Assignment 1.ipynb

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    "---\n",
    "\n",
    "_You are currently looking at **version 1.3** of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the [Jupyter Notebook FAQ](https://www.coursera.org/learn/python-machine-learning/resources/bANLa) course resource._\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Assignment 1 - Introduction to Machine Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this assignment, you will be using the Breast Cancer Wisconsin (Diagnostic) Database to create a classifier that can help diagnose patients. First, read through the description of the dataset (below)."
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.datasets import load_breast_cancer\n",
    "\n",
    "cancer = load_breast_cancer()\n",
    "\n",
    "#print(cancer.DESCR) # Print the data set description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The object returned by `load_breast_cancer()` is a scikit-learn Bunch object, which is similar to a dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data', 'target', 'target_names', 'DESCR', 'feature_names'])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancer.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 0 (Example)\n",
    "\n",
    "How many features does the breast cancer dataset have?\n",
    "\n",
    "*This function should return an integer.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
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    {
     "data": {
      "text/plain": [
       "30"
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   "source": [
    "# You should write your whole answer within the function provided. The autograder will call\n",
    "# this function and compare the return value against the correct solution value\n",
    "def answer_zero():\n",
    "    # This function returns the number of features of the breast cancer dataset, which is an integer. \n",
    "    # The assignment question description will tell you the general format the autograder is expecting\n",
    "    return len(cancer['feature_names'])\n",
    "\n",
    "# You can examine what your function returns by calling it in the cell. If you have questions\n",
    "# about the assignment formats, check out the discussion forums for any FAQs\n",
    "answer_zero() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 1\n",
    "\n",
    "Scikit-learn works with lists, numpy arrays, scipy-sparse matrices, and pandas DataFrames, so converting the dataset to a DataFrame is not necessary for training this model. Using a DataFrame does however help make many things easier such as munging data, so let's practice creating a classifier with a pandas DataFrame. \n",
    "\n",
    "\n",
    "\n",
    "Convert the sklearn.dataset `cancer` to a DataFrame. \n",
    "\n",
    "*This function should return a `(569, 31)` DataFrame with * \n",
    "\n",
    "*columns = *\n",
    "\n",
    "    ['mean radius', 'mean texture', 'mean perimeter', 'mean area',\n",
    "    'mean smoothness', 'mean compactness', 'mean concavity',\n",
    "    'mean concave points', 'mean symmetry', 'mean fractal dimension',\n",
    "    'radius error', 'texture error', 'perimeter error', 'area error',\n",
    "    'smoothness error', 'compactness error', 'concavity error',\n",
    "    'concave points error', 'symmetry error', 'fractal dimension error',\n",
    "    'worst radius', 'worst texture', 'worst perimeter', 'worst area',\n",
    "    'worst smoothness', 'worst compactness', 'worst concavity',\n",
    "    'worst concave points', 'worst symmetry', 'worst fractal dimension',\n",
    "    'target']\n",
    "\n",
    "*and index = *\n",
    "\n",
    "    RangeIndex(start=0, stop=569, step=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
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     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>...</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.990</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>0.300100</td>\n",
       "      <td>0.147100</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>...</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.16220</td>\n",
       "      <td>0.66560</td>\n",
       "      <td>0.71190</td>\n",
