Predicting_Causes_for_CardioVasular_Disease.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Predicting_Causes_for_CardioVasular_Disease.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNWgAvZFVjZtQyojOUt3Wzb",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/annanya-mathur/Cardiovascular-Disease-Detection/blob/main/Predicting_Causes_for_CardioVasular_Disease.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HPMJmC5LuZMz"
      },
      "source": [
        "  **ATTRIBUTE INFO-** \n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "     \n",
        "1.  age \n",
        "2.  sex       \n",
        "3. chest pain type  (4 values)       \n",
        "4. resting blood pressure  \n",
        "5. serum cholestoral in mg/dl      \n",
        "6. fasting blood sugar > 120 mg/dl       \n",
        "7. resting electrocardiographic results  (values 0,1,2) \n",
        "8. maximum heart rate achieved  \n",
        "9. exercise induced angina    \n",
        "10. oldpeak = ST depression induced by exercise relative to rest   \n",
        "11. the slope of the peak exercise ST segment     \n",
        "12. number of major vessels (0-3) colored by flourosopy        \n",
        "13.  thal: 3 = normal; 6 = fixed defect; 7 = reversable defect   \n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a_P3nMA_uiCm"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as pt\n",
        "import seaborn as sb"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yay8_Yxb5o05"
      },
      "source": [
        "from google.colab import files"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": "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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "PUrrGpeq57Yt",
        "outputId": "096338e0-3bd0-4d3c-8734-65ae896369e7"
      },
      "source": [
        "uploaded=files.upload()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-88e6de4f-475f-427f-902c-ed8a15423366\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-88e6de4f-475f-427f-902c-ed8a15423366\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving cardio-statlog_csv.csv to cardio-statlog_csv.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "04olE5Ex6H3Q",
        "outputId": "a50072c0-2a25-4ff9-e04e-a79a1c3485ad"
      },
      "source": [
        "dataframe=pd.read_csv('cardio-statlog_csv.csv')\n",
        "dataframe.head(10)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>chest</th>\n",
              "      <th>resting_blood_pressure</th>\n",
              "      <th>serum_cholestoral</th>\n",
              "      <th>fasting_blood_sugar</th>\n",
              "      <th>resting_electrocardiographic_results</th>\n",
              "      <th>maximum_heart_rate_achieved</th>\n",
              "      <th>exercise_induced_angina</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>number_of_major_vessels</th>\n",
              "      <th>thal</th>\n",
              "      <th>cardio</th>\n",
              "      <th>diabetes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>130</td>\n",
              "      <td>322</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>109</td>\n",
              "      <td>0</td>\n",
              "      <td>2.4</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>67</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>115</td>\n",
              "      <td>564</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>160</td>\n",
              "      <td>0</td>\n",
              "      <td>1.6</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>57</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>124</td>\n",
              "      <td>261</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>141</td>\n",
              "      <td>0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>64</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>128</td>\n",
              "      <td>263</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>105</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>74</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>120</td>\n",
              "      <td>269</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>121</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>120</td>\n",
              "      <td>177</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>0</td>\n",
              "      <td>0.4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>130</td>\n",
              "      <td>256</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>142</td>\n",
              "      <td>1</td>\n",
              "      <td>0.6</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>59</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>110</td>\n",
              "      <td>239</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>142</td>\n",
              "      <td>1</td>\n",
              "      <td>1.2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>140</td>\n",
              "      <td>293</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>170</td>\n",
              "      <td>0</td>\n",
              "      <td>1.2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>63</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>150</td>\n",
              "      <td>407</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>154</td>\n",
              "      <td>0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  sex  chest  ...  thal  cardio  diabetes\n",
