Practise2.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMrcc0KDzKWik+8FNlOwyty",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Vivek-00101/Assignment-1-2025/blob/main/Practise2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "S6nsaDx6VfeN"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"breast-cancer.csv\")"
      ],
      "metadata": {
        "id": "7r-KbyiYlLg0"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "Y1dXJxw_le0v",
        "outputId": "b225b1ee-3fd4-4ce1-fd49-1dc14f272578"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         id diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
              "564  926424         M        21.56         22.39          142.00     1479.0   \n",
              "565  926682         M        20.13         28.25          131.20     1261.0   \n",
              "566  926954         M        16.60         28.08          108.30      858.1   \n",
              "567  927241         M        20.60         29.33          140.10     1265.0   \n",
              "568   92751         B         7.76         24.54           47.92      181.0   \n",
              "\n",
              "     smoothness_mean  compactness_mean  concavity_mean  concave points_mean  \\\n",
              "564          0.11100           0.11590         0.24390              0.13890   \n",
              "565          0.09780           0.10340         0.14400              0.09791   \n",
              "566          0.08455           0.10230         0.09251              0.05302   \n",
              "567          0.11780           0.27700         0.35140              0.15200   \n",
              "568          0.05263           0.04362         0.00000              0.00000   \n",
              "\n",
              "     ...  radius_worst  texture_worst  perimeter_worst  area_worst  \\\n",
              "564  ...        25.450          26.40           166.10      2027.0   \n",
              "565  ...        23.690          38.25           155.00      1731.0   \n",
              "566  ...        18.980          34.12           126.70      1124.0   \n",
              "567  ...        25.740          39.42           184.60      1821.0   \n",
              "568  ...         9.456          30.37            59.16       268.6   \n",
              "\n",
              "     smoothness_worst  compactness_worst  concavity_worst  \\\n",
              "564           0.14100            0.21130           0.4107   \n",
              "565           0.11660            0.19220           0.3215   \n",
              "566           0.11390            0.30940           0.3403   \n",
              "567           0.16500            0.86810           0.9387   \n",
              "568           0.08996            0.06444           0.0000   \n",
              "\n",
              "     concave points_worst  symmetry_worst  fractal_dimension_worst  \n",
              "564                0.2216          0.2060                  0.07115  \n",
              "565                0.1628          0.2572                  0.06637  \n",
              "566                0.1418          0.2218                  0.07820  \n",
              "567                0.2650          0.4087                  0.12400  \n",