       "      <td>0.26540</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.570</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>0.086900</td>\n",
       "      <td>0.070170</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>...</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.12380</td>\n",
       "      <td>0.18660</td>\n",
       "      <td>0.24160</td>\n",
       "      <td>0.18600</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.690</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>0.197400</td>\n",
       "      <td>0.127900</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>...</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.14440</td>\n",
       "      <td>0.42450</td>\n",
       "      <td>0.45040</td>\n",
       "      <td>0.24300</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.420</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>0.241400</td>\n",
       "      <td>0.105200</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>...</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.20980</td>\n",
       "      <td>0.86630</td>\n",
       "      <td>0.68690</td>\n",
       "      <td>0.25750</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.290</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>0.198000</td>\n",
       "      <td>0.104300</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>...</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.13740</td>\n",
       "      <td>0.20500</td>\n",
       "      <td>0.40000</td>\n",
       "      <td>0.16250</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12.450</td>\n",
       "      <td>15.70</td>\n",
       "      <td>82.57</td>\n",
       "      <td>477.1</td>\n",
       "      <td>0.12780</td>\n",
       "      <td>0.17000</td>\n",
       "      <td>0.157800</td>\n",
       "      <td>0.080890</td>\n",
       "      <td>0.2087</td>\n",
       "      <td>0.07613</td>\n",
       "      <td>...</td>\n",
       "      <td>23.75</td>\n",
       "      <td>103.40</td>\n",
       "      <td>741.6</td>\n",
       "      <td>0.17910</td>\n",
       "      <td>0.52490</td>\n",
       "      <td>0.53550</td>\n",
       "      <td>0.17410</td>\n",
       "      <td>0.3985</td>\n",
       "      <td>0.12440</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18.250</td>\n",
       "      <td>19.98</td>\n",
       "      <td>119.60</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>0.09463</td>\n",
       "      <td>0.10900</td>\n",
       "      <td>0.112700</td>\n",
       "      <td>0.074000</td>\n",
       "      <td>0.1794</td>\n",
       "      <td>0.05742</td>\n",
       "      <td>...</td>\n",
       "      <td>27.66</td>\n",
       "      <td>153.20</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>0.14420</td>\n",
       "      <td>0.25760</td>\n",
       "      <td>0.37840</td>\n",
       "      <td>0.19320</td>\n",
       "      <td>0.3063</td>\n",
       "      <td>0.08368</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13.710</td>\n",
       "      <td>20.83</td>\n",
       "      <td>90.20</td>\n",
       "      <td>577.9</td>\n",
       "      <td>0.11890</td>\n",
       "      <td>0.16450</td>\n",
       "      <td>0.093660</td>\n",
       "      <td>0.059850</td>\n",
       "      <td>0.2196</td>\n",
       "      <td>0.07451</td>\n",
       "      <td>...</td>\n",
       "      <td>28.14</td>\n",
       "      <td>110.60</td>\n",
       "      <td>897.0</td>\n",
       "      <td>0.16540</td>\n",
       "      <td>0.36820</td>\n",
       "      <td>0.26780</td>\n",
       "      <td>0.15560</td>\n",
       "      <td>0.3196</td>\n",
       "      <td>0.11510</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13.000</td>\n",
       "      <td>21.82</td>\n",
       "      <td>87.50</td>\n",
       "      <td>519.8</td>\n",
       "      <td>0.12730</td>\n",
       "      <td>0.19320</td>\n",
       "      <td>0.185900</td>\n",
       "      <td>0.093530</td>\n",
       "      <td>0.2350</td>\n",
       "      <td>0.07389</td>\n",
       "      <td>...</td>\n",
       "      <td>30.73</td>\n",
       "      <td>106.20</td>\n",
       "      <td>739.3</td>\n",
       "      <td>0.17030</td>\n",
       "      <td>0.54010</td>\n",
       "      <td>0.53900</td>\n",
       "      <td>0.20600</td>\n",
