review2_heart_prediction(updated).ipynb

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  "metadata": {
    "colab": {
      "name": "review2 heart prediction.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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      "name": "python"
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          "height": 206
        },
        "outputId": "17486f36-422b-4a30-ca61-780fc1437954"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn import datasets\n",
        "heart_failure = pd.read_csv(\"/content/heart.csv\")\n",
        "heart_failure.head()\n",
        "\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trtbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalachh</th>\n",
              "      <th>exng</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slp</th>\n",
              "      <th>caa</th>\n",
              "      <th>thall</th>\n",
              "      <th>output</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>63</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>145</td>\n",
              "      <td>233</td>\n",
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              "      <td>37</td>\n",
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              "      <td>130</td>\n",
              "      <td>250</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>187</td>\n",
              "      <td>0</td>\n",
              "      <td>3.5</td>\n",
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              "      <td>41</td>\n",
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              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>172</td>\n",
              "      <td>0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>120</td>\n",
              "      <td>236</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>178</td>\n",
              "      <td>0</td>\n",
              "      <td>0.8</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>57</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>120</td>\n",
              "      <td>354</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>163</td>\n",
              "      <td>1</td>\n",
              "      <td>0.6</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "   age  sex  cp  trtbps  chol  fbs  ...  exng  oldpeak  slp  caa  thall  output\n",
              "0   63    1   3     145   233    1  ...     0      2.3    0    0      1       1\n",
              "1   37    1   2     130   250    0  ...     0      3.5    0    0      2       1\n",
              "2   41    0   1     130   204    0  ...     0      1.4    2    0      2       1\n",
              "3   56    1   1     120   236    0  ...     0      0.8    2    0      2       1\n",
              "4   57    0   0     120   354    0  ...     1      0.6    2    0      2       1\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
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    {
      "cell_type": "code",
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        "id": "0UrAlZ2UrcIz",
        "outputId": "716e20f4-9062-4852-cb55-fd191dd09035"
      },
      "source": [
        "heart_failure.info()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 303 entries, 0 to 302\n",
            "Data columns (total 14 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   age       303 non-null    int64  \n",
            " 1   sex       303 non-null    int64  \n",
            " 2   cp        303 non-null    int64  \n",
            " 3   trtbps    303 non-null    int64  \n",
            " 4   chol      303 non-null    int64  \n",
            " 5   fbs       303 non-null    int64  \n",
            " 6   restecg   303 non-null    int64  \n",
            " 7   thalachh  303 non-null    int64  \n",
            " 8   exng      303 non-null    int64  \n",
            " 9   oldpeak   303 non-null    float64\n",
            " 10  slp       303 non-null    int64  \n",
            " 11  caa       303 non-null    int64  \n",
            " 12  thall     303 non-null    int64  \n",
            " 13  output    303 non-null    int64  \n",
            "dtypes: float64(1), int64(13)\n",
            "memory usage: 33.3 KB\n"
          ]
        }
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    {
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        "outputId": "dcab8efe-c66a-40f7-eae2-6d4e4466f3e7"
      },
      "source": [
        "heart_failure.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age         0\n",
              "sex         0\n",
              "cp          0\n",
              "trtbps      0\n",
              "chol        0\n",
              "fbs         0\n",
              "restecg     0\n",
              "thalachh    0\n",
              "exng        0\n",
              "oldpeak     0\n",
              "slp         0\n",
              "caa         0\n",
              "thall       0\n",
              "output      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
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          "height": 320
        },
        "id": "YFxmgIssr2yh",
        "outputId": "a8c0ad2c-eb7e-4d23-840c-bbe926e512f7"
      },
      "source": [
        "heart_failure.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trtbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalachh</th>\n",
              "      <th>exng</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slp</th>\n",
              "      <th>caa</th>\n",
              "      <th>thall</th>\n",
              "      <th>output</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>54.366337</td>\n",
              "      <td>0.683168</td>\n",
              "      <td>0.966997</td>\n",
              "      <td>131.623762</td>\n",
              "      <td>246.264026</td>\n",
              "      <td>0.148515</td>\n",
              "      <td>0.528053</td>\n",
              "      <td>149.646865</td>\n",
              "      <td>0.326733</td>\n",
              "      <td>1.039604</td>\n",
              "      <td>1.399340</td>\n",
              "      <td>0.729373</td>\n",
