{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## **Assignment #1: EDA & Dataset**\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "w84cR3AZIU0e"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Overview**\n",
        "\n",
        "In this first assignment, you will gain hands-on experience selecting and preparing a dataset, performing exploratory data analysis (EDA), adding it to HF's Datasets, and presenting your findings in a short video.\n",
        "\n",
        "Through these steps, you’ll begin building essential data science skills in Python.\n",
        "\n",
        "Think of your notebook as a cohesive story where EDA reveals the narrative of your data, which provides the resolution to the main question or goal."
      ],
      "metadata": {
        "id": "n7afdXdxIbLA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Objectives**\n",
        "\n",
        "1. Explore various data tools/hubs (e.g., Kaggle, UCI, or local data) to find a suitable dataset.\n",
        "2. Prepare the selected dataset, focusing on cleaning, transformation, manipulation, and quality.\n",
        "3. Build foundational EDA skills, including  missing data, outlier handling, and clear data visualization.\n",
        "4. Upload your work and your dataset to HuggingFace.\n",
        "5. Communicate findings concisely in both a structured notebook, README file,  and a short video presentation, demonstrating clarity in each step of the workflow."
      ],
      "metadata": {
        "id": "lJAPMumvIUyW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Submission Guidelines**\n",
        "\n",
        "1. Please note that this is an individual assignment.\n",
        "2. Submit a text file with your info and the link to HF's dataset.\n",
        "3. The dataset will include all of your work.\n",
        "  - **Python Notebook**: a well-structured notebook (e.g.`.ipynb` file) with clear comments or markdown explanations of each step.\n",
        "  - **Video Link**: the README file will include your short video presentation at the beginning of the file.\n",
        "4. **Oral Report**: Students may be randomly chosen to present their work in a quick online session with the T.A., typically lasting ±10 minutes.\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "MwRmaJBiIjMR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Evaluation Criteria**\n",
        "\n",
        "- **Organization & Clarity (20%)**: Overall structure of your HF Dataset, code, notebook, clear communication, and a concise summary.\n",
        "- **Data Handling (30%)**: Quality of data cleaning, appropriate handling of outliers, and more.\n",
        "- **Visualizations (30%)**: well-presented relevant visuals.\n",
        "- **Presentation (20%)**: Clearly communicated approach and findings in your 2–3 minute overview.\n",
        "\n"
      ],
      "metadata": {
        "id": "hD9SZmagIjOV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Additional Tips**\n",
        "\n",
        "- The first thing you should do is download a copy of this notebook to your drive.\n",
        "- Keep your dataset size manageable. If the dataset is large, you can sample a subset.\n",
        "- A few clear visuals are more effective than many complicated ones.\n",
        "- Ask for help or feedback early if you get stuck."
      ],
      "metadata": {
        "id": "h3vpVHSxIUwI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<br><br><br>\n",
        "\n",
        "---\n",
        "\n",
        "Reminder: Always start with copy the NOTEBOOK to your drive."
      ],
      "metadata": {
        "id": "6kUonEv8Ipkp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![image.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "RMcHZdKiaPNW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "\n",
        "<br><br><br>"
      ],
      "metadata": {
        "id": "7ql9QlVfaSEL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 1: Select a Dataset**\n",
        "\n",
        "1. Choose a numeric tabular dataset, such as the . If you prefer, you may use other open-source datasets; [Hugginface](https://huggingface.co/datasets?task_categories=task_categories:tabular-classification&sort=trending), [Kaggle](https://www.kaggle.com/datasets?tags=13302-Classification&minUsabilityRating=8.00+or+higher), etc.\n",
        "\n",
        "\n",
        "    Examples for a good dataset:\n",
        "      - \"Determine a genre of a song\"\n",
        "      - \"Determine the type of flowers\"\n",
        "      - \"Determine the animal - cat or dog\"\n",
        "      - \"Determine the category of a product\"\n",
        "      - \"Determine if an email is spam or not spam\"\n",
        "      - \"Determine whether a tumor is malignant or benign\"\n",
        "      - \"Determine whether a transaction is fraudulent or not\"\n",
        "      - \"Determine whether a student is likely to pass a course\"\n",
        "\n",
        "2. Avoid choosing a \"basic\"/\"small\" dataset.\n",
        "      - 1K rows and more.\n",
        "      - 10 features and more.\n",
        "\n",
        "\n",
        "3. Please submit your dataset [here](https://forms.gle/YYiRLXJnbwUfwuwc7), to share it with the class so everyone can see.\n",
        "And make sure your chosen dataset is unique using this [link](https://docs.google.com/spreadsheets/d/1M8uojrzhSyVnOlSAJpzCKxrhWdzPR77k4x8Kxvr8VDk/edit?usp=sharing).\n",
        "\n",
        "      *Note: Due to their popularity, the following are datasets you may not choose.*\n",
        "      > - Iris dataset\n",
        "      > - Wine dataset\n",
        "      > - Titanic dataset\n",
        "      > - Boston Housing dataset\n",
        "\n",
        "4. Choose a dataset with moslty numaric values. This way you would have enough information to work on, and you could drop columns that aren't numeric.\n",