       "      <td>0.4378</td>\n",
       "      <td>0.10720</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12.460</td>\n",
       "      <td>24.04</td>\n",
       "      <td>83.97</td>\n",
       "      <td>475.9</td>\n",
       "      <td>0.11860</td>\n",
       "      <td>0.23960</td>\n",
       "      <td>0.227300</td>\n",
       "      <td>0.085430</td>\n",
       "      <td>0.2030</td>\n",
       "      <td>0.08243</td>\n",
       "      <td>...</td>\n",
       "      <td>40.68</td>\n",
       "      <td>97.65</td>\n",
       "      <td>711.4</td>\n",
       "      <td>0.18530</td>\n",
       "      <td>1.05800</td>\n",
       "      <td>1.10500</td>\n",
       "      <td>0.22100</td>\n",
       "      <td>0.4366</td>\n",
       "      <td>0.20750</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16.020</td>\n",
       "      <td>23.24</td>\n",
       "      <td>102.70</td>\n",
       "      <td>797.8</td>\n",
       "      <td>0.08206</td>\n",
       "      <td>0.06669</td>\n",
       "      <td>0.032990</td>\n",
       "      <td>0.033230</td>\n",
       "      <td>0.1528</td>\n",
       "      <td>0.05697</td>\n",
       "      <td>...</td>\n",
       "      <td>33.88</td>\n",
       "      <td>123.80</td>\n",
       "      <td>1150.0</td>\n",
       "      <td>0.11810</td>\n",
       "      <td>0.15510</td>\n",
       "      <td>0.14590</td>\n",
       "      <td>0.09975</td>\n",
       "      <td>0.2948</td>\n",
       "      <td>0.08452</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>15.780</td>\n",
       "      <td>17.89</td>\n",
       "      <td>103.60</td>\n",
       "      <td>781.0</td>\n",
       "      <td>0.09710</td>\n",
       "      <td>0.12920</td>\n",
       "      <td>0.099540</td>\n",
       "      <td>0.066060</td>\n",
       "      <td>0.1842</td>\n",
       "      <td>0.06082</td>\n",
       "      <td>...</td>\n",
       "      <td>27.28</td>\n",
       "      <td>136.50</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>0.13960</td>\n",
       "      <td>0.56090</td>\n",
       "      <td>0.39650</td>\n",
       "      <td>0.18100</td>\n",
       "      <td>0.3792</td>\n",
       "      <td>0.10480</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>19.170</td>\n",
       "      <td>24.80</td>\n",
       "      <td>132.40</td>\n",
       "      <td>1123.0</td>\n",
       "      <td>0.09740</td>\n",
       "      <td>0.24580</td>\n",
       "      <td>0.206500</td>\n",
       "      <td>0.111800</td>\n",
       "      <td>0.2397</td>\n",
       "      <td>0.07800</td>\n",
       "      <td>...</td>\n",
       "      <td>29.94</td>\n",
       "      <td>151.70</td>\n",
       "      <td>1332.0</td>\n",
       "      <td>0.10370</td>\n",
       "      <td>0.39030</td>\n",
       "      <td>0.36390</td>\n",
       "      <td>0.17670</td>\n",
       "      <td>0.3176</td>\n",
       "      <td>0.10230</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>15.850</td>\n",
       "      <td>23.95</td>\n",
       "      <td>103.70</td>\n",
       "      <td>782.7</td>\n",
       "      <td>0.08401</td>\n",
       "      <td>0.10020</td>\n",
       "      <td>0.099380</td>\n",
       "      <td>0.053640</td>\n",
       "      <td>0.1847</td>\n",
       "      <td>0.05338</td>\n",
       "      <td>...</td>\n",
       "      <td>27.66</td>\n",
       "      <td>112.00</td>\n",
       "      <td>876.5</td>\n",
       "      <td>0.11310</td>\n",
       "      <td>0.19240</td>\n",
       "      <td>0.23220</td>\n",
       "      <td>0.11190</td>\n",
       "      <td>0.2809</td>\n",
       "      <td>0.06287</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.730</td>\n",
       "      <td>22.61</td>\n",
       "      <td>93.60</td>\n",
       "      <td>578.3</td>\n",
       "      <td>0.11310</td>\n",
       "      <td>0.22930</td>\n",
       "      <td>0.212800</td>\n",
       "      <td>0.080250</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.07682</td>\n",
       "      <td>...</td>\n",
       "      <td>32.01</td>\n",
       "      <td>108.80</td>\n",
       "      <td>697.7</td>\n",
       "      <td>0.16510</td>\n",
       "      <td>0.77250</td>\n",
       "      <td>0.69430</td>\n",
       "      <td>0.22080</td>\n",
       "      <td>0.3596</td>\n",
