Heart_Disease.ipynb

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  "metadata": {
    "colab": {
      "name": "Heart_Diseases.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "CbjFTDZbr4Gc"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression"
      ],
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "xB0aJFsTr7fu",
        "outputId": "dbbd6886-8b9d-4cb5-fe06-6442590bf6de"
      },
      "source": [
        "dataset = pd.read_csv('/content/sample_data/heart.csv')\n",
        "\n",
        "dataset"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<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>trestbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
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              "      <td>0</td>\n",
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              "      <td>120</td>\n",
              "      <td>354</td>\n",
              "      <td>0</td>\n",
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              "      <td>163</td>\n",
              "      <td>1</td>\n",
              "      <td>0.6</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>57</td>\n",
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              "      <td>140</td>\n",
              "      <td>241</td>\n",
              "      <td>0</td>\n",
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              "      <td>45</td>\n",
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              "      <td>3</td>\n",
              "      <td>110</td>\n",
              "      <td>264</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>132</td>\n",
              "      <td>0</td>\n",
              "      <td>1.2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
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              "      <td>68</td>\n",
              "      <td>1</td>\n",
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              "      <td>144</td>\n",
              "      <td>193</td>\n",
              "      <td>1</td>\n",
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              "      <td>57</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>303 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     age  sex  cp  trestbps  chol  fbs  ...  exang  oldpeak  slope  ca  thal  target\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",
              "298   57    0   0       140   241    0  ...      1      0.2      1   0     3       0\n",
              "299   45    1   3       110   264    0  ...      0      1.2      1   0     3       0\n",
              "300   68    1   0       144   193    1  ...      0      3.4      1   2     3       0\n",
              "301   57    1   0       130   131    0  ...      1      1.2      1   1     3       0\n",
              "302   57    0   1       130   236    0  ...      0      0.0      1   1     2       0\n",
              "\n",
              "[303 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OFaFJ9MpXWk8"