        "\n",
        "5. Briefly describe your chosen dataset (source, size, features) and the question you want to answer.\n",
        "\n",
        "6. Clearly identify the target variable to predict (if exists).\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "a_vsO0Q1IOMT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "GFaHgQJyKwa5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install --q kaggle"
      ],
      "metadata": {
        "id": "OI0MZzohKwfE"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import json\n",
        "import time\n",
        "import random\n",
        "from zipfile import ZipFile\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "C7r26R1gd19f"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "Lgum4x_tKwjL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "uploded = files.upload()"
      ],
      "metadata": {
        "id": "SWIrnfSLKwnE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "outputId": "2e035ce0-884b-47c4-8ec7-ce24a0864b10"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-df1c89fe-68af-4221-ac63-1e8d5b882232\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-df1c89fe-68af-4221-ac63-1e8d5b882232\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving heart.csv to heart.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from plotnine import *\n",
        "import pandas as pd\n"
      ],
      "metadata": {
        "id": "ecul0ni9avuk"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('heart.csv')"
      ],
      "metadata": {
        "id": "8hsN_Wv7fEYR"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Rn8L6l_SfUnS",
        "outputId": "17241dc9-5913-4737-f5e2-d721e63fb592"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
              "0   52    1   0       125   212    0        1      168      0      1.0      2   \n",
              "1   53    1   0       140   203    1        0      155      1      3.1      0   \n",
              "2   70    1   0       145   174    0        1      125      1      2.6      0   \n",
              "3   61    1   0       148   203    0        1      161      0      0.0      2   \n",
              "4   62    0   0       138   294    1        1      106      0      1.9      1   \n",
              "\n",
              "   ca  thal  target  \n",
              "0   2     3       0  \n",
              "1   0     3       0  \n",
              "2   0     3       0  \n",
              "3   1     3       0  \n",
              "4   3     2       0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f83fef77-325b-4a3c-b396-d160c05ed97a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>52</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>125</td>\n",
              "      <td>212</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>168</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>203</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>155</td>\n",
              "      <td>1</td>\n",
              "      <td>3.1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>145</td>\n",
              "      <td>174</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "      <td>1</td>\n",
              "      <td>2.6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>61</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>161</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>62</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>138</td>\n",
              "      <td>294</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>106</td>\n",
              "      <td>0</td>\n",
              "      <td>1.9</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f83fef77-325b-4a3c-b396-d160c05ed97a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f83fef77-325b-4a3c-b396-d160c05ed97a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f83fef77-325b-4a3c-b396-d160c05ed97a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    <div id=\"df-e47d545f-a0be-4ba1-a2d6-c569836fe987\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e47d545f-a0be-4ba1-a2d6-c569836fe987')\"\n",
              "                title=\"Suggest charts\"\n",
              "                style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "      <script>\n",
              "        async function quickchart(key) {\n",
              "          const quickchartButtonEl =\n",
              "            document.querySelector('#' + key + ' button');\n",
              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "          try {\n",
              "            const charts = await google.colab.kernel.invokeFunction(\n",
              "                'suggestCharts', [key], {});\n",
              "          } catch (error) {\n",
              "            console.error('Error during call to suggestCharts:', error);\n",
              "          }\n",
              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "        }\n",
              "        (() => {\n",
              "          let quickchartButtonEl =\n",
              "            document.querySelector('#df-e47d545f-a0be-4ba1-a2d6-c569836fe987 button');\n",
              "          quickchartButtonEl.style.display =\n",
              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "        })();\n",
              "      </script>\n",
