Statistics_for_Data_Science_using_Python9.ipynb

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      "source": [
        "# Import required libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import statsmodels.api as sm\n",
        "import datetime\n",
        "import scipy.stats\n",
        "%matplotlib inline\n",
        "\n"
      ]
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    {
      "cell_type": "code",
      "source": [
        "boston_url = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-ST0151EN-SkillsNetwork/labs/boston_housing.csv'\n",
        "boston_df=pd.read_csv(boston_url)"
      ],
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      "execution_count": 92,
      "outputs": []
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        "boston_df"
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              "     Unnamed: 0     CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  PTRATIO  LSTAT  MEDV\n",
              "0             0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0     15.3   4.98  24.0\n",
              "1             1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0     17.8   9.14  21.6\n",
              "2             2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0     17.8   4.03  34.7\n",
              "3             3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0     18.7   2.94  33.4\n",
              "4             4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0     18.7   5.33  36.2\n",
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              "501         501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0     21.0   9.67  22.4\n",
              "502         502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0     21.0   9.08  20.6\n",
              "503         503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0     21.0   5.64  23.9\n",
              "504         504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0     21.0   6.48  22.0\n",
              "505         505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0     21.0   7.88  11.9\n",
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              "      <th>CRIM</th>\n",
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          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Task 4: Generate Descriptive Statistics and Visualizations:\n"
      ],
      "metadata": {
        "id": "3Qx0dsTBiqHp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***4.1. For the \"Median value of owner-occupied homes\" provide a boxplot***"
      ],
      "metadata": {
        "id": "ReHaeGJxnQRI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6,4))\n",
        "sns.boxplot(x=boston_df.MEDV)\n",
        "plt.title(\"Boxplot for MEDV\")\n",
        "plt.show()"
      ],
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        "id": "Hoh8Sqn2irez",
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      "execution_count": 94,
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        {
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              "<Figure size 600x400 with 1 Axes>"
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***4.2. Provide a bar plot for the Charles river variable***"
      ],
      "metadata": {
        "id": "mMZ0gHf2nYdL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6,4))\n",
        "sns.distplot(a=boston_df.CHAS,bins=10, kde=False)\n",
        "plt.title(\"Histogram for Charles river\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "7J6MVAlAjQhv",
        "outputId": "0ff7bfbf-c6b6-4350-e80a-ba76135fcb99"
      },
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***4.3. Provide a boxplot for the MEDV variable vs the AGE variable. (Discretize the age variable into three groups of 35 years and younger, between 35 and 70 years and 70 years and older)***\n"
      ],
      "metadata": {
        "id": "5PHixwFCnaue"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df.loc[(boston_df[\"AGE\"] <= 35),'Age_group'] = '35 years and younger'\n",
        "boston_df.loc[(boston_df[\"AGE\"] > 35) & (boston_df[\"AGE\"]<70),'Age_group'] = 'between 35 and 70 years'\n",
        "boston_df.loc[(boston_df[\"AGE\"] >= 70),'Age_group'] = '70 years and older'"
      ],
      "metadata": {
        "id": "i8MW8XWJjoJ3"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "tSui-FgakKfx",
        "outputId": "d866d823-2b0c-4520-aeba-6881f21107c3"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Unnamed: 0     CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  PTRATIO  LSTAT  MEDV                Age_group\n",
              "0             0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0     15.3   4.98  24.0  between 35 and 70 years\n",
              "1             1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0     17.8   9.14  21.6       70 years and older\n",
              "2             2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0     17.8   4.03  34.7  between 35 and 70 years\n",
              "3             3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0     18.7   2.94  33.4  between 35 and 70 years\n",
              "4             4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0     18.7   5.33  36.2  between 35 and 70 years\n",
              "..          ...      ...   ...    ...   ...    ...    ...   ...     ...  ...    ...      ...    ...   ...                      ...\n",
              "501         501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0     21.0   9.67  22.4  between 35 and 70 years\n",