              "0   70    1      4  ...     3       1         1\n",
              "1   67    0      3  ...     7       0         0\n",
              "2   57    1      2  ...     7       1         1\n",
              "3   64    1      4  ...     7       0         1\n",
              "4   74    0      2  ...     3       0         0\n",
              "5   65    1      4  ...     7       0         0\n",
              "6   56    1      3  ...     6       1         1\n",
              "7   59    1      4  ...     7       1         1\n",
              "8   60    1      4  ...     7       1         1\n",
              "9   63    0      4  ...     7       1         1\n",
              "\n",
              "[10 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "srB1F-qR6cmk",
        "outputId": "cc5eadb0-c44e-4641-8159-44d3d3a38aec"
      },
      "source": [
        "dataframe.isna().sum()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age                                     0\n",
              "sex                                     0\n",
              "chest                                   0\n",
              "resting_blood_pressure                  0\n",
              "serum_cholestoral                       0\n",
              "fasting_blood_sugar                     0\n",
              "resting_electrocardiographic_results    0\n",
              "maximum_heart_rate_achieved             0\n",
              "exercise_induced_angina                 0\n",
              "oldpeak                                 0\n",
              "slope                                   0\n",
              "number_of_major_vessels                 0\n",
              "thal                                    0\n",
              "cardio                                  0\n",
              "diabetes                                0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LA5NOdnEB9BI",
        "outputId": "35aff6da-c491-4fea-803f-c62124856039"
      },
      "source": [
        "dataframe.isnull().values.any()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LQo4zwhkCGx-",
        "outputId": "4b7198a4-3929-4e6e-81d7-1772dd3013e1"
      },
      "source": [
        "dataframe.shape"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(270, 15)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DbxkxP0NCQOD"
      },
      "source": [
        "**Generating basic statistics**\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "As standard deviation\n",
        ", Mean \n",
        ", Count\n",
        ", MAX value\n",
        ", MIN value\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 304
        },
        "id": "5LF-nCl_CK29",
        "outputId": "ac71af27-0f61-4a82-d642-03593e899218"
      },
      "source": [
        "dataframe.describe()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>chest</th>\n",
              "      <th>resting_blood_pressure</th>\n",
              "      <th>serum_cholestoral</th>\n",
              "      <th>fasting_blood_sugar</th>\n",
              "      <th>resting_electrocardiographic_results</th>\n",
              "      <th>maximum_heart_rate_achieved</th>\n",
              "      <th>exercise_induced_angina</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>number_of_major_vessels</th>\n",
              "      <th>thal</th>\n",
              "      <th>cardio</th>\n",
              "      <th>diabetes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.00000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "      <td>270.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>54.433333</td>\n",
              "      <td>0.677778</td>\n",
              "      <td>3.174074</td>\n",
              "      <td>131.344444</td>\n",
              "      <td>249.659259</td>\n",
              "      <td>0.148148</td>\n",
              "      <td>1.022222</td>\n",
              "      <td>149.677778</td>\n",
              "      <td>0.329630</td>\n",
              "      <td>1.05000</td>\n",
              "      <td>1.585185</td>\n",
              "      <td>0.670370</td>\n",
              "      <td>4.696296</td>\n",
              "      <td>0.444444</td>\n",
              "      <td>0.414815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.109067</td>\n",
              "      <td>0.468195</td>\n",
              "      <td>0.950090</td>\n",
              "      <td>17.861608</td>\n",
              "      <td>51.686237</td>\n",
              "      <td>0.355906</td>\n",
              "      <td>0.997891</td>\n",
              "      <td>23.165717</td>\n",
              "      <td>0.470952</td>\n",
              "      <td>1.14521</td>\n",
              "      <td>0.614390</td>\n",
              "      <td>0.943896</td>\n",
              "      <td>1.940659</td>\n",
              "      <td>0.497827</td>\n",
              "      <td>0.493605</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>94.000000</td>\n",
              "      <td>126.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>213.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>133.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>55.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>130.000000</td>\n",