              "    </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 1025,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9,\n        \"min\": 29,\n        \"max\": 77,\n        \"num_unique_values\": 41,\n        \"samples\": [\n          65,\n          50,\n          54\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\": 1,\n        \"min\": 0,\n        \"max\": 3,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 17,\n        \"min\": 94,\n        \"max\": 200,\n        \"num_unique_values\": 49,\n        \"samples\": [\n          128,\n          172\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51,\n        \"min\": 126,\n        \"max\": 564,\n        \"num_unique_values\": 152,\n        \"samples\": [\n          267,\n          262\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          1,\n          0\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          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 23,\n        \"min\": 71,\n        \"max\": 202,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          180,\n          152\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\": 1.175053255150173,\n        \"min\": 0.0,\n        \"max\": 6.2,\n        \"num_unique_values\": 40,\n        \"samples\": [\n          2.8,\n          0.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\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\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 4,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0,\n          4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 3,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          2,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target\",\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": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Akg8z079ftW5",
        "outputId": "8e25bedc-e97b-4db2-f87f-1eab9d200808"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1025, 14)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "deG3_vAWfwL2",
        "outputId": "0461f7d4-eff7-441e-8e9d-c8f9c12c8c8b"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1025 entries, 0 to 1024\n",
            "Data columns (total 14 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   age       1025 non-null   int64  \n",
            " 1   sex       1025 non-null   int64  \n",
            " 2   cp        1025 non-null   int64  \n",
            " 3   trestbps  1025 non-null   int64  \n",
            " 4   chol      1025 non-null   int64  \n",
            " 5   fbs       1025 non-null   int64  \n",
            " 6   restecg   1025 non-null   int64  \n",
            " 7   thalach   1025 non-null   int64  \n",
            " 8   exang     1025 non-null   int64  \n",
            " 9   oldpeak   1025 non-null   float64\n",
            " 10  slope     1025 non-null   int64  \n",
            " 11  ca        1025 non-null   int64  \n",
            " 12  thal      1025 non-null   int64  \n",
            " 13  target    1025 non-null   int64  \n",
            "dtypes: float64(1), int64(13)\n",
            "memory usage: 112.2 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "eBfQrpZqifXL",
        "outputId": "2087a7c0-f749-44e4-ac10-3096b6adc0fa"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               age          sex           cp     trestbps        chol  \\\n",
              "count  1025.000000  1025.000000  1025.000000  1025.000000  1025.00000   \n",
              "mean     54.434146     0.695610     0.942439   131.611707   246.00000   \n",
              "std       9.072290     0.460373     1.029641    17.516718    51.59251   \n",
              "min      29.000000     0.000000     0.000000    94.000000   126.00000   \n",
              "25%      48.000000     0.000000     0.000000   120.000000   211.00000   \n",
              "50%      56.000000     1.000000     1.000000   130.000000   240.00000   \n",
              "75%      61.000000     1.000000     2.000000   140.000000   275.00000   \n",
              "max      77.000000     1.000000     3.000000   200.000000   564.00000   \n",
              "\n",
              "               fbs      restecg      thalach        exang      oldpeak  \\\n",
              "count  1025.000000  1025.000000  1025.000000  1025.000000  1025.000000   \n",
              "mean      0.149268     0.529756   149.114146     0.336585     1.071512   \n",
              "std       0.356527     0.527878    23.005724     0.472772     1.175053   \n",
              "min       0.000000     0.000000    71.000000     0.000000     0.000000   \n",
              "25%       0.000000     0.000000   132.000000     0.000000     0.000000   \n",
              "50%       0.000000     1.000000   152.000000     0.000000     0.800000   \n",
              "75%       0.000000     1.000000   166.000000     1.000000     1.800000   \n",
              "max       1.000000     2.000000   202.000000     1.000000     6.200000   \n",
              "\n",
              "             slope           ca         thal       target  \n",
              "count  1025.000000  1025.000000  1025.000000  1025.000000  \n",
              "mean      1.385366     0.754146     2.323902     0.513171  \n",
              "std       0.617755     1.030798     0.620660     0.500070  \n",
              "min       0.000000     0.000000     0.000000     0.000000  \n",
              "25%       1.000000     0.000000     2.000000     0.000000  \n",
              "50%       1.000000     0.000000     2.000000     1.000000  \n",
              "75%       2.000000     1.000000     3.000000     1.000000  \n",
              "max       2.000000     4.000000     3.000000     1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d39762b2-af3d-432f-ad94-5c3a402d61dd\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.00000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>54.434146</td>\n",
              "      <td>0.695610</td>\n",
              "      <td>0.942439</td>\n",
              "      <td>131.611707</td>\n",
              "      <td>246.00000</td>\n",
              "      <td>0.149268</td>\n",
              "      <td>0.529756</td>\n",
              "      <td>149.114146</td>\n",
              "      <td>0.336585</td>\n",