              "502         502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0     21.0   9.08  20.6       70 years and older\n",
              "503         503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0     21.0   5.64  23.9       70 years and older\n",
              "504         504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0     21.0   6.48  22.0       70 years and older\n",
              "505         505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0     21.0   7.88  11.9       70 years and older\n",
              "\n",
              "[506 rows x 15 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5f36686f-6ffe-440a-aaae-5df2308e23af\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>LSTAT</th>\n",
              "      <th>MEDV</th>\n",
              "      <th>Age_group</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>4.98</td>\n",
              "      <td>24.0</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>9.14</td>\n",
              "      <td>21.6</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>4.03</td>\n",
              "      <td>34.7</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>2.94</td>\n",
              "      <td>33.4</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>5.33</td>\n",
              "      <td>36.2</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>501</td>\n",
              "      <td>0.06263</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.593</td>\n",
              "      <td>69.1</td>\n",
              "      <td>2.4786</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>9.67</td>\n",
              "      <td>22.4</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>502</td>\n",
              "      <td>0.04527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.120</td>\n",
              "      <td>76.7</td>\n",
              "      <td>2.2875</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>9.08</td>\n",
              "      <td>20.6</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>503</td>\n",
              "      <td>0.06076</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.976</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2.1675</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>5.64</td>\n",
              "      <td>23.9</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>504</td>\n",
              "      <td>0.10959</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.794</td>\n",
              "      <td>89.3</td>\n",
              "      <td>2.3889</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>6.48</td>\n",
              "      <td>22.0</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>505</td>\n",
              "      <td>0.04741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.030</td>\n",
              "      <td>80.8</td>\n",
              "      <td>2.5050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7.88</td>\n",
              "      <td>11.9</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>506 rows × 15 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5f36686f-6ffe-440a-aaae-5df2308e23af')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5f36686f-6ffe-440a-aaae-5df2308e23af 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-5f36686f-6ffe-440a-aaae-5df2308e23af');\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",
              "\n",
              "\n",
              "<div id=\"df-e5a33a14-c890-4420-bf18-61e99fd24b03\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e5a33a14-c890-4420-bf18-61e99fd24b03')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const charts = await google.colab.kernel.invokeFunction(\n",
              "          'suggestCharts', [key], {});\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e5a33a14-c890-4420-bf18-61e99fd24b03 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6,4))\n",
        "sns.boxplot(x=boston_df.MEDV, y=boston_df.Age_group, data=boston_df)\n",
        "plt.title(\"Boxplot for the MEDV variable vs the AGE variable\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "JdIkABLpkTuo",
        "outputId": "c46765af-9a9a-4a4f-f783-cbd38a686ca2"
      },
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***4.4. Provide a scatter plot to show the relationship between Nitric oxide concentrations and the proportion of non-retail business acres per town. What can you say about the relationship?***\n"
      ],
      "metadata": {
        "id": "O_dQ9uCTndqT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.scatterplot(x=boston_df.NOX, y=boston_df.INDUS, data=boston_df)\n",
        "plt.title(\"Relationship between NOX and INDUS\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "id": "bugkhMv6kjnJ",
        "outputId": "9513a41d-a5c0-40e0-ad58-3f356f722d08"
      },
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- A linear relationship exists until 0.6"
      ],
      "metadata": {
        "id": "1Mbl2OO1lCLj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***4.5. Create a histogram for the pupil to teacher ratio variable***\n"
      ],
      "metadata": {
        "id": "KvpEEhCInhQc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.distplot(a=boston_df.PTRATIO,bins=10, kde=True)\n",
        "plt.title(\"Histogram for the pupil to teacher ratio variable\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "id": "icNpjgAilBul",
        "outputId": "eafc7e61-85a2-40a1-d3e6-1bd6948a6c13"
      },
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Task 5: Use the appropriate tests to answer the questions provided."
