Week 2- Breast Cancer detection using Machine Learning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Week 2: Breast Cancer detection using Machine Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In week 2, we will be implementing the tools we learnt in week 1 on the breast cancer data set. In the second half, we will also learn some of the basic commands from the library scikit learn. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Breast Cancer Dataset is available at: https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+%28original%29"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Those who are having trouble downloading the Dataset from the website, the data will be uploaded in the folder and you can directly download from there. In the following few code cells, I will write all the instructions step wise, your assignment for this week is to write codes for the steps simultaneously in your python file and take time to analyze. \n",
    "In future projects, you will have to think and come up with these steps alongwith writing the codes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 1: Open the file in your python notebook, print first 5 rows of the dataset and mention what are the dependent and independent variables in the Data.\n",
    "\n",
    "#### Step 2: Find the statistical parameters of the Data that you have\n",
    "\n",
    "#### Step 3: Find the shape of the Dataset in hand. \n",
    "\n",
    "#### Step 4: Find missing values from the Dataset\n",
    "\n",
    "#### Step 5: Find the value count of B(Benign) and M(Malignant) cancer cells in the column \"diagnosis\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 1: Open the file in your python notebook, print first 5 rows of the dataset and mention what are the dependent and independent variables in the Data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Step 1: Open the file in your python notebook, print first 5 rows of the dataset and mention what are the dependent and independent variables in the Data\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <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",
       "      <td>0</td>\n",
       "      <td>842302</td>\n",
       "      <td>M</td>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>...</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>842517</td>\n",
       "      <td>M</td>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>...</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>84300903</td>\n",
       "      <td>M</td>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>...</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>84348301</td>\n",
       "      <td>M</td>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>...</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>84358402</td>\n",
       "      <td>M</td>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>...</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 32 columns</p>\n",
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      "text/plain": [
       "         id diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
       "0    842302         M        17.99         10.38          122.80     1001.0   \n",
       "1    842517         M        20.57         17.77          132.90     1326.0   \n",
       "2  84300903         M        19.69         21.25          130.00     1203.0   \n",
       "3  84348301         M        11.42         20.38           77.58      386.1   \n",
       "4  84358402         M        20.29         14.34          135.10     1297.0   \n",
       "\n",
       "   smoothness_mean  compactness_mean  concavity_mean  concave points_mean  \\\n",
       "0          0.11840           0.27760          0.3001              0.14710   \n",
       "1          0.08474           0.07864          0.0869              0.07017   \n",
       "2          0.10960           0.15990          0.1974              0.12790   \n",
       "3          0.14250           0.28390          0.2414              0.10520   \n",
       "4          0.10030           0.13280          0.1980              0.10430   \n",
       "\n",
       "   ...  radius_worst  texture_worst  perimeter_worst  area_worst  \\\n",
       "0  ...         25.38          17.33           184.60      2019.0   \n",
       "1  ...         24.99          23.41           158.80      1956.0   \n",
       "2  ...         23.57          25.53           152.50      1709.0   \n",
       "3  ...         14.91          26.50            98.87       567.7   \n",
       "4  ...         22.54          16.67           152.20      1575.0   \n",
       "\n",
       "   smoothness_worst  compactness_worst  concavity_worst  concave points_worst  \\\n",
       "0            0.1622             0.6656           0.7119                0.2654   \n",
       "1            0.1238             0.1866           0.2416                0.1860   \n",
       "2            0.1444             0.4245           0.4504                0.2430   \n",
       "3            0.2098             0.8663           0.6869                0.2575   \n",
       "4            0.1374             0.2050           0.4000                0.1625   \n",
       "\n",
       "   symmetry_worst  fractal_dimension_worst  \n",
       "0          0.4601                  0.11890  \n",
       "1          0.2750                  0.08902  \n",
       "2          0.3613                  0.08758  \n",
       "3          0.6638                  0.17300  \n",
       "4          0.2364                  0.07678  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('cancer dataset.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Independent:radius_mean\ttexture_mean\tperimeter_mean\tarea_mean\tsmoothness_mean\tcompactness_mean\tconcavity_mean\tconcave points_mean\t...\tradius_worst\ttexture_worst\tperimeter_worst\tarea_worst\tsmoothness_worst\tcompactness_worst\tconcavity_worst\tconcave points_worst\tsymmetry_worst\tfractal_dimension_wors\n",
    "\n",
    "dependent: diagnosis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 2: Find the statistical parameters of the Data that you have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 569 entries, 0 to 568\n",
      "Data columns (total 32 columns):\n",
      "id                         569 non-null int64\n",
      "diagnosis                  569 non-null object\n",
      "radius_mean                569 non-null float64\n",
      "texture_mean               569 non-null float64\n",
      "perimeter_mean             569 non-null float64\n",
      "area_mean                  569 non-null float64\n",
      "smoothness_mean            569 non-null float64\n",
      "compactness_mean           569 non-null float64\n",
      "concavity_mean             569 non-null float64\n",
      "concave points_mean        569 non-null float64\n",
      "symmetry_mean              569 non-null float64\n",
      "fractal_dimension_mean     569 non-null float64\n",
      "radius_se                  569 non-null float64\n",
      "texture_se                 569 non-null float64\n",
      "perimeter_se               569 non-null float64\n",