              "      <td>1.071512</td>\n",
              "      <td>1.385366</td>\n",
              "      <td>0.754146</td>\n",
              "      <td>2.323902</td>\n",
              "      <td>0.513171</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.072290</td>\n",
              "      <td>0.460373</td>\n",
              "      <td>1.029641</td>\n",
              "      <td>17.516718</td>\n",
              "      <td>51.59251</td>\n",
              "      <td>0.356527</td>\n",
              "      <td>0.527878</td>\n",
              "      <td>23.005724</td>\n",
              "      <td>0.472772</td>\n",
              "      <td>1.175053</td>\n",
              "      <td>0.617755</td>\n",
              "      <td>1.030798</td>\n",
              "      <td>0.620660</td>\n",
              "      <td>0.500070</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>94.000000</td>\n",
              "      <td>126.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>211.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>132.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>56.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>130.000000</td>\n",
              "      <td>240.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>152.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>61.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>275.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.800000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>77.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>564.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>202.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.200000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d39762b2-af3d-432f-ad94-5c3a402d61dd')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d39762b2-af3d-432f-ad94-5c3a402d61dd button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d39762b2-af3d-432f-ad94-5c3a402d61dd');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    <div id=\"df-cfa482c1-effb-4208-bf93-a46655f9189e\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cfa482c1-effb-4208-bf93-a46655f9189e')\"\n",
              "                title=\"Suggest charts\"\n",
              "                style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "      <script>\n",
              "        async function quickchart(key) {\n",
              "          const quickchartButtonEl =\n",
              "            document.querySelector('#' + key + ' button');\n",
              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "          try {\n",
              "            const charts = await google.colab.kernel.invokeFunction(\n",
              "                'suggestCharts', [key], {});\n",
              "          } catch (error) {\n",
              "            console.error('Error during call to suggestCharts:', error);\n",
              "          }\n",
              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "        }\n",
              "        (() => {\n",
              "          let quickchartButtonEl =\n",
              "            document.querySelector('#df-cfa482c1-effb-4208-bf93-a46655f9189e button');\n",
              "          quickchartButtonEl.style.display =\n",
              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "        })();\n",
              "      </script>\n",
              "    </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 346.1150023272597,\n        \"min\": 9.072290233244281,\n        \"max\": 1025.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          54.43414634146342,\n          56.0,\n          1025.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.1825587675373,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.6956097560975609,\n          1.0,\n          0.4603733241196503\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 361.9909299680307,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          1025.0,\n          0.9424390243902439,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 324.3475475669103,\n        \"min\": 17.516718005376408,\n        \"max\": 1025.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          131.61170731707318,\n          130.0,\n          1025.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 313.5134241805058,\n        \"min\": 51.59251020618206,\n        \"max\": 1025.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          246.0,\n          240.0,\n          1025.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fbs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.3163339641884,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.14926829268292682,\n          1.0,\n          0.3565266897271594\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"restecg\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.1373492815066,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          1025.0,\n          0.5297560975609756,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 322.1492006877167,\n        \"min\": 23.005723745977196,\n        \"max\": 1025.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          149.11414634146342,\n          152.0,\n          1025.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"exang\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.2505698153287,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.33658536585365856,\n          1.0,\n          0.4727723760037095\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 361.83970171608024,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          1025.0,\n          1.0715121951219515,\n          1.8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 361.9886284380937,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          1025.0,\n          1.3853658536585365,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.05191221025626,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          1025.0,\n          0.7541463414634146,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 361.7399759382844,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          1025.0,\n          2.32390243902439,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 362.1897651954653,\n        \"min\": 0.0,\n        \"max\": 1025.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.5131707317073171,\n          1.0,\n          0.5000704980788051\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<br><br><br>\n",