       "      <td>0.14310</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>14.540</td>\n",
       "      <td>27.54</td>\n",
       "      <td>96.73</td>\n",
       "      <td>658.8</td>\n",
       "      <td>0.11390</td>\n",
       "      <td>0.15950</td>\n",
       "      <td>0.163900</td>\n",
       "      <td>0.073640</td>\n",
       "      <td>0.2303</td>\n",
       "      <td>0.07077</td>\n",
       "      <td>...</td>\n",
       "      <td>37.13</td>\n",
       "      <td>124.10</td>\n",
       "      <td>943.2</td>\n",
       "      <td>0.16780</td>\n",
       "      <td>0.65770</td>\n",
       "      <td>0.70260</td>\n",
       "      <td>0.17120</td>\n",
       "      <td>0.4218</td>\n",
       "      <td>0.13410</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>14.680</td>\n",
       "      <td>20.13</td>\n",
       "      <td>94.74</td>\n",
       "      <td>684.5</td>\n",
       "      <td>0.09867</td>\n",
       "      <td>0.07200</td>\n",
       "      <td>0.073950</td>\n",
       "      <td>0.052590</td>\n",
       "      <td>0.1586</td>\n",
       "      <td>0.05922</td>\n",
       "      <td>...</td>\n",
       "      <td>30.88</td>\n",
       "      <td>123.40</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>0.14640</td>\n",
       "      <td>0.18710</td>\n",
       "      <td>0.29140</td>\n",
       "      <td>0.16090</td>\n",
       "      <td>0.3029</td>\n",
       "      <td>0.08216</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>16.130</td>\n",
       "      <td>20.68</td>\n",
       "      <td>108.10</td>\n",
       "      <td>798.8</td>\n",
       "      <td>0.11700</td>\n",
       "      <td>0.20220</td>\n",
       "      <td>0.172200</td>\n",
       "      <td>0.102800</td>\n",
       "      <td>0.2164</td>\n",
       "      <td>0.07356</td>\n",
       "      <td>...</td>\n",
       "      <td>31.48</td>\n",
       "      <td>136.80</td>\n",
       "      <td>1315.0</td>\n",
       "      <td>0.17890</td>\n",
       "      <td>0.42330</td>\n",
       "      <td>0.47840</td>\n",
       "      <td>0.20730</td>\n",
       "      <td>0.3706</td>\n",
       "      <td>0.11420</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19.810</td>\n",
       "      <td>22.15</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1260.0</td>\n",
       "      <td>0.09831</td>\n",
       "      <td>0.10270</td>\n",
       "      <td>0.147900</td>\n",
       "      <td>0.094980</td>\n",
       "      <td>0.1582</td>\n",
       "      <td>0.05395</td>\n",
       "      <td>...</td>\n",
       "      <td>30.88</td>\n",
       "      <td>186.80</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>0.15120</td>\n",
       "      <td>0.31500</td>\n",
       "      <td>0.53720</td>\n",
       "      <td>0.23880</td>\n",
       "      <td>0.2768</td>\n",
       "      <td>0.07615</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>13.540</td>\n",
       "      <td>14.36</td>\n",
       "      <td>87.46</td>\n",
       "      <td>566.3</td>\n",
       "      <td>0.09779</td>\n",
       "      <td>0.08129</td>\n",
       "      <td>0.066640</td>\n",
       "      <td>0.047810</td>\n",
       "      <td>0.1885</td>\n",
       "      <td>0.05766</td>\n",
       "      <td>...</td>\n",
       "      <td>19.26</td>\n",
       "      <td>99.70</td>\n",
       "      <td>711.2</td>\n",
       "      <td>0.14400</td>\n",
       "      <td>0.17730</td>\n",
       "      <td>0.23900</td>\n",
       "      <td>0.12880</td>\n",
       "      <td>0.2977</td>\n",
       "      <td>0.07259</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>13.080</td>\n",
       "      <td>15.71</td>\n",
       "      <td>85.63</td>\n",
       "      <td>520.0</td>\n",
       "      <td>0.10750</td>\n",
       "      <td>0.12700</td>\n",
       "      <td>0.045680</td>\n",
       "      <td>0.031100</td>\n",
       "      <td>0.1967</td>\n",
       "      <td>0.06811</td>\n",
       "      <td>...</td>\n",
       "      <td>20.49</td>\n",
       "      <td>96.09</td>\n",
       "      <td>630.5</td>\n",
       "      <td>0.13120</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.18900</td>\n",
       "      <td>0.07283</td>\n",
       "      <td>0.3184</td>\n",
       "      <td>0.08183</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>9.504</td>\n",