      ],
      "metadata": {
        "id": "N6eZtqgEoAQK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***5.1. Is there a significant difference in median value of houses bounded by the Charles river or not? (T-test for independent samples)***"
      ],
      "metadata": {
        "id": "vpdsqD_7oCad"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Null Hypothesis: Both average MEDV are the same\n",
        "\n",
        "Alternative Hypothesis: Both average MEDV are NOT the same"
      ],
      "metadata": {
        "id": "D905lNKWpBvR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df[\"CHAS\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xp0qFeZHnODm",
        "outputId": "cf615465-ccbe-48fe-bdb8-8083145de121"
      },
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0    471\n",
              "1.0     35\n",
              "Name: CHAS, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = boston_df[boston_df[\"CHAS\"] == 0][\"MEDV\"]\n",
        "x"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R3jjvnn3qwZZ",
        "outputId": "831e60a7-0cd3-46c0-cc08-f33c4862b1e8"
      },
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      24.0\n",
              "1      21.6\n",
              "2      34.7\n",
              "3      33.4\n",
              "4      36.2\n",
              "       ... \n",
              "501    22.4\n",
              "502    20.6\n",
              "503    23.9\n",
              "504    22.0\n",
              "505    11.9\n",
              "Name: MEDV, Length: 471, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y = boston_df[boston_df[\"CHAS\"] == 1][\"MEDV\"]\n",
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_otSGxt4q_hn",
        "outputId": "1ff5d4fd-b269-411a-af5e-c00fc82f67c6"
      },
      "execution_count": 103,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "142    13.4\n",
              "152    15.3\n",
              "154    17.0\n",
              "155    15.6\n",
              "160    27.0\n",
              "162    50.0\n",
              "163    50.0\n",
              "208    24.4\n",
              "209    20.0\n",
              "210    21.7\n",
              "211    19.3\n",
              "212    22.4\n",
              "216    23.3\n",
              "218    21.5\n",
              "219    23.0\n",
              "220    26.7\n",
              "221    21.7\n",
              "222    27.5\n",
              "234    29.0\n",
              "236    25.1\n",
              "269    20.7\n",
              "273    35.2\n",
              "274    32.4\n",
              "276    33.2\n",
              "277    33.1\n",
              "282    46.0\n",
              "283    50.0\n",
              "356    17.8\n",
              "357    21.7\n",
              "358    22.7\n",
              "363    16.8\n",
              "364    21.9\n",
              "369    50.0\n",
              "370    50.0\n",
              "372    50.0\n",
              "Name: MEDV, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "scipy.stats.ttest_ind(x,y,axis=0,equal_var=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qSMfzN2GrY5t",
        "outputId": "14a0a105-a184-4818-b4c1-ad979d703ae7"
      },
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Ttest_indResult(statistic=-3.996437466090509, pvalue=7.390623170519905e-05)"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "pvalue is > Fvalue (0.005) hence fail to reject the null hypothesis. Thus Alternative Hypothesis: Both average MEDV are not the same"
      ],
      "metadata": {
        "id": "hSGxSSbqrmCA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***5.2. Is there a difference in Median values of houses (MEDV) for each proportion of owner occupied units built prior to 1940 (AGE)? (ANOVA)***"
      ],
      "metadata": {
        "id": "jtO-La6KrzXG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df[\"AGE\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0hkXUc85r7fx",
        "outputId": "97ba90f5-a866-4441-edc5-a78a6b964005"
      },
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "100.0    43\n",
              "95.4      4\n",
              "96.0      4\n",
              "98.2      4\n",
              "97.9      4\n",
              "         ..\n",
              "58.4      1\n",
              "74.4      1\n",
              "73.4      1\n",
              "33.1      1\n",
              "89.3      1\n",
              "Name: AGE, Length: 356, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df.loc[(df[\"AGE\"] <= 35),'Age_group'] = '35 years and younger'\n",
        "boston_df.loc[(df[\"AGE\"] > 35) & (boston_df[\"AGE\"]<70),'Age_group'] = 'between 35 and 70 years'\n",
        "boston_df.loc[(df[\"AGE\"] >= 70),'Age_group'] = '70 years and older'"
      ],
      "metadata": {
        "id": "FO1v5fJ1r9Yx"
      },
      "execution_count": 106,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "mhoryN9cr9e0",
        "outputId": "d17e5633-3fc8-4b66-b701-a29541fee228"
      },
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Unnamed: 0     CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  PTRATIO  LSTAT  MEDV                Age_group\n",
              "0             0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0     15.3   4.98  24.0  between 35 and 70 years\n",
              "1             1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0     17.8   9.14  21.6       70 years and older\n",
              "2             2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0     17.8   4.03  34.7  between 35 and 70 years\n",
              "3             3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0     18.7   2.94  33.4  between 35 and 70 years\n",