        "\n",
        "---\n",
        "\n",
        "<br><br><br>"
      ],
      "metadata": {
        "id": "4t2QNyE6IPKS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 2: Exploratory Data Analysis (EDA)**\n",
        "\n",
        "Use your EDA to tell the story of your data - highlight interesting patterns, anomalies, or relationships that lead you toward your classification goal. Ask interesting questions, and answer them.\n",
        "\n",
        "\n",
        "1. **Data Cleaning** : Check for missing values, duplicate entries, scaling/normalize issues,  parsing dates, fixing typos, or any inconsistencies.  Document how you address them.\n",
        "2. **Outlier Detection & Handling**: Identify outliers and decide whether to keep or remove them, providing a short justification.\n",
        "3. **Descriptive Statistics**: Summarize the data (e.g., mean, median, correlations) to reveal patterns.\n",
        "4. Read further on [A Comprehensive Guide to Mastering Exploratory Data Analysis](https://www.dasca.org/world-of-data-science/article/a-comprehensive-guide-to-mastering-exploratory-data-analysis).\n",
        "5. **Visualizations**: Use a set of  plots (e.g., histograms, scatter plots, box plots) to illustrate **key insights.** Label charts, axes, and legends clearly.\n",
        "\n",
        "Tip: not necessarily in this order."
      ],
      "metadata": {
        "id": "6eLmNWJJIPS0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![image.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "e3JpM_9Wl84T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***להוריד כפילויות***"
      ],
      "metadata": {
        "id": "HpVMSPEqucWt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KuQdyJCTrAkV",
        "outputId": "8364e33e-dd68-4e58-bf48-8f7be1abd47b"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "np.int64(723)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop_duplicates()"
      ],
      "metadata": {
        "id": "4zihfZI0rThW"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A3NrvvKrrZ1i",
        "outputId": "f9b34321-01de-423c-c077-1910ddbb2971"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "np.int64(0)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 523
        },
        "id": "3ijIiU6Ex0JU",
        "outputId": "63827d65-b261-48a9-8dd0-34686ed3c076"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age           int64\n",
              "sex           int64\n",
              "cp            int64\n",
              "trestbps      int64\n",
              "chol          int64\n",
              "fbs           int64\n",
              "restecg       int64\n",
              "thalach       int64\n",
              "exang         int64\n",
              "oldpeak     float64\n",
              "slope         int64\n",
              "ca            int64\n",
              "thal          int64\n",
              "target        int64\n",
              "dtype: object"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cp</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>trestbps</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>chol</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fbs</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>restecg</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>thalach</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>exang</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>oldpeak</th>\n",
              "      <td>float64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>slope</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ca</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>thal</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>target</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> object</label>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()\n"
      ],
      "metadata": {
        "id": "fUEbi2wOhssS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "outputId": "c8745659-7c50-4bfc-fc22-0d7f6abb8fc6"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             age         sex          cp    trestbps        chol         fbs  \\\n",
              "count  302.00000  302.000000  302.000000  302.000000  302.000000  302.000000   \n",
              "mean    54.42053    0.682119    0.963576  131.602649  246.500000    0.149007   \n",
              "std      9.04797    0.466426    1.032044   17.563394   51.753489    0.356686   \n",
              "min     29.00000    0.000000    0.000000   94.000000  126.000000    0.000000   \n",
              "25%     48.00000    0.000000    0.000000  120.000000  211.000000    0.000000   \n",
              "50%     55.50000    1.000000    1.000000  130.000000  240.500000    0.000000   \n",
              "75%     61.00000    1.000000    2.000000  140.000000  274.750000    0.000000   \n",
              "max     77.00000    1.000000    3.000000  200.000000  564.000000    1.000000   \n",
              "\n",
              "          restecg     thalach       exang     oldpeak       slope          ca  \\\n",
              "count  302.000000  302.000000  302.000000  302.000000  302.000000  302.000000   \n",
