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\"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.59974772958769,\n \"min\": 94.0,\n \"max\": 200.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 124.0,\n 192.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.77691754263704,\n \"min\": 126.0,\n \"max\": 564.0,\n \"num_unique_values\": 152,\n \"samples\": [\n 321.0,\n 187.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.35619787492797644,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9949712915251782,\n \"min\": 0.0,\n \"max\": 2.0,\n \"num_unique_values\": 3,\n \"samples\": [\n 2.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 22.875003276980376,\n \"min\": 71.0,\n \"max\": 202.0,\n \"num_unique_values\": 91,\n \"samples\": [\n 170.0,\n 114.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.46979446452231655,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 1.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.1610750220686348,\n \"min\": 0.0,\n \"max\": 6.2,\n \"num_unique_values\": 40,\n \"samples\": [\n 2.4,\n 0.2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.6162261453459619,\n \"min\": 1.0,\n \"max\": 3.0,\n \"num_unique_values\": 3,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"3.0\",\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"3.0\",\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 2 } ], "source": [ "# URL dataset dari UCI Machine Learning Repository\n", "url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.cleveland.data'\n", "\n", "# Gunakan fungsi read_csv() untuk memuat dataset dari URL\n", "cleveland_df = pd.read_csv(url, header=None)\n", "columns = ['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'num']\n", "cleveland_df.columns = columns\n", "\n", "# Tampilkan beberapa baris pertama dari dataset\n", "print(cleveland_df.shape)\n", "cleveland_df.head()" ] }, { "cell_type": "code", "source": [ "# URL dataset dari UCI Machine Learning Repository\n", "url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.hungarian.data'\n", "\n", "# Gunakan fungsi read_csv() untuk memuat dataset dari URL\n", "hungarian_df = pd.read_csv(url, header=None)\n", "columns = ['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'num']\n", "hungarian_df.columns = columns\n", "\n", "# Tampilkan beberapa baris pertama dari dataset\n", "print(hungarian_df.shape)\n", "hungarian_df.head()" 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agesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "hungarian_df", "summary": "{\n \"name\": \"hungarian_df\",\n \"rows\": 294,\n \"fields\": [\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 7,\n \"min\": 28,\n \"max\": 66,\n \"num_unique_values\": 38,\n \"samples\": [\n 61,\n 65,\n 32\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 4,\n \"num_unique_values\": 4,\n \"samples\": [\n 1,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 32,\n \"samples\": [\n \"136\",\n \"142\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 154,\n \"samples\": [\n \"264\",\n \"217\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"0\",\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"0\",\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 72,\n \"samples\": [\n \"165\",\n \"99\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"0\",\n \"1\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9086479156256426,\n \"min\": 0.0,\n \"max\": 5.0,\n \"num_unique_values\": 10,\n \"samples\": [\n 4.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"2\",\n \"3\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"0\",\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"6\",\n \"7\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 1,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 3 } ] }, { "cell_type": "code", "source": [ "# URL dataset dari UCI Machine Learning Repository\n", "url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.switzerland.data'\n", "\n", "# Gunakan fungsi read_csv() untuk memuat dataset dari URL\n", "switzerland_df = pd.read_csv(url, header=None)\n", "columns = ['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'num']\n", "switzerland_df.columns = columns\n", "\n", "# Tampilkan beberapa baris pertama dari dataset\n", "print(switzerland_df.shape)\n", "switzerland_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "N955KTQF54yK", "outputId": "05347136-ad19-4474-a8d5-4be26fbc7ae1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(123, 14)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " age sex cp trestbps chol fbs restecg thalach exang oldpeak slope ca \\\n", "0 32 1 1 95 0 ? 0 127 0 .7 1 ? \n", "1 34 1 4 115 0 ? ? 154 0 .2 1 ? \n", "2 35 1 4 ? 0 ? 0 130 1 ? ? ? \n", "3 36 1 4 110 0 ? 0 125 1 1 2 ? \n", "4 38 0 4 105 0 ? 0 166 0 2.8 1 ? \n", "\n", " thal num \n", "0 ? 1 \n", "1 ? 1 \n", "2 7 3 \n", "3 6 1 \n", "4 ? 2 " ], "text/html": [ "\n", "
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agesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "switzerland_df", "summary": "{\n \"name\": \"switzerland_df\",\n \"rows\": 123,\n \"fields\": [\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9,\n \"min\": 32,\n \"max\": 74,\n \"num_unique_values\": 37,\n \"samples\": [\n 54,\n 50,\n 38\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 4,\n \"num_unique_values\": 4,\n \"samples\": [\n 4,\n 2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 21,\n \"samples\": [\n \"95\",\n \"180\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 0,\n \"num_unique_values\": 1,\n \"samples\": [\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 68,\n \"samples\": [\n \"175\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 36,\n \"samples\": [\n \"1.3\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"7\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 4 } ] }, { "cell_type": "code", "source": [ "# URL dataset dari UCI Machine Learning Repository\n", "url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.va.data'\n", "\n", "# Gunakan fungsi read_csv() untuk memuat dataset dari URL\n", "va_df = pd.read_csv(url, header=None)\n", "columns = ['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'num']\n", "va_df.columns = columns\n", "\n", "# Tampilkan beberapa baris pertama dari dataset\n", "print(va_df.shape)\n", "va_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "rnZ58Q_36Lhc", "outputId": "ff44df0a-cfea-46fc-dc1f-7bb68d1b39fc" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(200, 14)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " age sex cp trestbps chol fbs restecg thalach exang oldpeak slope ca \\\n", "0 63 1 4 140 260 0 1 112 1 3 2 ? \n", "1 44 1 4 130 209 0 1 127 0 0 ? ? \n", "2 60 1 4 132 218 0 1 140 1 1.5 3 ? \n", "3 55 1 4 142 228 0 1 149 1 2.5 1 ? \n", "4 66 1 3 110 213 1 2 99 1 1.3 2 ? \n", "\n", " thal num \n", "0 ? 2 \n", "1 ? 0 \n", "2 ? 2 \n", "3 ? 1 \n", "4 ? 0 " ], "text/html": [ "\n", "