      },
      "source": [
        "#Data Analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4qWGeX1BXirC"
      },
      "source": [
        "Univariate"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 162
        },
        "id": "3aZAxmF8u3oL",
        "outputId": "70a32051-fc03-477f-d98d-e27671a3d263"
      },
      "source": [
        "dataset.groupby('target').mean()"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>target</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>56.601449</td>\n",
              "      <td>0.826087</td>\n",
              "      <td>0.478261</td>\n",
              "      <td>134.398551</td>\n",
              "      <td>251.086957</td>\n",
              "      <td>0.159420</td>\n",
              "      <td>0.449275</td>\n",
              "      <td>139.101449</td>\n",
              "      <td>0.550725</td>\n",
              "      <td>1.585507</td>\n",
              "      <td>1.166667</td>\n",
              "      <td>1.166667</td>\n",
              "      <td>2.543478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>52.496970</td>\n",
              "      <td>0.563636</td>\n",
              "      <td>1.375758</td>\n",
              "      <td>129.303030</td>\n",
              "      <td>242.230303</td>\n",
              "      <td>0.139394</td>\n",
              "      <td>0.593939</td>\n",
              "      <td>158.466667</td>\n",
              "      <td>0.139394</td>\n",
              "      <td>0.583030</td>\n",
              "      <td>1.593939</td>\n",
              "      <td>0.363636</td>\n",
              "      <td>2.121212</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              age       sex        cp  ...     slope        ca      thal\n",
              "target                                 ...                              \n",
              "0       56.601449  0.826087  0.478261  ...  1.166667  1.166667  2.543478\n",
              "1       52.496970  0.563636  1.375758  ...  1.593939  0.363636  2.121212\n",
              "\n",
              "[2 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J6CwchsBtK0J",
        "outputId": "007969fd-0955-4972-b3bd-51c93a41fc71"
      },
      "source": [
        "target.shape"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(303,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mP2K9ru_tS6w",
        "outputId": "0c616833-092f-4df3-9001-21711666c173"
      },
      "source": [
        "dataset.shape"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(303, 14)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qe3SHBKOYZfj"
      },
      "source": [
        "from sklearn.feature_selection import SelectKBest\n",
        "from sklearn.feature_selection import chi2\n",
        "\n",
        "data = dataset.copy()"
      ],
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wrFGsNAptUt3"
      },
      "source": [
        "X = data.iloc[:,0:13]\n",
        "Y = data.iloc[:,-1]\n",
