLy+vXZvGxkY8/vjjCAgIgLe3N37+859fs8Amtbd27VoMHz7ctsBZcnIyPv/8c9vzvKY947XXXrMt59GG17Z7XnrpJUgkknaPuLg42/O8rt1XXFyMX/ziFwgICECfPn0wbNgwHD161Pa8M3x/MQCJyGg0IiEhAWvWrOnw+b/85S946623sG7dOhw+fBheXl5ITU1FY2Pndu11V/v378fjjz+OQ4cOYffu3WhqasL06dNhNBptbX7/+9/jk08+wbZt27B//36UlJRg9uzZIlbt+Pr27YvXXnsNWVlZOHr0KG655RbMmjULp06dAsBr2hO+++47/N///R+GDx/e7jivbfcNHToUpaWltseBAwdsz/G6dk91dTUmTJgADw8PfP755zh9+jRWrFgBPz8/Wxun+P4SyCEAELZv3277vdVqFbRarfDGG2/YjtXU1AhKpVL44IMPRKjQeZWXlwsAhP379wuC0HIdPTw8hG3bttnanDlzRgAgZGZmilWmU/Lz8xP+8Y9/8Jr2gNraWiE2NlbYvXu3MHnyZGHhwoWCIPDP681YtmyZkJCQ0OFzvK7dt2jRImHixInXfd5Zvr/YA+Sg8vPzodPpkJKSYjum0WiQlJSEzMxMEStzPnq9HgDg7+8PAMjKykJTU1O7axsXF4fIyEhe206yWCzYsmULjEYjkpOTeU17wOOPP46ZM2e2u4YA/7zerPPnzyMsLAz9+/fHAw88gMLCQgC8rjfj448/xujRo3HPPfcgODgYI0aMwNtvv2173lm+vxiAHJROpwMA24rYbUJCQmzP0U+zWq146qmnMGHCBNtq4TqdDgqF4poNb3ltf9qJEyfg7e0NpVKJRx99FNu3b8eQIUN4TW/Sli1bkJ2dbdvy54d4bbsvKSkJGzduxK5du7B27Vrk5+dj0qRJqK2t5XW9CZcuXcLatWsRGxuLL774Ao899hh+97vfYdOmTQCc5/tL9K0wiOzp8ccfx8mTJ9uN+1P3DRo0CLm5udDr9fjwww8xf/587N+/X+yynFpRUREWLlyI3bt3O812Pc7i1ltvtf16+PDhSEpKQr9+/fDvf/8bffr0EbEy52a1WjF69Gj8+c9/BgCMGDECJ0+exLp16zB//nyRq+s89gA5KK1WCwDX3JFQVlZme45u7IknnsDOnTuxd+9e9O3b13Zcq9XCbDajpqamXXte25+mUCgQExODUaNGYfny5UhISMCqVat4TW9CVlYWysvLMXLkSMjlcsjlcuzfvx9vvfUW5HI5QkJCeG17iK+vLwYOHIgLFy7wz+xNCA0NxZAhQ9odGzx4sG140Vm+vxiAHFR0dDS0Wi0yMjJsxwwGAw4fPozk5GQRK3N8giDgiSeewPbt27Fnzx5ER0e3e37UqFHw8PBod23z8vJQWFjIa9tFVqsVJpOJ1/QmTJs2DSdOnEBubq7tMXr0aDzwwAO2X/Pa9oy6ujpcvHgRoaGh/DN7EyZMmHDN0iLnzp1Dv379ADjR95fYs7DdWW1trZCTkyPk5OQIAIQ333xTyMnJEQoKCgRBEITXXntN8PX1Ff773/8Kx48fF2bNmiVER0cLDQ0NIlfu2B577DFBo9EI+/btE0pLS22P+vp6W5tHH31UiIyMFPbs2SMcPXpUSE5OFpKTk0Ws2vEtXrxY2L9/v5Cfny8cP35cWLx4sSCRSIQvv/xSEARe0570w7vABIHXtruefvppYd++fUJ+fr7w7bffCikpKUJgYKBQXl4uCAKva3cdOXJEkMvlwquvviqcP39eeP/99wVPT0/hvffes7Vxhu8vBiAR7d27VwBwzWP+/PmCILTcSvjiiy8KISEhglKpFKZNmybk5eWJW7QT6OiaAhA2bNhga9PQ0CD89re/Ffz8/ARPT0/hrrvuEkpLS8Ur2gn86le/Evr16ycoFAohKChImDZtmi38CAKvaU/6cQDite2eOXPmCKGhoYJCoRDCw8OFOXPmCBcuXLA9z+vafZ988okQHx8vKJVKIS4uTli/fn27553h+0siCIIgTt8TERERkTg4B4iIiIjcDgMQERERuR0GICIiInI7DEBERETkdhiAiIiIyO0wABEREZHbYQAiIiIit8MARERERG6HAYiIum3KlCl46qmnrvu8RCLBjh07Ov1++/btg0QiuWaDSiKiniYXuwAicl2lpaXw8/MTuwwiomswABGR3Wi1WrFLICLqEIfAiOimWK1W/OEPf4C/vz+0Wi1eeukl23M/HgI7ePAgEhMToVKpMHr0aOzYsQMSiQS5ubnt3jMrKwujR4+Gp6cnxo8fj7y8PACAXq+HTCbD0aNHbZ/t7++PcePG2V773nvvISIiwvb7RYsWYeDAgfD09ET//v3x4osvoqmpCQBw+fJlSKVS2/u1WblyJfr16wer1drhOT/44INIS0vDn//8Z4SEhMDX1xd/+tOf0NzcjGeffRb+/v7o27cvNmzYYHvN5cuXIZFIsGXLFowfPx4qlQrx8fHYv39/u/f++OOPERsbC5VKhalTp2LTpk0cFiSyAwYgIropmzZtgpeXFw4fPoy//OUv+NOf/oTdu3df085gMOCOO+7AsGHDkJ2djZdffhmLFi3q8D2ff/55rFixAkePHoVcLsevfvUrAIBGo0FiYiL27dsHADhx4gQkEglycnJQV1cHANi/fz8mT55sey8fHx9s3LgRp0+fxqpVq/D222/jb3/7GwAgKioKKSkp7YIKAGzYsAEPPvggpNLr/4jcs2cPSkpK8PXXX+PNN9/EsmXLcPvtt8PPzw+HDx/Go48+ikceeQRXrlxp97pnn30WTz/9NHJycpCcnIw77rgDV69eBQDk5+fj7rvvRlpaGo4dO4ZHHnkEzz///I0uPxF1l9jb0ROR85o8ebIwceLEdsfGjBkjLFq0SBAEQQAgbN++XRAEQVi7dq0QEBAgNDQ02Nq+/fbbAgAhJydHEARB2Lt3rwBA+Oqrr2xtPv30UwGA7XXp6enCzJkzBUEQhJUrVwpz5swREhIShM8//1wQBEGIiYkR1q9ff92a33jjDWHUqFG232/dulXw8/MTGhsbBUEQhKysLEEikQj5+fnXfY/58+cL/fr1EywWi+3YoEGDhEmTJtl+39zcLHh5eQkffPCBIAiCkJ+fLwAQXnvtNVubpqYmoW/fvsLrr78uCIIgLFq0SIiPj2/3Wc8//7wAQKiurr5uPUTUdewBIqKbMnz48Ha/Dw0NRXl5+TXt8vLyMHz4cKhUKtuxsWPH/uR7hoaGAoDtPSdPnowDBw7AYrFg//79mDJlCqZMmYJ9+/ahpKQEFy5cwJQpU2yv37p1KyZMmACtVgtvb2+88MILKCwstD2flpYGmUyG7du3AwA2btyIqVOnIioqCoWFhfD29rY9/vznP9teN3To0HY9RCEhIRg2bJjt9zKZDAEBAddci+TkZNuv5XI5Ro8ejTNnztiu0ZgxY9q1v941IqKbwwBERDfFw8Oj3e8lEsl158505z0lEgkA2