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 103,\n \"samples\": [\n 165.0,\n \"132\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 336,\n \"samples\": [\n 257.0,\n 277.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 0.0,\n \"1\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 2.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 198,\n \"samples\": [\n 126.0,\n \"138\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 6 } ] }, { "cell_type": "code", "source": [ "# heart_disease_df.to_csv('heart_disease.csv', index=False)" ], "metadata": { "id": "6zqNClgD7HlI" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# heart_disease_df = pd.read_csv('./heart_disease.csv')\n", "# heart_disease_df" ], "metadata": { "id": "tADQJi148G5n" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "GY-KjbcxB-FL", "outputId": "f9e2f2fc-4aba-4513-d3f5-4b4a005eec5b" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null object \n", " 5 chol 920 non-null object \n", " 6 fbs 920 non-null object \n", " 7 restecg 920 non-null object \n", " 8 thalach 920 non-null object \n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(3), int64(2), object(10)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['trestbps'].replace({'?': 0}, inplace=True)" ], "metadata": { "id": "zHzlTKrzFJTB" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df['trestbps'] = heart_disease_df['trestbps'].astype(float)" ], "metadata": { "id": "c9XtHA3KF2zC" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].mean()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "7k7o87B_IAFM", "outputId": "beeee69e-0528-46c6-fb71-bb8d34848f84" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "132.28604651162792" ] }, "metadata": {}, "execution_count": 12 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].median()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "QjtgzMiTIsOP", "outputId": "1ad4697a-2530-44e2-94a4-d9a0ff7b926d" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "130.0" ] }, "metadata": {}, "execution_count": 13 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].mode()[0]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "dVFBGliBI_mz", "outputId": "390bf838-607b-49bc-b599-1fd094d636b8" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "120.0" ] }, "metadata": {}, "execution_count": 14 } ] }, { "cell_type": "code", "source": [ "sns.histplot(data=heart_disease_df[heart_disease_df['trestbps'] != 0], x=\"trestbps\")\n", "plt.vlines(heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].mean(), 0, 200, color='red', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].median(), 0, 200, color='green', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['trestbps'] != 0]['trestbps'].mode(), 0, 200, color='blue', linestyle='-', lw=3)\n", "plt.legend(labels=[\"Mean\",\"Median\", \"Mode\"])\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "id": "WiyrZYkiGnBl", "outputId": "9ebbf983-5237-4fae-ebbe-d6b8e1b3f236" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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0063.01.01.0145.0233.01.02.0150.00.02.33.00.06.00
1167.01.04.0160.0286.00.02.0108.01.01.52.03.03.02
2267.01.04.0120.0229.00.02.0129.01.02.62.02.07.01
3337.01.03.0130.0250.00.00.0187.00.03.53.00.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 336,\n \"samples\": [\n 257.0,\n 277.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 0.0,\n \"1\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 2.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 198,\n \"samples\": [\n 126.0,\n \"138\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NxVi2sCqKZ6N", "outputId": "3287004d-92a3-4a12-fc5b-536349076084" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null object \n", " 6 fbs 920 non-null object \n", " 7 restecg 920 non-null object \n", " 8 thalach 920 non-null object \n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(4), int64(2), object(9)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['chol'].replace({'?': 0}, inplace=True)" ], "metadata": { "id": "xirflmdWKwaB" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df['chol'] = heart_disease_df['chol'].astype(float)" ], "metadata": { "id": "C06t1c9QKwaC" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['chol'] != 0]['chol'].mean()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "3ec33b26-2583-48d0-fabb-ec48c55eb4c0", "id": "4nwYWdlgKwaD" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "246.83286908077994" ] }, "metadata": {}, "execution_count": 21 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['chol'] != 0]['chol'].median()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "dfb1b425-3f00-4fb5-acbc-c6c8e21e00cd", "id": "_L4K08ehKwaE" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "239.5" ] }, "metadata": {}, "execution_count": 22 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['chol'] != 0]['chol'].mode()[0]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "3a1408df-081e-48b5-c0d7-2cefb69b588d", "id": "wvAi7QaFKwaF" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "220.0" ] }, "metadata": {}, "execution_count": 23 } ] }, { "cell_type": "code", "source": [ "sns.histplot(data=heart_disease_df[heart_disease_df['chol'] != 0], x=\"chol\")\n", "plt.vlines(heart_disease_df[heart_disease_df['chol'] != 0]['chol'].mean(), 0, 100, color='red', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['chol'] != 0]['chol'].median(), 0, 100, color='green', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['chol'] != 0]['chol'].mode()[0], 0, 100, color='blue', linestyle='-', lw=3)\n", "plt.legend(labels=[\"Mean\",\"Median\", \"Mode\"])\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "e4574523-9c43-4df0-b946-f439dad8eb33", "id": "Epw-H7cRKwaF" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['chol'].replace({0: heart_disease_df[heart_disease_df['chol'] != 0]['chol'].median()}, inplace=True)" ], "metadata": { "id": "RyH3eWN-KwaG" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "pOZi1s-BMB6g", "outputId": "e9954cde-c03d-43aa-c374-9e09e3e02b69" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1.0 2.0 150.0 0.0 2.3 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0.0 2.0 108.0 1.0 1.5 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0.0 2.0 129.0 1.0 2.6 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0.0 0.0 187.0 0.0 3.5 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0.0 2.0 172.0 0.0 1.4 \n", "\n", " slope ca thal num \n", "0 3.0 0.0 6.0 0 \n", "1 2.0 3.0 3.0 2 \n", "2 2.0 2.0 7.0 1 \n", "3 3.0 0.0 3.0 0 \n", "4 1.0 0.0 3.0 0 " ], "text/html": [ "\n", "
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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.01.02.0150.00.02.33.00.06.00
1167.01.04.0160.0286.00.02.0108.01.01.52.03.03.02
2267.01.04.0120.0229.00.02.0129.01.02.62.02.07.01
3337.01.03.0130.0250.00.00.0187.00.03.53.00.03.00
4441.00.02.0130.0204.00.02.0172.00.01.41.00.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 0.0,\n \"1\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 2.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 198,\n \"samples\": [\n 126.0,\n \"138\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 26 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "VDZgSB_NMZo6", "outputId": "55e81aae-12c7-4b5c-dd12-bb7decf932be" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null object \n", " 7 restecg 920 non-null object \n", " 8 thalach 920 non-null object \n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(5), int64(2), object(8)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['fbs'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['fbs'] = heart_disease_df['fbs'].astype(int)" ], "metadata": { "id": "Vg23tH_6Mjhs" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"fbs\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "id": "ZCNE_-PVNJW6", "outputId": "5d64b665-8c00-471e-bbf1-c5897a6c48f7" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['fbs'].replace({-1: 0}, inplace=True)" ], "metadata": { "id": "ZFRtSOv4Ndu-" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "9EnT-8HCNl1F", "outputId": "0c1126be-c9f4-4d2c-d9bb-9371df3b326f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2.0 150.0 0.0 2.3 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2.0 108.0 1.0 1.5 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2.0 129.0 1.0 2.6 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0.0 187.0 0.0 3.5 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2.0 172.0 0.0 1.4 \n", "\n", " slope ca thal 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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012.0150.00.02.33.00.06.00