              "568                0.0000          0.2871                  0.07039  \n",
              "\n",
              "[5 rows x 32 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-926ba795-4d01-4944-bc4f-d84ddac65dcf\">\n",
              "    <div 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>id</th>\n",
              "      <th>diagnosis</th>\n",
              "      <th>radius_mean</th>\n",
              "      <th>texture_mean</th>\n",
              "      <th>perimeter_mean</th>\n",
              "      <th>area_mean</th>\n",
              "      <th>smoothness_mean</th>\n",
              "      <th>compactness_mean</th>\n",
              "      <th>concavity_mean</th>\n",
              "      <th>concave points_mean</th>\n",
              "      <th>...</th>\n",
              "      <th>radius_worst</th>\n",
              "      <th>texture_worst</th>\n",
              "      <th>perimeter_worst</th>\n",
              "      <th>area_worst</th>\n",
              "      <th>smoothness_worst</th>\n",
              "      <th>compactness_worst</th>\n",
              "      <th>concavity_worst</th>\n",
              "      <th>concave points_worst</th>\n",
              "      <th>symmetry_worst</th>\n",
              "      <th>fractal_dimension_worst</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>564</th>\n",
              "      <td>926424</td>\n",
              "      <td>M</td>\n",
              "      <td>21.56</td>\n",
              "      <td>22.39</td>\n",
              "      <td>142.00</td>\n",
              "      <td>1479.0</td>\n",
              "      <td>0.11100</td>\n",
              "      <td>0.11590</td>\n",
              "      <td>0.24390</td>\n",
              "      <td>0.13890</td>\n",
              "      <td>...</td>\n",
              "      <td>25.450</td>\n",
              "      <td>26.40</td>\n",
              "      <td>166.10</td>\n",
              "      <td>2027.0</td>\n",
              "      <td>0.14100</td>\n",
              "      <td>0.21130</td>\n",
              "      <td>0.4107</td>\n",
              "      <td>0.2216</td>\n",
              "      <td>0.2060</td>\n",
              "      <td>0.07115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>565</th>\n",
              "      <td>926682</td>\n",
              "      <td>M</td>\n",
              "      <td>20.13</td>\n",
              "      <td>28.25</td>\n",
              "      <td>131.20</td>\n",
              "      <td>1261.0</td>\n",
              "      <td>0.09780</td>\n",
              "      <td>0.10340</td>\n",
              "      <td>0.14400</td>\n",
              "      <td>0.09791</td>\n",
              "      <td>...</td>\n",
              "      <td>23.690</td>\n",
              "      <td>38.25</td>\n",
              "      <td>155.00</td>\n",
              "      <td>1731.0</td>\n",
              "      <td>0.11660</td>\n",
              "      <td>0.19220</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>0.2572</td>\n",
              "      <td>0.06637</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>566</th>\n",
              "      <td>926954</td>\n",
              "      <td>M</td>\n",