       "      <td>12.44</td>\n",
       "      <td>60.34</td>\n",
       "      <td>273.9</td>\n",
       "      <td>0.10240</td>\n",
       "      <td>0.06492</td>\n",
       "      <td>0.029560</td>\n",
       "      <td>0.020760</td>\n",
       "      <td>0.1815</td>\n",
       "      <td>0.06905</td>\n",
       "      <td>...</td>\n",
       "      <td>15.66</td>\n",
       "      <td>65.13</td>\n",
       "      <td>314.9</td>\n",
       "      <td>0.13240</td>\n",
       "      <td>0.11480</td>\n",
       "      <td>0.08867</td>\n",
       "      <td>0.06227</td>\n",
       "      <td>0.2450</td>\n",
       "      <td>0.07773</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>15.340</td>\n",
       "      <td>14.26</td>\n",
       "      <td>102.50</td>\n",
       "      <td>704.4</td>\n",
       "      <td>0.10730</td>\n",
       "      <td>0.21350</td>\n",
       "      <td>0.207700</td>\n",
       "      <td>0.097560</td>\n",
       "      <td>0.2521</td>\n",
       "      <td>0.07032</td>\n",
       "      <td>...</td>\n",
       "      <td>19.08</td>\n",
       "      <td>125.10</td>\n",
       "      <td>980.9</td>\n",
       "      <td>0.13900</td>\n",
       "      <td>0.59540</td>\n",
       "      <td>0.63050</td>\n",
       "      <td>0.23930</td>\n",
       "      <td>0.4667</td>\n",
       "      <td>0.09946</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>21.160</td>\n",
       "      <td>23.04</td>\n",
       "      <td>137.20</td>\n",
       "      <td>1404.0</td>\n",
       "      <td>0.09428</td>\n",
       "      <td>0.10220</td>\n",
       "      <td>0.109700</td>\n",
       "      <td>0.086320</td>\n",
       "      <td>0.1769</td>\n",
       "      <td>0.05278</td>\n",
       "      <td>...</td>\n",
       "      <td>35.59</td>\n",
       "      <td>188.00</td>\n",
       "      <td>2615.0</td>\n",
       "      <td>0.14010</td>\n",
       "      <td>0.26000</td>\n",
       "      <td>0.31550</td>\n",
       "      <td>0.20090</td>\n",
       "      <td>0.2822</td>\n",
       "      <td>0.07526</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>16.650</td>\n",
       "      <td>21.38</td>\n",
       "      <td>110.00</td>\n",
       "      <td>904.6</td>\n",
       "      <td>0.11210</td>\n",
       "      <td>0.14570</td>\n",
       "      <td>0.152500</td>\n",
       "      <td>0.091700</td>\n",
       "      <td>0.1995</td>\n",
       "      <td>0.06330</td>\n",
       "      <td>...</td>\n",
       "      <td>31.56</td>\n",
       "      <td>177.00</td>\n",
       "      <td>2215.0</td>\n",
       "      <td>0.18050</td>\n",
       "      <td>0.35780</td>\n",
       "      <td>0.46950</td>\n",
       "      <td>0.20950</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.09564</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>17.140</td>\n",
       "      <td>16.40</td>\n",
       "      <td>116.00</td>\n",
       "      <td>912.7</td>\n",
       "      <td>0.11860</td>\n",
       "      <td>0.22760</td>\n",
       "      <td>0.222900</td>\n",
       "      <td>0.140100</td>\n",
       "      <td>0.3040</td>\n",
       "      <td>0.07413</td>\n",
       "      <td>...</td>\n",
       "      <td>21.40</td>\n",
       "      <td>152.40</td>\n",
       "      <td>1461.0</td>\n",
       "      <td>0.15450</td>\n",
       "      <td>0.39490</td>\n",
       "      <td>0.38530</td>\n",
       "      <td>0.25500</td>\n",
       "      <td>0.4066</td>\n",
       "      <td>0.10590</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>14.580</td>\n",
       "      <td>21.53</td>\n",
       "      <td>97.41</td>\n",
       "      <td>644.8</td>\n",
       "      <td>0.10540</td>\n",
       "      <td>0.18680</td>\n",
       "      <td>0.142500</td>\n",
       "      <td>0.087830</td>\n",
       "      <td>0.2252</td>\n",
       "      <td>0.06924</td>\n",
       "      <td>...</td>\n",
       "      <td>33.21</td>\n",
       "      <td>122.40</td>\n",
       "      <td>896.9</td>\n",
       "      <td>0.15250</td>\n",
       "      <td>0.66430</td>\n",
       "      <td>0.55390</td>\n",
       "      <td>0.27010</td>\n",
       "      <td>0.4264</td>\n",
       "      <td>0.12750</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>18.610</td>\n",
       "      <td>20.25</td>\n",