        "bestFeatures = SelectKBest(score_func=chi2) \n",
        "#X_train, X_test, Y_train, Y_test = train_test_split(dataset, target, test_size= 0.2, stratify=target, random_state=2)"
      ],
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pJbOy86gYxyv"
      },
      "source": [
        "fit = bestFeatures.fit(X,Y)"
      ],
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "496Zcy6CY4DX",
        "outputId": "36d73860-c5f5-4f1b-eb73-7a3280ddb153"
      },
      "source": [
        "dfscores = pd.DataFrame(fit.scores_)\n",
        "dfcolumns = pd.DataFrame(X.columns)\n",
        "\n",
        "#concat two df\n",
        "featureScores = pd.concat([dfcolumns,dfscores], axis=1)\n",
        "featureScores.columns = ['Specs','Scores']\n",
        "features_selected = featureScores.nlargest(10,'Scores')\n",
        "print(features_selected)"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "       Specs      Scores\n",
            "7    thalach  188.320472\n",
            "9    oldpeak   72.644253\n",
            "11        ca   66.440765\n",
            "2         cp   62.598098\n",
            "8      exang   38.914377\n",
            "4       chol   23.936394\n",
            "0        age   23.286624\n",
            "3   trestbps   14.823925\n",
            "10     slope    9.804095\n",
            "1        sex    7.576835\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IHeTh5eMbpwi"
      },
      "source": [
        "#Filtering the columns selected\n",
        "X = X.loc[:,X.columns.isin(features_selected['Specs'])]"
      ],
      "execution_count": 85,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g8YozwlLY32E"
      },
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size= 0.2, stratify=target, random_state=2)"
      ],
      "execution_count": 86,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DuBal1K4uPR8"
      },
      "source": [
        "#Model Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZfYaV4c6tqa3",
        "outputId": "1c1aab7c-f667-40a9-c946-9a6f083b9cc4"
      },
      "source": [
        "model = LogisticRegression()\n",
        "\n",
        "model.fit(X_train, Y_train)\n",
        "\n",
        "feature_imp = pd.DataFrame(model.coef_[0], index = X.columns, columns=['Importance']).sort_values('Importance',ascending=False)\n",
        "print(feature_imp)"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "          Importance\n",
            "cp          0.863900\n",
            "slope       0.340224\n",
            "thalach     0.026026\n",
            "age        -0.000366\n",
            "chol       -0.005355\n",
            "trestbps   -0.009859\n",
            "oldpeak    -0.473914\n",
            "ca         -0.771433\n",
            "exang      -0.985842\n",
            "sex        -1.707641\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "67c1mS_otuJm",
        "outputId": "03d39ece-e660-428d-abe3-b939bb398af9"
      },
      "source": [