              "4             4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0     18.7   5.33  36.2  between 35 and 70 years\n",
              "..          ...      ...   ...    ...   ...    ...    ...   ...     ...  ...    ...      ...    ...   ...                      ...\n",
              "501         501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0     21.0   9.67  22.4  between 35 and 70 years\n",
              "502         502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0     21.0   9.08  20.6       70 years and older\n",
              "503         503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0     21.0   5.64  23.9       70 years and older\n",
              "504         504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0     21.0   6.48  22.0       70 years and older\n",
              "505         505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0     21.0   7.88  11.9       70 years and older\n",
              "\n",
              "[506 rows x 15 columns]"
            ],
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              "\n",
              "  <div id=\"df-c326b3ec-7099-445d-a3d8-be566fa97e87\" class=\"colab-df-container\">\n",
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              "<style scoped>\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>LSTAT</th>\n",
              "      <th>MEDV</th>\n",
              "      <th>Age_group</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>4.98</td>\n",
              "      <td>24.0</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>9.14</td>\n",
              "      <td>21.6</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>4.03</td>\n",
              "      <td>34.7</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>2.94</td>\n",
              "      <td>33.4</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>5.33</td>\n",
              "      <td>36.2</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>501</td>\n",
              "      <td>0.06263</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.593</td>\n",
              "      <td>69.1</td>\n",
              "      <td>2.4786</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>9.67</td>\n",
              "      <td>22.4</td>\n",
              "      <td>between 35 and 70 years</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>502</td>\n",
              "      <td>0.04527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.120</td>\n",
              "      <td>76.7</td>\n",
              "      <td>2.2875</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>9.08</td>\n",
              "      <td>20.6</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>503</td>\n",
              "      <td>0.06076</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.976</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2.1675</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>5.64</td>\n",
              "      <td>23.9</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>504</td>\n",
              "      <td>0.10959</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.794</td>\n",
              "      <td>89.3</td>\n",
              "      <td>2.3889</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>6.48</td>\n",
              "      <td>22.0</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>505</td>\n",
              "      <td>0.04741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.030</td>\n",
              "      <td>80.8</td>\n",
              "      <td>2.5050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7.88</td>\n",
              "      <td>11.9</td>\n",
              "      <td>70 years and older</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>506 rows × 15 columns</p>\n",
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          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "State the hypothesis\n",
        "\n",
        "Null-hypothesis: the three population means are equal\n",
        "\n",
        "Alterntive-hypothesis: At least one of the means differ"
      ],
      "metadata": {
        "id": "LfoSoDkssH9p"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "low = boston_df[boston_df[\"Age_group\"] == '35 years and younger'][\"MEDV\"]\n",
        "mid = boston_df[boston_df[\"Age_group\"] == 'between 35 and 70 years'][\"MEDV\"]\n",
        "high = boston_df[boston_df[\"Age_group\"] == '70 years and older'][\"MEDV\"]"
      ],
      "metadata": {
        "id": "QS_Pm_FzsQ6k"
      },
      "execution_count": 108,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "f_stats, p_value = scipy.stats.f_oneway(low,mid,high,axis=0)"
      ],
      "metadata": {
        "id": "oOGSOLIDsTPd"
      },
      "execution_count": 109,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"F-Statistic={0}, P-value={1}\".format(f_stats,p_value))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lkRpTpIksWWf",
        "outputId": "72b2c3be-435f-4323-baf4-9bee342d6d12"
      },
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "F-Statistic=36.40764999196599, P-value=1.7105011022702984e-15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "p-value is > alpha value (0.05) hence failed to reject null hypothesis."
      ],
      "metadata": {
        "id": "0jtCmk7WsYiA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***5.3. Can we conclude that there is no relationship between Nitric oxide concentrations and proportion of non-retail business acres per town? (Pearson Correlation)***\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "W2BOv0q4tJYH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "State the hypothesis\n",
        "\n",