              "      <td>245.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>153.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.80000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>61.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>280.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.60000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>77.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>564.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>202.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.20000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              age         sex       chest  ...        thal      cardio    diabetes\n",
              "count  270.000000  270.000000  270.000000  ...  270.000000  270.000000  270.000000\n",
              "mean    54.433333    0.677778    3.174074  ...    4.696296    0.444444    0.414815\n",
              "std      9.109067    0.468195    0.950090  ...    1.940659    0.497827    0.493605\n",
              "min     29.000000    0.000000    1.000000  ...    3.000000    0.000000    0.000000\n",
              "25%     48.000000    0.000000    3.000000  ...    3.000000    0.000000    0.000000\n",
              "50%     55.000000    1.000000    3.000000  ...    3.000000    0.000000    0.000000\n",
              "75%     61.000000    1.000000    4.000000  ...    7.000000    1.000000    1.000000\n",
              "max     77.000000    1.000000    4.000000  ...    7.000000    1.000000    1.000000\n",
              "\n",
              "[8 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "npapkmhTDbK7",
        "outputId": "c0283318-23e9-4d60-8a12-be68682ef410"
      },
      "source": [
        "dataframe['cardio'].value_counts()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    150\n",
              "1    120\n",
              "Name: cardio, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3T15ZdGiDqz5"
      },
      "source": [
        "According to the dataset there are 120 people out of 270 having cardiovascular disease"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "nHf19kk7DCJI",
        "outputId": "0cc64a30-4aec-48a2-b45a-f11519d43089"
      },
      "source": [
        "sb.countplot(dataframe['cardio'])"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6c45d81790>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "id": "H9KaPCUFDYj2",
        "outputId": "ebdf1797-eb5e-47cb-a419-0539e2b5dcbd"
      },
      "source": [
        "pt.figure(figsize=(12,6))\n",
        "sb.countplot(x='age',hue='cardio',data=dataframe,palette='colorblind', edgecolor=sb.color_palette('dark',n_colors=1))"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6c4585c190>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ShYfTK88MwEU"
      },
      "source": [
        "**Here, we can clearly see that increase risk to cardiovascular disease is after age of 55**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 511
        },
        "id": "DFZpZz-YNBNt",
        "outputId": "697475e1-cecb-4b39-f86a-1671d42ed052"
      },
      "source": [
        "dataframe.corr()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>chest</th>\n",
              "      <th>resting_blood_pressure</th>\n",
              "      <th>serum_cholestoral</th>\n",
              "      <th>fasting_blood_sugar</th>\n",
              "      <th>resting_electrocardiographic_results</th>\n",
              "      <th>maximum_heart_rate_achieved</th>\n",
              "      <th>exercise_induced_angina</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>number_of_major_vessels</th>\n",
              "      <th>thal</th>\n",
              "      <th>cardio</th>\n",
              "      <th>diabetes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.094401</td>\n",
              "      <td>0.096920</td>\n",
              "      <td>0.273053</td>\n",
              "      <td>0.220056</td>\n",
              "      <td>0.123458</td>\n",
              "      <td>0.128171</td>\n",
              "      <td>-0.402215</td>\n",
              "      <td>0.098297</td>\n",
              "      <td>0.194234</td>\n",
              "      <td>0.159774</td>\n",
              "      <td>0.356081</td>\n",
              "      <td>0.106100</td>\n",
              "      <td>0.212322</td>\n",
              "      <td>0.193028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <td>-0.094401</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.034636</td>\n",
              "      <td>-0.062693</td>\n",
              "      <td>-0.201647</td>\n",
              "      <td>0.042140</td>\n",
              "      <td>0.039253</td>\n",
              "      <td>-0.076101</td>\n",
              "      <td>0.180022</td>\n",
              "      <td>0.097412</td>\n",
              "      <td>0.050545</td>\n",
              "      <td>0.086830</td>\n",
              "      <td>0.391046</td>\n",
              "      <td>0.297721</td>\n",
              "      <td>0.242716</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>chest</th>\n",
              "      <td>0.096920</td>\n",
              "      <td>0.034636</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.043196</td>\n",
              "      <td>0.090465</td>\n",
              "      <td>-0.098537</td>\n",
              "      <td>0.074325</td>\n",
              "      <td>-0.317682</td>\n",
              "      <td>0.353160</td>\n",
              "      <td>0.167244</td>\n",
              "      <td>0.136900</td>\n",
              "      <td>0.225890</td>\n",
              "      <td>0.262659</td>\n",
              "      <td>0.417436</td>\n",
              "      <td>0.392411</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>resting_blood_pressure</th>\n",
              "      <td>0.273053</td>\n",
              "      <td>-0.062693</td>\n",
              "      <td>-0.043196</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.173019</td>\n",
              "      <td>0.155681</td>\n",
              "      <td>0.116157</td>\n",
              "      <td>-0.039136</td>\n",
              "      <td>0.082793</td>\n",
              "      <td>0.222800</td>\n",
              "      <td>0.142472</td>\n",
              "      <td>0.085697</td>\n",
              "      <td>0.132045</td>\n",
              "      <td>0.155383</td>\n",
              "      <td>0.134683</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>serum_cholestoral</th>\n",
              "      <td>0.220056</td>\n",
              "      <td>-0.201647</td>\n",
              "      <td>0.090465</td>\n",
              "      <td>0.173019</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.025186</td>\n",
              "      <td>0.167652</td>\n",
              "      <td>-0.018739</td>\n",
              "      <td>0.078243</td>\n",
              "      <td>0.027709</td>\n",
              "      <td>-0.005755</td>\n",
              "      <td>0.126541</td>\n",
              "      <td>0.028836</td>\n",
              "      <td>0.118021</td>\n",
              "      <td>0.080602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fasting_blood_sugar</th>\n",
              "      <td>0.123458</td>\n",
              "      <td>0.042140</td>\n",
              "      <td>-0.098537</td>\n",
              "      <td>0.155681</td>\n",
              "      <td>0.025186</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.053499</td>\n",
              "      <td>0.022494</td>\n",
              "      <td>-0.004107</td>\n",
              "      <td>-0.025538</td>\n",
              "      <td>0.044076</td>\n",
              "      <td>0.123774</td>\n",
              "      <td>0.049237</td>\n",
              "      <td>-0.016319</td>\n",
              "      <td>-0.033701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>resting_electrocardiographic_results</th>\n",
              "      <td>0.128171</td>\n",
              "      <td>0.039253</td>\n",
              "      <td>0.074325</td>\n",
              "      <td>0.116157</td>\n",
              "      <td>0.167652</td>\n",
              "      <td>0.053499</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.074628</td>\n",
              "      <td>0.095098</td>\n",
              "      <td>0.120034</td>\n",
              "      <td>0.160614</td>\n",
              "      <td>0.114368</td>\n",
              "      <td>0.007337</td>\n",
              "      <td>0.182091</td>\n",
              "      <td>0.154801</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>maximum_heart_rate_achieved</th>\n",
              "      <td>-0.402215</td>\n",
              "      <td>-0.076101</td>\n",
              "      <td>-0.317682</td>\n",
              "      <td>-0.039136</td>\n",
              "      <td>-0.018739</td>\n",
              "      <td>0.022494</td>\n",
              "      <td>-0.074628</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.380719</td>\n",
              "      <td>-0.349045</td>\n",
              "      <td>-0.386847</td>\n",
              "      <td>-0.265333</td>\n",
              "      <td>-0.253397</td>\n",
              "      <td>-0.418514</td>\n",
              "      <td>-0.392372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>exercise_induced_angina</th>\n",
              "      <td>0.098297</td>\n",
              "      <td>0.180022</td>\n",
              "      <td>0.353160</td>\n",
              "      <td>0.082793</td>\n",
              "      <td>0.078243</td>\n",
              "      <td>-0.004107</td>\n",
              "      <td>0.095098</td>\n",
              "      <td>-0.380719</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.274672</td>\n",
              "      <td>0.255908</td>\n",
              "      <td>0.153347</td>\n",
              "      <td>0.321449</td>\n",
              "      <td>0.419303</td>\n",
              "      <td>0.385101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>oldpeak</th>\n",
              "      <td>0.194234</td>\n",
              "      <td>0.097412</td>\n",
              "      <td>0.167244</td>\n",
              "      <td>0.222800</td>\n",
              "      <td>0.027709</td>\n",
              "      <td>-0.025538</td>\n",
              "      <td>0.120034</td>\n",
              "      <td>-0.349045</td>\n",
              "      <td>0.274672</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.609712</td>\n",
              "      <td>0.255005</td>\n",
              "      <td>0.324333</td>\n",
              "      <td>0.417967</td>\n",
              "      <td>0.359067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>slope</th>\n",
              "      <td>0.159774</td>\n",
              "      <td>0.050545</td>\n",
              "      <td>0.136900</td>\n",
              "      <td>0.142472</td>\n",
              "      <td>-0.005755</td>\n",
              "      <td>0.044076</td>\n",
              "      <td>0.160614</td>\n",
              "      <td>-0.386847</td>\n",
              "      <td>0.255908</td>\n",
              "      <td>0.609712</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.109498</td>\n",