        "model.predict(X_train)"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1,\n",
              "       1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,\n",
              "       1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1,\n",
              "       0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1,\n",
              "       1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0,\n",
              "       1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0,\n",
              "       1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0,\n",
              "       1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0,\n",
              "       0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1,\n",
              "       0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,\n",
              "       1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "399VpOG7ufJc",
        "outputId": "091d3772-2b48-46ab-aae3-0ba1c465a77a"
      },
      "source": [
        "print(accuracy_score(Y_train, model.predict(X_train)))"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.8347107438016529\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yY1UqgO0upGM",
        "outputId": "5bce0fe7-7392-40b0-cfa9-73a5b153c52d"
      },
      "source": [
        "print(accuracy_score(Y_test, model.predict(X_test)))"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.8524590163934426\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U72YeKMMTg6B"
      },
      "source": [
        "#Visualization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "NyCVZVFeuveX",
        "outputId": "4710e2d4-ab54-4560-e29a-8e3ba2d6df97"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "plt.figure(figsize=(12,10))\n",
        "sns.heatmap(dataset.corr(), annot=True, cmap=\"Blues\", fmt='.2f')"
      ],
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2e0763c710>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iu-oOaKqerLO"
      },
      "source": [
        "#Count Plot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8kpO_1XPdsZ6"
      },
      "source": [
        "sns.set_style('darkgrid')\n",
        "sns.set_palette('Set2')\n",
        "\n",
        "def chng(sex):\n",
        "  if sex == 0:\n",
        "    return 'Female'\n",
        "  return 'Male'\n",
        "\n",
        "def chng2(prob):\n",
        "  if prob == 0:\n",
        "    return 'Heart disease'\n",
        "  return 'No Heart Disease'\n",
        "\n",
        "data['sex'] = data['sex'].apply(chng)\n",
        "data['target'] = data['target'].apply(chng2)"
      ],
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "DTW0HLtMeznb",
        "outputId": "a1c021fb-2114-440a-c33f-0840f02efd9e"
      },
      "source": [
        "sns.countplot(data=data, x='sex', hue='target')\n",
        "plt.title('Gender vs Target')\n",
        "plt.show()"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fvo1//SsaQggsXDgXZ86koFOnLuWq93EYCkSkN/XqWWHgwMGIidkGU1MzufyXX85i5cp/AgAGDhyMjRs3PHJ/L6/+D40pPNj/Z9y4cQ0zZkwGAGg0arRr92Aq7ZSUU/jiiy0oLi7C/fv38eKLzWUoeHv3r/S5PGrGoIYNG+G331Kxbl0IXF3d0b17zydO2X3vXgaWLl2EzMzfoVar8fzzjQA8mNTvgw/WYcCAQfD07AtHRyf88MNxnDx5HBMnjgUAFBYW4M6dWwwFIqrdRo16DZMmjcPLLw+psjaFEOjatQfee29lmeXFxcUIC1uDzZu3wMnJGZGRm1BS8t8n7FlYWFT6mJcuXXxogNva2hpRUV/hhx++R1zcLhw4sB9vvjnvsVN2r1sXgjFjxsLd3RMpKafw6acRAAB//wno1csd339/FDNmTMbatR9CCIFx4ybAz+/VStf8KLwllYj0ytraBl5e/RAfHyeXtW/fAd9+uxfAg+cmdOjQuUJttmv3En7++SfcufOgO6mwsBC3bt2Uz1uwtbVFQUEBkpOTHttGRabPTk5OwsmTJ9Cvn0+Z5SqVCkKUok8fb0yZMgOXLl184pTd+fl5eO45RwDAnj0Jsp3U1Dto3rwFxo2bABeXtrh58wZ69HBFQsK/ZY337mUgOzurXPU+Ca8UiAjFavUfdwxVXXsVMWbMOOzatUO+njPnLaxc+R6++mqrHGiuCDs7O7z77jIsW/au7JqZMmUG/va3JhgyxA/+/qPRoEEDuLi0e2wb3t4DEBISjJiYbVix4uGB5h07vsS+fd+gqKgQTZs2x/r1G2FnZ1dmm3v3MrBq1XsoLX3QtfTngPqSJcsRGroa0dGR0Go18PYegJYtW2HSpKlYvHgh6tevj7//vRt++y1VHisl5RSMjIzw4ovN0LNnL5iamuLGjeuYPn0iAMDCwhJLliyHnZ19hX5X/6vaps5etGgRkpOT0aBBA8THxwN4kJpz5sxBamoqGjVqhPDwcNjY2EAIgeDgYBw6dAjm5uZYvXo12rV7/B/rT5w6u2px6uz/4tTZVFdUdOrsaus+Gj58ODZv3lxmWUREBFxdXbFv3z64uroiIuJBf9nhw4dx48YN7Nu3D8uXL8eyZcuqqywiInqCaguFbt26wcbGpsyypKQk+Pn5AQD8/Pzw7bffllmuUCjQqVMn3L9/HxkZGdVVGhERPYZOxxQyMzPh6PhgEMXBwQGZmZkAgPT09DJfTHF2dkZ6errc9nGMjRWwtbWsvoLJoNXl91Z6ugLGxrzPxBAoFBX7nNTbQLNCoYBCoXimNrRawTGFKvSkfkZDVJffW0IIaLWl+i6DdECIhz8n9TKm8CgNGjSQ3UIZGRmwt38wSu7k5IS0tDS5XVpaGpycnHRZGhERQceh4OXlhdjYWABAbGwsvL29yywXQuDMmTOoX7/+U7uOiIio6lVb99HcuXPxww8/IDs7Gx4eHpg9ezamTp2KoKAgxMTEoGHDhggPDwcAeHp64tChQ+jfvz8sLCywcuXKp7RORFXJ3sYMxqamVdaetqQEWTnFT9ymf//e2L//iHz9qKmwK+vu3d/w889nMWDAwKduGxy8TM5xVJunvK4q1RYKa9eufeTy6Ojoh5YpFAosXVqxL6cQUdUxNjWt0u+oOM4IAfDkUKguGo0Gd+/+hm+/3VOuUPir2jzldVXhN5qJqMbJzs5GaOhKpKenAwACA+eiQ4dOOH/+HNavD0NJSTHMzMzxzjtL8Le/vYjExP/g0KEDKCwsRGlpKUpKSnDz5nVMmPA6Bg0ajNGjx8q2hRBYty4EJ0+egKOjM0xM/vsxWJunvK4qDAUi0ovi4mJMmPC6fH3/fo6crXT9+lCMGjUWHTt2QlpaGubNm4UvvohBkyYv4qOP/gWlUomTJ09g06aPEBz8YDbVS5cuIjr6K1hb2yAl5RS2bfscISHhDx338OGDuHXrJj7/fCeys7MwbtxIDB7sW2ab2jjldVVhKBCRXpiZmZWZKfTPMQUAOHXqB9y4cV2uy8/PR0FBAfLy8rBixTLcuXMLCoUCGo1GbtOtWw9YW5f9wuyjnDlzGv36+cDY2BjPPeeALl26PbRNbZzyuqowFIioxhGiFJs2fQYzM7Myy9etC0GXLl2xalUo7t79DbNn/7fbxdzcvMqOXxunvK4q/EojEdU43br1xK5d2+Xry5cvAgDy8vLg4OAA4MGVxeNYWtZ77LTXnTp1xoED+6HVavH7778jJeXUQ9vUximvqwqvFIgI2pKSP+4Yqrr2nkVQ0AKsXbsGAQFjoNVq0bFjZyxY8A7Gjh2PFSuWITo6Eq6u7o/dv0WLljAyMkJAwGt4+eVXygw0e3j0xY8/nsS4cSPh5OSM9u1femj/2jjldVWptqmzdYFTZ1ctTp39X5w6m+qKik6dbfBXCta25jAzMdF3GURENYLBh4KZiQnmfbNF32XUCFX55C0iqp040ExkoGpxzzGVU2X+xgwFIgOkVJoiP/8+g6EOE0IgP/8+lMqKzWll8N1HRIbIzs4B2dn3kJen0ncpVI2USlPY2TlUbJ9qqoWIajBjYyWee+55fZdBNRC7j4iISGIoEBGRxFAgIiKJoUBERBJDgYiIJIYCERFJDAUiIpIYCkREJDEUiIhIYigQEZHEUCAiIomhQEREEkOBiIgkhgIREUl6mTo7KioKO3fuhEKhQKtWrbBq1SpkZGRg7ty5UKlUaNeuHUJCQmBqWrGHQxAR0bPR+ZVCeno6tmzZgl27diE+Ph5arRYJCQkIDQ3FhAkTsH//flhbWyMmJkbXpRERGTy9dB9ptVoUFRVBo9GgqKgIDg4OOH78OHx8fAAAw4YNQ1JSkj5KIyIyaDrvPnJycsKkSZPQt29fmJmZwc3NDe3atYO1tTWUygflODs7Iz09/altGRsrYGtrWd0lk4Hie4sMkc5DIScnB0lJSUhKSkL9+vXx5ptv4siRI5VqS6sVUKkKnqkeB4f6z7Q/1V3P+t4iqqme9Lmn81D47rvv8MILL8De3h4AMGDAAKSkpOD+/fvQaDRQKpVIS0uDk5OTrksjIjJ4Oh9TaNiwIX766ScUFhZCCIHvv/8eLVq0QI8ePbB3714AwO7du+Hl5aXr0oiIDJ7OrxQ6duwIHx8fDBs2DEqlEi4uLhg9ejT69OmDOXPmIDw8HC4uLhg5cqSuSyMiMnh6+Z5CYGAgAgMDyyxr3Lgxb0MlItIzfqOZiIgkhgIREUkMBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCS9fKOZiJ7O2tYcZiYm+i6jRihWq3FfVaTvMgwCQ4GohjIzMcG8b7bou4waIWzQeAAMBV1g9xEREUkMBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCSGAhERSeUKhYCAgHItIyKi2u2J01wUFxejsLAQ2dnZyMnJgRACAJCXl4f09HSdFEhERLrzxFDYtm0boqOjkZGRgeHDh8tQsLKywrhx43RSIBER6c4TQyEgIAABAQHYunUr/P39dVUTERHpSblmSfX390dKSgpSU1Oh1Wrlcj8/v2orjIiIdK9cobBgwQLcvn0bbdq0gbGxMQBAoVAwFIiI6phyhcK5c+eQmJgIhUJR3fUQEZEeleuW1JYtW+LevXvVXQsREelZua4UsrOzMXjwYHTo0AEmf3k84CeffFKpg96/fx//93//h0uXLkGhUGDlypVo2rQp5syZg9TUVDRq1Ajh4eGwsbGpVPtERFQ55QqF2bNnV+lBg4OD0bt3b2zYsAElJSUoKirCJ598AldXV0ydOhURERGIiIjAggULqvS4RET0ZOUKhe7du1fZAXNzc3Hy5EmsXr0aAGBqagpTU1MkJSVh69atAB7c1eTv789QICLSsXKFQufOneUgs1qthkajgYWFBVJSUip8wDt37sDe3h6LFi3Cr7/+inbt2uHdd99FZmYmHB0dAQAODg7IzMx8alvGxgrY2lpWuAai8uB7q2bh30M3yhUKp0+flj8LIZCUlIQzZ85U6oAajQbnz5/H4sWL0bFjR6xYsQIRERFltlEoFOW600mrFVCpCipVx58cHOo/0/5Udz3re+tZ8b1Zlr7/HnXJk95bFZ4lVaFQoF+/fjh69GilinF2doazszM6duwIABg4cCDOnz+PBg0aICMjAwCQkZEBe3v7SrVPRESVV64rhX379smfS0tLce7cOZiZmVXqgA4ODnB2dsa1a9fQrFkzfP/992jevDmaN2+O2NhYTJ06FbGxsfD29q5U+0REVHnlCoWDBw/Kn42NjdGoUSN8/PHHlT7o4sWLMX/+fKjVajRu3BirVq1CaWkpgoKCEBMTg4YNGyI8PLzS7RMRUeWUKxRWrVpVpQd1cXHB119//dDy6OjoKj0OERFVTLnGFNLS0jBz5ky4urrC1dUVs2fPRlpaWnXXRkREOlauUFi0aBG8vLxw5MgRHDlyBH379sWiRYuquzYiItKxcoVCVlYWXn31VSiVSiiVSgwfPhxZWVnVXRsREelYuULB1tYWcXFx0Gq10Gq1iIuLg62tbXXXRkREOlauUFi5ciW++eYbuLm5wd3dHXv37pXTVBARUd1RrruPNmzYgDVr1shZS1UqFdasWVPldyUREZF+letK4eLFi2Wmsba1tcWFCxeqrSgiItKPcoVCaWkpcnJy5GuVSlXmWc1ERFQ3lKv7aNKkSRg9ejQGDhwIANizZw+mT59erYUREZHulSsU/Pz80L59exw/fhwA8OGHH6JFixbVWhgREeleuUIBAFq0aMEgICKq4yo8dTYREdVdDAUiIpIYCkREJDEUiIhIYigQEZHEUCAiIomhQEREEkOBiIgkhgIREUkMBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCS9hYJWq4Wfnx+mTZsGALh9+zZGjhyJ/v37IygoCCUlJfoqjYjIYOktFLZs2YLmzZvL16GhoZgwYQL2798Pa2trxMTE6Ks0IiKDpZdQSEtLQ3JyMkaMGAEAEELg+PHj8PHxAQAMGzYMSUlJ+iiNiMiglfsZzVVp5cqVWLBgAfLz8wEA2dnZsLa2hlL5oBxnZ2ekp6c/tR1jYwVsbS2rtVYyXHxv1Sz8e+iGzkPh4MGDsLe3R/v27XHixIlnakurFVCpCp6pDQeH+s+0P9Vdz/reelZ8b5al779HXfKk95bOQyElJQUHDhzA4cOHUVxcjLy8PAQHB+P+/fvQaDRQKpVIS0uDk5OTrksjIjJ4Oh9TmDdvHg4fPowDBw5g7dq16NmzJ8LCwtCjRw/s3bsXALB79254eXnpujQiIoNXY76nsGDBAnz22Wfo378/VCoVRo4cqe+SiIgMjl4Gmv/Uo0cP9OjRAwDQuHFj3oZKRKRnNeZKgYiI9I+hQEREEkOBiIgkhgIREUkMBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCSGAhERSQwFIiKSGApERCQxFIiISGIoEBGRxFAgIiKJoUBERBJDgYiIJIYCERFJDAUiIpIYCkREJDEUiIhIUuq7ACKipxEaNRwc6uu7jBpBW1KCrJziamufoUBENZ5CaYKMjW/pu4wawXFGCIDqCwV2HxERkcRQICIiSefdR3fv3sVbb72FzMxMKBQKjBo1CgEBAVCpVJgzZw5SU1PRqFEjhIeHw8bGRtflEREZNJ1fKRgbG2PhwoVITEzE9u3b8eWXX+LKlSuIiIiAq6sr9u3bB1dXV0REROi6NCIig6fzUHB0dES7du0AAFZWVmjWrBnS09ORlJQEPz8/AICfnx++/fZbXZdGRGTw9Hr30Z07d3DhwgV07NgRmZmZcHR0BAA4ODggMzPzqfsbGytga2tZ3WWSgeJ7i2qq6nxv6i0U8vPzERgYiHfeeQdWVlZl1ikUCigUiqe2odUKqFQFz1QH732mx3nW99az4nuTHqc6P/f0cveRWq1GYGAghgwZggEDBgAAGjRogIyMDABARkYG7O3t9VEaEZFB03koCCHw7rvvolmzZpg4caJc7uXlhdjYWABAbGwsvL29dV0aEZHB03n30Y8//oi4uDi0atUKQ8M5J7sAAAc/SURBVIcOBQDMnTsXU6dORVBQEGJiYtCwYUOEh4frujQiIoOn81Do2rUrLl68+Mh10dHROq6GiIj+it9oJiIiiaFAREQSQ4GIiCSGAhERSQwFIiKSGApERCQxFIiISGIoEBGRxFAgIiKJoUBERBJDgYiIJIYCERFJDAUiIpIYCkREJDEUiIhIYigQEZHEUCAiIomhQEREEkOBiIgkhgIREUkMBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCSGAhERSTUqFA4fPgwfHx/0798fERER+i6HiMjg1JhQ0Gq1eP/997F582YkJCQgPj4eV65c0XdZREQGpcaEwtmzZ9GkSRM0btwYpqamGDx4MJKSkvRdFhGRQVEIIYS+iwCAPXv24MiRIwgODgYAxMbG4uzZs1iyZImeKyMiMhw15kqBiIj0r8aEgpOTE9LS0uTr9PR0ODk56bEiIiLDU2NC4aWXXsKNGzdw+/ZtlJSUICEhAV5eXvoui4jIoCj1XcCflEollixZgn/84x/QarV49dVX0bJlS32XRURkUGrMQDMREelfjek+IiIi/WMoEBGRxFCo41q3bo358+fL1xqNBj179sS0adOeuN+JEyeeug1Rebi4uGDo0KHyvzt37lTbsby8vJCVlVVt7RuCGjPQTNXD0tISly9fRlFREczNzXHs2DHe6ks6ZW5ujri4OH2XQeXEUDAAnp6eSE5OxsCBA5GQkIDBgwfjxx9/BPBgepHg4GAUFxfD3NwcK1euRLNmzcrsX1BQgOXLl+Py5cvQaDSYNWsW+vXrp49ToTri3LlzWL16NQoKCmBnZ4dVq1bB0dER/v7+cHFxwalTp1BYWIg1a9YgIiICly5dwqBBgzBnzhwAwBtvvIG0tDQUFxdj/PjxGD169EPHiIuLw9atW6FWq9GxY0csXboUxsbGuj7V2kdQndapUydx4cIFMXv2bFFUVCR8fX3F8ePHxdSpU4UQQuTm5gq1Wi2EEOLYsWNi1qxZQghRZpuwsDARGxsrhBAiJydHDBgwQOTn5+vhbKg2atOmjfD19RW+vr7ijTfeECUlJWL06NEiMzNTCCFEQkKCWLhwoRBCiHHjxomQkBAhhBBRUVHCzc1NpKeni+LiYtG7d2+RlZUlhBAiOztbCCFEYWGhGDx4sFzet29fkZmZKa5cuSKmTZsmSkpKhBBCLF26VOzevVun511b8UrBALRp0wZ37txBfHw8PD09y6zLzc3F22+/jZs3b0KhUECtVj+0/9GjR3HgwAF8+umnAIDi4mLcvXsXzZs310n9VLv9b/fRpUuXcOnSJUycOBEAUFpaCgcHB7n+zy+ttmrVCi1btoSjoyMAoHHjxkhLS4OdnR22bt2K/fv3AwDu3r2Lmzdvws7OTrbx/fff49y5cxgxYgQAoKioCA0aNKjeE60jGAoGwsvLCyEhIdiyZQtUKpVcvn79evTo0QMfffQR7ty5g/Hjxz9y/w0bNjzUrURUGUIItGzZEtu3b3/kelNTUwCAkZGR/PnP1xqNBidOnMB3332H7du3w8LCAv7+/iguLn7oGMOGDcO8efOq70TqKN59ZCBGjBiBmTNnonXr1mWW5+bmyoHn3bt3P3Jfd3d3fP755xB/fM/x/Pnz1Vss1WlNmzZFVlYWTp8+DQBQq9W4fPlyuffPzc2FjY0NLCwscPXqVZw5c+ahbVxdXbF3715kZmYCAFQqFVJTU6vmBOo4hoKBcHZ2fuRVwD/+8Q+sXbsWfn5+0Gg0j9z3jTfegEajga+vLwYPHoz169dXd7lUh5mammLDhg0IDQ2Fr68v/Pz8ZECUh4eHBzQaDQYNGoSwsDB06tTpoW1atGiBoKAgTJo0CUOGDMGkSZNw7969qjyNOovTXBARkcQrBSIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiCSGAlElFRQUYOrUqfD19cUrr7yCxMREnDt3DuPGjcPw4cMxefJkZGRkIDc3Fz4+Prh27RoAYO7cudixY4eeqyd6NM59RFRJR44cgaOjIyIiIgA8mH5hypQp+Pjjj2Fvb4/ExESsW7cOq1atwpIlS7Bo0SKMHz8eOTk5GDVqlJ6rJ3o0fqOZqJKuX7+OyZMnY9CgQejbty+sra0xZswYNG7cGMB/Z//8c3bZxYsXY9++fYiLi4Ozs7M+Syd6LF4pEFVS06ZN8fXXX+PQoUMIDw9Hz549Hzv7Z2lpKa5evQpzc3Pk5OQwFKjG4pgCUSWlp6fDwsICQ4cOxeTJk/HTTz89dvbPqKgoNG/eHGFhYVi0aNEjn1tBVBPwSoGoki5duoSQkBAYGRlBqVRi2bJlUCqVWLFiBXJzc6HVahEQEABjY2Ps3LkTO3fuhJWVFbp164aNGzciMDBQ36dA9BCOKRARkcTuIyIikhgKREQkMRSIiEhiKBARkcRQICIiiaFAREQSQ4GIiKT/B3QxunKgV0/5AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "jzvdTMc3fnez",
        "outputId": "4cf16950-e07e-4a98-f3fb-e2088a302c53"
      },
      "source": [
        "sns.countplot(data=data, x='slope', hue='target')\n",
        "plt.title('Chest Pain vs Target')\n",
        "plt.show()"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OEFv4TTXgZ11"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}