        " Null-hypothesis: NOX is not correlated with INDUS\n",
        "\n",
        " Alternative-hypothesis: NOX is correlated with INDUS"
      ],
      "metadata": {
        "id": "Z3UUHI1qtz3v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pearson,p_value = scipy.stats.pearsonr(boston_df[\"NOX\"],boston_df[\"INDUS\"])"
      ],
      "metadata": {
        "id": "wzNIkP0yts-L"
      },
      "execution_count": 111,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Pearson Coefficient value={0}, P-value={1}\".format(pearson,p_value))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XF2qoKE5t9W5",
        "outputId": "b86aa013-7df8-4366-bd0b-2512f9f6d7eb"
      },
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Pearson Coefficient value=0.7636514469209151, P-value=7.913361061239527e-98\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "8dM-3a8Bua1X"
      },
      "execution_count": 112,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Pvalue < 0.05, thus Null-hypothesis is rejected. Thus NOX is correlated with INDUS"
      ],
      "metadata": {
        "id": "MGGF2dNUuAff"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***5.4. What is the impact of an additional weighted distance  to the five Boston employment centres on the median value of owner occupied homes? (Regression analysis)***"
      ],
      "metadata": {
        "id": "GNeiPGbquYF_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "State Hypothesis\n",
        "\n",
        "Null-hypothesis: weighted distances to five Boston employment centres are not related to median value\n",
        "\n",
        "Alternative-hypothesis: weighted distances to five Boston employment centres are related to median value"
      ],
      "metadata": {
        "id": "0_5ZIWD0uc40"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LIjBDJxIuoMP",
        "outputId": "988e6237-8a42-4117-ae3b-4f7d1c63a5cf"
      },
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Unnamed: 0', 'CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX', 'PTRATIO', 'LSTAT', 'MEDV', 'Age_group'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = boston_df['MEDV']\n",
        "b = boston_df['DIS']"
      ],
      "metadata": {
        "id": "oxQ7k8iNuvet"
      },
      "execution_count": 114,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = sm.add_constant(a)"
      ],
      "metadata": {
        "id": "Kp6t41zyu5L3"
      },
      "execution_count": 115,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "results = sm.OLS(b,a).fit()"
      ],
      "metadata": {
        "id": "x9pSm2lbu9ho"
      },
      "execution_count": 116,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "results.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "Km6dj2kDvAik",
        "outputId": "9f4ecf62-0868-4eb0-98d2-8223e3958735"
      },
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                            OLS Regression Results                            \n",
              "==============================================================================\n",
              "Dep. Variable:                    DIS   R-squared:                       0.062\n",
              "Model:                            OLS   Adj. R-squared:                  0.061\n",
              "Method:                 Least Squares   F-statistic:                     33.58\n",
              "Date:                Thu, 17 Aug 2023   Prob (F-statistic):           1.21e-08\n",
              "Time:                        18:53:01   Log-Likelihood:                -1078.0\n",
              "No. Observations:                 506   AIC:                             2160.\n",
              "Df Residuals:                     504   BIC:                             2168.\n",
              "Df Model:                           1                                         \n",
              "Covariance Type:            nonrobust                                         \n",
              "==============================================================================\n",
              "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
              "------------------------------------------------------------------------------\n",
              "const          2.5057      0.240     10.428      0.000       2.034       2.978\n",
              "MEDV           0.0572      0.010      5.795      0.000       0.038       0.077\n",
              "==============================================================================\n",
              "Omnibus:                       70.837   Durbin-Watson:                   0.138\n",
              "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               98.167\n",
              "Skew:                           1.000   Prob(JB):                     4.82e-22\n",
              "Kurtosis:                       3.809   Cond. No.                         64.5\n",
              "==============================================================================\n",
              "\n",
              "Notes:\n",
              "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
              "\"\"\""
            ],