              "mean     0.526490  149.569536    0.327815    1.043046    1.397351    0.718543   \n",
              "std      0.526027   22.903527    0.470196    1.161452    0.616274    1.006748   \n",
              "min      0.000000   71.000000    0.000000    0.000000    0.000000    0.000000   \n",
              "25%      0.000000  133.250000    0.000000    0.000000    1.000000    0.000000   \n",
              "50%      1.000000  152.500000    0.000000    0.800000    1.000000    0.000000   \n",
              "75%      1.000000  166.000000    1.000000    1.600000    2.000000    1.000000   \n",
              "max      2.000000  202.000000    1.000000    6.200000    2.000000    4.000000   \n",
              "\n",
              "             thal      target  \n",
              "count  302.000000  302.000000  \n",
              "mean     2.314570    0.543046  \n",
              "std      0.613026    0.498970  \n",
              "min      0.000000    0.000000  \n",
              "25%      2.000000    0.000000  \n",
              "50%      2.000000    1.000000  \n",
              "75%      3.000000    1.000000  \n",
              "max      3.000000    1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b4b98869-971b-4a0f-aef3-68f54b7ae5f4\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>chol</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>302.00000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "      <td>302.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>54.42053</td>\n",
              "      <td>0.682119</td>\n",
              "      <td>0.963576</td>\n",
              "      <td>131.602649</td>\n",
              "      <td>246.500000</td>\n",
              "      <td>0.149007</td>\n",
              "      <td>0.526490</td>\n",
              "      <td>149.569536</td>\n",
              "      <td>0.327815</td>\n",
              "      <td>1.043046</td>\n",
              "      <td>1.397351</td>\n",
              "      <td>0.718543</td>\n",
              "      <td>2.314570</td>\n",
              "      <td>0.543046</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.04797</td>\n",
              "      <td>0.466426</td>\n",
              "      <td>1.032044</td>\n",
              "      <td>17.563394</td>\n",
              "      <td>51.753489</td>\n",
              "      <td>0.356686</td>\n",
              "      <td>0.526027</td>\n",
              "      <td>22.903527</td>\n",
              "      <td>0.470196</td>\n",
              "      <td>1.161452</td>\n",
              "      <td>0.616274</td>\n",
              "      <td>1.006748</td>\n",
              "      <td>0.613026</td>\n",
              "      <td>0.498970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>29.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>94.000000</td>\n",
              "      <td>126.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>48.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>211.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>133.250000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>55.50000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>130.000000</td>\n",
              "      <td>240.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>152.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>61.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>274.750000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>77.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>564.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>202.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.200000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4b98869-971b-4a0f-aef3-68f54b7ae5f4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b4b98869-971b-4a0f-aef3-68f54b7ae5f4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b4b98869-971b-4a0f-aef3-68f54b7ae5f4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    <div id=\"df-c97d7409-c852-45ec-99c4-01d8c48b08c7\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c97d7409-c852-45ec-99c4-01d8c48b08c7')\"\n",
              "                title=\"Suggest charts\"\n",
              "                style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "      <script>\n",
              "        async function quickchart(key) {\n",
              "          const quickchartButtonEl =\n",
              "            document.querySelector('#' + key + ' button');\n",
              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "          try {\n",
              "            const charts = await google.colab.kernel.invokeFunction(\n",
              "                'suggestCharts', [key], {});\n",
              "          } catch (error) {\n",
              "            console.error('Error during call to suggestCharts:', error);\n",
              "          }\n",
              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "        }\n",
              "        (() => {\n",
              "          let quickchartButtonEl =\n",
              "            document.querySelector('#df-c97d7409-c852-45ec-99c4-01d8c48b08c7 button');\n",
              "          quickchartButtonEl.style.display =\n",
              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "        })();\n",
              "      </script>\n",