N7zZz/7GWpra5GdnY2vv/66XQDav38/wsLCEBsbCwDIzMzEAw88gNtuuw07d+5ETk4Onn/+eZjNZtv7KxQKzJs3Dxs2bIDZbMbmzZttQ25hYWHIzc21PR599NEbnrc9rgUR2QcDEBH1ikGDBuHEiRMwmUy2Y999912X38fX1xfDhw/H6tWr4eHhgbi4OPzsZz9DTk4Odu7c2W7+z8GDB9GvXz88//zzGD16NGJjY1FQUHDNez788MP46quv8Pe//x3Nzc2YPXs2gJYempiYGNvD39+/G2fe3qFDh2y/bm5uRlZWFgYPHgyg5Rr9eEJ2d64REf00BiAi6hX3338/rFYrfvOb3+DMmTP44osv8Ne//hXA9708nTVlyhS8//77trDj7++PwYMHY+vWre0CUGxsLAoLC7FlyxZcvHgRb731lm2o64cGDx6McePGYdGiRZg7dy769OlzE2d6Y2vWrMH27dtx9uxZPP7446iurrb1OD3yyCM4e/YsFi1ahHPnzuHf//43Nm7cCKDr14iIbowBiIh6hVqtxieffILc3FwkJibi+eefx9KlSwGg3bygzpg8eTIsFku7uT5Tpky55tidd96J3//+93jiiSeQmJiIgwcP4sUXX+zwPR966CGYzWZbGLGX1157Da+99hoSEhJw4MABfPzxxwgMDAQAREdH48MPP8RHH32E4cOHY+3atba7wJRKpV3rInI3EkEQBLGLICL39P7772PBggXQ6/V27XXpjJdffhnbtm3D8ePH7fL+ly9fRnR0NHJycpCYmNjp17366qtYt24dioqK7FIXkbviStBE1Gveffdd9O/fH+Hh4Th27BgWLVqEe++9V9TwU1dXh8uXL2P16tV45ZVXRKujzd///neMGTMGAQEB+Pbbb/HGG2/giSeeELssIpfDAEREvUan02Hp0qXQ6XQIDQ3FPffcg1dffVXUmp544gl88MEHSEtLs/vwV2ecP38er7zyCqqqqhAZGYmnn34aS5YsEbssIpfDITAiIiJyO5wETURERG6HAYiIiIjcDgMQERERuR0GICIiInI7DEBERETkdhiAiIiIyO0wABEREZHbYQAiIiIit/P/14ZM5TZ2TrYAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here we can see that all attribute are skewed except height.\n",
        "\n",
        "There are two ways of removing skewness \n",
        "1.sqrt.transformation\n",
        "2.log transformation\n",
        "\n",
        "In real world senarios normally log transformation is used.\n",
        "\n",
        "Before removing the skewness there are certain things that we nedd to check:\n",
        "\n",
        "1.If the attribute is having good co-relation with target(y) then  do not remove skewness.\n",
        "\n",
        "2.If their is negative skewness for any of the attribute then also do not remove it. "
      ],
      "metadata": {
        "id": "LqyK8uB4oYhC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "n2IFyhy1qRFy",
        "outputId": "b0da254e-1c69-49a4-afd1-1217a3fa3c3a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   symboling  normalized-losses         make fuel-type   body-style  \\\n",
              "0          3              122.0  alfa-romero       gas  convertible   \n",
              "1          3              122.0  alfa-romero       gas  convertible   \n",
              "2          1              122.0  alfa-romero       gas    hatchback   \n",
              "3          2              164.0         audi       gas        sedan   \n",
              "4          2              164.0         audi       gas        sedan   \n",
              "\n",
              "  drive-wheels engine-location  width  height engine-type  engine-size  \\\n",
              "0          rwd           front   64.1    48.8        dohc          130   \n",
              "1          rwd           front   64.1    48.8        dohc          130   \n",
              "2          rwd           front   65.5    52.4        ohcv          152   \n",
              "3          fwd           front   66.2    54.3         ohc          109   \n",
              "4          4wd           front   66.4    54.3         ohc          136   \n",
              "\n",
              "   horsepower  city-mpg  highway-mpg  price  \n",
              "0       111.0        21           27  13495  \n",
              "1       111.0        21           27  16500  \n",
              "2       154.0        19           26  16500  \n",
              "3       102.0        24           30  13950  \n",