              "      <td>2.313531</td>\n",
              "      <td>0.544554</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.082101</td>\n",
              "      <td>0.466011</td>\n",
              "      <td>1.032052</td>\n",
              "      <td>17.538143</td>\n",
              "      <td>51.830751</td>\n",
              "      <td>0.356198</td>\n",
              "      <td>0.525860</td>\n",
              "      <td>22.905161</td>\n",
              "      <td>0.469794</td>\n",
              "      <td>1.161075</td>\n",
              "      <td>0.616226</td>\n",
              "      <td>1.022606</td>\n",
              "      <td>0.612277</td>\n",
              "      <td>0.498835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</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>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>47.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>211.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>133.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</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>1.000000</td>\n",
              "      <td>130.000000</td>\n",
              "      <td>240.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>153.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>61.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>274.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</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>3.000000</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>6.200000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              age         sex          cp  ...         caa       thall      output\n",
              "count  303.000000  303.000000  303.000000  ...  303.000000  303.000000  303.000000\n",
              "mean    54.366337    0.683168    0.966997  ...    0.729373    2.313531    0.544554\n",
              "std      9.082101    0.466011    1.032052  ...    1.022606    0.612277    0.498835\n",
              "min     29.000000    0.000000    0.000000  ...    0.000000    0.000000    0.000000\n",
              "25%     47.500000    0.000000    0.000000  ...    0.000000    2.000000    0.000000\n",
              "50%     55.000000    1.000000    1.000000  ...    0.000000    2.000000    1.000000\n",
              "75%     61.000000    1.000000    2.000000  ...    1.000000    3.000000    1.000000\n",
              "max     77.000000    1.000000    3.000000  ...    4.000000    3.000000    1.000000\n",
              "\n",
              "[8 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
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        "id": "k8WcXMnCr3OC"
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      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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      "metadata": {
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          "height": 568
        },
        "id": "Z1s25-zwrKa9",
        "outputId": "caae52d3-3eeb-4127-ac5a-ec1d51bbf77f"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"male(1) nd female(0) count\")\n",
        "sns.countplot(heart_failure['sex'])\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "yBgUUYtwt_Fc",
        "outputId": "1bcca5ce-72b0-41cb-ad35-fa6bb77e1ec7"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"age count\")\n",
        "sns.distplot(heart_failure['age'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda79d550>"
            ]
          },
          "metadata": {},
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "aDE5PiDivruw",
        "outputId": "bc92d402-efdc-495d-a82d-efffdac87c38"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"chest pain count\")\n",
        "sns.countplot(heart_failure['cp'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "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"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda667050>"
            ]
          },
          "metadata": {},
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "RtViFPQgwD06",
        "outputId": "e6e90d56-547e-458d-ee86-300dafea9a68"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"cholestrol plot\")\n",
        "sns.distplot(heart_failure['chol'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5ce524d490>"
            ]
          },
          "metadata": {},
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 620
        },
        "id": "Nye1cwuiwtIj",
        "outputId": "f2622e3e-4f10-4b4f-a4aa-0504b109d356"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"output vs age plot\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==1]['age'],color=\"blue\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==0]['age'],color=\"red\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda7b9610>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 620
        },
        "id": "bg-eGEv2zE5i",
        "outputId": "da88f593-7f1f-4c50-a84f-781e44d9d593"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"output vs chol\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==1]['chol'],color=\"blue\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==0]['chol'],color=\"red\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cdc627990>"
            ]
          },
          "metadata": {},
          "execution_count": 52
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 620
        },
        "id": "DvwTeeYzzYQq",
        "outputId": "ff274a9c-64d2-460b-a1c9-2a4afd9a3bf9"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"output vs trtbps\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==1]['trtbps'],color=\"blue\")\n",
        "sns.distplot(heart_failure[heart_failure['output']==0]['trtbps'],color=\"red\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda7bbb10>"
            ]
          },
          "metadata": {},
          "execution_count": 53
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "YLqo8V-ezliz",
        "outputId": "326da2a8-28b4-47eb-a58e-fbe7b555fcd7"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\" output vs gender barplot\")\n",
        "sns.barplot(x=heart_failure['sex'],y=heart_failure['output'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda4814d0>"