              "      <td>16.60</td>\n",
              "      <td>28.08</td>\n",
              "      <td>108.30</td>\n",
              "      <td>858.1</td>\n",
              "      <td>0.08455</td>\n",
              "      <td>0.10230</td>\n",
              "      <td>0.09251</td>\n",
              "      <td>0.05302</td>\n",
              "      <td>...</td>\n",
              "      <td>18.980</td>\n",
              "      <td>34.12</td>\n",
              "      <td>126.70</td>\n",
              "      <td>1124.0</td>\n",
              "      <td>0.11390</td>\n",
              "      <td>0.30940</td>\n",
              "      <td>0.3403</td>\n",
              "      <td>0.1418</td>\n",
              "      <td>0.2218</td>\n",
              "      <td>0.07820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>567</th>\n",
              "      <td>927241</td>\n",
              "      <td>M</td>\n",
              "      <td>20.60</td>\n",
              "      <td>29.33</td>\n",
              "      <td>140.10</td>\n",
              "      <td>1265.0</td>\n",
              "      <td>0.11780</td>\n",
              "      <td>0.27700</td>\n",
              "      <td>0.35140</td>\n",
              "      <td>0.15200</td>\n",
              "      <td>...</td>\n",
              "      <td>25.740</td>\n",
              "      <td>39.42</td>\n",
              "      <td>184.60</td>\n",
              "      <td>1821.0</td>\n",
              "      <td>0.16500</td>\n",
              "      <td>0.86810</td>\n",
              "      <td>0.9387</td>\n",
              "      <td>0.2650</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.12400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>568</th>\n",
              "      <td>92751</td>\n",
              "      <td>B</td>\n",
              "      <td>7.76</td>\n",
              "      <td>24.54</td>\n",
              "      <td>47.92</td>\n",
              "      <td>181.0</td>\n",
              "      <td>0.05263</td>\n",
              "      <td>0.04362</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>...</td>\n",
              "      <td>9.456</td>\n",
              "      <td>30.37</td>\n",
              "      <td>59.16</td>\n",
              "      <td>268.6</td>\n",
              "      <td>0.08996</td>\n",
              "      <td>0.06444</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2871</td>\n",
              "      <td>0.07039</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 32 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-926ba795-4d01-4944-bc4f-d84ddac65dcf')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-926ba795-4d01-4944-bc4f-d84ddac65dcf 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-926ba795-4d01-4944-bc4f-d84ddac65dcf');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.keys()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xCdU1vBwlgUI",
        "outputId": "49138585-36f4-4bb0-d8b4-0ca36fb7b325"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', 'diagnosis', 'radius_mean', 'texture_mean', 'perimeter_mean',\n",
              "       'area_mean', 'smoothness_mean', 'compactness_mean', 'concavity_mean',\n",