      "area_se                    569 non-null float64\n",
      "smoothness_se              569 non-null float64\n",
      "compactness_se             569 non-null float64\n",
      "concavity_se               569 non-null float64\n",
      "concave points_se          569 non-null float64\n",
      "symmetry_se                569 non-null float64\n",
      "fractal_dimension_se       569 non-null float64\n",
      "radius_worst               569 non-null float64\n",
      "texture_worst              569 non-null float64\n",
      "perimeter_worst            569 non-null float64\n",
      "area_worst                 569 non-null float64\n",
      "smoothness_worst           569 non-null float64\n",
      "compactness_worst          569 non-null float64\n",
      "concavity_worst            569 non-null float64\n",
      "concave points_worst       569 non-null float64\n",
      "symmetry_worst             569 non-null float64\n",
      "fractal_dimension_worst    569 non-null float64\n",
      "dtypes: float64(30), int64(1), object(1)\n",
      "memory usage: 142.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 3: Find the shape of the Dataset in hand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(569, 32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 4: Find missing values from the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                         0\n",
       "diagnosis                  0\n",
       "radius_mean                0\n",
       "texture_mean               0\n",
       "perimeter_mean             0\n",
       "area_mean                  0\n",
       "smoothness_mean            0\n",
       "compactness_mean           0\n",
       "concavity_mean             0\n",
       "concave points_mean        0\n",
       "symmetry_mean              0\n",
       "fractal_dimension_mean     0\n",
       "radius_se                  0\n",
       "texture_se                 0\n",
       "perimeter_se               0\n",
       "area_se                    0\n",
       "smoothness_se              0\n",
       "compactness_se             0\n",
       "concavity_se               0\n",
       "concave points_se          0\n",
       "symmetry_se                0\n",
       "fractal_dimension_se       0\n",
       "radius_worst               0\n",
       "texture_worst              0\n",
       "perimeter_worst            0\n",
       "area_worst                 0\n",
       "smoothness_worst           0\n",
       "compactness_worst          0\n",
       "concavity_worst            0\n",
       "concave points_worst       0\n",
       "symmetry_worst             0\n",
       "fractal_dimension_worst    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check for any duplicate values\n",
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 5: Find the value count of B(Benign) and M(Malignant) cancer cells in the column \"diagnosis\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B    357\n",
       "M    212\n",
       "Name: diagnosis, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"diagnosis\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before proceeding to step 6, we will learn an important concept which is called label encoding. While navigating through the data, you would have seen that the classification has been done in form of words B and M for benign and malignant cancer cells. But we need this to be converted in number so that this parameter can also be used statistically. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "labelencoder_Y=LabelEncoder()\n",
    "df.iloc[:,1]=labelencoder_Y.fit_transform(df.iloc[:,1].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the above code, we have applied label encoding on all the rows and one column. This is the syntax, there is nothing much to understand here, so just write this code in your notebook and remeber that whenever you will be needing to convert textual feature in form of numbers, you will be needing this coding and this process is called label encoding. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 6: Creating a pairplot and mention the findings\n",
    "Before proceeding to creating a pairplot of all the columns, know that the number of columns in the dataset is huge and if we attempt to create a pairplot, either our hardware will not support it or it will crash if it supports. Even if our hardware is able to do so, the pairplot would be so large that it will be virtually impossible to make a sense of the data. Therefore, we will only create a pairplot of first 5 columns and write the findings. \n",
    "\n",
    "We can do better analysis with the help of correlation matrix. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 7: Create a correlation matrix and mention strongly, weakly and negatively correlated quantities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "      <th>radius_mean</th>\n",
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       "      <td>0.044158</td>\n",
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       "      <td>0.107187</td>\n",
       "      <td>0.010338</td>\n",
       "      <td>-0.002968</td>\n",
       "      <td>0.023203</td>\n",
       "      <td>0.035174</td>\n",
       "      <td>-0.044224</td>\n",
       "      <td>-0.029866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>radius_mean</td>\n",
       "      <td>0.074626</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.323782</td>\n",
       "      <td>0.997855</td>\n",
       "      <td>0.987357</td>\n",
       "      <td>0.170581</td>\n",
       "      <td>0.506124</td>\n",
       "      <td>0.676764</td>\n",
       "      <td>0.822529</td>\n",
       "      <td>0.147741</td>\n",
       "      <td>...</td>\n",
       "      <td>0.969539</td>\n",
       "      <td>0.297008</td>\n",
       "      <td>0.965137</td>\n",
       "      <td>0.941082</td>\n",
       "      <td>0.119616</td>\n",
       "      <td>0.413463</td>\n",
       "      <td>0.526911</td>\n",
       "      <td>0.744214</td>\n",
       "      <td>0.163953</td>\n",
       "      <td>0.007066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>texture_mean</td>\n",
       "      <td>0.099770</td>\n",
       "      <td>0.323782</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.329533</td>\n",
       "      <td>0.321086</td>\n",
       "      <td>-0.023389</td>\n",
       "      <td>0.236702</td>\n",
       "      <td>0.302418</td>\n",
       "      <td>0.293464</td>\n",
       "      <td>0.071401</td>\n",
       "      <td>...</td>\n",
       "      <td>0.352573</td>\n",
       "      <td>0.912045</td>\n",
       "      <td>0.358040</td>\n",
       "      <td>0.343546</td>\n",
       "      <td>0.077503</td>\n",
       "      <td>0.277830</td>\n",
       "      <td>0.301025</td>\n",
       "      <td>0.295316</td>\n",
       "      <td>0.105008</td>\n",
       "      <td>0.119205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>perimeter_mean</td>\n",
       "      <td>0.073159</td>\n",
       "      <td>0.997855</td>\n",