       "      <td>122.10</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>0.09440</td>\n",
       "      <td>0.10660</td>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.077310</td>\n",
       "      <td>0.1697</td>\n",
       "      <td>0.05699</td>\n",
       "      <td>...</td>\n",
       "      <td>27.26</td>\n",
       "      <td>139.90</td>\n",
       "      <td>1403.0</td>\n",
       "      <td>0.13380</td>\n",
       "      <td>0.21170</td>\n",
       "      <td>0.34460</td>\n",
       "      <td>0.14900</td>\n",
       "      <td>0.2341</td>\n",
       "      <td>0.07421</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>15.300</td>\n",
       "      <td>25.27</td>\n",
       "      <td>102.40</td>\n",
       "      <td>732.4</td>\n",
       "      <td>0.10820</td>\n",
       "      <td>0.16970</td>\n",
       "      <td>0.168300</td>\n",
       "      <td>0.087510</td>\n",
       "      <td>0.1926</td>\n",
       "      <td>0.06540</td>\n",
       "      <td>...</td>\n",
       "      <td>36.71</td>\n",
       "      <td>149.30</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>0.16410</td>\n",
       "      <td>0.61100</td>\n",
       "      <td>0.63350</td>\n",
       "      <td>0.20240</td>\n",
       "      <td>0.4027</td>\n",
       "      <td>0.09876</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>17.570</td>\n",
       "      <td>15.05</td>\n",
       "      <td>115.00</td>\n",
       "      <td>955.1</td>\n",
       "      <td>0.09847</td>\n",
       "      <td>0.11570</td>\n",
       "      <td>0.098750</td>\n",
       "      <td>0.079530</td>\n",
       "      <td>0.1739</td>\n",
       "      <td>0.06149</td>\n",
       "      <td>...</td>\n",
       "      <td>19.52</td>\n",
       "      <td>134.90</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>0.12550</td>\n",
       "      <td>0.28120</td>\n",
       "      <td>0.24890</td>\n",
       "      <td>0.14560</td>\n",
       "      <td>0.2756</td>\n",
       "      <td>0.07919</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539</th>\n",
       "      <td>7.691</td>\n",
       "      <td>25.44</td>\n",
       "      <td>48.34</td>\n",
       "      <td>170.4</td>\n",
       "      <td>0.08668</td>\n",
       "      <td>0.11990</td>\n",
       "      <td>0.092520</td>\n",
       "      <td>0.013640</td>\n",
       "      <td>0.2037</td>\n",
       "      <td>0.07751</td>\n",
       "      <td>...</td>\n",
       "      <td>31.89</td>\n",
       "      <td>54.49</td>\n",
       "      <td>223.6</td>\n",
       "      <td>0.15960</td>\n",
       "      <td>0.30640</td>\n",
       "      <td>0.33930</td>\n",
       "      <td>0.05000</td>\n",
       "      <td>0.2790</td>\n",
       "      <td>0.10660</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>540</th>\n",
       "      <td>11.540</td>\n",
       "      <td>14.44</td>\n",
       "      <td>74.65</td>\n",
       "      <td>402.9</td>\n",
       "      <td>0.09984</td>\n",
       "      <td>0.11200</td>\n",
       "      <td>0.067370</td>\n",
       "      <td>0.025940</td>\n",
       "      <td>0.1818</td>\n",
       "      <td>0.06782</td>\n",
       "      <td>...</td>\n",
       "      <td>19.68</td>\n",
       "      <td>78.78</td>\n",
       "      <td>457.8</td>\n",
       "      <td>0.13450</td>\n",
       "      <td>0.21180</td>\n",
       "      <td>0.17970</td>\n",
       "      <td>0.06918</td>\n",
       "      <td>0.2329</td>\n",
       "      <td>0.08134</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>14.470</td>\n",
       "      <td>24.99</td>\n",
       "      <td>95.81</td>\n",
       "      <td>656.4</td>\n",
       "      <td>0.08837</td>\n",
       "      <td>0.12300</td>\n",
       "      <td>0.100900</td>\n",
       "      <td>0.038900</td>\n",
       "      <td>0.1872</td>\n",
       "      <td>0.06341</td>\n",
       "      <td>...</td>\n",
       "      <td>31.73</td>\n",
       "      <td>113.50</td>\n",
       "      <td>808.9</td>\n",
       "      <td>0.13400</td>\n",
       "      <td>0.42020</td>\n",
       "      <td>0.40400</td>\n",
       "      <td>0.12050</td>\n",
       "      <td>0.3187</td>\n",
       "      <td>0.10230</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>14.740</td>\n",
       "      <td>25.42</td>\n",
       "      <td>94.70</td>\n",