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>OLS Regression Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>           <td>DIS</td>       <th>  R-squared:         </th> <td>   0.062</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.061</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   33.58</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>             <td>Thu, 17 Aug 2023</td> <th>  Prob (F-statistic):</th> <td>1.21e-08</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>                 <td>18:53:01</td>     <th>  Log-Likelihood:    </th> <td> -1078.0</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>No. Observations:</th>      <td>   506</td>      <th>  AIC:               </th> <td>   2160.</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Residuals:</th>          <td>   504</td>      <th>  BIC:               </th> <td>   2168.</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "    <td></td>       <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>const</th> <td>    2.5057</td> <td>    0.240</td> <td>   10.428</td> <td> 0.000</td> <td>    2.034</td> <td>    2.978</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>MEDV</th>  <td>    0.0572</td> <td>    0.010</td> <td>    5.795</td> <td> 0.000</td> <td>    0.038</td> <td>    0.077</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "  <th>Omnibus:</th>       <td>70.837</td> <th>  Durbin-Watson:     </th> <td>   0.138</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(Omnibus):</th> <td> 0.000</td> <th>  Jarque-Bera (JB):  </th> <td>  98.167</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Skew:</th>          <td> 1.000</td> <th>  Prob(JB):          </th> <td>4.82e-22</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Kurtosis:</th>      <td> 3.809</td> <th>  Cond. No.          </th> <td>    64.5</td>\n",
              "</tr>\n",
              "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
            ],
            "text/latex": "\\begin{center}\n\\begin{tabular}{lclc}\n\\toprule\n\\textbf{Dep. Variable:}    &       DIS        & \\textbf{  R-squared:         } &     0.062   \\\\\n\\textbf{Model:}            &       OLS        & \\textbf{  Adj. R-squared:    } &     0.061   \\\\\n\\textbf{Method:}           &  Least Squares   & \\textbf{  F-statistic:       } &     33.58   \\\\\n\\textbf{Date:}             & Thu, 17 Aug 2023 & \\textbf{  Prob (F-statistic):} &  1.21e-08   \\\\\n\\textbf{Time:}             &     18:53:01     & \\textbf{  Log-Likelihood:    } &   -1078.0   \\\\\n\\textbf{No. Observations:} &         506      & \\textbf{  AIC:               } &     2160.   \\\\\n\\textbf{Df Residuals:}     &         504      & \\textbf{  BIC:               } &     2168.   \\\\\n\\textbf{Df Model:}         &           1      & \\textbf{                     } &             \\\\\n\\textbf{Covariance Type:}  &    nonrobust     & \\textbf{                     } &             \\\\\n\\bottomrule\n\\end{tabular}\n\\begin{tabular}{lcccccc}\n               & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n\\midrule\n\\textbf{const} &       2.5057  &        0.240     &    10.428  &         0.000        &        2.034    &        2.978     \\\\\n\\textbf{MEDV}  &       0.0572  &        0.010     &     5.795  &         0.000        &        0.038    &        0.077     \\\\\n\\bottomrule\n\\end{tabular}\n\\begin{tabular}{lclc}\n\\textbf{Omnibus:}       & 70.837 & \\textbf{  Durbin-Watson:     } &    0.138  \\\\\n\\textbf{Prob(Omnibus):} &  0.000 & \\textbf{  Jarque-Bera (JB):  } &   98.167  \\\\\n\\textbf{Skew:}          &  1.000 & \\textbf{  Prob(JB):          } & 4.82e-22  \\\\\n\\textbf{Kurtosis:}      &  3.809 & \\textbf{  Cond. No.          } &     64.5  \\\\\n\\bottomrule\n\\end{tabular}\n%\\caption{OLS Regression Results}\n\\end{center}\n\nNotes: \\newline\n [1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate Pearson Coeffiecent value\n",
        "np.sqrt(0.062)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J1xHricYvKDT",
        "outputId": "26982477-e2df-4f25-e43c-02cec90dd8e7"
      },
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.24899799195977465"
            ]
          },
          "metadata": {},
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " Pearson Coeffiecent value is 0.25, indicating weak correlation between two features"
      ],
      "metadata": {
        "id": "DPq7RMVkvO7W"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "Q5j1iRayvhqm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boston_df.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "8MeCVu_8vhzT",
        "outputId": "2b57f8dc-2b58-472a-e54b-04ebedc68a37"
      },
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Unnamed: 0      CRIM        ZN     INDUS      CHAS       NOX        RM       AGE       DIS       RAD       TAX   PTRATIO     LSTAT      MEDV\n",
              "Unnamed: 0    1.000000  0.407407 -0.103393  0.399439 -0.003759  0.398736 -0.079971  0.203784 -0.302211  0.686002  0.666626  0.291074  0.258465 -0.226604\n",
              "CRIM          0.407407  1.000000 -0.200469  0.406583 -0.055892  0.420972 -0.219247  0.352734 -0.379670  0.625505  0.582764  0.289946  0.455621 -0.388305\n",
              "ZN           -0.103393 -0.200469  1.000000 -0.533828 -0.042697 -0.516604  0.311991 -0.569537  0.664408 -0.311948 -0.314563 -0.391679 -0.412995  0.360445\n",
              "INDUS         0.399439  0.406583 -0.533828  1.000000  0.062938  0.763651 -0.391676  0.644779 -0.708027  0.595129  0.720760  0.383248  0.603800 -0.483725\n",
              "CHAS         -0.003759 -0.055892 -0.042697  0.062938  1.000000  0.091203  0.091251  0.086518 -0.099176 -0.007368 -0.035587 -0.121515 -0.053929  0.175260\n",
              "NOX           0.398736  0.420972 -0.516604  0.763651  0.091203  1.000000 -0.302188  0.731470 -0.769230  0.611441  0.668023  0.188933  0.590879 -0.427321\n",
              "RM           -0.079971 -0.219247  0.311991 -0.391676  0.091251 -0.302188  1.000000 -0.240265  0.205246 -0.209847 -0.292048 -0.355501 -0.613808  0.695360\n",
              "AGE           0.203784  0.352734 -0.569537  0.644779  0.086518  0.731470 -0.240265  1.000000 -0.747881  0.456022  0.506456  0.261515  0.602339 -0.376955\n",