       "      <td>0.329533</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.986507</td>\n",
       "      <td>0.207278</td>\n",
       "      <td>0.556936</td>\n",
       "      <td>0.716136</td>\n",
       "      <td>0.850977</td>\n",
       "      <td>0.183027</td>\n",
       "      <td>...</td>\n",
       "      <td>0.969476</td>\n",
       "      <td>0.303038</td>\n",
       "      <td>0.970387</td>\n",
       "      <td>0.941550</td>\n",
       "      <td>0.150549</td>\n",
       "      <td>0.455774</td>\n",
       "      <td>0.563879</td>\n",
       "      <td>0.771241</td>\n",
       "      <td>0.189115</td>\n",
       "      <td>0.051019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>area_mean</td>\n",
       "      <td>0.096893</td>\n",
       "      <td>0.987357</td>\n",
       "      <td>0.321086</td>\n",
       "      <td>0.986507</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.177028</td>\n",
       "      <td>0.498502</td>\n",
       "      <td>0.685983</td>\n",
       "      <td>0.823269</td>\n",
       "      <td>0.151293</td>\n",
       "      <td>...</td>\n",
       "      <td>0.962746</td>\n",
       "      <td>0.287489</td>\n",
       "      <td>0.959120</td>\n",
       "      <td>0.959213</td>\n",
       "      <td>0.123523</td>\n",
       "      <td>0.390410</td>\n",
       "      <td>0.512606</td>\n",
       "      <td>0.722017</td>\n",
       "      <td>0.143570</td>\n",
       "      <td>0.003738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>smoothness_mean</td>\n",
       "      <td>-0.012968</td>\n",
       "      <td>0.170581</td>\n",
       "      <td>-0.023389</td>\n",
       "      <td>0.207278</td>\n",
       "      <td>0.177028</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.659123</td>\n",
       "      <td>0.521984</td>\n",
       "      <td>0.553695</td>\n",
       "      <td>0.557775</td>\n",
       "      <td>...</td>\n",
       "      <td>0.213120</td>\n",
       "      <td>0.036072</td>\n",
       "      <td>0.238853</td>\n",
       "      <td>0.206718</td>\n",
       "      <td>0.805324</td>\n",
       "      <td>0.472468</td>\n",
       "      <td>0.434926</td>\n",
       "      <td>0.503053</td>\n",
       "      <td>0.394309</td>\n",
       "      <td>0.499316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>compactness_mean</td>\n",
       "      <td>0.000096</td>\n",
       "      <td>0.506124</td>\n",
       "      <td>0.236702</td>\n",
       "      <td>0.556936</td>\n",
       "      <td>0.498502</td>\n",
       "      <td>0.659123</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.883121</td>\n",
       "      <td>0.831135</td>\n",
       "      <td>0.602641</td>\n",
       "      <td>...</td>\n",
       "      <td>0.535315</td>\n",
       "      <td>0.248133</td>\n",
       "      <td>0.590210</td>\n",
       "      <td>0.509604</td>\n",
       "      <td>0.565541</td>\n",
       "      <td>0.865809</td>\n",
       "      <td>0.816275</td>\n",
       "      <td>0.815573</td>\n",
       "      <td>0.510223</td>\n",
       "      <td>0.687382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concavity_mean</td>\n",
       "      <td>0.050080</td>\n",
       "      <td>0.676764</td>\n",
       "      <td>0.302418</td>\n",
       "      <td>0.716136</td>\n",
       "      <td>0.685983</td>\n",
       "      <td>0.521984</td>\n",
       "      <td>0.883121</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.921391</td>\n",
       "      <td>0.500667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.688236</td>\n",
       "      <td>0.299879</td>\n",
       "      <td>0.729565</td>\n",
       "      <td>0.675987</td>\n",
       "      <td>0.448822</td>\n",
       "      <td>0.754968</td>\n",
       "      <td>0.884103</td>\n",
       "      <td>0.861323</td>\n",
       "      <td>0.409464</td>\n",
       "      <td>0.514930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concave points_mean</td>\n",
       "      <td>0.044158</td>\n",
       "      <td>0.822529</td>\n",
       "      <td>0.293464</td>\n",
       "      <td>0.850977</td>\n",
       "      <td>0.823269</td>\n",
       "      <td>0.553695</td>\n",
       "      <td>0.831135</td>\n",
       "      <td>0.921391</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.462497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.830318</td>\n",
       "      <td>0.292752</td>\n",
       "      <td>0.855923</td>\n",
       "      <td>0.809630</td>\n",
       "      <td>0.452753</td>\n",
       "      <td>0.667454</td>\n",
       "      <td>0.752399</td>\n",
       "      <td>0.910155</td>\n",
       "      <td>0.375744</td>\n",
       "      <td>0.368661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>symmetry_mean</td>\n",
       "      <td>-0.022114</td>\n",
       "      <td>0.147741</td>\n",
       "      <td>0.071401</td>\n",
       "      <td>0.183027</td>\n",
       "      <td>0.151293</td>\n",
       "      <td>0.557775</td>\n",
       "      <td>0.602641</td>\n",
       "      <td>0.500667</td>\n",
       "      <td>0.462497</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.185728</td>\n",
       "      <td>0.090651</td>\n",
       "      <td>0.219169</td>\n",
       "      <td>0.177193</td>\n",
       "      <td>0.426675</td>\n",
       "      <td>0.473200</td>\n",
       "      <td>0.433721</td>\n",
       "      <td>0.430297</td>\n",
       "      <td>0.699826</td>\n",
       "      <td>0.438413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fractal_dimension_mean</td>\n",
       "      <td>-0.052511</td>\n",
       "      <td>-0.311631</td>\n",
       "      <td>-0.076437</td>\n",
       "      <td>-0.261477</td>\n",
       "      <td>-0.283110</td>\n",
       "      <td>0.584792</td>\n",
       "      <td>0.565369</td>\n",
       "      <td>0.336783</td>\n",
       "      <td>0.166917</td>\n",
       "      <td>0.479921</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.253691</td>\n",
       "      <td>-0.051269</td>\n",
       "      <td>-0.205151</td>\n",
       "      <td>-0.231854</td>\n",
       "      <td>0.504942</td>\n",
       "      <td>0.458798</td>\n",
       "      <td>0.346234</td>\n",
       "      <td>0.175325</td>\n",
       "      <td>0.334019</td>\n",
       "      <td>0.767297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>radius_se</td>\n",
       "      <td>0.143048</td>\n",
       "      <td>0.679090</td>\n",
       "      <td>0.275869</td>\n",
       "      <td>0.691765</td>\n",
       "      <td>0.732562</td>\n",
       "      <td>0.301467</td>\n",
       "      <td>0.497473</td>\n",
       "      <td>0.631925</td>\n",
       "      <td>0.698050</td>\n",
       "      <td>0.303379</td>\n",
       "      <td>...</td>\n",
       "      <td>0.715065</td>\n",
       "      <td>0.194799</td>\n",
       "      <td>0.719684</td>\n",
       "      <td>0.751548</td>\n",
       "      <td>0.141919</td>\n",
       "      <td>0.287103</td>\n",
       "      <td>0.380585</td>\n",
       "      <td>0.531062</td>\n",
       "      <td>0.094543</td>\n",
       "      <td>0.049559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>texture_se</td>\n",