       "      <td>668.6</td>\n",
       "      <td>0.08275</td>\n",
       "      <td>0.07214</td>\n",
       "      <td>0.041050</td>\n",
       "      <td>0.030270</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.05680</td>\n",
       "      <td>...</td>\n",
       "      <td>32.29</td>\n",
       "      <td>107.40</td>\n",
       "      <td>826.4</td>\n",
       "      <td>0.10600</td>\n",
       "      <td>0.13760</td>\n",
       "      <td>0.16110</td>\n",
       "      <td>0.10950</td>\n",
       "      <td>0.2722</td>\n",
       "      <td>0.06956</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>543</th>\n",
       "      <td>13.210</td>\n",
       "      <td>28.06</td>\n",
       "      <td>84.88</td>\n",
       "      <td>538.4</td>\n",
       "      <td>0.08671</td>\n",
       "      <td>0.06877</td>\n",
       "      <td>0.029870</td>\n",
       "      <td>0.032750</td>\n",
       "      <td>0.1628</td>\n",
       "      <td>0.05781</td>\n",
       "      <td>...</td>\n",
       "      <td>37.17</td>\n",
       "      <td>92.48</td>\n",
       "      <td>629.6</td>\n",
       "      <td>0.10720</td>\n",
       "      <td>0.13810</td>\n",
       "      <td>0.10620</td>\n",
       "      <td>0.07958</td>\n",
       "      <td>0.2473</td>\n",
       "      <td>0.06443</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>13.870</td>\n",
       "      <td>20.70</td>\n",
       "      <td>89.77</td>\n",
       "      <td>584.8</td>\n",
       "      <td>0.09578</td>\n",
       "      <td>0.10180</td>\n",
       "      <td>0.036880</td>\n",
       "      <td>0.023690</td>\n",
       "      <td>0.1620</td>\n",
       "      <td>0.06688</td>\n",
       "      <td>...</td>\n",
       "      <td>24.75</td>\n",
       "      <td>99.17</td>\n",
       "      <td>688.6</td>\n",
       "      <td>0.12640</td>\n",
       "      <td>0.20370</td>\n",
       "      <td>0.13770</td>\n",
       "      <td>0.06845</td>\n",
       "      <td>0.2249</td>\n",
       "      <td>0.08492</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>13.620</td>\n",
       "      <td>23.23</td>\n",
       "      <td>87.19</td>\n",
       "      <td>573.2</td>\n",
       "      <td>0.09246</td>\n",
       "      <td>0.06747</td>\n",
       "      <td>0.029740</td>\n",
       "      <td>0.024430</td>\n",
       "      <td>0.1664</td>\n",
       "      <td>0.05801</td>\n",
       "      <td>...</td>\n",
       "      <td>29.09</td>\n",
       "      <td>97.58</td>\n",
       "      <td>729.8</td>\n",
       "      <td>0.12160</td>\n",
       "      <td>0.15170</td>\n",
       "      <td>0.10490</td>\n",
       "      <td>0.07174</td>\n",
       "      <td>0.2642</td>\n",
       "      <td>0.06953</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>10.320</td>\n",
       "      <td>16.35</td>\n",
       "      <td>65.31</td>\n",
       "      <td>324.9</td>\n",
       "      <td>0.09434</td>\n",
       "      <td>0.04994</td>\n",
       "      <td>0.010120</td>\n",
       "      <td>0.005495</td>\n",
       "      <td>0.1885</td>\n",
       "      <td>0.06201</td>\n",
       "      <td>...</td>\n",
       "      <td>21.77</td>\n",
       "      <td>71.12</td>\n",
       "      <td>384.9</td>\n",
       "      <td>0.12850</td>\n",
       "      <td>0.08842</td>\n",
       "      <td>0.04384</td>\n",
       "      <td>0.02381</td>\n",
       "      <td>0.2681</td>\n",
       "      <td>0.07399</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547</th>\n",
       "      <td>10.260</td>\n",
       "      <td>16.58</td>\n",
       "      <td>65.85</td>\n",
       "      <td>320.8</td>\n",
       "      <td>0.08877</td>\n",
       "      <td>0.08066</td>\n",
       "      <td>0.043580</td>\n",
       "      <td>0.024380</td>\n",
       "      <td>0.1669</td>\n",
       "      <td>0.06714</td>\n",
       "      <td>...</td>\n",
       "      <td>22.04</td>\n",
       "      <td>71.08</td>\n",
       "      <td>357.4</td>\n",
       "      <td>0.14610</td>\n",
       "      <td>0.22460</td>\n",
       "      <td>0.17830</td>\n",
       "      <td>0.08333</td>\n",
       "      <td>0.2691</td>\n",
       "      <td>0.09479</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>9.683</td>\n",
       "      <td>19.34</td>\n",
       "      <td>61.05</td>\n",