              "4       115.0        18           22  17450  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>symboling</th>\n",
              "      <th>normalized-losses</th>\n",
              "      <th>make</th>\n",
              "      <th>fuel-type</th>\n",
              "      <th>body-style</th>\n",
              "      <th>drive-wheels</th>\n",
              "      <th>engine-location</th>\n",
              "      <th>width</th>\n",
              "      <th>height</th>\n",
              "      <th>engine-type</th>\n",
              "      <th>engine-size</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>city-mpg</th>\n",
              "      <th>highway-mpg</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>122.0</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>dohc</td>\n",
              "      <td>130</td>\n",
              "      <td>111.0</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>13495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>122.0</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>dohc</td>\n",
              "      <td>130</td>\n",
              "      <td>111.0</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>16500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>122.0</td>\n",
              "      <td>alfa-romero</td>\n",
              "      <td>gas</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>152</td>\n",
              "      <td>154.0</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>16500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>164.0</td>\n",
              "      <td>audi</td>\n",
              "      <td>gas</td>\n",
              "      <td>sedan</td>\n",
              "      <td>fwd</td>\n",
              "      <td>front</td>\n",
              "      <td>66.2</td>\n",
              "      <td>54.3</td>\n",
              "      <td>ohc</td>\n",
              "      <td>109</td>\n",
              "      <td>102.0</td>\n",
              "      <td>24</td>\n",
              "      <td>30</td>\n",
              "      <td>13950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>164.0</td>\n",
              "      <td>audi</td>\n",
              "      <td>gas</td>\n",
              "      <td>sedan</td>\n",
              "      <td>4wd</td>\n",
              "      <td>front</td>\n",
              "      <td>66.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>ohc</td>\n",
              "      <td>136</td>\n",
              "      <td>115.0</td>\n",
              "      <td>18</td>\n",
              "      <td>22</td>\n",
              "      <td>17450</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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        "df.corr() "
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      "execution_count": 20,
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              "                   symboling  normalized-losses     width    height  \\\n",
              "symboling           1.000000           0.465190 -0.232919 -0.541038   \n",
              "normalized-losses   0.465190           1.000000  0.084195 -0.370706   \n",
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              "horsepower          0.071389           0.203434  0.642195 -0.110137   \n",
              "city-mpg           -0.035823          -0.218749 -0.642704 -0.048640   \n",
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              "price              -0.085781           0.133424  0.718253  0.132444   \n",
              "\n",