       "      <td>-0.007526</td>\n",
       "      <td>-0.097317</td>\n",
       "      <td>0.386358</td>\n",
       "      <td>-0.086761</td>\n",
       "      <td>-0.066280</td>\n",
       "      <td>0.068406</td>\n",
       "      <td>0.046205</td>\n",
       "      <td>0.076218</td>\n",
       "      <td>0.021480</td>\n",
       "      <td>0.128053</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.111690</td>\n",
       "      <td>0.409003</td>\n",
       "      <td>-0.102242</td>\n",
       "      <td>-0.083195</td>\n",
       "      <td>-0.073658</td>\n",
       "      <td>-0.092439</td>\n",
       "      <td>-0.068956</td>\n",
       "      <td>-0.119638</td>\n",
       "      <td>-0.128215</td>\n",
       "      <td>-0.045655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>perimeter_se</td>\n",
       "      <td>0.137331</td>\n",
       "      <td>0.674172</td>\n",
       "      <td>0.281673</td>\n",
       "      <td>0.693135</td>\n",
       "      <td>0.726628</td>\n",
       "      <td>0.296092</td>\n",
       "      <td>0.548905</td>\n",
       "      <td>0.660391</td>\n",
       "      <td>0.710650</td>\n",
       "      <td>0.313893</td>\n",
       "      <td>...</td>\n",
       "      <td>0.697201</td>\n",
       "      <td>0.200371</td>\n",
       "      <td>0.721031</td>\n",
       "      <td>0.730713</td>\n",
       "      <td>0.130054</td>\n",
       "      <td>0.341919</td>\n",
       "      <td>0.418899</td>\n",
       "      <td>0.554897</td>\n",
       "      <td>0.109930</td>\n",
       "      <td>0.085433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>area_se</td>\n",
       "      <td>0.177742</td>\n",
       "      <td>0.735864</td>\n",
       "      <td>0.259845</td>\n",
       "      <td>0.744983</td>\n",
       "      <td>0.800086</td>\n",
       "      <td>0.246552</td>\n",
       "      <td>0.455653</td>\n",
       "      <td>0.617427</td>\n",
       "      <td>0.690299</td>\n",
       "      <td>0.223970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.757373</td>\n",
       "      <td>0.196497</td>\n",
       "      <td>0.761213</td>\n",
       "      <td>0.811408</td>\n",
       "      <td>0.125389</td>\n",
       "      <td>0.283257</td>\n",
       "      <td>0.385100</td>\n",
       "      <td>0.538166</td>\n",
       "      <td>0.074126</td>\n",
       "      <td>0.017539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>smoothness_se</td>\n",
       "      <td>0.096781</td>\n",
       "      <td>-0.222600</td>\n",
       "      <td>0.006614</td>\n",
       "      <td>-0.202694</td>\n",
       "      <td>-0.166777</td>\n",
       "      <td>0.332375</td>\n",
       "      <td>0.135299</td>\n",
       "      <td>0.098564</td>\n",
       "      <td>0.027653</td>\n",
       "      <td>0.187321</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.230691</td>\n",
       "      <td>-0.074743</td>\n",
       "      <td>-0.217304</td>\n",
       "      <td>-0.182195</td>\n",
       "      <td>0.314457</td>\n",
       "      <td>-0.055558</td>\n",
       "      <td>-0.058298</td>\n",
       "      <td>-0.102007</td>\n",
       "      <td>-0.107342</td>\n",
       "      <td>0.101480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>compactness_se</td>\n",
       "      <td>0.033961</td>\n",
       "      <td>0.206000</td>\n",
       "      <td>0.191975</td>\n",
       "      <td>0.250744</td>\n",
       "      <td>0.212583</td>\n",
       "      <td>0.318943</td>\n",
       "      <td>0.738722</td>\n",
       "      <td>0.670279</td>\n",
       "      <td>0.490424</td>\n",
       "      <td>0.421659</td>\n",
       "      <td>...</td>\n",
       "      <td>0.204607</td>\n",
       "      <td>0.143003</td>\n",
       "      <td>0.260516</td>\n",
       "      <td>0.199371</td>\n",
       "      <td>0.227394</td>\n",
       "      <td>0.678780</td>\n",
       "      <td>0.639147</td>\n",
       "      <td>0.483208</td>\n",
       "      <td>0.277878</td>\n",
       "      <td>0.590973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concavity_se</td>\n",
       "      <td>0.055239</td>\n",
       "      <td>0.194204</td>\n",
       "      <td>0.143293</td>\n",
       "      <td>0.228082</td>\n",
       "      <td>0.207660</td>\n",
       "      <td>0.248396</td>\n",
       "      <td>0.570517</td>\n",
       "      <td>0.691270</td>\n",
       "      <td>0.439167</td>\n",
       "      <td>0.342627</td>\n",
       "      <td>...</td>\n",
       "      <td>0.186904</td>\n",
       "      <td>0.100241</td>\n",
       "      <td>0.226680</td>\n",
       "      <td>0.188353</td>\n",
       "      <td>0.168481</td>\n",
       "      <td>0.484858</td>\n",
       "      <td>0.662564</td>\n",
       "      <td>0.440472</td>\n",
       "      <td>0.197788</td>\n",
       "      <td>0.439329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concave points_se</td>\n",
       "      <td>0.078768</td>\n",
       "      <td>0.376169</td>\n",
       "      <td>0.163851</td>\n",
       "      <td>0.407217</td>\n",
       "      <td>0.372320</td>\n",
       "      <td>0.380676</td>\n",
       "      <td>0.642262</td>\n",
       "      <td>0.683260</td>\n",
       "      <td>0.615634</td>\n",
       "      <td>0.393298</td>\n",
       "      <td>...</td>\n",
       "      <td>0.358127</td>\n",
       "      <td>0.086741</td>\n",
       "      <td>0.394999</td>\n",
       "      <td>0.342271</td>\n",
       "      <td>0.215351</td>\n",
       "      <td>0.452888</td>\n",
       "      <td>0.549592</td>\n",
       "      <td>0.602450</td>\n",
       "      <td>0.143116</td>\n",
       "      <td>0.310655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>symmetry_se</td>\n",
       "      <td>-0.017306</td>\n",
       "      <td>-0.104321</td>\n",
       "      <td>0.009127</td>\n",
       "      <td>-0.081629</td>\n",
       "      <td>-0.072497</td>\n",
       "      <td>0.200774</td>\n",
       "      <td>0.229977</td>\n",
       "      <td>0.178009</td>\n",
       "      <td>0.095351</td>\n",
       "      <td>0.449137</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.128121</td>\n",
       "      <td>-0.077473</td>\n",
       "      <td>-0.103753</td>\n",
       "      <td>-0.110343</td>\n",
       "      <td>-0.012662</td>\n",
       "      <td>0.060255</td>\n",
       "      <td>0.037119</td>\n",
       "      <td>-0.030413</td>\n",
       "      <td>0.389402</td>\n",
       "      <td>0.078079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fractal_dimension_se</td>\n",
       "      <td>0.025725</td>\n",
       "      <td>-0.042641</td>\n",
       "      <td>0.054458</td>\n",
       "      <td>-0.005523</td>\n",
       "      <td>-0.019887</td>\n",
       "      <td>0.283607</td>\n",
       "      <td>0.507318</td>\n",
       "      <td>0.449301</td>\n",
       "      <td>0.257584</td>\n",
       "      <td>0.331786</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.037488</td>\n",
       "      <td>-0.003195</td>\n",
       "      <td>-0.001000</td>\n",
       "      <td>-0.022736</td>\n",
       "      <td>0.170568</td>\n",