              "       'concave points_mean', 'symmetry_mean', 'fractal_dimension_mean',\n",
              "       'radius_se', 'texture_se', 'perimeter_se', 'area_se', 'smoothness_se',\n",
              "       'compactness_se', 'concavity_se', 'concave points_se', 'symmetry_se',\n",
              "       'fractal_dimension_se', 'radius_worst', 'texture_worst',\n",
              "       'perimeter_worst', 'area_worst', 'smoothness_worst',\n",
              "       'compactness_worst', 'concavity_worst', 'concave points_worst',\n",
              "       'symmetry_worst', 'fractal_dimension_worst'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VbAKajVtlnj8",
        "outputId": "d2f9daab-3d13-4fa8-f1d1-4b5427ad1a94"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(569, 32)"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['diagnosis'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TLSFNnQjohtN",
        "outputId": "dab8dec8-d032-4220-8e9d-6fb9e0ea7426"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "B    357\n",
              "M    212\n",
              "Name: diagnosis, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(df['diagnosis'], label='count')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "LO9Q9JMvpDYj",
        "outputId": "e79ac32b-df90-4630-8bde-4f308ce0d251"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f788aa81490>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAASDklEQVR4nO3df7BndX3f8efLBYWpJED2lm5216y1tAyauOgVSdI2BMeKpOmiQxyYSVwt0zUz2DFpJhNIO2psmWqDYaJJmFnKT2tU6o9CLLUhBHWcUXCh67KA1K1C2R1+XBEQQqSz67t/fD/349fL3eW7wLnfy97nY+bM95zP53PO932Zu/fF55zzPd9UFZIkAbxo2gVIkpYPQ0GS1BkKkqTOUJAkdYaCJKk7bNoFPBerV6+uDRs2TLsMSXpBufXWW79bVTOL9b2gQ2HDhg1s27Zt2mVI0gtKknv31+fpI0lSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVL3gv5Es3Qo+78f+Nlpl6Bl6GXvvX3Q4w82U0hyRJJbknwjyR1J/qC1X5nkO0m2t2Vja0+SjyTZlWRHktcMVZskaXFDzhSeAk6rqieSHA58Jcn/aH2/W1WfXjD+zcDxbXk9cEl7lSQtkcFmCjXyRNs8vC0H+kLoTcDVbb+vAUcnWTNUfZKkpxv0QnOSVUm2Aw8BN1TVza3rwnaK6OIkL2lta4H7xnbf3doWHnNLkm1Jts3NzQ1ZviStOIOGQlXtq6qNwDrg5CSvAi4ATgBeBxwL/N5BHnNrVc1W1ezMzKKPA5ckPUtLcktqVT0K3AScXlX3t1NETwFXACe3YXuA9WO7rWttkqQlMuTdRzNJjm7rRwJvBL45f50gSYAzgZ1tl+uAt7e7kE4BHquq+4eqT5L0dEPefbQGuCrJKkbhc01VfT7JXyeZAQJsB36zjb8eOAPYBTwJvHPA2iRJixgsFKpqB3DSIu2n7Wd8AecNVY8k6Zn5mAtJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkbrBQSHJEkluSfCPJHUn+oLW/PMnNSXYl+VSSF7f2l7TtXa1/w1C1SZIWN+RM4SngtKp6NbAROD3JKcCHgIur6h8AjwDntvHnAo+09ovbOEnSEhosFGrkibZ5eFsKOA34dGu/CjizrW9q27T+NyTJUPVJkp5u0GsKSVYl2Q48BNwA/B/g0ara24bsBta29bXAfQCt/zHgpxY55pYk25Jsm5ubG7J8SVpxBg2FqtpXVRuBdcDJwAnPwzG3VtVsVc3OzMw85xolST+yJHcfVdWjwE3AzwNHJzmsda0D9rT1PcB6gNb/k8DDS1GfJGlkyLuPZpIc3daPBN4I3MUoHM5qwzYD17b169o2rf+vq6qGqk+S9HSHPfOQZ20NcFWSVYzC55qq+nySO4FPJvkPwP8CLmvjLwM+lmQX8D3g7AFrkyQtYrBQqKodwEmLtH+b0fWFhe0/AH5tqHokSc/MTzRLkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYOFQpL1SW5KcmeSO5K8p7W/P8meJNvbcsbYPhck2ZXk7iRvGqo2SdLiDhvw2HuB36mq25IcBdya5IbWd3FVXTQ+OMmJwNnAK4GfBv4qyT+sqn0D1ihJGjPYTKGq7q+q29r648BdwNoD7LIJ+GRVPVVV3wF2AScPVZ8k6emW5JpCkg3AScDNrendSXYkuTzJMa1tLXDf2G67WSREkmxJsi3Jtrm5uQGrlqSVZ/BQSPJS4DPAb1XV94FLgFcAG4H7gQ8fzPGqamtVzVbV7MzMzPNeryStZIOGQpLDGQXCx6vqswBV9WBV7auqHwKX8qNTRHuA9WO7r2ttkqQlMuTdRwEuA+6qqj8aa18zNuwtwM62fh1wdpKXJHk5cDxwy1D1SZKebsi7j34R+A3g9iTbW