              "    </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 92.24634585738892,\n        \"min\": 9.04796974624746,\n        \"max\": 302.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          54.420529801324506,\n          55.5,\n          302.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.56441136917542,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.6821192052980133,\n          1.0,\n          0.4664257380672639\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.373891168386,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          302.0,\n          0.9635761589403974,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 82.36893210059165,\n        \"min\": 17.563394230037563,\n        \"max\": 302.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          131.60264900662253,\n          130.0,\n          302.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 150.32331637314442,\n        \"min\": 51.75348865574056,\n        \"max\": 564.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          246.5,\n          240.5,\n          302.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fbs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.69762766400389,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.1490066225165563,\n          1.0,\n          0.3566860293648132\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"restecg\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.51988268714389,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          302.0,\n          0.5264900662251656,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 83.44838929381501,\n        \"min\": 22.903527251969837,\n        \"max\": 302.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          149.56953642384107,\n          152.5,\n          302.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"exang\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.63261370805944,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.32781456953642385,\n          1.0,\n          0.47019596400976915\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.2458369741905,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          302.0,\n          1.0430463576158941,\n          1.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.37049565715138,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          302.0,\n          1.3973509933774835,\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.44154442680603,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          302.0,\n          0.7185430463576159,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.12547106736513,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          302.0,\n          2.314569536423841,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.56978221617638,\n        \"min\": 0.0,\n        \"max\": 302.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.543046357615894,\n          1.0,\n          0.4989703596114114\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "w69eaRq6hr9K"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***נרצה לראות כמה חולים/בריאים יש:***"
      ],
      "metadata": {
        "id": "58MqkXgmuJK2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['target'].value_counts()"
      ],
      "metadata": {
        "id": "Qe5k-9DLK07M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 178
        },
        "outputId": "96d469cf-f809-4482-b15f-a39b7c703f86"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "target\n",
              "1    164\n",
              "0    138\n",
              "Name: count, dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>target</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>164</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>138</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['target'].value_counts().plot(kind='bar')\n",
        "plt.title(\"Target Distribution\")\n",
        "plt.xlabel(\"Heart Disease (1=yes)\")\n",
        "plt.ylabel(\"Count\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "L25yyHKOwvKQ",
        "outputId": "18534ae8-33d9-43f6-cccd-4b488ed4336b"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***התפלגות משתנים חשובים:***"
      ],
      "metadata": {
        "id": "QfoZKHdGutGk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Research:** Pose relevant questions about your dataset, then answer them using visual elements (e.g. charts or plots) to provide clear insights.\n",
        "\n",
        "For example, in the 2nd lecture the entire class took a survey. Then, we talked about the collected data and desplayed the collected data using the right **plots** - Lines, Bars, Hist, Pie, Map, HeatMap, Area, Time, etc.\n",
        "\n",
        "An aditional more specific example, would be the questions we asked during the recitation on the `Titanic` dataset:\n",
        "  - \"Did survival rates differ by gender?\"\n",
        "  - \"Was passenger class related to survival?\"\n",
        "  - \"What was the age distribution of survivors vs. non-survivors?\"\n",
        "  - \"Did embarking location (port) have any effect on survival?\"    \n",
        "  \n",
        "And how we answered those questions using **plots**.\n",
        "\n",
        "The idea is to pose questions that can uncover patterns, correlations, or anomalies in your dataset, then back those up with clean, insightful visualizations."
      ],
      "metadata": {
        "id": "lo68PsjTK0_j"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***AGE:***"
      ],
      "metadata": {
        "id": "2nG8vV9PxnwW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "sns.boxplot(x='target', y='age', data=df)\n",
        "plt.title(\"Age vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "bjYQcboyxsMN",
        "outputId": "8f648e33-5e4b-4614-9af3-d0c131326905"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***CHOL:***"
      ],
      "metadata": {
        "id": "bMr9hlBozHl_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x='target', y='chol', data=df)\n",
        "plt.title(\"Cholesterol vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "rgxcKGPAzKq6",
        "outputId": "0eda1cc7-ac6d-4b3b-aa93-0d37fcfbc604"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***thalach:***"