       "      <td>0.390159</td>\n",
       "      <td>0.379975</td>\n",
       "      <td>0.215204</td>\n",
       "      <td>0.111094</td>\n",
       "      <td>0.591328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>radius_worst</td>\n",
       "      <td>0.082405</td>\n",
       "      <td>0.969539</td>\n",
       "      <td>0.352573</td>\n",
       "      <td>0.969476</td>\n",
       "      <td>0.962746</td>\n",
       "      <td>0.213120</td>\n",
       "      <td>0.535315</td>\n",
       "      <td>0.688236</td>\n",
       "      <td>0.830318</td>\n",
       "      <td>0.185728</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.359921</td>\n",
       "      <td>0.993708</td>\n",
       "      <td>0.984015</td>\n",
       "      <td>0.216574</td>\n",
       "      <td>0.475820</td>\n",
       "      <td>0.573975</td>\n",
       "      <td>0.787424</td>\n",
       "      <td>0.243529</td>\n",
       "      <td>0.093492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>texture_worst</td>\n",
       "      <td>0.064720</td>\n",
       "      <td>0.297008</td>\n",
       "      <td>0.912045</td>\n",
       "      <td>0.303038</td>\n",
       "      <td>0.287489</td>\n",
       "      <td>0.036072</td>\n",
       "      <td>0.248133</td>\n",
       "      <td>0.299879</td>\n",
       "      <td>0.292752</td>\n",
       "      <td>0.090651</td>\n",
       "      <td>...</td>\n",
       "      <td>0.359921</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.365098</td>\n",
       "      <td>0.345842</td>\n",
       "      <td>0.225429</td>\n",
       "      <td>0.360832</td>\n",
       "      <td>0.368366</td>\n",
       "      <td>0.359755</td>\n",
       "      <td>0.233027</td>\n",
       "      <td>0.219122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>perimeter_worst</td>\n",
       "      <td>0.079986</td>\n",
       "      <td>0.965137</td>\n",
       "      <td>0.358040</td>\n",
       "      <td>0.970387</td>\n",
       "      <td>0.959120</td>\n",
       "      <td>0.238853</td>\n",
       "      <td>0.590210</td>\n",
       "      <td>0.729565</td>\n",
       "      <td>0.855923</td>\n",
       "      <td>0.219169</td>\n",
       "      <td>...</td>\n",
       "      <td>0.993708</td>\n",
       "      <td>0.365098</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.977578</td>\n",
       "      <td>0.236775</td>\n",
       "      <td>0.529408</td>\n",
       "      <td>0.618344</td>\n",
       "      <td>0.816322</td>\n",
       "      <td>0.269493</td>\n",
       "      <td>0.138957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>area_worst</td>\n",
       "      <td>0.107187</td>\n",
       "      <td>0.941082</td>\n",
       "      <td>0.343546</td>\n",
       "      <td>0.941550</td>\n",
       "      <td>0.959213</td>\n",
       "      <td>0.206718</td>\n",
       "      <td>0.509604</td>\n",
       "      <td>0.675987</td>\n",
       "      <td>0.809630</td>\n",
       "      <td>0.177193</td>\n",
       "      <td>...</td>\n",
       "      <td>0.984015</td>\n",
       "      <td>0.345842</td>\n",
       "      <td>0.977578</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.209145</td>\n",
       "      <td>0.438296</td>\n",
       "      <td>0.543331</td>\n",
       "      <td>0.747419</td>\n",
       "      <td>0.209146</td>\n",
       "      <td>0.079647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>smoothness_worst</td>\n",
       "      <td>0.010338</td>\n",
       "      <td>0.119616</td>\n",
       "      <td>0.077503</td>\n",
       "      <td>0.150549</td>\n",
       "      <td>0.123523</td>\n",
       "      <td>0.805324</td>\n",
       "      <td>0.565541</td>\n",
       "      <td>0.448822</td>\n",
       "      <td>0.452753</td>\n",
       "      <td>0.426675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.216574</td>\n",
       "      <td>0.225429</td>\n",
       "      <td>0.236775</td>\n",
       "      <td>0.209145</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.568187</td>\n",
       "      <td>0.518523</td>\n",
       "      <td>0.547691</td>\n",
       "      <td>0.493838</td>\n",
       "      <td>0.617624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>compactness_worst</td>\n",
       "      <td>-0.002968</td>\n",
       "      <td>0.413463</td>\n",
       "      <td>0.277830</td>\n",
       "      <td>0.455774</td>\n",
       "      <td>0.390410</td>\n",
       "      <td>0.472468</td>\n",
       "      <td>0.865809</td>\n",
       "      <td>0.754968</td>\n",
       "      <td>0.667454</td>\n",
       "      <td>0.473200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.475820</td>\n",
       "      <td>0.360832</td>\n",
       "      <td>0.529408</td>\n",
       "      <td>0.438296</td>\n",
       "      <td>0.568187</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.892261</td>\n",
       "      <td>0.801080</td>\n",
       "      <td>0.614441</td>\n",
       "      <td>0.810455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concavity_worst</td>\n",
       "      <td>0.023203</td>\n",
       "      <td>0.526911</td>\n",
       "      <td>0.301025</td>\n",
       "      <td>0.563879</td>\n",
       "      <td>0.512606</td>\n",
       "      <td>0.434926</td>\n",
       "      <td>0.816275</td>\n",
       "      <td>0.884103</td>\n",
       "      <td>0.752399</td>\n",
       "      <td>0.433721</td>\n",
       "      <td>...</td>\n",
       "      <td>0.573975</td>\n",
       "      <td>0.368366</td>\n",
       "      <td>0.618344</td>\n",
       "      <td>0.543331</td>\n",
       "      <td>0.518523</td>\n",
       "      <td>0.892261</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.855434</td>\n",
       "      <td>0.532520</td>\n",
       "      <td>0.686511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>concave points_worst</td>\n",
       "      <td>0.035174</td>\n",
       "      <td>0.744214</td>\n",
       "      <td>0.295316</td>\n",
       "      <td>0.771241</td>\n",
       "      <td>0.722017</td>\n",
       "      <td>0.503053</td>\n",
       "      <td>0.815573</td>\n",
       "      <td>0.861323</td>\n",
       "      <td>0.910155</td>\n",
       "      <td>0.430297</td>\n",
       "      <td>...</td>\n",
       "      <td>0.787424</td>\n",
       "      <td>0.359755</td>\n",
       "      <td>0.816322</td>\n",
       "      <td>0.747419</td>\n",
       "      <td>0.547691</td>\n",
       "      <td>0.801080</td>\n",
       "      <td>0.855434</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.502528</td>\n",
       "      <td>0.511114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>symmetry_worst</td>\n",
       "      <td>-0.044224</td>\n",
       "      <td>0.163953</td>\n",
       "      <td>0.105008</td>\n",
       "      <td>0.189115</td>\n",
       "      <td>0.143570</td>\n",
       "      <td>0.394309</td>\n",
       "      <td>0.510223</td>\n",
       "      <td>0.409464</td>\n",
       "      <td>0.375744</td>\n",
       "      <td>0.699826</td>\n",
       "      <td>...</td>\n",
       "      <td>0.243529</td>\n",
