data_set_.ipynb

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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns \n",
        "from matplotlib import pyplot as pls"
      ]
    },
    {
      "cell_type": "code",
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        "id": "oyF23BpRWhcA"
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      "source": [
        "mydata=pd.read_csv(\"https://raw.githubusercontent.com/Premalatha-success/Datasets/main/CardioGoodFitness-1.csv\")"
      ],
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        "id": "nX4pzpK4VZAE"
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      "outputs": []
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      "source": [
        "mydata.columns"
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        "outputId": "9857b89e-d76d-4606-e767-e1f95a92f084"
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            "text/plain": [
              "Index(['Product', 'Age', 'Gender', 'Education', 'MaritalStatus', 'Usage',\n",
              "       'Fitness', 'Income', 'Miles'],\n",
              "      dtype='object')"
            ]
          },
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          "execution_count": 4
        }
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        "mydata.info()"
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 180 entries, 0 to 179\n",
            "Data columns (total 9 columns):\n",
            " #   Column         Non-Null Count  Dtype \n",
            "---  ------         --------------  ----- \n",
            " 0   Product        180 non-null    object\n",
            " 1   Age            180 non-null    int64 \n",
            " 2   Gender         180 non-null    object\n",
            " 3   Education      180 non-null    int64 \n",
            " 4   MaritalStatus  180 non-null    object\n",
            " 5   Usage          180 non-null    int64 \n",
            " 6   Fitness        180 non-null    int64 \n",
            " 7   Income         180 non-null    int64 \n",
            " 8   Miles          180 non-null    int64 \n",
            "dtypes: int64(6), object(3)\n",
            "memory usage: 12.8+ KB\n"
          ]
        }
      ]
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      "source": [
        "mydata.isnull().sum()"
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              "Product          0\n",
              "Age              0\n",
              "Gender           0\n",
              "Education        0\n",
              "MaritalStatus    0\n",
              "Usage            0\n",
              "Fitness          0\n",
              "Income           0\n",
              "Miles            0\n",
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        "mydata.describe()"
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              "              Age   Education       Usage     Fitness         Income  \\\n",
              "count  180.000000  180.000000  180.000000  180.000000     180.000000   \n",
              "mean    28.788889   15.572222    3.455556    3.311111   53719.577778   \n",
              "std      6.943498    1.617055    1.084797    0.958869   16506.684226   \n",
              "min     18.000000   12.000000    2.000000    1.000000   29562.000000   \n",
              "25%     24.000000   14.000000    3.000000    3.000000   44058.750000   \n",
              "50%     26.000000   16.000000    3.000000    3.000000   50596.500000   \n",
              "75%     33.000000   16.000000    4.000000    4.000000   58668.000000   \n",
              "max     50.000000   21.000000    7.000000    5.000000  104581.000000   \n",
              "\n",
              "            Miles  \n",
              "count  180.000000  \n",
              "mean   103.194444  \n",
              "std     51.863605  \n",
              "min     21.000000  \n",
              "25%     66.000000  \n",
              "50%     94.000000  \n",
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              "max    360.000000  "
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              "               count unique        top freq          mean           std  \\\n",
              "Product          180      3      TM195   80           NaN           NaN   \n",
              "Age            180.0    NaN        NaN  NaN     28.788889      6.943498   \n",
              "Gender           180      2       Male  104           NaN           NaN   \n",
              "Education      180.0    NaN        NaN  NaN     15.572222      1.617055   \n",
              "MaritalStatus    180      2  Partnered  107           NaN           NaN   \n",
              "Usage          180.0    NaN        NaN  NaN      3.455556      1.084797   \n",
              "Fitness        180.0    NaN        NaN  NaN      3.311111      0.958869   \n",
              "Income         180.0    NaN        NaN  NaN  53719.577778  16506.684226   \n",
              "Miles          180.0    NaN        NaN  NaN    103.194444     51.863605   \n",
              "\n",
              "                   min       25%      50%      75%       max  \n",
              "Product            NaN       NaN      NaN      NaN       NaN  \n",
              "Age               18.0      24.0     26.0     33.0      50.0  \n",
              "Gender             NaN       NaN      NaN      NaN       NaN  \n",
              "Education         12.0      14.0     16.0     16.0      21.0  \n",
              "MaritalStatus      NaN       NaN      NaN      NaN       NaN  \n",
              "Usage              2.0       3.0      3.0      4.0       7.0  \n",
              "Fitness            1.0       3.0      3.0      4.0       5.0  \n",
              "Income         29562.0  44058.75  50596.5  58668.0  104581.0  \n",
              "Miles             21.0      66.0     94.0   114.75     360.0  "
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              "      <td>180.0</td>\n",
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              "      <td>15.572222</td>\n",
              "      <td>1.617055</td>\n",
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              "      <td>2</td>\n",
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              "      <th>Usage</th>\n",
              "      <td>180.0</td>\n",
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              "      <td>180.0</td>\n",
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              "      <td>66.0</td>\n",
              "      <td>94.0</td>\n",
              "      <td>114.75</td>\n",
              "      <td>360.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f16afb62-fe2f-41a2-9c2d-517e514ffb59')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-f16afb62-fe2f-41a2-9c2d-517e514ffb59 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-f16afb62-fe2f-41a2-9c2d-517e514ffb59');\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": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "9GZj3djUY-4M"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}