9vvA+ck2QgUcA/wLoCquiPJNcCdjO5cOs87jyRpaQ0WClX1FSCLdF1/gH0uBC4cqiZJ0oH5iWZJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6ob85rUXhNf+7tXTLkHL0K1/+PZplyBNhTMFSVJnKEiSuolCIcmNk7RJkl7YDhgKSY5IciywOskxSY5tywZg7TPsuz7JTUnuTHJHkve09mOT3JDkW+31mNaeJB9JsivJjiSveX5+REnSpJ5ppvAu4FbghPY6v1wL/Mkz7LsX+J2qOhE4BTgvyYnA+cCNVXU8cGPbBngzcHxbtgCXHPRPI0l6Tg5491FV/THwx0n+dVV99GAOXFX3A/e39ceT3MVodrEJOLUNuwr4IvB7rf3qqirga0mOTrKmHUeStAQmuiW1qj6a5BeADeP7VNVE93O2000nATcDx439oX8AOK6trwXuG9ttd2v7sVBIsoXRTIKXvexlk7y9JGlCE4VCko8BrwC2A/tacwHPGApJXgp8Bvitqvp+kt5XVZWkDqbgqtoKbAWYnZ09qH0lSQc26YfXZoET26mdiSU5nFEgfLyqPtuaH5w/LZRkDfBQa98DrB/bfV1rkyQtkUk/p7AT+HsHc+CMpgSXAXdV1R+NdV0HbG7rmxldtJ5vf3u7C+kU4DGvJ0jS0pp0prAauDPJLcBT841V9S8OsM8vAr8B3J5ke2v7feCDwDVJzgXuBd7W+q4HzgB2AU8C75z0h5AkPT8mDYX3H+yBq+orQPbT/YZFxhdw3sG+jyTp+TPp3UdfGroQSdL0TXr30eOM7jYCeDFwOPA3VfUTQxUmSVp6k84UjppfbxeQNzH6lLIk6RBy0E9JrZH/BrxpgHokSVM06emjt45tvojR5xZ+MEhFkqSpmfTuo18dW98L3MPoFJIk6RAy6TUFPzMgSSvApF+ysy7J55I81JbPJFk3dHGSpKU16YXmKxg9huKn2/IXrU2SdAiZNBRmquqKqtrbliuBmQHrkiRNwaSh8HCSX0+yqi2/Djw8ZGGSpKU3aSj8S0YPrnuA0ZfenAW8Y6CaJElTMuktqR8ANlfVIwBJjgUuYhQWkqRDxKQzhZ+bDwSAqvoeo6/XlCQdQiYNhRclOWZ+o80UJp1lSJJeICb9w/5h4KtJ/mvb/jXgwmFKkiRNy6SfaL46yTbgtNb01qq6c7iyJEnTMPEpoBYCBoEkHcIO+tHZkqRDl6EgSeoGC4Ukl7eH5+0ca3t/kj1JtrfljLG+C5LsSnJ3Er/AR5KmYMiZwpXA6Yu0X1xVG9tyPUCSE4GzgVe2ff4syaoBa5MkLWKwUKiqLwPfm3D4JuCTVfVUVX0H2AWcPFRtkqTFTeOawruT7Ginl+Y/ELcWuG9szO7W9jRJtiTZlmTb3Nzc0LVK0oqy1KFwCfAKYCOjB+t9+GAPUFVbq2q2qmZnZnx6tyQ9n5Y0FKrqwaraV1U/BC7lR6eI9gDrx4aua22SpCW0pKGQZM3Y5luA+TuTrgPOTvKSJC8HjgduWcraJEkDPtQuySeAU4HVSXYD7wNOTbIRKOAe4F0AVXVHkmsYfWJ6L3BeVe0bqjZJ0uIGC4WqOmeR5ssOMP5CfMieJE2Vn2iWJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gYLhSSXJ3koyc6xtmOT3JDkW+31mNaeJB9JsivJjiSvGaouSdL+DTlTuBI4fUHb+cCNVXU8cGPbBngzcHxbtgCXDFiXJGk/BguFqvoy8L0FzZuAq9r6VcCZY+1X18jXgKOTrBmqNknS4pb6msJxVXV/W38AOK6trwXuGxu3u7U9TZItSbYl2TY3NzdcpZK0Ak3tQnNVFVDPYr+tVTVbVbMzMzMDVCZJK9dSh8KD86eF2utDrX0PsH5s3LrWJklaQksdCtcBm9v6ZuDasfa3t7uQTgEeGzvNJElaIocNdeAknwBOBVYn2Q28D/ggcE2Sc4F7gbe14dcDZwC7gCeBdw5VlyRp/wYLhao6Zz9db1hkbAHnDVWLJGkyfqJZktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTtsGm+a5B7gcWAfsLeqZpMcC3wK2ADcA7ytqh6ZRn2StFJNc6bwy1W1sapm2/b5wI1VdTxwY9uWJC2h5XT6aBNwVVu/CjhzirVI0oo0rVAo4C+T3JpkS2s7rqrub+sPAMcttmOSLUm2Jdk2Nze3FLVK0ooxlWsKwD+uqj1J/i5wQ5JvjndWVSWpxXasqq3AVoDZ2dlFx0iSnp2pzBSqak97fQj4HHAy8GCSNQDt9aFp1CZJK9mSh0KSv5PkqPl14J8BO4HrgM1t2Gbg2qWuTZJWummcPjoO+FyS+ff/86r6QpKvA9ckORe4F3jbFGqTpBVtyUOhqr4NvHqR9oeBNyx1PZKkH1lOt6RKkqbMUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSd2yC4Ukpye5O8muJOdPux5JWkmWVSgkWQX8KfBm4ETgnCQnTrcqSVo5llUoACcDu6rq21X1/4BPApumXJMkrRiHTbuABdYC941t7wZePz4gyRZgS9t8IsndS1TbSrAa+O60i1gOctHmaZegH+fv5rz35fk4ys/sr2O5hcIzqqqtwNZp13EoSrKtqmanXYe0kL+bS2e5nT7aA6wf217X2iRJS2C5hcLXgeOTvDzJi4GzgeumXJMkrRjL6vRRVe1N8m7gfwKrgMur6o4pl7WSeFpOy5W/m0skVTXtGiRJy8RyO30kSZoiQ0GS1BkKK1ySSvJfxrYPSzKX5PPTrEsCSLIvyfYk30hyW5JfmHZNh7pldaFZU/E3wKuSHFlVfwu8EW8D1vLxt1W1ESDJm4D/CPzSdEs6tDlTEMD1wK+09XOAT0yxFml/fgJ4ZNpFHOoMBcHoGVNnJzkC+Dng5inXI807sp0++ibwn4F/P+2CDnWePhJVtSPJBkazhOunW430Y8ZPH/08cHWSV5X30g/GmYLmXQdchKeOtExV1VcZPRhvZtq1HMqcKWje5cCjVXV7klOnXYy0UJITGD3p4OFp13IoMxQEQFXtBj4y7TqkBY5Msr2tB9hcVfumWdChzsdcSJI6rylIkjpDQZLUGQqSpM5QkCR1hoIkqfOWVKlJ8n7gCUbP2PlyVf3VFGv5wLRr0MpkKEgLVNV7rUErlaePtKIl+bdJ/neSrwD/qLVdmeSstv7eJF9PsjPJ1iRp7a9LsqM9rO0Pk+xs7e9I8tkkX0jyrST/aey9zklyezvWh1rbqvZ+O1vfby9SwweT3Nne76Il/Q+kFceZglasJK8FzgY2Mvq3cBtw64Jhf1JVH2jjPwb8c+AvgCuAf1VVX03ywQX7bAROAp4C7k7yUWAf8CHgtYwe//yXSc4E7gPWVtWr2nscvaDGnwLeApxQVbWwX3q+OVPQSvZPgM9V1ZNV9X1GDwVc6JeT3JzkduA04JXtD/NR7QFtAH++YJ8bq+qxqvoBcCfwM8DrgC9W1VxV7QU+DvxT4NvA30/y0SSnA99fcKzHgB8AlyV5K/Dkc/6ppQMwFKT9aN8v8WfAWVX1s8ClwBET7PrU2Po+DjAjr6pHgFcDXwR+k9F3Boz37wVOBj7NaJbyhcl/AungGQpayb4MnJnkyCRHAb+6oH8+AL6b5KXAWQBV9SjweJLXt/6zJ3ivW4BfSrI6ySpG313xpSSrgRdV1WeAfwe8Znyn9r4/WVXXA7/NKECkwXhNQStWVd2W5FPAN4CHgK8v6H80yaXATuCBBf3nApcm+SHwJUaneQ70XvcnOR+4idHTPv97VV2b5NXAFUnm/wftggW7HgVc22YtAf7Ns/hRpYn5lFTpWUjy0qp6oq2fD6ypqvdMuSzpOXOmID07v5LkAkb/hu4F3jHdcqTnhzMFSVLnhWZJUmcoSJI6Q0GS1BkKkqTOUJAkdf8f0rm+gk1Pwo0AAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "labelencoder_Y = LabelEncoder()\n",
        "df.iloc[:,-1] = labelencoder_Y.fit_transform(df.iloc[:,1].values)\n",
        "df.iloc[:,1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "btoRe-BipkbQ",
        "outputId": "190bfe1b-1db1-4ad4-b3a3-5eb6c2be0919"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      M\n",
              "1      M\n",
              "2      M\n",
              "3      M\n",
              "4      M\n",
              "      ..\n",
              "564    M\n",
              "565    M\n",
              "566    M\n",
              "567    M\n",
              "568    B\n",
              "Name: diagnosis, Length: 569, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.pairplot(df.iloc[:,1:5], hue='diagnosis')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 568
        },
        "id": "rszfMst2qWZs",
        "outputId": "fe510ec2-9867-430a-8cdf-2442ee0a8266"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7f788a99adf0>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 595.5x540 with 12 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9yIDAxUTera-",
        "outputId": "721e62dc-ad5e-4323-dd62-b28b42880548"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 569 entries, 0 to 568\n",
            "Data columns (total 32 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   id                       569 non-null    int64  \n",
            " 1   diagnosis                569 non-null    object \n",
            " 2   radius_mean              569 non-null    float64\n",
            " 3   texture_mean             569 non-null    float64\n",
            " 4   perimeter_mean           569 non-null    float64\n",
            " 5   area_mean                569 non-null    float64\n",
            " 6   smoothness_mean          569 non-null    float64\n",
            " 7   compactness_mean         569 non-null    float64\n",
            " 8   concavity_mean           569 non-null    float64\n",
            " 9   concave points_mean      569 non-null    float64\n",
            " 10  symmetry_mean            569 non-null    float64\n",
            " 11  fractal_dimension_mean   569 non-null    float64\n",
            " 12  radius_se                569 non-null    float64\n",
            " 13  texture_se               569 non-null    float64\n",
            " 14  perimeter_se             569 non-null    float64\n",