       "      <td>0.233027</td>\n",
       "      <td>0.269493</td>\n",
       "      <td>0.209146</td>\n",
       "      <td>0.493838</td>\n",
       "      <td>0.614441</td>\n",
       "      <td>0.532520</td>\n",
       "      <td>0.502528</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.537848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fractal_dimension_worst</td>\n",
       "      <td>-0.029866</td>\n",
       "      <td>0.007066</td>\n",
       "      <td>0.119205</td>\n",
       "      <td>0.051019</td>\n",
       "      <td>0.003738</td>\n",
       "      <td>0.499316</td>\n",
       "      <td>0.687382</td>\n",
       "      <td>0.514930</td>\n",
       "      <td>0.368661</td>\n",
       "      <td>0.438413</td>\n",
       "      <td>...</td>\n",
       "      <td>0.093492</td>\n",
       "      <td>0.219122</td>\n",
       "      <td>0.138957</td>\n",
       "      <td>0.079647</td>\n",
       "      <td>0.617624</td>\n",
       "      <td>0.810455</td>\n",
       "      <td>0.686511</td>\n",
       "      <td>0.511114</td>\n",
       "      <td>0.537848</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               id  radius_mean  texture_mean  perimeter_mean  \\\n",
       "id                       1.000000     0.074626      0.099770        0.073159   \n",
       "radius_mean              0.074626     1.000000      0.323782        0.997855   \n",
       "texture_mean             0.099770     0.323782      1.000000        0.329533   \n",
       "perimeter_mean           0.073159     0.997855      0.329533        1.000000   \n",
       "area_mean                0.096893     0.987357      0.321086        0.986507   \n",
       "smoothness_mean         -0.012968     0.170581     -0.023389        0.207278   \n",
       "compactness_mean         0.000096     0.506124      0.236702        0.556936   \n",
       "concavity_mean           0.050080     0.676764      0.302418        0.716136   \n",
       "concave points_mean      0.044158     0.822529      0.293464        0.850977   \n",
       "symmetry_mean           -0.022114     0.147741      0.071401        0.183027   \n",
       "fractal_dimension_mean  -0.052511    -0.311631     -0.076437       -0.261477   \n",
       "radius_se                0.143048     0.679090      0.275869        0.691765   \n",
       "texture_se              -0.007526    -0.097317      0.386358       -0.086761   \n",
       "perimeter_se             0.137331     0.674172      0.281673        0.693135   \n",
       "area_se                  0.177742     0.735864      0.259845        0.744983   \n",
       "smoothness_se            0.096781    -0.222600      0.006614       -0.202694   \n",
       "compactness_se           0.033961     0.206000      0.191975        0.250744   \n",
       "concavity_se             0.055239     0.194204      0.143293        0.228082   \n",
       "concave points_se        0.078768     0.376169      0.163851        0.407217   \n",
       "symmetry_se             -0.017306    -0.104321      0.009127       -0.081629   \n",
       "fractal_dimension_se     0.025725    -0.042641      0.054458       -0.005523   \n",
       "radius_worst             0.082405     0.969539      0.352573        0.969476   \n",
       "texture_worst            0.064720     0.297008      0.912045        0.303038   \n",
       "perimeter_worst          0.079986     0.965137      0.358040        0.970387   \n",
       "area_worst               0.107187     0.941082      0.343546        0.941550   \n",
       "smoothness_worst         0.010338     0.119616      0.077503        0.150549   \n",
       "compactness_worst       -0.002968     0.413463      0.277830        0.455774   \n",
       "concavity_worst          0.023203     0.526911      0.301025        0.563879   \n",
       "concave points_worst     0.035174     0.744214      0.295316        0.771241   \n",
       "symmetry_worst          -0.044224     0.163953      0.105008        0.189115   \n",
       "fractal_dimension_worst -0.029866     0.007066      0.119205        0.051019   \n",
       "\n",
       "                         area_mean  smoothness_mean  compactness_mean  \\\n",
       "id                        0.096893        -0.012968          0.000096   \n",
       "radius_mean               0.987357         0.170581          0.506124   \n",
       "texture_mean              0.321086        -0.023389          0.236702   \n",
       "perimeter_mean            0.986507         0.207278          0.556936   \n",
       "area_mean                 1.000000         0.177028          0.498502   \n",
       "smoothness_mean           0.177028         1.000000          0.659123   \n",
       "compactness_mean          0.498502         0.659123          1.000000   \n",
       "concavity_mean            0.685983         0.521984          0.883121   \n",
       "concave points_mean       0.823269         0.553695          0.831135   \n",
       "symmetry_mean             0.151293         0.557775          0.602641   \n",
       "fractal_dimension_mean   -0.283110         0.584792          0.565369   \n",
       "radius_se                 0.732562         0.301467          0.497473   \n",
       "texture_se               -0.066280         0.068406          0.046205   \n",
       "perimeter_se              0.726628         0.296092          0.548905   \n",
       "area_se                   0.800086         0.246552          0.455653   \n",
       "smoothness_se            -0.166777         0.332375          0.135299   \n",
       "compactness_se            0.212583         0.318943          0.738722   \n",
       "concavity_se              0.207660         0.248396          0.570517   \n",
       "concave points_se         0.372320         0.380676          0.642262   \n",
       "symmetry_se              -0.072497         0.200774          0.229977   \n",
       "fractal_dimension_se     -0.019887         0.283607          0.507318   \n",
       "radius_worst              0.962746         0.213120          0.535315   \n",
       "texture_worst             0.287489         0.036072          0.248133   \n",
       "perimeter_worst           0.959120         0.238853          0.590210   \n",
       "area_worst                0.959213         0.206718          0.509604   \n",
       "smoothness_worst          0.123523         0.805324          0.565541   \n",
       "compactness_worst         0.390410         0.472468          0.865809   \n",
       "concavity_worst           0.512606         0.434926          0.816275   \n",
       "concave points_worst      0.722017         0.503053          0.815573   \n",
       "symmetry_worst            0.143570         0.394309          0.510223   \n",
       "fractal_dimension_worst   0.003738         0.499316          0.687382   \n",
       "\n",
       "                         concavity_mean  concave points_mean  symmetry_mean  \\\n",
       "id                             0.050080             0.044158      -0.022114   \n",
       "radius_mean                    0.676764             0.822529       0.147741   \n",
       "texture_mean                   0.302418             0.293464       0.071401   \n",