              "                   engine-size  horsepower  city-mpg  highway-mpg     price  \n",
              "symboling            -0.105790    0.071389 -0.035823     0.034606 -0.085781  \n",
              "normalized-losses     0.110997    0.203434 -0.218749    -0.178221  0.133424  \n",
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              "#T_32c7a_row5_col2 {\n",
              "  background-color: #0569a5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_32c7a_row5_col3 {\n",
              "  background-color: #c6cce3;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row5_col4 {\n",
              "  background-color: #045687;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_32c7a_row5_col8 {\n",
              "  background-color: #045e94;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_32c7a_row6_col0 {\n",
              "  background-color: #b7c5df;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row6_col2 {\n",
              "  background-color: #fcf4fa;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row6_col3 {\n",
              "  background-color: #b9c6e0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row6_col4, #T_32c7a_row6_col8, #T_32c7a_row7_col5 {\n",
              "  background-color: #fdf5fa;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row6_col7, #T_32c7a_row7_col6 {\n",
              "  background-color: #023c5f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_32c7a_row7_col1 {\n",
              "  background-color: #e9e5f1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row8_col0 {\n",
              "  background-color: #c1cae2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row8_col1 {\n",
              "  background-color: #a8bedc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row8_col2 {\n",
              "  background-color: #046299;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_32c7a_row8_col3 {\n",
              "  background-color: #8eb3d5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_32c7a_row8_col5 {\n",
              "  background-color: #045c90;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_32c7a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_32c7a_level0_col0\" class=\"col_heading level0 col0\" >symboling</th>\n",
              "      <th id=\"T_32c7a_level0_col1\" class=\"col_heading level0 col1\" >normalized-losses</th>\n",
              "      <th id=\"T_32c7a_level0_col2\" class=\"col_heading level0 col2\" >width</th>\n",
              "      <th id=\"T_32c7a_level0_col3\" class=\"col_heading level0 col3\" >height</th>\n",
              "      <th id=\"T_32c7a_level0_col4\" class=\"col_heading level0 col4\" >engine-size</th>\n",
              "      <th id=\"T_32c7a_level0_col5\" class=\"col_heading level0 col5\" >horsepower</th>\n",
              "      <th id=\"T_32c7a_level0_col6\" class=\"col_heading level0 col6\" >city-mpg</th>\n",
              "      <th id=\"T_32c7a_level0_col7\" class=\"col_heading level0 col7\" >highway-mpg</th>\n",
              "      <th id=\"T_32c7a_level0_col8\" class=\"col_heading level0 col8\" >price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row0\" class=\"row_heading level0 row0\" >symboling</th>\n",
              "      <td id=\"T_32c7a_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row0_col1\" class=\"data row0 col1\" >0.465190</td>\n",
              "      <td id=\"T_32c7a_row0_col2\" class=\"data row0 col2\" >-0.232919</td>\n",