            " 15  area_se                  569 non-null    float64\n",
            " 16  smoothness_se            569 non-null    float64\n",
            " 17  compactness_se           569 non-null    float64\n",
            " 18  concavity_se             569 non-null    float64\n",
            " 19  concave points_se        569 non-null    float64\n",
            " 20  symmetry_se              569 non-null    float64\n",
            " 21  fractal_dimension_se     569 non-null    float64\n",
            " 22  radius_worst             569 non-null    float64\n",
            " 23  texture_worst            569 non-null    float64\n",
            " 24  perimeter_worst          569 non-null    float64\n",
            " 25  area_worst               569 non-null    float64\n",
            " 26  smoothness_worst         569 non-null    float64\n",
            " 27  compactness_worst        569 non-null    float64\n",
            " 28  concavity_worst          569 non-null    float64\n",
            " 29  concave points_worst     569 non-null    float64\n",
            " 30  symmetry_worst           569 non-null    float64\n",
            " 31  fractal_dimension_worst  569 non-null    int64  \n",
            "dtypes: float64(29), int64(2), object(1)\n",
            "memory usage: 142.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "Label_Encoder= LabelEncoder()\n",
        "df['diagnosis'] = Label_Encoder.fit_transform(df['diagnosis'])"
      ],
      "metadata": {
        "id": "XW5vzUmle4c2"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['diagnosis'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J-MtPa92e_KQ",
        "outputId": "18fdbddc-f27d-44b5-9ce9-5d1408c86b9c"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    357\n",
              "1    212\n",
              "Name: diagnosis, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X= df.drop('diagnosis',axis= 1)\n",
        "Y = df['diagnosis']"
      ],
      "metadata": {
        "id": "TP0y9FXyfDYU"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.25, random_state = 0)"
      ],
      "metadata": {
        "id": "89U9XhZYfKCn"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "I1dYKIIcfLcN"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.model_selection import cross_val_score\n",
        "\n",
        "accuracy_rate=[]\n",
        "\n",
        "for i in range(1,40):\n",
        "    classifier= KNeighborsClassifier(n_neighbors =i)\n",
        "    score = cross_val_score(classifier,X,Y,cv=10)\n",
        "    accuracy_rate.append(score.mean())"
      ],
      "metadata": {
        "id": "BTKN69bRfO20"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(range(1,40),accuracy_rate, color= 'red',linestyle = 'solid',marker='*', markersize=5)\n",
        "plt.title('Accuracy Rate vs K-Value')\n",
        "plt.xlabel('K-Value')\n",
        "plt.ylabel('Accuracy_Rate')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "KS_xUtHtfRrd",
        "outputId": "0615a558-e867-4618-99e3-f398d036b187"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Accuracy_Rate')"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yJKXWxc7fWqN"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}