1167.01.04.0160.0286.002.0108.01.01.52.03.03.02
2267.01.04.0120.0229.002.0129.01.02.62.02.07.01
3337.01.03.0130.0250.000.0187.00.03.53.00.03.00
4441.00.02.0130.0204.002.0172.00.01.41.00.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 2.0,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 198,\n \"samples\": [\n 126.0,\n \"138\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 31 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YLYdmZmuNmhD", "outputId": "5f8816b4-0263-464d-c3d0-00290d558da8" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null object \n", " 8 thalach 920 non-null object \n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(5), int64(3), object(7)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['restecg'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['restecg'] = heart_disease_df['restecg'].astype(int)" ], "metadata": { "id": "NNSZKKdwOKvs" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"restecg\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "d89c032d-41fe-41e2-b74c-a8d8540956ae", "id": "J3S3sDHUOKvt" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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asGGDtm3bprffflsOh0MzZsxQQUGBEhMTZbfbNXv2bLndbo0ePVqSlJWVpbS0NE2bNk1Lly6V1+vV/Pnz5fF4OHMDAAAkdTB2Hnjgga/dvnbt2gt6nLq6Ok2fPl3Hjh2Tw+HQjTfeqLffflu33367JGnZsmWKiIhQbm6umpublZ2drVWrVgXuHxkZqc2bN2vWrFlyu93q2bOn8vLyLuqLDQEAgNk6FDtfffVV0O3W1lZ9/PHHqq+vP+cfCD2fF1544Wu3d+/eXStXrtTKlSvPu0///v31t7/97YKfEwAAXFk6FDsbN248a117e7tmzZqla6+99pKHAgAACJUO/22ssx4oIkIFBQVatmxZqB4SAADgkoUsdiTpyJEj/BFOAAAQVjr0Ntb/fiGfJPn9fh07dkxvvvmm8vLyQjIYAABAKHQodj744IOg2xEREUpKStKTTz75jZ/UAgAA6Eodip333nsv1HMAAAB0ikv6UsHjx4+rsrJS0n/+xlVSUlJIhgIAAAiVDl2g3NjYqAceeEB9+vTRLbfcoltuuUUpKSmaMWOG/vWvf4V6RgAAgA7rUOwUFBSotLRUb7zxhurr61VfX6/XX39dpaWl+vnPfx7qGQEAADqsQ29j/fnPf9Zrr72msWPHBtbdcccdio2N1T333KPVq1eHaj4AAIBL0qEzO//617/kdDrPWp+cnMzbWAAAIKx0KHbcbrcWLlyopqamwLp///vf+vWvfy232x2y4QAAAC5Vh97GWr58ucaPH6++fftq2LBhkqQPP/xQMTEx2rp1a0gHBAAAuBQdip309HQdOnRIL7/8sj777DNJ0pQpUzR16lTFxsaGdEAAAIBL0aHYKSoqktPp1MyZM4PWr127VsePH9e8efNCMhwAAMCl6tA1O88++6wGDx581vqhQ4dqzZo1lzwUAABAqHQodrxer/r06XPW+qSkJB07duyShwIAAAiVDsVOamqqysrKzlpfVlamlJSUSx4KAAAgVDp0zc7MmTM1Z84ctba2aty4cZKkkpISPfzww3yDMgAACCsdip25c+fqn//8p37yk5+opaVFktS9e3fNmzdPhYWFIR0QAADgUnQodmw2mx5//HE98sgj+vTTTxUbG6vrrrtOMTExoZ4PAADgknQods6Ii4vTyJEjQzULAABAyHXoAmUAAIDLBbEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKNZGjtFRUUaOXKk4uPjlZycrEmTJqmysjJon6amJnk8HvXq1UtxcXHKzc1VbW1t0D5VVVXKyclRjx49lJycrLlz5+r06dNdeSgAACBMWRo7paWl8ng82rVrl4qLi9Xa2qqsrCw1NjYG9nnooYf0xhtv6NVXX1Vpaalqamo0efLkwPa2tjbl5OSopaVFO3fu1Pr167Vu3TotWLDAikMCAABhxub3+/1WD3HG8ePHlZycrNLSUt1yyy1qaGhQUlKSNmzYoLvvvluS9Nlnn2nIkCEqLy/X6NGj9dZbb+nOO+9UTU2NnE6nJGnNmjWaN2+ejh8/rujo6G98Xp/PJ4fDoYaGBtnt9k49RlyeMua+ZPUI+K+KJ6ZbPQKAMHGhv7/D6pqdhoYGSVJiYqIkqaKiQq2trcrMzAzsM3jwYPXr10/l5eWSpPLycqWnpwdCR5Kys7Pl8/l08ODBcz5Pc3OzfD5f0AIAAMwUNrHT3t6uOXPm6Oabb9YNN9wgSfJ6vYqOjlZCQkLQvk6nU16vN7DP/4bOme1ntp1LUVGRHA5HYElNTQ3x0QAAgHARNrHj8Xj08ccf65VXXun05yosLFRDQ0Ngqa6u7vTnBAAA1oiyegBJys/P1+bNm7V9+3b17ds3sN7lcqmlpUX19fVBZ3dqa2vlcrkC++zZsyfo8c58WuvMPv9XTEyMYmJiQnwUAAAgHFl6Zsfv9ys/P18bN27Uu+++q4EDBwZtz8jIULdu3VRSUhJYV1lZqaqqKrndbkmS2+3WgQMHVFdXF9inuLhYdrtdaWlpXXMgAAAgbFl6Zsfj8WjDhg16/fXXFR8fH7jGxuFwKDY2Vg6HQzNmzFBBQYESExNlt9s1e/Zsud1ujR49WpKUlZWltLQ0TZs2TUuXLpXX69X8+fPl8Xg4ewMAAKyNndWrV0uSxo4dG7T+xRdf1H333SdJWrZsmSIiIpSbm6vm5mZlZ2dr1apVgX0jIyO1efNmzZo1S263Wz179lReXp4WL17cVYcBAADCWFh9z45V+J4dfBO+Zyd88D07AM64LL9nBwAAINTC4tNYAABYhTO34aOzztxyZgcAABiN2AEAAEYjdgAAgNGIHQAAYDQuUAaA/4MLVsMHXzWAUODMDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxmaexs375dEydOVEpKimw2mzZt2hS03e/3a8GCBerTp49iY2OVmZmpQ4cOBe1z4sQJTZ06VXa7XQkJCZoxY4ZOnTrVhUcBAADCmaWx09jYqGHDhmnlypXn3L506VKtWLFCa9as0e7du9WzZ09lZ2erqakpsM/UqVN18OBBFRcXa/Pmzdq+fbsefPDBrjoEAAAQ5qKsfPIJEyZowoQJ59zm9/u1fPlyzZ8/X3fddZck6aWXXpLT6dSmTZt077336tNPP9WWLVu0d+9ejRgxQpL09NNP64477tDvfvc7paSkdNmxAACA8BS21+wcPXpUXq9XmZmZgXUOh0OjRo1SeXm5JKm8vFwJCQmB0JGkzMxMRUREaPfu3ed97ObmZvl8vqAFAACYKWxjx+v1SpKcTmfQeqfTGdjm9XqVnJwctD0qKkqJiYmBfc6lqKhIDocjsKSmpoZ4egAAEC7CNnY6U2FhoRoaGgJLdXW11SMBAIBOErax43K5JEm1tbVB62trawPbXC6X6urqgrafPn1aJ06cCOxzLjExMbLb7UELAAAwU9jGzsCBA+VyuVRSUhJY5/P5tHv3brndbkmS2+1WfX29KioqAvu8++67am9v16hRo7p8ZgAAEH4s/TTWqVOndPjw4cDto0ePav/+/UpMTFS/fv00Z84cLVmyRNddd50GDhyoRx55RCkpKZo0aZIkaciQIRo/frxmzpypNWvWqLW1Vfn5+br33nv5JBYAAJBkcey8//77uvXWWwO3CwoKJEl5eXlat26dHn74YTU2NurBBx9UfX29xowZoy1btqh79+6B+7z88svKz8/XbbfdpoiICOXm5mrFihVdfiwAACA8WRo7Y8eOld/vP+92m82mxYsXa/HixefdJzExURs2bOiM8QAAgAHC9podAACAUCB2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGMyZ2Vq5cqQEDBqh79+4aNWqU9uzZY/VIAAAgDBgRO3/84x9VUFCghQsXat++fRo2bJiys7NVV1dn9WgAAMBiUVYPEApPPfWUZs6cqfvvv1+StGbNGr355ptau3atfvnLX3bKc2bMfalTHhcXr+KJ6VaPAAAIY5d97LS0tKiiokKFhYWBdREREcrMzFR5efk579Pc3Kzm5ubA7YaGBkmSz+e74Odta/53BydGqF3M69ZRvN7hg9f7ysLrfWW52Nf7zP5+v//rd/Rf5v7xj3/4Jfl37twZtH7u3Ln+m2666Zz3WbhwoV8SCwsLCwsLiwFLdXX117bCZX9mpyMKCwtVUFAQuN3e3q4TJ06oV69estlsFk7WtXw+n1JTU1VdXS273W71OOhkvN5XFl7vK8uV+nr7/X6dPHlSKSkpX7vfZR87vXv3VmRkpGpra4PW19bWyuVynfM+MTExiomJCVqXkJDQWSOGPbvdfkX9x3Gl4/W+svB6X1muxNfb4XB84z6X/aexoqOjlZGRoZKSksC69vZ2lZSUyO12WzgZAAAIB5f9mR1JKigoUF5enkaMGKGbbrpJy5cvV2NjY+DTWQAA4MplROz88Ic/1PHjx7VgwQJ5vV4NHz5cW7ZskdPptHq0sBYTE6OFCxee9ZYezMTrfWXh9b6y8Hp/PZvf/02f1wIAALh8XfbX7AAAAHwdYgcAABiN2AEAAEYjdgAAgNGInSvUX/7yF2VlZQW+NXr//v1Wj4ROtHLlSg0YMEDdu3fXqFGjtGfPHqtHQifZvn27Jk6cqJS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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['restecg'].replace({-1: 0}, inplace=True)" ], "metadata": { "id": "iz-SOcckOKvt" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "HAs0FILtPTTU", "outputId": "17ac70be-40ff-4721-993a-0e07333c2da8" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2 150.0 0.0 2.3 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2 108.0 1.0 1.5 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2 129.0 1.0 2.6 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0 187.0 0.0 3.5 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2 172.0 0.0 1.4 \n", "\n", " slope ca thal num 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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012150.00.02.33.00.06.00
1167.01.04.0160.0286.002108.01.01.52.03.03.02
2267.01.04.0120.0229.002129.01.02.62.02.07.01
3337.01.03.0130.0250.000187.00.03.53.00.03.00