              "      <td id=\"T_32c7a_row0_col3\" class=\"data row0 col3\" >-0.541038</td>\n",
              "      <td id=\"T_32c7a_row0_col4\" class=\"data row0 col4\" >-0.105790</td>\n",
              "      <td id=\"T_32c7a_row0_col5\" class=\"data row0 col5\" >0.071389</td>\n",
              "      <td id=\"T_32c7a_row0_col6\" class=\"data row0 col6\" >-0.035823</td>\n",
              "      <td id=\"T_32c7a_row0_col7\" class=\"data row0 col7\" >0.034606</td>\n",
              "      <td id=\"T_32c7a_row0_col8\" class=\"data row0 col8\" >-0.085781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row1\" class=\"row_heading level0 row1\" >normalized-losses</th>\n",
              "      <td id=\"T_32c7a_row1_col0\" class=\"data row1 col0\" >0.465190</td>\n",
              "      <td id=\"T_32c7a_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row1_col2\" class=\"data row1 col2\" >0.084195</td>\n",
              "      <td id=\"T_32c7a_row1_col3\" class=\"data row1 col3\" >-0.370706</td>\n",
              "      <td id=\"T_32c7a_row1_col4\" class=\"data row1 col4\" >0.110997</td>\n",
              "      <td id=\"T_32c7a_row1_col5\" class=\"data row1 col5\" >0.203434</td>\n",
              "      <td id=\"T_32c7a_row1_col6\" class=\"data row1 col6\" >-0.218749</td>\n",
              "      <td id=\"T_32c7a_row1_col7\" class=\"data row1 col7\" >-0.178221</td>\n",
              "      <td id=\"T_32c7a_row1_col8\" class=\"data row1 col8\" >0.133424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row2\" class=\"row_heading level0 row2\" >width</th>\n",
              "      <td id=\"T_32c7a_row2_col0\" class=\"data row2 col0\" >-0.232919</td>\n",
              "      <td id=\"T_32c7a_row2_col1\" class=\"data row2 col1\" >0.084195</td>\n",
              "      <td id=\"T_32c7a_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row2_col3\" class=\"data row2 col3\" >0.279210</td>\n",
              "      <td id=\"T_32c7a_row2_col4\" class=\"data row2 col4\" >0.735433</td>\n",
              "      <td id=\"T_32c7a_row2_col5\" class=\"data row2 col5\" >0.642195</td>\n",
              "      <td id=\"T_32c7a_row2_col6\" class=\"data row2 col6\" >-0.642704</td>\n",
              "      <td id=\"T_32c7a_row2_col7\" class=\"data row2 col7\" >-0.677218</td>\n",
              "      <td id=\"T_32c7a_row2_col8\" class=\"data row2 col8\" >0.718253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row3\" class=\"row_heading level0 row3\" >height</th>\n",
              "      <td id=\"T_32c7a_row3_col0\" class=\"data row3 col0\" >-0.541038</td>\n",
              "      <td id=\"T_32c7a_row3_col1\" class=\"data row3 col1\" >-0.370706</td>\n",
              "      <td id=\"T_32c7a_row3_col2\" class=\"data row3 col2\" >0.279210</td>\n",
              "      <td id=\"T_32c7a_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row3_col4\" class=\"data row3 col4\" >0.067149</td>\n",
              "      <td id=\"T_32c7a_row3_col5\" class=\"data row3 col5\" >-0.110137</td>\n",
              "      <td id=\"T_32c7a_row3_col6\" class=\"data row3 col6\" >-0.048640</td>\n",
              "      <td id=\"T_32c7a_row3_col7\" class=\"data row3 col7\" >-0.107358</td>\n",
              "      <td id=\"T_32c7a_row3_col8\" class=\"data row3 col8\" >0.132444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row4\" class=\"row_heading level0 row4\" >engine-size</th>\n",
              "      <td id=\"T_32c7a_row4_col0\" class=\"data row4 col0\" >-0.105790</td>\n",