              "      <td>0.283678</td>\n",
              "      <td>0.337616</td>\n",
              "      <td>0.299825</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>number_of_major_vessels</th>\n",
              "      <td>0.356081</td>\n",
              "      <td>0.086830</td>\n",
              "      <td>0.225890</td>\n",
              "      <td>0.085697</td>\n",
              "      <td>0.126541</td>\n",
              "      <td>0.123774</td>\n",
              "      <td>0.114368</td>\n",
              "      <td>-0.265333</td>\n",
              "      <td>0.153347</td>\n",
              "      <td>0.255005</td>\n",
              "      <td>0.109498</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.255648</td>\n",
              "      <td>0.455336</td>\n",
              "      <td>0.398296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>thal</th>\n",
              "      <td>0.106100</td>\n",
              "      <td>0.391046</td>\n",
              "      <td>0.262659</td>\n",
              "      <td>0.132045</td>\n",
              "      <td>0.028836</td>\n",
              "      <td>0.049237</td>\n",
              "      <td>0.007337</td>\n",
              "      <td>-0.253397</td>\n",
              "      <td>0.321449</td>\n",
              "      <td>0.324333</td>\n",
              "      <td>0.283678</td>\n",
              "      <td>0.255648</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.525020</td>\n",
              "      <td>0.504559</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cardio</th>\n",
              "      <td>0.212322</td>\n",
              "      <td>0.297721</td>\n",
              "      <td>0.417436</td>\n",
              "      <td>0.155383</td>\n",
              "      <td>0.118021</td>\n",
              "      <td>-0.016319</td>\n",
              "      <td>0.182091</td>\n",
              "      <td>-0.418514</td>\n",
              "      <td>0.419303</td>\n",
              "      <td>0.417967</td>\n",
              "      <td>0.337616</td>\n",
              "      <td>0.455336</td>\n",
              "      <td>0.525020</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.895931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>diabetes</th>\n",
              "      <td>0.193028</td>\n",
              "      <td>0.242716</td>\n",
              "      <td>0.392411</td>\n",
              "      <td>0.134683</td>\n",
              "      <td>0.080602</td>\n",
              "      <td>-0.033701</td>\n",
              "      <td>0.154801</td>\n",
              "      <td>-0.392372</td>\n",
              "      <td>0.385101</td>\n",
              "      <td>0.359067</td>\n",
              "      <td>0.299825</td>\n",
              "      <td>0.398296</td>\n",
              "      <td>0.504559</td>\n",
              "      <td>0.895931</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                           age       sex  ...    cardio  diabetes\n",
              "age                                   1.000000 -0.094401  ...  0.212322  0.193028\n",
              "sex                                  -0.094401  1.000000  ...  0.297721  0.242716\n",
              "chest                                 0.096920  0.034636  ...  0.417436  0.392411\n",
              "resting_blood_pressure                0.273053 -0.062693  ...  0.155383  0.134683\n",
              "serum_cholestoral                     0.220056 -0.201647  ...  0.118021  0.080602\n",
              "fasting_blood_sugar                   0.123458  0.042140  ... -0.016319 -0.033701\n",
              "resting_electrocardiographic_results  0.128171  0.039253  ...  0.182091  0.154801\n",
              "maximum_heart_rate_achieved          -0.402215 -0.076101  ... -0.418514 -0.392372\n",
              "exercise_induced_angina               0.098297  0.180022  ...  0.419303  0.385101\n",
              "oldpeak                               0.194234  0.097412  ...  0.417967  0.359067\n",
              "slope                                 0.159774  0.050545  ...  0.337616  0.299825\n",
              "number_of_major_vessels               0.356081  0.086830  ...  0.455336  0.398296\n",
              "thal                                  0.106100  0.391046  ...  0.525020  0.504559\n",
              "cardio                                0.212322  0.297721  ...  1.000000  0.895931\n",
              "diabetes                              0.193028  0.242716  ...  0.895931  1.000000\n",
              "\n",
              "[15 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 675
        },
        "id": "I8HPr_f1PWE_",
        "outputId": "3c20766b-58d3-4d58-80db-334d4ab24eaa"
      },
      "source": [
        "pt.figure(figsize=(12,8))\n",
        "sb.heatmap(dataframe.corr(),annot=True,fmt='.0%')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6c45d10d10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7BhG4MYYSkbC"
      },
      "source": [
        " *Risk* *of* *having* *cardiovascular* *diseases* *is* *affected* *by* *factors* *such* *as* ** **Diabetes** (90%) , **Thallium** **Stress** (53%) , **Chest** **Pain** (42%), \n",
        "**Sex** (30%) (since men are more prone to such diseases,However women mainly have it after menopause), \n",
        "**Age** (21%) (as we have seen after 55 yrs of age people are more prone).\n",
        "**Cholestoral** (12%)"
      ]
    }
  ]
}