              "DIS          -0.302211 -0.379670  0.664408 -0.708027 -0.099176 -0.769230  0.205246 -0.747881  1.000000 -0.494588 -0.534432 -0.232471 -0.496996  0.249929\n",
              "RAD           0.686002  0.625505 -0.311948  0.595129 -0.007368  0.611441 -0.209847  0.456022 -0.494588  1.000000  0.910228  0.464741  0.488676 -0.381626\n",
              "TAX           0.666626  0.582764 -0.314563  0.720760 -0.035587  0.668023 -0.292048  0.506456 -0.534432  0.910228  1.000000  0.460853  0.543993 -0.468536\n",
              "PTRATIO       0.291074  0.289946 -0.391679  0.383248 -0.121515  0.188933 -0.355501  0.261515 -0.232471  0.464741  0.460853  1.000000  0.374044 -0.507787\n",
              "LSTAT         0.258465  0.455621 -0.412995  0.603800 -0.053929  0.590879 -0.613808  0.602339 -0.496996  0.488676  0.543993  0.374044  1.000000 -0.737663\n",
              "MEDV         -0.226604 -0.388305  0.360445 -0.483725  0.175260 -0.427321  0.695360 -0.376955  0.249929 -0.381626 -0.468536 -0.507787 -0.737663  1.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0c98b68b-294b-4524-8a0b-d3def42c5307\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>LSTAT</th>\n",
              "      <th>MEDV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.407407</td>\n",
              "      <td>-0.103393</td>\n",
              "      <td>0.399439</td>\n",
              "      <td>-0.003759</td>\n",
              "      <td>0.398736</td>\n",
              "      <td>-0.079971</td>\n",
              "      <td>0.203784</td>\n",
              "      <td>-0.302211</td>\n",
              "      <td>0.686002</td>\n",
              "      <td>0.666626</td>\n",
              "      <td>0.291074</td>\n",
              "      <td>0.258465</td>\n",
              "      <td>-0.226604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CRIM</th>\n",
              "      <td>0.407407</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.200469</td>\n",
              "      <td>0.406583</td>\n",
              "      <td>-0.055892</td>\n",
              "      <td>0.420972</td>\n",
              "      <td>-0.219247</td>\n",
              "      <td>0.352734</td>\n",
              "      <td>-0.379670</td>\n",
              "      <td>0.625505</td>\n",
              "      <td>0.582764</td>\n",
              "      <td>0.289946</td>\n",
              "      <td>0.455621</td>\n",
              "      <td>-0.388305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZN</th>\n",
              "      <td>-0.103393</td>\n",
              "      <td>-0.200469</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.533828</td>\n",
              "      <td>-0.042697</td>\n",
              "      <td>-0.516604</td>\n",
              "      <td>0.311991</td>\n",
              "      <td>-0.569537</td>\n",
              "      <td>0.664408</td>\n",
              "      <td>-0.311948</td>\n",
              "      <td>-0.314563</td>\n",
              "      <td>-0.391679</td>\n",
              "      <td>-0.412995</td>\n",
              "      <td>0.360445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INDUS</th>\n",
              "      <td>0.399439</td>\n",
              "      <td>0.406583</td>\n",
              "      <td>-0.533828</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.062938</td>\n",
              "      <td>0.763651</td>\n",
              "      <td>-0.391676</td>\n",
              "      <td>0.644779</td>\n",
              "      <td>-0.708027</td>\n",
              "      <td>0.595129</td>\n",
              "      <td>0.720760</td>\n",
              "      <td>0.383248</td>\n",
              "      <td>0.603800</td>\n",
              "      <td>-0.483725</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CHAS</th>\n",
              "      <td>-0.003759</td>\n",
              "      <td>-0.055892</td>\n",
              "      <td>-0.042697</td>\n",
              "      <td>0.062938</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.091203</td>\n",
              "      <td>0.091251</td>\n",
              "      <td>0.086518</td>\n",
              "      <td>-0.099176</td>\n",
              "      <td>-0.007368</td>\n",
              "      <td>-0.035587</td>\n",
              "      <td>-0.121515</td>\n",
              "      <td>-0.053929</td>\n",
              "      <td>0.175260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NOX</th>\n",
              "      <td>0.398736</td>\n",
              "      <td>0.420972</td>\n",
              "      <td>-0.516604</td>\n",
              "      <td>0.763651</td>\n",
              "      <td>0.091203</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.302188</td>\n",
              "      <td>0.731470</td>\n",
              "      <td>-0.769230</td>\n",
              "      <td>0.611441</td>\n",
              "      <td>0.668023</td>\n",
              "      <td>0.188933</td>\n",
              "      <td>0.590879</td>\n",
              "      <td>-0.427321</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RM</th>\n",
              "      <td>-0.079971</td>\n",
              "      <td>-0.219247</td>\n",
              "      <td>0.311991</td>\n",
              "      <td>-0.391676</td>\n",
              "      <td>0.091251</td>\n",
              "      <td>-0.302188</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.240265</td>\n",
              "      <td>0.205246</td>\n",
              "      <td>-0.209847</td>\n",
              "      <td>-0.292048</td>\n",
              "      <td>-0.355501</td>\n",
              "      <td>-0.613808</td>\n",
              "      <td>0.695360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AGE</th>\n",