            ]
          },
          "metadata": {},
          "execution_count": 55
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 549
        },
        "id": "Xe86rc250gWN",
        "outputId": "af6e47ca-99a8-497b-a7d2-465aff0ba53e"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.title(\"correlation of each variable\")\n",
        "sns.heatmap(heart_failure.corr(),annot=True,cmap='RdBu')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5cda440850>"
            ]
          },
          "metadata": {},
          "execution_count": 56
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VYIowDfLlm6z"
      },
      "source": [
        "from matplotlib import cm\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "X = heart_failure.drop(columns = ['output'], axis= 1)\n",
        "y=heart_failure['output']\n",
        "X_train,X_test,y_train,y_test = train_test_split(X, y , random_state = 0)\n",
        "Scaler=MinMaxScaler()\n",
        "Scaler.fit(X_train)\n",
        "X_train_scaled = Scaler.transform(X_train)\n",
        "X_test_scaled = Scaler.transform(X_test)\n"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9Dhmt7vTsp9T",
        "outputId": "a7ae8a98-028e-4b1e-a925-3020d3c64cd1"
      },
      "source": [
        "'''from sklearn.linear_model import LogisticRegression \n",
        "lm =LogisticRegression()\n",
        "lm.fit(X_train,y_train)\n",
        "prediction=lm.predict(X_test)\n",
        "sc =accuracy_score(y_test,prediction)\n",
        "print(\"accuracy of model=\",sc*100)'''\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "lm = GaussianNB()\n",
        "lm.fit(X_train,y_train)\n",
        "lm.score(X_test,y_test)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8289473684210527"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xoFpJFgwOdAf"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        },
        "id": "2dXfFbbgt-8G",
        "outputId": "fc2b65f2-4913-4b41-dbab-cfb0e6353ef2"
      },
      "source": [
        "\n",
        "age = int(input('age'))\n",
        "gender = int(input('1 for M and 0 for F '))\n",
        "print('''1:typical angina \n",
        "2:atypical angina\n",
        "3:non anginal pain\n",
        "4:asymptomatic''')\n",
        "cp = int(input('type of chest pain'))\n",
        "#blood pressure\n",
        "bp = int(input('blood pressure'))\n",
        "chol = int(input('cholestrol'))\n",
        "#fasting blood sugar (diabetic or not)\n",
        "fbs = int(input(''' 1:if fbs>120\n",
        "0:otherwise'''))\n",
        "# normal heart rate\n",
        "rest_ecg = int(input('''0:normal ecg\n",
        "1:ST-T abnormality\n",
        "2:left ventricular hypertrophy ESTES' criteria'''))\n",
        "thalla = int(input('Max heart rate'))\n",
        "# exercise induced chest pain\n",
        "exng = int(input('''0:NO chest pain during exercise\n",
        "1:chest pain during exercise'''))\n",
        "# previous peak\n",
        "old = float(input('previous peak'))\n",
        "# slope \n",
        "slp = int(input('slope'))\n",
        "# no. of major vessels blocked\n",
        "caa = int(input('no. of major blood vessels blocked'))\n",
        "# thall rate \n",
        "thall = int(input('thall rate'))\n",
        "patient={\"age\":age,\"sex\":gender,\"cp\":cp,\"trtbps\":bp,\"chol\":chol,\"fbs\":fbs,\"restecg\":rest_ecg,\"thalachh\":thalla,\"exng\":exng,\"oldpeak\":old,\"slp\":slp,\"caa\":caa,\"thall\":[1]}\n",
        "df1 = pd.DataFrame(patient)\n",
        "df1"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "age63\n",
            "1 for M and 0 for F 1\n",
            "1:typical angina \n",
            "2:atypical angina\n",
            "3:non anginal pain\n",
            "4:asymptomatic\n",
            "type of chest pain3\n",
            "blood pressure145\n",
            "cholestrol233\n",
            " 1:if fbs>120\n",
            "0:otherwise1\n",
            "0:normal ecg\n",
            "1:ST-T abnormality\n",
            "2:left ventricular hypertrophy ESTES' criteria0\n",
            "Max heart rate150\n",
            "0:NO chest pain during exercise\n",
            "1:chest pain during exercise0\n",
            "previous peak2.3\n",
            "slope0\n",
            "no. of major blood vessels blocked0\n",
            "thall rate1\n"
          ]
        },
        {
          "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>cp</th>\n",
              "      <th>trtbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalachh</th>\n",
              "      <th>exng</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slp</th>\n",
              "      <th>caa</th>\n",
              "      <th>thall</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>63</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>145</td>\n",
              "      <td>233</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>150</td>\n",
              "      <td>0</td>\n",
              "      <td>2.3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  sex  cp  trtbps  chol  fbs  ...  thalachh  exng  oldpeak  slp  caa  thall\n",
              "0   63    1   3     145   233    1  ...       150     0      2.3    0    0      1\n",
              "\n",
              "[1 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JgA0_NkUOi8G",
        "outputId": "9adfbd12-63e5-4ba8-d3cc-4a232a408b49"
      },
      "source": [
        "print('you have ',lm.predict_proba(df1)[0][0]*100,'% chance of heart attack')"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "you have  72.2927465142987 % chance of heart attack\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DkQrywjXIpWd",
        "outputId": "5c01f8b5-aa70-4dc0-aeb6-ede89e699a55"
      },
      "source": [
        "if(lm.predict(df1)==[1]):\n",
        " print(\"you are having more chance of heart attack\")\n",
        "else:\n",
        " print(\"you are having less chance of heart attack safe\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "you are having more chance of heart attack\n"
          ]
        }
      ]
    }
  ]
}