       "perimeter_mean                 0.716136             0.850977       0.183027   \n",
       "area_mean                      0.685983             0.823269       0.151293   \n",
       "smoothness_mean                0.521984             0.553695       0.557775   \n",
       "compactness_mean               0.883121             0.831135       0.602641   \n",
       "concavity_mean                 1.000000             0.921391       0.500667   \n",
       "concave points_mean            0.921391             1.000000       0.462497   \n",
       "symmetry_mean                  0.500667             0.462497       1.000000   \n",
       "fractal_dimension_mean         0.336783             0.166917       0.479921   \n",
       "radius_se                      0.631925             0.698050       0.303379   \n",
       "texture_se                     0.076218             0.021480       0.128053   \n",
       "perimeter_se                   0.660391             0.710650       0.313893   \n",
       "area_se                        0.617427             0.690299       0.223970   \n",
       "smoothness_se                  0.098564             0.027653       0.187321   \n",
       "compactness_se                 0.670279             0.490424       0.421659   \n",
       "concavity_se                   0.691270             0.439167       0.342627   \n",
       "concave points_se              0.683260             0.615634       0.393298   \n",
       "symmetry_se                    0.178009             0.095351       0.449137   \n",
       "fractal_dimension_se           0.449301             0.257584       0.331786   \n",
       "radius_worst                   0.688236             0.830318       0.185728   \n",
       "texture_worst                  0.299879             0.292752       0.090651   \n",
       "perimeter_worst                0.729565             0.855923       0.219169   \n",
       "area_worst                     0.675987             0.809630       0.177193   \n",
       "smoothness_worst               0.448822             0.452753       0.426675   \n",
       "compactness_worst              0.754968             0.667454       0.473200   \n",
       "concavity_worst                0.884103             0.752399       0.433721   \n",
       "concave points_worst           0.861323             0.910155       0.430297   \n",
       "symmetry_worst                 0.409464             0.375744       0.699826   \n",
       "fractal_dimension_worst        0.514930             0.368661       0.438413   \n",
       "\n",
       "                         ...  radius_worst  texture_worst  perimeter_worst  \\\n",
       "id                       ...      0.082405       0.064720         0.079986   \n",
       "radius_mean              ...      0.969539       0.297008         0.965137   \n",
       "texture_mean             ...      0.352573       0.912045         0.358040   \n",
       "perimeter_mean           ...      0.969476       0.303038         0.970387   \n",
       "area_mean                ...      0.962746       0.287489         0.959120   \n",
       "smoothness_mean          ...      0.213120       0.036072         0.238853   \n",
       "compactness_mean         ...      0.535315       0.248133         0.590210   \n",
       "concavity_mean           ...      0.688236       0.299879         0.729565   \n",
       "concave points_mean      ...      0.830318       0.292752         0.855923   \n",
       "symmetry_mean            ...      0.185728       0.090651         0.219169   \n",
       "fractal_dimension_mean   ...     -0.253691      -0.051269        -0.205151   \n",
       "radius_se                ...      0.715065       0.194799         0.719684   \n",
       "texture_se               ...     -0.111690       0.409003        -0.102242   \n",
       "perimeter_se             ...      0.697201       0.200371         0.721031   \n",
       "area_se                  ...      0.757373       0.196497         0.761213   \n",
       "smoothness_se            ...     -0.230691      -0.074743        -0.217304   \n",
       "compactness_se           ...      0.204607       0.143003         0.260516   \n",
       "concavity_se             ...      0.186904       0.100241         0.226680   \n",
       "concave points_se        ...      0.358127       0.086741         0.394999   \n",
       "symmetry_se              ...     -0.128121      -0.077473        -0.103753   \n",
       "fractal_dimension_se     ...     -0.037488      -0.003195        -0.001000   \n",
       "radius_worst             ...      1.000000       0.359921         0.993708   \n",
       "texture_worst            ...      0.359921       1.000000         0.365098   \n",
       "perimeter_worst          ...      0.993708       0.365098         1.000000   \n",
       "area_worst               ...      0.984015       0.345842         0.977578   \n",
       "smoothness_worst         ...      0.216574       0.225429         0.236775   \n",
       "compactness_worst        ...      0.475820       0.360832         0.529408   \n",
       "concavity_worst          ...      0.573975       0.368366         0.618344   \n",
       "concave points_worst     ...      0.787424       0.359755         0.816322   \n",
       "symmetry_worst           ...      0.243529       0.233027         0.269493   \n",
       "fractal_dimension_worst  ...      0.093492       0.219122         0.138957   \n",
       "\n",
       "                         area_worst  smoothness_worst  compactness_worst  \\\n",
       "id                         0.107187          0.010338          -0.002968   \n",
       "radius_mean                0.941082          0.119616           0.413463   \n",
       "texture_mean               0.343546          0.077503           0.277830   \n",
       "perimeter_mean             0.941550          0.150549           0.455774   \n",
       "area_mean                  0.959213          0.123523           0.390410   \n",
       "smoothness_mean            0.206718          0.805324           0.472468   \n",
       "compactness_mean           0.509604          0.565541           0.865809   \n",
       "concavity_mean             0.675987          0.448822           0.754968   \n",
       "concave points_mean        0.809630          0.452753           0.667454   \n",
       "symmetry_mean              0.177193          0.426675           0.473200   \n",
       "fractal_dimension_mean    -0.231854          0.504942           0.458798   \n",
       "radius_se                  0.751548          0.141919           0.287103   \n",
       "texture_se                -0.083195         -0.073658          -0.092439   \n",
       "perimeter_se               0.730713          0.130054           0.341919   \n",
       "area_se                    0.811408          0.125389           0.283257   \n",
       "smoothness_se             -0.182195          0.314457          -0.055558   \n",
       "compactness_se             0.199371          0.227394           0.678780   \n",
       "concavity_se               0.188353          0.168481           0.484858   \n",