              "      <td id=\"T_32c7a_row4_col1\" class=\"data row4 col1\" >0.110997</td>\n",
              "      <td id=\"T_32c7a_row4_col2\" class=\"data row4 col2\" >0.735433</td>\n",
              "      <td id=\"T_32c7a_row4_col3\" class=\"data row4 col3\" >0.067149</td>\n",
              "      <td id=\"T_32c7a_row4_col4\" class=\"data row4 col4\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row4_col5\" class=\"data row4 col5\" >0.810713</td>\n",
              "      <td id=\"T_32c7a_row4_col6\" class=\"data row4 col6\" >-0.653658</td>\n",
              "      <td id=\"T_32c7a_row4_col7\" class=\"data row4 col7\" >-0.677470</td>\n",
              "      <td id=\"T_32c7a_row4_col8\" class=\"data row4 col8\" >0.852995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row5\" class=\"row_heading level0 row5\" >horsepower</th>\n",
              "      <td id=\"T_32c7a_row5_col0\" class=\"data row5 col0\" >0.071389</td>\n",
              "      <td id=\"T_32c7a_row5_col1\" class=\"data row5 col1\" >0.203434</td>\n",
              "      <td id=\"T_32c7a_row5_col2\" class=\"data row5 col2\" >0.642195</td>\n",
              "      <td id=\"T_32c7a_row5_col3\" class=\"data row5 col3\" >-0.110137</td>\n",
              "      <td id=\"T_32c7a_row5_col4\" class=\"data row5 col4\" >0.810713</td>\n",
              "      <td id=\"T_32c7a_row5_col5\" class=\"data row5 col5\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row5_col6\" class=\"data row5 col6\" >-0.803162</td>\n",
              "      <td id=\"T_32c7a_row5_col7\" class=\"data row5 col7\" >-0.770903</td>\n",
              "      <td id=\"T_32c7a_row5_col8\" class=\"data row5 col8\" >0.746589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row6\" class=\"row_heading level0 row6\" >city-mpg</th>\n",
              "      <td id=\"T_32c7a_row6_col0\" class=\"data row6 col0\" >-0.035823</td>\n",
              "      <td id=\"T_32c7a_row6_col1\" class=\"data row6 col1\" >-0.218749</td>\n",
              "      <td id=\"T_32c7a_row6_col2\" class=\"data row6 col2\" >-0.642704</td>\n",
              "      <td id=\"T_32c7a_row6_col3\" class=\"data row6 col3\" >-0.048640</td>\n",
              "      <td id=\"T_32c7a_row6_col4\" class=\"data row6 col4\" >-0.653658</td>\n",
              "      <td id=\"T_32c7a_row6_col5\" class=\"data row6 col5\" >-0.803162</td>\n",
              "      <td id=\"T_32c7a_row6_col6\" class=\"data row6 col6\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row6_col7\" class=\"data row6 col7\" >0.971337</td>\n",
              "      <td id=\"T_32c7a_row6_col8\" class=\"data row6 col8\" >-0.654611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row7\" class=\"row_heading level0 row7\" >highway-mpg</th>\n",
              "      <td id=\"T_32c7a_row7_col0\" class=\"data row7 col0\" >0.034606</td>\n",
              "      <td id=\"T_32c7a_row7_col1\" class=\"data row7 col1\" >-0.178221</td>\n",
              "      <td id=\"T_32c7a_row7_col2\" class=\"data row7 col2\" >-0.677218</td>\n",
              "      <td id=\"T_32c7a_row7_col3\" class=\"data row7 col3\" >-0.107358</td>\n",
              "      <td id=\"T_32c7a_row7_col4\" class=\"data row7 col4\" >-0.677470</td>\n",
              "      <td id=\"T_32c7a_row7_col5\" class=\"data row7 col5\" >-0.770903</td>\n",
              "      <td id=\"T_32c7a_row7_col6\" class=\"data row7 col6\" >0.971337</td>\n",
              "      <td id=\"T_32c7a_row7_col7\" class=\"data row7 col7\" >1.000000</td>\n",
              "      <td id=\"T_32c7a_row7_col8\" class=\"data row7 col8\" >-0.679048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32c7a_level0_row8\" class=\"row_heading level0 row8\" >price</th>\n",
              "      <td id=\"T_32c7a_row8_col0\" class=\"data row8 col0\" >-0.085781</td>\n",
              "      <td id=\"T_32c7a_row8_col1\" class=\"data row8 col1\" >0.133424</td>\n",
              "      <td id=\"T_32c7a_row8_col2\" class=\"data row8 col2\" >0.718253</td>\n",
              "      <td id=\"T_32c7a_row8_col3\" class=\"data row8 col3\" >0.132444</td>\n",
              "      <td id=\"T_32c7a_row8_col4\" class=\"data row8 col4\" >0.852995</td>\n",
              "      <td id=\"T_32c7a_row8_col5\" class=\"data row8 col5\" >0.746589</td>\n",
              "      <td id=\"T_32c7a_row8_col6\" class=\"data row8 col6\" >-0.654611</td>\n",
              "      <td id=\"T_32c7a_row8_col7\" class=\"data row8 col7\" >-0.679048</td>\n",
              "      <td id=\"T_32c7a_row8_col8\" class=\"data row8 col8\" >1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(df.corr(),cmap=\"Blues\",annot=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 563
        },
        "id": "JJDpBaSOq0TF",
        "outputId": "2576394c-e786-4576-e089-a2b7234293f3"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.corr()[\"price\"].sort_values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yxevEcLcsMxu",
        "outputId": "91faac42-9fb6-4e7b-94a7-612205806b37"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "highway-mpg         -0.679048\n",
              "city-mpg            -0.654611\n",
              "symboling           -0.085781\n",
              "height               0.132444\n",
              "normalized-losses    0.133424\n",
              "width                0.718253\n",
              "horsepower           0.746589\n",
              "engine-size          0.852995\n",
              "price                1.000000\n",
              "Name: price, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Form above we can see that there is need of removing skewness for normalized losses only."
      ],
      "metadata": {
        "id": "c-PrxgI-tYT-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "np.log(x[\"normalized-losses\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-plYbGXfs2h-",
        "outputId": "ded090c9-6370-4ef1-8596-5a5f96b9d2db"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      4.804021\n",
              "1      4.804021\n",
              "2      4.804021\n",
              "3      5.099866\n",
              "4      5.099866\n",
              "         ...   \n",
              "200    4.553877\n",
              "201    4.553877\n",
              "202    4.553877\n",
              "203    4.553877\n",
              "204    4.553877\n",
              "Name: normalized-losses, Length: 205, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x[\"normalized-losses\"]=np.log(x[\"normalized-losses\"])"
      ],
      "metadata": {
        "id": "4VepkI5XtyY7"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "skew(x[\"normalized-losses\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zQbjc-uvuLvC",
        "outputId": "ad4d6a0f-5a2b-4834-8a4f-f0da88e48a2b"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.03137735337911685"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "So the skewness for normalized losses is reduced to 0.0313 from 0.848"
      ],
      "metadata": {
        "id": "aTklwZtquXtA"
      }
    }
  ]
}