4441.00.02.0130.0204.002172.00.01.41.00.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 2,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 198,\n \"samples\": [\n 126.0,\n \"138\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 36 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "RMpdUhS9EY8p", "outputId": "75a0e362-a23d-469d-ccf5-9f4a3b9143d2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null object \n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(5), int64(4), object(6)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['thalach'].replace({'?': 0}, inplace=True)" ], "metadata": { "id": "_Ebm6XxP3cHV" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df['thalach'] = heart_disease_df['thalach'].astype(float)" ], "metadata": { "id": "_kqIdxc-3cHW" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].mean()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "b2956346-187d-458c-cef1-52ded76f07bb", "id": "sUqLNt4_3cHX" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "137.5456647398844" ] }, "metadata": {}, "execution_count": 40 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].median()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "438b2780-784e-499e-abbd-7fe05dcbcbdc", "id": "nGyralXK3cHX" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "140.0" ] }, "metadata": {}, "execution_count": 41 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].mode()[0]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "92073111-8f61-4514-860b-e50997e18d68", "id": "efhsL8p43cHY" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "150.0" ] }, "metadata": {}, "execution_count": 42 } ] }, { "cell_type": "code", "source": [ "sns.histplot(data=heart_disease_df[heart_disease_df['thalach'] != 0], x=\"thalach\")\n", "plt.vlines(heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].mean(), 0, 200, color='red', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].median(), 0, 200, color='green', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].mode()[0], 0, 200, color='blue', linestyle='-', lw=3)\n", "plt.legend(labels=[\"Mean\",\"Median\", \"Mode\"])\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "05679065-7bf4-4fd5-8b8b-966d1341c7da", "id": "8DYt7q0J3cHY" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['thalach'].replace({0: heart_disease_df[heart_disease_df['thalach'] != 0]['thalach'].median()}, inplace=True)" ], "metadata": { "id": "ZIcIEZiy3x6W" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "outputId": "8567c45c-7c56-48f4-b06a-bdfd8b3d6b23", "id": "qzuNriGR3x6Y" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2 150.0 0.0 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2 108.0 1.0 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2 129.0 1.0 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0 187.0 0.0 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2 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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012150.00.02.33.00.06.00
1167.01.04.0160.0286.002108.01.01.52.03.03.02
2267.01.04.0120.0229.002129.01.02.62.02.07.01
3337.01.03.0130.0250.000187.00.03.53.00.03.00
4441.00.02.0130.0204.002172.00.01.41.00.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 2,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25.145235299317264,\n \"min\": 60.0,\n \"max\": 202.0,\n \"num_unique_values\": 119,\n \"samples\": [\n 185.0,\n 134.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0,\n \"?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 82,\n \"samples\": [\n 0.1,\n 2.3\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 45 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "50118a1b-de7c-4ec7-aa4b-743a12c8436e", "id": "xq57BMRL3x6Y" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null object \n", " 10 oldpeak 920 non-null object \n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(6), int64(4), object(5)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['exang'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['exang'] = heart_disease_df['exang'].astype(int)" ], "metadata": { "id": "tvBmwPfT6IWR" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"exang\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "728cf099-4e1c-41a6-dc40-ff324d80176a", "id": "Yh_jsyAd6IWS" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 0,\n 2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 26.076305423948227,\n \"min\": 60.0,\n \"max\": 202.0,\n \"num_unique_values\": 97,\n \"samples\": [\n 90.0,\n 125.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 1,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"?\",\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 1.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"0.0\",\n \"1.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"7.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 1,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 54 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].mean()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "3g7nS6qq6f1F", "outputId": "deb98be9-1954-4df1-c9a7-3e157ff4c91b" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "0.8787878787878787" ] }, "metadata": {}, "execution_count": 55 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].median()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NtZ15VP68dnE", "outputId": "317a6da1-cd08-4b88-cc17-2960d86cdd5f" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "0.5" ] }, "metadata": {}, "execution_count": 56 } ] }, { "cell_type": "code", "source": [ "heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].mode()[0]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "7PGL6zQh8qSf", "outputId": "ac3db2b0-1181-45d3-9657-418102f130b1" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "0.0" ] }, "metadata": {}, "execution_count": 57 } ] }, { "cell_type": "code", "source": [ "sns.histplot(data=heart_disease_df[heart_disease_df['oldpeak'] != '?'], x=\"oldpeak\")\n", "plt.vlines(heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].mean(), 0, 400, color='red', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].median(), 0, 400, color='green', linestyle='-', lw=3)\n", "plt.vlines(heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].mode()[0], 0, 400, color='blue', linestyle='-', lw=3)\n", "plt.legend(labels=[\"Mean\",\"Median\", \"Mode\"])\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "id": "0FBHnYQ-8rng", "outputId": "00081344-cf34-4d30-bda6-2150fd943425" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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37rxp06Z67rnn1KpVK9lsNi1btkx33XWXvv32W91www2SpNGjR2vWrFn2dfz9/e1fl5eXKy4uTmFhYdq8ebOOHj2qhx56SN7e3pd9FD0AAJUREnL19mWzOb/uyJEjtXTpUg0ePFiStGTJEo0YMULr16+3j3nyySf1wQcfaNmyZWrWrJnmzp2r2NhYZWVlKTg4WIcOHdI999yjhIQEjRkzRtu3b9fjjz/usJ/s7Gz1799fzzzzjJYsWaJjx44pMTFRiYmJWrp0qfMHUA3cemZn0KBBGjhwoFq1aqXrr79ezz77rOrXr68tW7bYx/j7+yssLMy+/PoR7l988YX27dunt99+Wx06dNCAAQM0e/ZspaamqrS01B2HBACAWw0ZMkRff/21fvzxR/3444/atGmThgwZYu8vKirSokWL9Pzzz2vAgAGKiYnRG2+8IT8/P7355puSfrny0qJFC82fP1+tW7fW4MGDz5vvk5KSosGDB2vChAlq1aqVbr75Zr300kt66623VFxcfDUP+bI8Zs5OeXm5li9frqKiIlksFnv7O++8o0aNGunGG29UcnKyTp8+be/LyMhQ27ZtFRoaam+LjY2V1WrV3r17L7qvkpISWa1WhwUAACNo3Lix4uLilJaWpqVLlyouLk6NGjWy92dnZ6usrEw9evSwt3l7e+umm27S/v37JUn79+9Xt27dHLb769/NkvSvf/1LaWlpql+/vn2JjY1VRUWFDh48WI1HWHluvYwlSbt375bFYlFxcbHq16+vDz/8UDExMZKkBx98UM2aNVOTJk20a9cuTZ48WQcOHLBfi8zNzXUIOpLsr3Nzcy+6z5SUFM2cObOajggAAPcaOXKkEhMTJUmpqanVso/CwkI98sgjGj9+/Hl9njYZ2u1hp3Xr1tq5c6cKCgr0/vvva9iwYdqwYYNiYmI0ZswY+7i2bdsqPDxcffr0UXZ2tlq0aOH0PpOTk5WUlGR/bbVaFRERUaXjAAAYW36+uyu4cv3791dpaalMJpNiY2Md+lq0aKG6detq06ZNatasmSSprKxM27Zt04QJEyRJ0dHR+vjjjx3W+/UUE+mXydD79u1Ty5Ytq+9AXMTtYadu3br2b1Tnzp21bds2vfjii3rttdfOG3vulFpWVpZatGihsLAwffPNNw5j8vLyJElhYWEX3aePj498fHxcdQgAgFqgcWN3V3DlvLy87JekvLy8HPrq1aunsWPHatKkSQoODlZkZKTmzp2r06dPa9SoUZKkRx99VPPnz9ekSZP08MMPKzMzU2lpaQ7bmTx5srp3767ExEQ9/PDDqlevnvbt26c1a9bolVdeuSrHeaU8Zs7OORUVFSopKblg386dOyVJ4eHhkn65frh7927l/ypur1mzRmaz2X4pDACA2ujcx7pcyHPPPaf4+HgNHTpUnTp1UlZWllavXq0GDRpI+uUy1AcffKCPPvpI7du31+LFi8+7y7ldu3basGGD/v3vf+uWW25Rx44dNW3aNDVp0qTaj62y3HpmJzk5WQMGDFBkZKROnTql9PR0rV+/XqtXr1Z2drbS09M1cOBANWzYULt27dLEiRN16623ql27dpKkfv36KSYmRkOHDtXcuXOVm5urKVOmKCEhgTM3AIBa5bdnXn7ro48+sn/t6+url156SS+99NJFx99555268847HdpGjBjh8Lpr16764osvKl3r1ebWsJOfn6+HHnpIR48eVWBgoNq1a6fVq1frjjvu0KFDh7R27VotXLhQRUVFioiIUHx8vKZMmWJf38vLSytXrtTYsWNlsVhUr149DRs2zOFzeQAAQO3m1rBz7n7+C4mIiNCGDRsuu41mzZrps88+c2VZAADAQDxuzg4AAIArEXYAAIChEXYAAPgNW1UeTgWXcsV7QdgBAOB/vL29Jcnh0URwr3Pvxbn3xhlu/1BBAAA8hZeXl4KCguyf3+bv7y+TyeTmqmonm82m06dPKz8/X0FBQed9OGJlEHYAAPiVc5/An1+Tng9hYEFBQZd8KsKVIOwAAPArJpNJ4eHhCgkJUVlZmbvLqdW8vb2rdEbnHMIOAAAX4OXl5ZJftHA/JigDAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDI+wAAABDc2vYWbRokdq1ayez2Syz2SyLxaLPP//c3l9cXKyEhAQ1bNhQ9evXV3x8vPLy8hy2kZOTo7i4OPn7+yskJESTJk3S2bNnr/ahAAAAD+XWsNO0aVM999xzyszM1Pbt23X77bfrrrvu0t69eyVJEydO1CeffKL33ntPGzZs0JEjR3TPPffY1y8vL1dcXJxKS0u1efNmLVu2TGlpaZo2bZq7DgkAAHiYa9y580GDBjm8fvbZZ7Vo0SJt2bJFTZs21Ztvvqn09HTdfvvtkqSlS5cqOjpaW7ZsUffu3fXFF19o3759Wrt2rUJDQ9WhQwfNnj1bkydP1owZM1S3bl13HBYAAPAgHjNnp7y8XMuXL1dRUZEsFosyMzNVVlamvn372se0adNGkZGRysjIkCRlZGSobdu2Cg0NtY+JjY2V1Wq1nx26kJKSElmtVocFAAAYk9vDzu7du1W/fn35+Pjo0Ucf1YcffqiYmBjl5uaqbt26CgoKchgfGhqq3NxcSVJubq5D0DnXf67vYlJSUhQYGGhfIiIiXHtQAADAY7g97LRu3Vo7d+7U1q1bNXbsWA0bNkz79u2r1n0mJyeroKDAvhw6dKha9wcAANzHrXN2JKlu3bpq2bKlJKlz587atm2bXnzxRd13330qLS3VyZMnHc7u5OXlKSwsTJIUFhamb775xmF75+7WOjfmQnx8fOTj4+PiIwEAAJ7I7Wd2fquiokIlJSXq3LmzvL29tW7dOnvfgQMHlJOTI4vFIkmyWCzavXu38vPz7WPWrFkjs9msmJiYq147AADwPG49s5OcnKwBAwYoMjJSp06dUnp6utavX6/Vq1crMDBQo0aNUlJSkoKDg2U2mzVu3DhZLBZ1795dktSvXz/FxMRo6NChmjt3rnJzczVlyhQlJCRw5gYAAEhyc9jJz8/XQw89pKNHjyowMFDt2rXT6tWrdccdd0iSFixYoDp16ig+Pl4lJSWKjY3Vq6++al/fy8tLK1eu1NixY2WxWFSvXj0NGzZMs2bNctchAQAAD+PWsPPmm29est/X11epqalKTU296JhmzZrps88+c3VpAADAIDxuzg4AAIArEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChuTXspKSkqGvXrgoICFBISIjuvvtuHThwwGFM7969ZTKZHJZHH33UYUxOTo7i4uLk7++vkJAQTZo0SWfPnr2ahwIAADzUNe7c+YYNG5SQkKCuXbvq7Nmzevrpp9WvXz/t27dP9erVs48bPXq0Zs2aZX/t7+9v/7q8vFxxcXEKCwvT5s2bdfToUT300EPy9vbWnDlzrurxAAAAz+PWsLNq1SqH12lpaQoJCVFmZqZuvfVWe7u/v7/CwsIuuI0vvvhC+/bt09q1axUaGqoOHTpo9uzZmjx5smbMmKG6detW6zEAAADP5lFzdgoKCiRJwcHBDu3vvPOOGjVqpBtvvFHJyck6ffq0vS8jI0Nt27ZVaGiovS02NlZWq1V79+694H5KSkpktVodFgAAYExuPbPzaxUVFZowYYJ69OihG2+80d7+4IMPqlmzZmrSpIl27dqlyZMn68CBA1qxYoUkKTc31yHoSLK/zs3NveC+UlJSNHPmzGo6EgAA4Ek8JuwkJCRoz549+vrrrx3ax4wZY/+6bdu2Cg8PV58+fZSdna0WLVo4ta/k5GQlJSXZX1utVkVERDhXOAAA8GgecRkrMTFRK1eu1FdffaWmTZtecmy3bt0kSVlZWZKksLAw5eXlOYw59/pi83x8fHxkNpsdFgAAYExuDTs2m02JiYn68MMP9eWXXyoqKuqy6+zcuVOSFB4eLkmyWCzavXu38vPz7WPWrFkjs9msmJiYaqkbAADUHG69jJWQkKD09HT94x//UEBAgH2OTWBgoPz8/JSdna309HQNHDhQDRs21K5duzRx4kTdeuutateunSSpX79+iomJ0dChQzV37lzl5uZqypQpSkhIkI+PjzsPDwAAeAC3ntlZtGiRCgoK1Lt3b4WHh9uXd999V5JUt25drV27Vv369VObNm30+OOPKz4+Xp988ol9G15eXlq5cqW8vLxksVg0ZMgQPfTQQw6fywMAAGovt57Zsdlsl+yPiIjQhg0bLrudZs2a6bPPPnNVWQAAwEA8YoIyAABAdSHsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQyPsAAAAQ3Mq7DRv3lw//fTTee0nT55U8+bNq1wUAACAqzgVdn744QeVl5ef115SUqLDhw9XuSgAAABXqdSDQD/++GP716tXr1ZgYKD9dXl5udatW6frrrvOZcUBAABUVaXCzt133y1JMplMGjZsmEOft7e3rrvuOs2fP99lxQEAAFRVpcJORUWFJCkqKkrbtm1To0aNqqUoAAAAV6lU2Dnn4MGDrq4DAACgWjgVdiRp3bp1WrdunfLz8+1nfM5ZsmRJlQsDAABwBafCzsyZMzVr1ix16dJF4eHhMplMrq4LAADAJZwKO4sXL1ZaWpqGDh3q6noAAABcyqnP2SktLdXNN9/s6loAAABczqmw8/DDDys9Pd3VtQAAALicU5exiouL9frrr2vt2rVq166dvL29HfpfeOEFlxQHAABQVU6FnV27dqlDhw6SpD179jj0MVkZAAB4EqfCzldffeXqOgAAAKqFU3N2AAAAagqnzuzcdtttl7xc9eWXXzpdEAAAgCs5FXbOzdc5p6ysTDt37tSePXvOe0AoAACAOzkVdhYsWHDB9hkzZqiwsLBKBQEAALiSS+fsDBkyhOdiAQAAj+LSsJORkSFfX19XbhIAAKBKnLqMdc899zi8ttlsOnr0qLZv366pU6e6pDAAAABXcCrsBAYGOryuU6eOWrdurVmzZqlfv34uKQwAAMAVnAo7S5cudXUdAAAA1aJKc3YyMzP19ttv6+2339a3335b6fVTUlLUtWtXBQQEKCQkRHfffbcOHDjgMKa4uFgJCQlq2LCh6tevr/j4eOXl5TmMycnJUVxcnPz9/RUSEqJJkybp7NmzVTk0AABgEE6Fnfz8fN1+++3q2rWrxo8fr/Hjx6tz587q06ePjh07dsXb2bBhgxISErRlyxatWbNGZWVl6tevn4qKiuxjJk6cqE8++UTvvfeeNmzYoCNHjjjMGSovL1dcXJxKS0u1efNmLVu2TGlpaZo2bZozhwYAAAzGqbAzbtw4nTp1Snv37tWJEyd04sQJ7dmzR1arVePHj7/i7axatUrDhw/XDTfcoPbt2ystLU05OTnKzMyUJBUUFOjNN9/UCy+8oNtvv12dO3fW0qVLtXnzZm3ZskWS9MUXX2jfvn16++231aFDBw0YMECzZ89WamqqSktLnTk8AABgIE6FnVWrVunVV19VdHS0vS0mJkapqan6/PPPnS6moKBAkhQcHCzpl8tkZWVl6tu3r31MmzZtFBkZqYyMDEm/3O7etm1bhYaG2sfExsbKarVq7969F9xPSUmJrFarwwIAAIzJqbBTUVEhb2/v89q9vb1VUVHhVCEVFRWaMGGCevTooRtvvFGSlJubq7p16yooKMhhbGhoqHJzc+1jfh10zvWf67uQlJQUBQYG2peIiAinagYAAJ7PqbBz++23649//KOOHDlibzt8+LAmTpyoPn36OFVIQkKC9uzZo+XLlzu1fmUkJyeroKDAvhw6dKja9wkAANzDqbDzyiuvyGq16rrrrlOLFi3UokULRUVFyWq16uWXX6709hITE7Vy5Up99dVXatq0qb09LCxMpaWlOnnypMP4vLw8hYWF2cf89u6sc6/PjfktHx8fmc1mhwUAABiTU5+zExERoR07dmjt2rX67rvvJEnR0dEOc2uuhM1m07hx4/Thhx9q/fr1ioqKcujv3LmzvL29tW7dOsXHx0uSDhw4oJycHFksFkmSxWLRs88+q/z8fIWEhEiS1qxZI7PZrJiYGGcODwAAGEilws6XX36pxMREbdmyRWazWXfccYfuuOMOSb9MLr7hhhu0ePFi3XLLLVe0vYSEBKWnp+sf//iHAgIC7HNsAgMD5efnp8DAQI0aNUpJSUkKDg6W2WzWuHHjZLFY1L17d0lSv379FBMTo6FDh2ru3LnKzc3VlClTlJCQIB8fn8ocHgAAMKBKXcZauHChRo8efcHLPoGBgXrkkUf0wgsvXPH2Fi1apIKCAvXu3Vvh4eH25d1337WPWbBgge68807Fx8fr1ltvVVhYmFasWGHv9/Ly0sqVK+Xl5SWLxaIhQ4booYce0qxZsypzaAAAwKAqdWbnX//6l/785z9ftL9fv36aN2/eFW/PZrNddoyvr69SU1OVmpp60THNmjXTZ599dsX7BQAAtUelzuzk5eVd8Jbzc6655ppKfYIyAABAdatU2Ln22mu1Z8+ei/bv2rVL4eHhVS4KAADAVSoVdgYOHKipU6equLj4vL4zZ85o+vTpuvPOO11WHAAAQFVVas7OlClTtGLFCl1//fVKTExU69atJUnfffedUlNTVV5erj/96U/VUigAAIAzKhV2QkNDtXnzZo0dO1bJycn2CcYmk0mxsbFKTU0979ENAAAA7lTpDxU8d+fTzz//rKysLNlsNrVq1UoNGjSojvoAAACqxKlPUJakBg0aqGvXrq6sBQAAwOWcejYWAABATUHYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhkbYAQAAhubWsLNx40YNGjRITZo0kclk0kcffeTQP3z4cJlMJoelf//+DmNOnDihwYMHy2w2KygoSKNGjVJhYeFVPAoAAODJ3Bp2ioqK1L59e6Wmpl50TP/+/XX06FH78re//c2hf/Dgwdq7d6/WrFmjlStXauPGjRozZkx1lw4AAGqIa9y58wEDBmjAgAGXHOPj46OwsLAL9u3fv1+rVq3Stm3b1KVLF0nSyy+/rIEDB2revHlq0qSJy2sGAAA1i8fP2Vm/fr1CQkLUunVrjR07Vj/99JO9LyMjQ0FBQfagI0l9+/ZVnTp1tHXr1otus6SkRFar1WEBAADG5NFhp3///nrrrbe0bt06/fnPf9aGDRs0YMAAlZeXS5Jyc3MVEhLisM4111yj4OBg5ebmXnS7KSkpCgwMtC8RERHVehwAAMB93HoZ63Luv/9++9dt27ZVu3bt1KJFC61fv159+vRxervJyclKSkqyv7ZarQQeAAAMyqPP7PxW8+bN1ahRI2VlZUmSwsLClJ+f7zDm7NmzOnHixEXn+Ui/zAMym80OCwAAMKYaFXb++9//6qefflJ4eLgkyWKx6OTJk8rMzLSP+fLLL1VRUaFu3bq5q0wAAOBB3HoZq7Cw0H6WRpIOHjyonTt3Kjg4WMHBwZo5c6bi4+MVFham7OxsPfnkk2rZsqViY2MlSdHR0erfv79Gjx6txYsXq6ysTImJibr//vu5EwsAAEhy85md7du3q2PHjurYsaMkKSkpSR07dtS0adPk5eWlXbt26Xe/+52uv/56jRo1Sp07d9Y///lP+fj42LfxzjvvqE2bNurTp48GDhyonj176vXXX3fXIQEAAA/j1jM7vXv3ls1mu2j/6tWrL7uN4OBgpaenu7IsAABgIDVqzg4AAEBlEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChEXYAAIChuTXsbNy4UYMGDVKTJk1kMpn00UcfOfTbbDZNmzZN4eHh8vPzU9++ffWf//zHYcyJEyc0ePBgmc1mBQUFadSoUSosLLyKRwEAADyZW8NOUVGR2rdvr9TU1Av2z507Vy+99JIWL16srVu3ql69eoqNjVVxcbF9zODBg7V3716tWbNGK1eu1MaNGzVmzJirdQgAAMDDXePOnQ8YMEADBgy4YJ/NZtPChQs1ZcoU3XXXXZKkt956S6Ghofroo490//33a//+/Vq1apW2bdumLl26SJJefvllDRw4UPPmzVOTJk2u2rEAAADP5LFzdg4ePKjc3Fz17dvX3hYYGKhu3bopIyNDkpSRkaGgoCB70JGkvn37qk6dOtq6detFt11SUiKr1eqwAAAAY/LYsJObmytJCg0NdWgPDQ219+Xm5iokJMSh/5prrlFwcLB9zIWkpKQoMDDQvkRERLi4egAA4Ck8NuxUp+TkZBUUFNiXQ4cOubskAABQTTw27ISFhUmS8vLyHNrz8vLsfWFhYcrPz3foP3v2rE6cOGEfcyE+Pj4ym80OCwAAMCaPDTtRUVEKCwvTunXr7G1Wq1Vbt26VxWKRJFksFp08eVKZmZn2MV9++aUqKirUrVu3q14zAADwPG69G6uwsFBZWVn21wcPHtTOnTsVHBysyMhITZgwQc8884xatWqlqKgoTZ06VU2aNNHdd98tSYqOjlb//v01evRoLV68WGVlZUpMTNT999/PnVgAAECSm8PO9u3bddttt9lfJyUlSZKGDRumtLQ0PfnkkyoqKtKYMWN08uRJ9ezZU6tWrZKvr699nXfeeUeJiYnq06eP6tSpo/j4eL300ktX/VgAAIBncmvY6d27t2w220X7TSaTZs2apVmzZl10THBwsNLT06ujPAAAYABuDTsAapZdu3bpbIMGlVqnUaNGioyMrKaKAODyCDsArlifvn11vJLr+Pn567vv9hN4ALgNYQfAFes94UUV1Lvyj2qwHv1BW5fM1PHjxwk7ANyGsAPgigU1bSmvgMpdxgIAd/PYz9kBAABwBcIOAAAwNMIOAAAwNObsADC8nJwcHT9e2fvI/j9unwdqNsIOAEPLyclRmzbROnPmtNPb4PZ5oGYj7AAwtOPHj+vMmdPqNnK6zOHXVXp9bp8Haj7CDoBawRx+nYIjW7u7DABuwARlAABgaIQdAABgaFzGAuDxqnI31f79+11cDYCahrADwKO54m4qSSorKXVRRQBqGsIOAI9W1bupju7O0J6PX9fZs2ddXxyAGoGwA6BGcPZuKuvRH1xfDIAahQnKAADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Ag7AADA0Dw67MyYMUMmk8lhadOmjb2/uLhYCQkJatiwoerXr6/4+Hjl5eW5sWIAAOBpPDrsSNINN9ygo0eP2pevv/7a3jdx4kR98skneu+997RhwwYdOXJE99xzjxurBQAAnuYadxdwOddcc43CwsLOay8oKNCbb76p9PR03X777ZKkpUuXKjo6Wlu2bFH37t2vdqkAAMADefyZnf/85z9q0qSJmjdvrsGDBysnJ0eSlJmZqbKyMvXt29c+tk2bNoqMjFRGRsYlt1lSUiKr1eqwAAAAY/LosNOtWzelpaVp1apVWrRokQ4ePKhbbrlFp06dUm5ururWraugoCCHdUJDQ5Wbm3vJ7aakpCgwMNC+REREVONRAAAAd/Loy1gDBgywf92uXTt169ZNzZo109///nf5+fk5vd3k5GQlJSXZX1utVgIPAAAG5dFndn4rKChI119/vbKyshQWFqbS0lKdPHnSYUxeXt4F5/j8mo+Pj8xms8MCAACMqUaFncLCQmVnZys8PFydO3eWt7e31q1bZ+8/cOCAcnJyZLFY3FglAADwJB59GeuJJ57QoEGD1KxZMx05ckTTp0+Xl5eXHnjgAQUGBmrUqFFKSkpScHCwzGazxo0bJ4vFwp1YAADAzqPDzn//+1898MAD+umnn9S4cWP17NlTW7ZsUePGjSVJCxYsUJ06dRQfH6+SkhLFxsbq1VdfdXPVAADAk3h02Fm+fPkl+319fZWamqrU1NSrVBEAAKhpatScHQAAgMoi7AAAAEMj7AAAAEPz6Dk7AIxh//79blkXACTCDoBqdKbgJ0kmDRkypMrbKisprXpBNVROTo6OHz/u9PqNGjVSZGSkCysCahbCDoBqU3b6lCSbOjw4WY2j2ji1jaO7M7Tn49d19uxZ1xZXQ+Tk5KhNm2idOXPa6W34+fnru+/2E3hQaxF2gBrgSi/l/Fzy83lt27ZvU1jApR+hciHX/Pyz2lV6rQurHxKp4MjWTq1rPfqDi6qomY4fP64zZ06r28jpModfV+n1rUd/0NYlM3X8+HHCDmotwg7gwSp9Gchf0pOOTXFxcVJR5ffdSNKxyq+GamIOv87pwAjUdoQdwINV9jJQqazaoD86Ntrk1GWkwCKrtPCPlx8IAB6OsAPUAFd6Gai4/Gcp3/n1fy3g1PmXxACgJuJzdgAAgKERdgAAgKERdgAAgKERdgAAgKERdgAAgKFxNxYAVLOqPO6BZ4MBVUfYAYBq5IrHPUi1+9lgQFURdgCgGlX1cQ+1/dlggCsQdgDgKnD2cQ+1/dlggCswQRkAABgaYQcAABgaYQcAABgaYQcAABgaYQcAABgaYQcAABgaYQcAABgan7MDAFfA2cc28LgHwP0IOwBwCWcKfpJk0pAhQ6q0ndr8uIeqPBtMkho1aqTIyEgXVoTahrADAJdQdvqUJJs6PDhZjaPaVHp9IzzuoSph5ejRo/q///uDiovPOL1/Pz9/fffdfgIPnEbYAYArUD8kslY+7sFVDzLtPPRpBUe2qvR61qM/aOuSmTp+/DhhB04j7AAALspVDzL1a3itU2ERcAXCDgDgsniQKWoywg48HpMbAQBVYZiwk5qaqueff165ublq3769Xn75Zd10003uLgtV5Ir5Aj4+vvrgg/cVHh7u1PqEJRgBt86jNjNE2Hn33XeVlJSkxYsXq1u3blq4cKFiY2N14MABhYSEuLs8VEFV5wsc+8+/tPPvL+rOO+90ugbuBEFNZpRb56sSuviDBYYIOy+88IJGjx6tESNGSJIWL16sTz/9VEuWLNFTTz3l1tqqegmmpKREPj4+Tq/viv/k7jyGcz/gqjZfwPnbhs/dCfLPf/5T0dHRlV6fv4rhbjX91nlXhLWqnt2Vqv6z1N2X443wu6gqanzYKS0tVWZmppKTk+1tderUUd++fZWRkXHBdUpKSlRSUmJ/XVBQIEmyWq0ure3QoUPq0qVrlT5foqp8fHz117++pdDQUKfWz8vL09ChD6mkpNjFlVXOsaw9OltS+e+j9eiPkqTyshKn1j/9c74kVfmv4uM/7JPk+O/rePYu1a136b+Wz9VfcPg/8r7GdNn9lOrU+f+rbVe+/q8VF53Sb/9HHMveI2u9gCveRmXrr45tsH7V/g+Ul5W6ZP/Orv9T9h5JNjXv/QcFhjat9PoFR77X9//8R5XO7kpV+1nqip+j7t5/Vfn6+mn79m2KiIhw6XbP/d622WyXHmir4Q4fPmyTZNu8ebND+6RJk2w33XTTBdeZPn26TRILCwsLCwuLAZZDhw5dMivU+DM7zkhOTlZSUpL9dUVFhU6cOKGGDRvKZHLur09PY7VaFRERoUOHDslsNru7HPwP74vn4r3xTLwvnssT3hubzaZTp06pSZMmlxxX48NOo0aN5OXlpby8PIf2vLw8hYWFXXAdHx+f8649BgUFVVeJbmU2m/kB4YF4XzwX741n4n3xXO5+bwIDAy87ps5VqKNa1a1bV507d9a6devsbRUVFVq3bp0sFosbKwMAAJ6gxp/ZkaSkpCQNGzZMXbp00U033aSFCxeqqKjIfncWAACovQwRdu677z4dO3ZM06ZNU25urjp06KBVq1Y5fQeSEfj4+Gj69OlVulUQrsf74rl4bzwT74vnqknvjclmu9z9WgAAADVXjZ+zAwAAcCmEHQAAYGiEHQAAYGiEHQAAYGiEHYP74YcfNGrUKEVFRcnPz08tWrTQ9OnTVVrq3icY11apqam67rrr5Ovrq27duumbb75xd0m1XkpKirp27aqAgACFhITo7rvv1oEDB9xdFn7jueeek8lk0oQJE9xdSq13+PBhDRkyRA0bNpSfn5/atm2r7du3u7usSyLsGNx3332niooKvfbaa9q7d68WLFigxYsX6+mnn3Z3abXOu+++q6SkJE2fPl07duxQ+/btFRsbq/z8fHeXVqtt2LBBCQkJ2rJli9asWaOysjL169dPRUVF7i4N/7Nt2za99tprateunbtLqfV+/vln9ejRQ97e3vr888+1b98+zZ8/Xw0aNHB3aZfEree10PPPP69Fixbp+++/d3cptUq3bt3UtWtXvfLKK5J++aTviIgIjRs3Tk899ZSbq8M5x44dU0hIiDZs2KBbb73V3eXUeoWFherUqZNeffVVPfPMM+rQoYMWLlzo7rJqraeeekqbNm3SP//5T3eXUimc2amFCgoKFBwc7O4yapXS0lJlZmaqb9++9rY6deqob9++ysjIcGNl+K2CggJJ4v+Ih0hISFBcXJzD/x24z8cff6wuXbroD3/4g0JCQtSxY0e98cYb7i7rsgg7tUxWVpZefvllPfLII+4upVY5fvy4ysvLz/tU79DQUOXm5rqpKvxWRUWFJkyYoB49eujGG290dzm13vLly7Vjxw6lpKS4uxT8z/fff69FixapVatWWr16tcaOHavx48dr2bJl7i7tkgg7NdRTTz0lk8l0yeW7775zWOfw4cPq37+//vCHP2j06NFuqhzwXAkJCdqzZ4+WL1/u7lJqvUOHDumPf/yj3nnnHfn6+rq7HPxPRUWFOnXqpDlz5qhjx44aM2aMRo8ercWLF7u7tEsyxLOxaqPHH39cw4cPv+SY5s2b278+cuSIbrvtNt188816/fXXq7k6/FajRo3k5eWlvLw8h/a8vDyFhYW5qSr8WmJiolauXKmNGzeqadOm7i6n1svMzFR+fr46depkbysvL9fGjRv1yiuvqKSkRF5eXm6ssHYKDw9XTEyMQ1t0dLQ++OADN1V0ZQg7NVTjxo3VuHHjKxp7+PBh3XbbbercubOWLl2qOnU4oXe11a1bV507d9a6det09913S/rlL6R169YpMTHRvcXVcjabTePGjdOHH36o9evXKyoqyt0lQVKfPn20e/duh7YRI0aoTZs2mjx5MkHHTXr06HHeRzP8+9//VrNmzdxU0ZUh7Bjc4cOH1bt3bzVr1kzz5s3TsWPH7H2cUbi6kpKSNGzYMHXp0kU33XSTFi5cqKKiIo0YMcLdpdVqCQkJSk9P1z/+8Q8FBATY51AFBgbKz8/PzdXVXgEBAefNm6pXr54aNmzIfCo3mjhxom6++WbNmTNH9957r7755hu9/vrrHn/FgLBjcGvWrFFWVpaysrLOOzXPpw5cXffdd5+OHTumadOmKTc3Vx06dNCqVavOm7SMq2vRokWSpN69ezu0L1269LKXioHapmvXrvrwww+VnJysWbNmKSoqSgsXLtTgwYPdXdol8Tk7AADA0Ji8AQAADI2wAwAADI2wAwAADI2wAwAADI2wAwAADI2wAwAADI2wAwAADI2wAwAADI2wA8AjrV+/XiaTSSdPnrzomLS0NAUFBV21ms6ZMWOGOnTocNX3C8A5hB0AAGBohB0AAGBohB0AblNSUqLx48crJCREvr6+6tmzp7Zt23bR8WlpaYqMjJS/v79+//vf66effnLoP3d56bXXXlNERIT8/f117733qqCgwGHcX/7yF0VHR8vX11dt2rTRq6++6tA/efJkXX/99fL391fz5s01depUlZWVXbSu7OxsNW/eXImJiTxgF/BAhB0AbvPkk0/qgw8+0LJly7Rjxw61bNlSsbGxOnHixHljt27dqlGjRikxMVE7d+7Ubbfdpmeeeea8cVlZWfr73/+uTz75RKtWrdK3336rxx57zN7/zjvvaNq0aXr22We1f/9+zZkzR1OnTtWyZcvsYwICApSWlqZ9+/bpxRdf1BtvvKEFCxZc8Bh27dqlnj176sEHH9Qrr7wik8nkgu8MAJeyAYAbFBYW2ry9vW3vvPOOva20tNTWpEkT29y5c21fffWVTZLt559/ttlsNtsDDzxgGzhwoMM27rvvPltgYKD99fTp021eXl62//73v/a2zz//3FanTh3b0aNHbTabzdaiRQtbenq6w3Zmz55ts1gsF631+eeft3Xu3NlhP+3bt7dt2rTJ1qBBA9u8efMqffwArp5r3B22ANRO2dnZKisrU48ePext3t7euummm7R//3517drVYfz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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['oldpeak'].replace({'?': heart_disease_df[heart_disease_df['oldpeak'] != '?']['oldpeak'].median()}, inplace=True)" ], "metadata": { "id": "gu7t7Yvm9T0m" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "outputId": "d910bc0c-5fd2-4843-8766-e8985f851d13", "id": "uQ0kTmwOB7lS" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2 150.0 0 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2 108.0 1 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2 129.0 1 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0 187.0 0 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2 172.0 0 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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 2,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25.145235299317264,\n \"min\": 60.0,\n \"max\": 202.0,\n \"num_unique_values\": 119,\n \"samples\": [\n 185.0,\n 134.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 1,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.0580486984557573,\n \"min\": -2.6,\n \"max\": 6.2,\n \"num_unique_values\": 53,\n \"samples\": [\n 2.4,\n -1.1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n 3.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 60 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "aaaf652a-6f5e-47bd-c8b1-fe4868dfb8a5", "id": "3zvilbqUB7lT" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null int64 \n", " 10 oldpeak 920 non-null float64\n", " 11 slope 920 non-null object \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(7), int64(5), object(3)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['slope'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['slope'] = heart_disease_df['slope'].astype(int)" ], "metadata": { "id": "m_QEztqiCSh5" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"slope\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "8372c89c-5371-4683-cbce-e6355e5e5009", "id": "DHa4GjbdCSh6" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['slope'].replace({-1: 2}, inplace=True)" ], "metadata": { "id": "HNYL4_A2CSh7" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "outputId": "bf87bf2c-d90c-42f1-ddcb-ca527792b942", "id": "TB5FL6uxCSh7" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2 150.0 0 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2 108.0 1 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2 129.0 1 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0 187.0 0 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2 172.0 0 \n", "\n", " oldpeak slope ca thal num \n", "0 2.3 3 0.0 6.0 0 \n", "1 1.5 2 3.0 3.0 2 \n", "2 2.6 2 2.0 7.0 1 \n", "3 3.5 3 0.0 3.0 0 \n", "4 1.4 1 0.0 3.0 0 " ], "text/html": [ "\n", "
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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012150.002.330.06.00
1167.01.04.0160.0286.002108.011.523.03.02
2267.01.04.0120.0229.002129.012.622.07.01
3337.01.03.0130.0250.000187.003.530.03.00