       "concave points_se          0.342271          0.215351           0.452888   \n",
       "symmetry_se               -0.110343         -0.012662           0.060255   \n",
       "fractal_dimension_se      -0.022736          0.170568           0.390159   \n",
       "radius_worst               0.984015          0.216574           0.475820   \n",
       "texture_worst              0.345842          0.225429           0.360832   \n",
       "perimeter_worst            0.977578          0.236775           0.529408   \n",
       "area_worst                 1.000000          0.209145           0.438296   \n",
       "smoothness_worst           0.209145          1.000000           0.568187   \n",
       "compactness_worst          0.438296          0.568187           1.000000   \n",
       "concavity_worst            0.543331          0.518523           0.892261   \n",
       "concave points_worst       0.747419          0.547691           0.801080   \n",
       "symmetry_worst             0.209146          0.493838           0.614441   \n",
       "fractal_dimension_worst    0.079647          0.617624           0.810455   \n",
       "\n",
       "                         concavity_worst  concave points_worst  \\\n",
       "id                              0.023203              0.035174   \n",
       "radius_mean                     0.526911              0.744214   \n",
       "texture_mean                    0.301025              0.295316   \n",
       "perimeter_mean                  0.563879              0.771241   \n",
       "area_mean                       0.512606              0.722017   \n",
       "smoothness_mean                 0.434926              0.503053   \n",
       "compactness_mean                0.816275              0.815573   \n",
       "concavity_mean                  0.884103              0.861323   \n",
       "concave points_mean             0.752399              0.910155   \n",
       "symmetry_mean                   0.433721              0.430297   \n",
       "fractal_dimension_mean          0.346234              0.175325   \n",
       "radius_se                       0.380585              0.531062   \n",
       "texture_se                     -0.068956             -0.119638   \n",
       "perimeter_se                    0.418899              0.554897   \n",
       "area_se                         0.385100              0.538166   \n",
       "smoothness_se                  -0.058298             -0.102007   \n",
       "compactness_se                  0.639147              0.483208   \n",
       "concavity_se                    0.662564              0.440472   \n",
       "concave points_se               0.549592              0.602450   \n",
       "symmetry_se                     0.037119             -0.030413   \n",
       "fractal_dimension_se            0.379975              0.215204   \n",
       "radius_worst                    0.573975              0.787424   \n",
       "texture_worst                   0.368366              0.359755   \n",
       "perimeter_worst                 0.618344              0.816322   \n",
       "area_worst                      0.543331              0.747419   \n",
       "smoothness_worst                0.518523              0.547691   \n",
       "compactness_worst               0.892261              0.801080   \n",
       "concavity_worst                 1.000000              0.855434   \n",
       "concave points_worst            0.855434              1.000000   \n",
       "symmetry_worst                  0.532520              0.502528   \n",
       "fractal_dimension_worst         0.686511              0.511114   \n",
       "\n",
       "                         symmetry_worst  fractal_dimension_worst  \n",
       "id                            -0.044224                -0.029866  \n",
       "radius_mean                    0.163953                 0.007066  \n",
       "texture_mean                   0.105008                 0.119205  \n",
       "perimeter_mean                 0.189115                 0.051019  \n",
       "area_mean                      0.143570                 0.003738  \n",
       "smoothness_mean                0.394309                 0.499316  \n",
       "compactness_mean               0.510223                 0.687382  \n",
       "concavity_mean                 0.409464                 0.514930  \n",
       "concave points_mean            0.375744                 0.368661  \n",
       "symmetry_mean                  0.699826                 0.438413  \n",
       "fractal_dimension_mean         0.334019                 0.767297  \n",
       "radius_se                      0.094543                 0.049559  \n",
       "texture_se                    -0.128215                -0.045655  \n",
       "perimeter_se                   0.109930                 0.085433  \n",
       "area_se                        0.074126                 0.017539  \n",
       "smoothness_se                 -0.107342                 0.101480  \n",
       "compactness_se                 0.277878                 0.590973  \n",
       "concavity_se                   0.197788                 0.439329  \n",
       "concave points_se              0.143116                 0.310655  \n",
       "symmetry_se                    0.389402                 0.078079  \n",
       "fractal_dimension_se           0.111094                 0.591328  \n",
       "radius_worst                   0.243529                 0.093492  \n",
       "texture_worst                  0.233027                 0.219122  \n",
       "perimeter_worst                0.269493                 0.138957  \n",
       "area_worst                     0.209146                 0.079647  \n",
       "smoothness_worst               0.493838                 0.617624  \n",
       "compactness_worst              0.614441                 0.810455  \n",
       "concavity_worst                0.532520                 0.686511  \n",
       "concave points_worst           0.502528                 0.511114  \n",
       "symmetry_worst                 1.000000                 0.537848  \n",
       "fractal_dimension_worst        0.537848                 1.000000  \n",
       "\n",
       "[31 rows x 31 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr(method=\"pearson\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We tend to drop features having very strong correlation. Why? Think and try to write the answer. I will write this question's answer in week 3 module. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (Optional) Step 8: Create a heatmap of the correlated features (helps in visualization) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c7527bcb08>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.heatmap(df.corr(), annot=True,fmt=\"0.0%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That is all for week 2! We will learn about various algorithms in week 3 and implement them. See you next week!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the best!"
   ]
  }
 ],
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