      ],
      "metadata": {
        "id": "nSBdFkORzwlv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x='target', y='thalach', data=df)\n",
        "plt.title(\"Max Heart Rate vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "0ch5l8tIK1Dt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "outputId": "4fb891ed-4e6c-4420-c924-a02fb1357790"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***oldpeak:***"
      ],
      "metadata": {
        "id": "ZwKLA2t-0bXS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x='target', y='oldpeak', data=df)\n",
        "plt.title(\"Oldpeak vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "yDfXQ0UV0fHJ",
        "outputId": "53f93745-ff33-49f1-ac40-c153613cc82a"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***cp - chest pain:***"
      ],
      "metadata": {
        "id": "kDYbQ7wX1eJQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x='cp', hue='target', data=df)\n",
        "plt.title(\"Chest Pain vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "sN9qh5zx12d1",
        "outputId": "c934706b-ff11-4328-ef6c-2fa75f2037a3"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***exang - pain during effort:***"
      ],
      "metadata": {
        "id": "S1AAGUPG2gtK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x='exang', hue='target', data=df)\n",
        "plt.title(\"Exercise-Induced Angina vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "uVrljeIx297n",
        "outputId": "8de458e6-824e-4b0c-f6c5-d9bf05dd98b9"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***CA - BLOCKED BLOOD VESSELS:***"
      ],
      "metadata": {
        "id": "cX7COIAA31Br"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x='target', y='ca', data=df)\n",
        "plt.title(\"Number of Major Vessels vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "DRQPCRe44KET",
        "outputId": "288b2fec-c8da-4cc1-d9e1-75f726276c5e"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***THAL:***"
      ],
      "metadata": {
        "id": "u60WEuWwc7ka"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x='target', y='thal', data=df)\n",
        "plt.title(\"Thal vs Heart Disease\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "0n59p3npdAGy",
        "outputId": "e7752ace-9b41-4228-89d4-5768e02b1e44"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "_M62cZH7mc12"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "5diQ4kRlmc6z"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<br><br><br>\n",
        "\n",
        "---\n",
        "\n",
        "<br><br><br>"
      ],
      "metadata": {
        "id": "zrIvgbNoIPU6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 3: README file**\n",
        "\n",
        "1. Upload the dataset to HuggingFace.\n",
        "\n",
        "2. Upload your work (code, notebook) to your HF's Dataset.\n",
        "\n",
        "3. Create a `README` file in a Markdown format. This page should include the end result of your work. Meaning include the visualizations, Questions, Answers, insights, Decisions, and more.\n"
      ],
      "metadata": {
        "id": "TxKHPqppIPZT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "EfniaMYBK6sK"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "uLxQ5tJQK6xG"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "0GnQN63RK61Q"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "euWXtGKHK65d"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<br><br><br>\n",
        "\n",
        "---\n",
        "\n",
        "<br><br><br>"
      ],
      "metadata": {
        "id": "hkerNEsMIPbK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 4: Presentation Video**\n",
        "\n",
        "- Record a brief video (2–3 minutes) with screen sharing of you walk through the HF's Dataset, README, notebook and sharing your process & results. Make sure to include a screen share while also recording yourself talking during the walk through.\n",
        "\n",
        "- Videos without your face talking while going ower your work wont be acceptable.\n",
        "\n",
        "- You should include:\n",
        "  - A quick dataset overview and your main goal.\n",
        "  - Key EDA steps and highlights of visual insights. (!)\n",
        "  - Reflections on any challenges and lessons learned.\n"
      ],
      "metadata": {
        "id": "mzYCO54GIPdP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "> For help:\n",
        "> - Youtube [Watch this video](https://www.youtube.com/watch?v=DK7Z_nYhjjg)\n",
        "> - Loom [Watch this video](https://www.youtube.com/watch?v=eSCHNXTsJK8)\n",
        "> - Zoom [Watch this video](https://www.youtube.com/watch?v=njwbjFYCbGU)\n"
      ],
      "metadata": {
        "id": "si7mk6JgJurV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally, attach the video to the end of the `README` file, and make sure everything works."
      ],
      "metadata": {
        "id": "QJ8Rux_SY1JH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<br><br><br>"
      ],
      "metadata": {
        "id": "hoLjb_ZrY2Nm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 5: Moodle**"
      ],
      "metadata": {
        "id": "km5C5-WyjO3R"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Submit to Moodle the link to your HF's Dataset.**  \n",
        "(or use a `.txt` file)\n",
        "\n",
        "> As the dataset already includes the video presentation, and the code notebook - we should haver everything there to examine.\n"
      ],
      "metadata": {
        "id": "Bx7dlp5xjT4r"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "---\n",
        "\n",
        "Good luck and have fun exploring your first DS project!"
      ],
      "metadata": {
        "id": "rN8TJ_5oIPfm"
      }
    }
  ]
}