4441.00.02.0130.0204.002172.001.410.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 2,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25.145235299317264,\n \"min\": 60.0,\n \"max\": 202.0,\n \"num_unique_values\": 119,\n \"samples\": [\n 185.0,\n 134.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 1,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.0580486984557573,\n \"min\": -2.6,\n \"max\": 6.2,\n \"num_unique_values\": 53,\n \"samples\": [\n 2.4,\n -1.1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 3,\n \"num_unique_values\": 3,\n \"samples\": [\n 3,\n 2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"3.0\",\n \"0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 65 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "eecad243-7de3-4608-bb85-93b818f2e0ba", "id": "ZVei1MT9CSh7" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null int64 \n", " 10 oldpeak 920 non-null float64\n", " 11 slope 920 non-null int64 \n", " 12 ca 920 non-null object \n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(7), int64(6), object(2)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['ca'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['ca'] = heart_disease_df['ca'].astype(float)" ], "metadata": { "id": "a98BEn3BEA3H" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"ca\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "baf98dfd-5ef3-4874-905b-c6b1ef1dc4f8", "id": "aEBDuVHuEA3I" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "heart_disease_df['ca'].replace({-1: 0}, inplace=True)" ], "metadata": { "id": "3QpwOp0NEA3J" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "print(heart_disease_df.shape)\n", "heart_disease_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "outputId": "d9b01fce-e158-4f1e-9e1d-33bd210f0348", "id": "7gVcF_zhEA3J" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 15)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " index age sex cp trestbps chol fbs restecg thalach exang \\\n", "0 0 63.0 1.0 1.0 145.0 233.0 1 2 150.0 0 \n", "1 1 67.0 1.0 4.0 160.0 286.0 0 2 108.0 1 \n", "2 2 67.0 1.0 4.0 120.0 229.0 0 2 129.0 1 \n", "3 3 37.0 1.0 3.0 130.0 250.0 0 0 187.0 0 \n", "4 4 41.0 0.0 2.0 130.0 204.0 0 2 172.0 0 \n", "\n", " oldpeak slope ca thal num \n", "0 2.3 3 0.0 6.0 0 \n", "1 1.5 2 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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012150.002.330.06.00
1167.01.04.0160.0286.002108.011.523.03.02
2267.01.04.0120.0229.002129.012.622.07.01
3337.01.03.0130.0250.000187.003.530.03.00
4441.00.02.0130.0204.002172.001.410.03.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "heart_disease_df", "summary": "{\n \"name\": \"heart_disease_df\",\n \"rows\": 920,\n \"fields\": [\n {\n \"column\": \"index\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 82,\n \"min\": 0,\n \"max\": 302,\n \"num_unique_values\": 303,\n \"samples\": [\n 179,\n 228,\n 111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9.424685209576857,\n \"min\": 28.0,\n \"max\": 77.0,\n \"num_unique_values\": 50,\n \"samples\": [\n 64.0,\n 74.0,\n 39.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sex\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.4081478432714873,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"cp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.9309688168655602,\n \"min\": 1.0,\n \"max\": 4.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 4.0,\n 2.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"trestbps\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 17.929760898407423,\n \"min\": 80.0,\n \"max\": 200.0,\n \"num_unique_values\": 60,\n \"samples\": [\n 145.0,\n 172.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"chol\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 51.78532758464655,\n \"min\": 85.0,\n \"max\": 603.0,\n \"num_unique_values\": 217,\n \"samples\": [\n 384.0,\n 333.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fbs\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"restecg\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 2,\n \"num_unique_values\": 3,\n \"samples\": [\n 2,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thalach\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25.145235299317264,\n \"min\": 60.0,\n \"max\": 202.0,\n \"num_unique_values\": 119,\n \"samples\": [\n 185.0,\n 134.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"exang\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 1,\n 0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"oldpeak\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.0580486984557573,\n \"min\": -2.6,\n \"max\": 6.2,\n \"num_unique_values\": 53,\n \"samples\": [\n 2.4,\n -1.1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"slope\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 3,\n \"num_unique_values\": 3,\n \"samples\": [\n 3,\n 2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ca\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.628936484381527,\n \"min\": 0.0,\n \"max\": 3.0,\n \"num_unique_values\": 4,\n \"samples\": [\n 3.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"thal\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"6.0\",\n \"3.0\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"num\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 0,\n \"max\": 4,\n \"num_unique_values\": 5,\n \"samples\": [\n 2,\n 4\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 70 } ] }, { "cell_type": "code", "source": [ "heart_disease_df.info()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "d21c62f8-a2ab-47b5-995b-4807c39f0a70", "id": "URCAnuzHEA3K" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "RangeIndex: 920 entries, 0 to 919\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null int64 \n", " 10 oldpeak 920 non-null float64\n", " 11 slope 920 non-null int64 \n", " 12 ca 920 non-null float64\n", " 13 thal 920 non-null object \n", " 14 num 920 non-null int64 \n", "dtypes: float64(8), int64(6), object(1)\n", "memory usage: 107.9+ KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['thal'].unique()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "zUccRxlLDzwU", "outputId": "c3f8416a-3677-4f33-e6b1-63c917d7d112" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "array(['6.0', '3.0', '7.0', '?', '6', '3', '7'], dtype=object)" ] }, "metadata": {}, "execution_count": 72 } ] }, { "cell_type": "code", "source": [ "heart_disease_df['thal'].replace({'?': -1}, inplace=True)\n", "heart_disease_df['thal'] = heart_disease_df['thal'].astype(float)" ], "metadata": { "id": "eZAZFnifEgRh" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"thal\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "outputId": "fa3ed330-1dc1-43d2-8625-19e15d7f904a", "id": "6XB2K12AEgRi" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null int64 \n", " 10 oldpeak 920 non-null float64\n", " 11 slope 920 non-null int64 \n", " 12 ca 920 non-null float64\n", " 13 thal 920 non-null float64\n", " 14 num 920 non-null int64 \n", "dtypes: float64(9), int64(6)\n", "memory usage: 107.9 KB\n" ] } ] }, { "cell_type": "code", "source": [ "heart_disease_df['num'].replace({2: 1, 3: 1, 4: 1}, inplace=True)" ], "metadata": { "id": "MPdZLeEZEa0d" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sns.countplot(heart_disease_df, x=\"num\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 449 }, "id": "HQEkj6EXFMMi", "outputId": "e884cfbe-53b6-4b9c-b929-fb0c102ff355" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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indexagesexcptrestbpscholfbsrestecgthalachexangoldpeakslopecathalnum
0063.01.01.0145.0233.012150.002.330.06.00
1167.01.04.0160.0286.002108.011.523.03.01
2267.01.04.0120.0229.002129.012.622.07.01