              "      <td>0.203784</td>\n",
              "      <td>0.352734</td>\n",
              "      <td>-0.569537</td>\n",
              "      <td>0.644779</td>\n",
              "      <td>0.086518</td>\n",
              "      <td>0.731470</td>\n",
              "      <td>-0.240265</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.747881</td>\n",
              "      <td>0.456022</td>\n",
              "      <td>0.506456</td>\n",
              "      <td>0.261515</td>\n",
              "      <td>0.602339</td>\n",
              "      <td>-0.376955</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DIS</th>\n",
              "      <td>-0.302211</td>\n",
              "      <td>-0.379670</td>\n",
              "      <td>0.664408</td>\n",
              "      <td>-0.708027</td>\n",
              "      <td>-0.099176</td>\n",
              "      <td>-0.769230</td>\n",
              "      <td>0.205246</td>\n",
              "      <td>-0.747881</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.494588</td>\n",
              "      <td>-0.534432</td>\n",
              "      <td>-0.232471</td>\n",
              "      <td>-0.496996</td>\n",
              "      <td>0.249929</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RAD</th>\n",
              "      <td>0.686002</td>\n",
              "      <td>0.625505</td>\n",
              "      <td>-0.311948</td>\n",
              "      <td>0.595129</td>\n",
              "      <td>-0.007368</td>\n",
              "      <td>0.611441</td>\n",
              "      <td>-0.209847</td>\n",
              "      <td>0.456022</td>\n",
              "      <td>-0.494588</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.910228</td>\n",
              "      <td>0.464741</td>\n",
              "      <td>0.488676</td>\n",
              "      <td>-0.381626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TAX</th>\n",
              "      <td>0.666626</td>\n",
              "      <td>0.582764</td>\n",
              "      <td>-0.314563</td>\n",
              "      <td>0.720760</td>\n",
              "      <td>-0.035587</td>\n",
              "      <td>0.668023</td>\n",
              "      <td>-0.292048</td>\n",
              "      <td>0.506456</td>\n",
              "      <td>-0.534432</td>\n",
              "      <td>0.910228</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.460853</td>\n",
              "      <td>0.543993</td>\n",
              "      <td>-0.468536</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PTRATIO</th>\n",
              "      <td>0.291074</td>\n",
              "      <td>0.289946</td>\n",
              "      <td>-0.391679</td>\n",
              "      <td>0.383248</td>\n",
              "      <td>-0.121515</td>\n",
              "      <td>0.188933</td>\n",
              "      <td>-0.355501</td>\n",
              "      <td>0.261515</td>\n",
              "      <td>-0.232471</td>\n",
              "      <td>0.464741</td>\n",
              "      <td>0.460853</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.374044</td>\n",
              "      <td>-0.507787</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LSTAT</th>\n",
              "      <td>0.258465</td>\n",
              "      <td>0.455621</td>\n",
              "      <td>-0.412995</td>\n",
              "      <td>0.603800</td>\n",
              "      <td>-0.053929</td>\n",
              "      <td>0.590879</td>\n",
              "      <td>-0.613808</td>\n",
              "      <td>0.602339</td>\n",
              "      <td>-0.496996</td>\n",
              "      <td>0.488676</td>\n",
              "      <td>0.543993</td>\n",
              "      <td>0.374044</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.737663</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MEDV</th>\n",
              "      <td>-0.226604</td>\n",
              "      <td>-0.388305</td>\n",
              "      <td>0.360445</td>\n",
              "      <td>-0.483725</td>\n",
              "      <td>0.175260</td>\n",
              "      <td>-0.427321</td>\n",
              "      <td>0.695360</td>\n",
              "      <td>-0.376955</td>\n",
              "      <td>0.249929</td>\n",
              "      <td>-0.381626</td>\n",
              "      <td>-0.468536</td>\n",
              "      <td>-0.507787</td>\n",
              "      <td>-0.737663</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-buttons div {\n",
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              "\n",
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              "        document.querySelector('#df-0c98b68b-294b-4524-8a0b-d3def42c5307 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
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              "        const element = document.querySelector('#df-0c98b68b-294b-4524-8a0b-d3def42c5307');\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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              "\n",
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              "\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const charts = await google.colab.kernel.invokeFunction(\n",
              "          'suggestCharts', [key], {});\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0c7c4b58-3961-4758-bdcd-6f8dd4ce0c7e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,6))\n",
        "sns.heatmap(boston_df.corr(),cmap=\"coolwarm\",annot=True,fmt='.2f',linewidths=2, cbar=False)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "Vcxods11vl9j",
        "outputId": "3c0c8f18-ebdc-41eb-9921-48c9d4ea0561"
      },
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}