3337.01.03.0130.0250.000187.003.530.03.00
4441.00.02.0130.0204.002172.001.410.03.00
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Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 index 920 non-null int64 \n", " 1 age 920 non-null float64\n", " 2 sex 920 non-null float64\n", " 3 cp 920 non-null float64\n", " 4 trestbps 920 non-null float64\n", " 5 chol 920 non-null float64\n", " 6 fbs 920 non-null int64 \n", " 7 restecg 920 non-null int64 \n", " 8 thalach 920 non-null float64\n", " 9 exang 920 non-null int64 \n", " 10 oldpeak 920 non-null float64\n", " 11 slope 920 non-null int64 \n", " 12 ca 920 non-null float64\n", " 13 thal 920 non-null float64\n", " 14 num 920 non-null int64 \n", "dtypes: float64(9), int64(6)\n", "memory usage: 107.9 KB\n" ] } ] }, { "cell_type": "code", "source": [ "for column in heart_disease_df.columns:\n", " print(heart_disease_df[column].value_counts())" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "4APsGOxBG3pB", "outputId": "8eb31e4a-07c4-45f3-e22e-19b527ddf7ea" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "0 4\n", "78 4\n", "92 4\n", "91 4\n", "90 4\n", " ..\n", "298 1\n", "299 1\n", "300 1\n", "301 1\n", "302 1\n", "Name: index, Length: 303, dtype: int64\n", "54.0 51\n", "58.0 43\n", "55.0 41\n", "56.0 38\n", "57.0 38\n", "52.0 36\n", "62.0 35\n", "51.0 35\n", "59.0 35\n", "53.0 33\n", "60.0 32\n", "61.0 31\n", "48.0 31\n", "63.0 30\n", "50.0 25\n", "41.0 24\n", "46.0 24\n", "43.0 24\n", "64.0 22\n", "49.0 22\n", "65.0 21\n", "44.0 19\n", "47.0 19\n", "45.0 18\n", "42.0 18\n", "38.0 16\n", "67.0 15\n", "39.0 15\n", "69.0 13\n", "40.0 13\n", "66.0 13\n", "35.0 11\n", "37.0 11\n", "68.0 10\n", "34.0 7\n", "70.0 7\n", "74.0 7\n", "36.0 6\n", "32.0 5\n", "71.0 5\n", "72.0 4\n", "29.0 3\n", "75.0 3\n", "31.0 2\n", "33.0 2\n", "76.0 2\n", "77.0 2\n", "30.0 1\n", "28.0 1\n", "73.0 1\n", "Name: age, dtype: int64\n", "1.0 726\n", "0.0 194\n", "Name: sex, dtype: int64\n", "4.0 496\n", "3.0 204\n", "2.0 174\n", "1.0 46\n", "Name: cp, dtype: int64\n", "130.0 175\n", "120.0 131\n", "140.0 102\n", "110.0 59\n", "150.0 56\n", "160.0 50\n", "125.0 29\n", "115.0 19\n", "135.0 18\n", "128.0 17\n", "145.0 16\n", "100.0 15\n", "138.0 15\n", "112.0 14\n", "170.0 14\n", "124.0 12\n", "180.0 12\n", "122.0 12\n", "132.0 12\n", "118.0 10\n", "134.0 9\n", "142.0 9\n", "105.0 9\n", "136.0 8\n", "155.0 8\n", "108.0 7\n", "152.0 7\n", "126.0 7\n", "144.0 6\n", "95.0 6\n", "200.0 4\n", "158.0 4\n", "178.0 3\n", "146.0 3\n", "106.0 3\n", "104.0 3\n", "154.0 3\n", "102.0 3\n", "156.0 2\n", "114.0 2\n", "190.0 2\n", "116.0 2\n", "165.0 2\n", "94.0 2\n", "148.0 2\n", "172.0 2\n", "113.0 1\n", "96.0 1\n", "185.0 1\n", "80.0 1\n", "117.0 1\n", "92.0 1\n", "123.0 1\n", "129.0 1\n", "98.0 1\n", "164.0 1\n", "101.0 1\n", "174.0 1\n", "192.0 1\n", "127.0 1\n", "Name: trestbps, dtype: int64\n", "239.5 202\n", "254.0 10\n", "220.0 10\n", "230.0 9\n", "216.0 9\n", " ... \n", "412.0 1\n", "358.0 1\n", "360.0 1\n", "321.0 1\n", "385.0 1\n", "Name: chol, Length: 217, dtype: int64\n", "0 782\n", "1 138\n", "Name: fbs, dtype: int64\n", "0 553\n", "2 188\n", "1 179\n", "Name: restecg, dtype: int64\n", "140.0 96\n", "150.0 43\n", "120.0 35\n", "130.0 30\n", "160.0 26\n", " ..\n", "195.0 1\n", "91.0 1\n", "87.0 1\n", "192.0 1\n", "73.0 1\n", "Name: thalach, Length: 119, dtype: int64\n", "0 583\n", "1 337\n", "Name: exang, dtype: int64\n", " 0.0 370\n", " 1.0 83\n", " 0.5 81\n", " 2.0 76\n", " 1.5 48\n", " 3.0 28\n", " 1.2 17\n", " 2.5 16\n", " 1.4 15\n", " 0.8 15\n", " 1.6 14\n", " 0.2 14\n", " 0.6 14\n", " 1.8 12\n", " 0.4 10\n", " 0.1 9\n", " 4.0 8\n", " 2.6 7\n", " 2.8 7\n", " 1.3 5\n", " 2.2 5\n", " 0.7 5\n", " 1.9 5\n", " 0.3 5\n", " 3.6 4\n", " 2.4 4\n", " 1.1 4\n", " 0.9 4\n", " 3.4 3\n", " 1.7 2\n", "-1.0 2\n", " 4.2 2\n", " 2.3 2\n", " 2.1 2\n", "-0.5 2\n", " 3.2 2\n", " 3.5 2\n", "-0.8 1\n", "-0.1 1\n", "-0.9 1\n", "-2.0 1\n", "-0.7 1\n", "-2.6 1\n", " 6.2 1\n", "-1.5 1\n", "-1.1 1\n", " 5.0 1\n", " 4.4 1\n", " 3.8 1\n", " 2.9 1\n", " 5.6 1\n", " 3.1 1\n", " 3.7 1\n", "Name: oldpeak, dtype: int64\n", "2 654\n", "1 203\n", "3 63\n", "Name: slope, dtype: int64\n", "0.0 792\n", "1.0 67\n", "2.0 41\n", "3.0 20\n", "Name: ca, dtype: int64\n", "3.0 682\n", "7.0 192\n", "6.0 46\n", "Name: thal, dtype: int64\n", "1 509\n", "0 411\n", "Name: num, dtype: int64\n" ] } ] }, { "cell_type": "code", "source": [ "enc = OneHotEncoder(handle_unknown='ignore')\n", "enc.fit(heart_disease_df[['cp', 'restecg', 'slope', 'thal']])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 75 }, "id": "YQHl_m0XGBoJ", "outputId": "1193e647-4cc3-475a-f90a-52a2fbe7ef63" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "OneHotEncoder(handle_unknown='ignore')" ], "text/html": [ "
OneHotEncoder(handle_unknown='ignore')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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" ] }, "metadata": {}, "execution_count": 83 } ] }, { "cell_type": "code", "source": [ "enc.categories_" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0DGmVl5KIlVP", "outputId": "b74dabe6-f519-4152-9c75-e7d58246ba47" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "[array([1., 2., 3., 4.]),\n", " array([0, 1, 2]),\n", " array([1, 2, 3]),\n", " array([3., 6., 7.])]" ] }, "metadata": {}, "execution_count": 84 } ] }, { "cell_type": "code", "source": [ "enc.transform(heart_disease_df[['cp', 'restecg', 'slope', 'thal']]).toarray()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "f30PZEXVI2Lc", "outputId": "e0bc9346-dd76-4010-c6d6-970ad93e743d" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "array([[1., 0., 0., ..., 0., 1., 0.],\n", " [0., 0., 0., ..., 1., 0., 0.],\n", " [0., 0., 0., ..., 0., 0., 1.],\n", " ...,\n", " [0., 0., 0., ..., 0., 1., 0.],\n", " [0., 0., 0., ..., 1., 0., 0.],\n", " [0., 1., 0., ..., 1., 0., 0.]])" ] }, "metadata": {}, "execution_count": 85 } ] }, { "cell_type": "code", "source": [ "enc.get_feature_names_out(['cp', 'restecg', 'slope', 'thal'])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NPTXOBcqIpz9", "outputId": "bcea7bc4-02a9-4c93-fc9d-6a7537e3517b" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "array(['cp_1.0', 'cp_2.0', 'cp_3.0', 'cp_4.0', 'restecg_0', 'restecg_1',\n", " 'restecg_2', 'slope_1', 'slope_2', 'slope_3', 'thal_3.0',\n", " 'thal_6.0', 'thal_7.0'], dtype=object)" ] }, "metadata": {}, "execution_count": 86 } ] }, { "cell_type": "code", "source": [ "cat_feature_df = pd.DataFrame(data=enc.transform(heart_disease_df[['cp', 'restecg', 'slope', 'thal']]).toarray(), columns=enc.get_feature_names_out(['cp', 'restecg', 'slope', 'thal']))\n", "cat_feature_df = pd.concat([heart_disease_df[['sex', 'fbs', 'exang']], cat_feature_df], axis=1)\n", "print(cat_feature_df.shape)\n", "cat_feature_df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 224 }, "id": "-8lC9MlMIy0o", "outputId": "85eadd55-b31f-4969-a478-28058f3fa9b2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(920, 16)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " sex fbs exang cp_1.0 cp_2.0 cp_3.0 cp_4.0 restecg_0 restecg_1 \\\n", "0 1.0 1 0 1.0 0.0 0.0 0.0 0.0 0.0 \n", "1 1.0 0 1 0.0 0.0 0.0 1.0 0.0 0.0 \n", "2 1.0 0 1 0.0 0.0 0.0 1.0 0.0 0.0 \n", "3 1.0 0 0 0.0 0.0 1.0 0.0 1.0 0.0 \n", "4 0.0 0 0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "\n", " restecg_2 slope_1 slope_2 slope_3 thal_3.0 thal_6.0 thal_7.0 \n", "0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 \n", "1 1.0 0.0 1.0 0.0 1.0 0.0 0.0 \n", "2 1.0 0.0 1.0 0.0 0.0 0.0 1.0 \n", "3 0.0 0.0 0.0 1.0 1.0 0.0 0.0 \n", "4 1.0 1.0 0.0 0.0 1.0 0.0 0.0 " ], "text/html": [ "\n", "
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