       "      <td>285.7</td>\n",
       "      <td>0.08491</td>\n",
       "      <td>0.05030</td>\n",
       "      <td>0.023370</td>\n",
       "      <td>0.009615</td>\n",
       "      <td>0.1580</td>\n",
       "      <td>0.06235</td>\n",
       "      <td>...</td>\n",
       "      <td>25.59</td>\n",
       "      <td>69.10</td>\n",
       "      <td>364.2</td>\n",
       "      <td>0.11990</td>\n",
       "      <td>0.09546</td>\n",
       "      <td>0.09350</td>\n",
       "      <td>0.03846</td>\n",
       "      <td>0.2552</td>\n",
       "      <td>0.07920</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>10.820</td>\n",
       "      <td>24.21</td>\n",
       "      <td>68.89</td>\n",
       "      <td>361.6</td>\n",
       "      <td>0.08192</td>\n",
       "      <td>0.06602</td>\n",
       "      <td>0.015480</td>\n",
       "      <td>0.008160</td>\n",
       "      <td>0.1976</td>\n",
       "      <td>0.06328</td>\n",
       "      <td>...</td>\n",
       "      <td>31.45</td>\n",
       "      <td>83.90</td>\n",
       "      <td>505.6</td>\n",
       "      <td>0.12040</td>\n",
       "      <td>0.16330</td>\n",
       "      <td>0.06194</td>\n",
       "      <td>0.03264</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>0.07626</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>10.860</td>\n",
       "      <td>21.48</td>\n",
       "      <td>68.51</td>\n",
       "      <td>360.5</td>\n",
       "      <td>0.07431</td>\n",
       "      <td>0.04227</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1661</td>\n",
       "      <td>0.05948</td>\n",
       "      <td>...</td>\n",
       "      <td>24.77</td>\n",
       "      <td>74.08</td>\n",
       "      <td>412.3</td>\n",
       "      <td>0.10010</td>\n",
       "      <td>0.07348</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.2458</td>\n",
       "      <td>0.06592</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>11.130</td>\n",
       "      <td>22.44</td>\n",
       "      <td>71.49</td>\n",
       "      <td>378.4</td>\n",
       "      <td>0.09566</td>\n",
       "      <td>0.08194</td>\n",
       "      <td>0.048240</td>\n",
       "      <td>0.022570</td>\n",
       "      <td>0.2030</td>\n",
       "      <td>0.06552</td>\n",
       "      <td>...</td>\n",
       "      <td>28.26</td>\n",
       "      <td>77.80</td>\n",
       "      <td>436.6</td>\n",
       "      <td>0.10870</td>\n",
       "      <td>0.17820</td>\n",
       "      <td>0.15640</td>\n",
       "      <td>0.06413</td>\n",
       "      <td>0.3169</td>\n",
       "      <td>0.08032</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>12.770</td>\n",
       "      <td>29.43</td>\n",
       "      <td>81.35</td>\n",
       "      <td>507.9</td>\n",
       "      <td>0.08276</td>\n",
       "      <td>0.04234</td>\n",
       "      <td>0.019970</td>\n",
       "      <td>0.014990</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.05637</td>\n",
       "      <td>...</td>\n",
       "      <td>36.00</td>\n",
       "      <td>88.10</td>\n",
       "      <td>594.7</td>\n",
       "      <td>0.12340</td>\n",
       "      <td>0.10640</td>\n",
       "      <td>0.08653</td>\n",
       "      <td>0.06498</td>\n",
       "      <td>0.2407</td>\n",
       "      <td>0.06484</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>9.333</td>\n",
       "      <td>21.94</td>\n",
       "      <td>59.01</td>\n",
       "      <td>264.0</td>\n",
       "      <td>0.09240</td>\n",
       "      <td>0.05605</td>\n",
       "      <td>0.039960</td>\n",
       "      <td>0.012820</td>\n",
       "      <td>0.1692</td>\n",
       "      <td>0.06576</td>\n",
       "      <td>...</td>\n",
       "      <td>25.05</td>\n",
       "      <td>62.86</td>\n",
       "      <td>295.8</td>\n",
       "      <td>0.11030</td>\n",
       "      <td>0.08298</td>\n",
       "      <td>0.07993</td>\n",
       "      <td>0.02564</td>\n",
       "      <td>0.2435</td>\n",
       "      <td>0.07393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>12.880</td>\n",
       "      <td>28.92</td>\n",
       "      <td>82.50</td>\n",
       "      <td>514.3</td>\n",
       "      <td>0.08123</td>\n",
       "      <td>0.05824</td>\n",
       "      <td>0.061950</td>\n",
       "      <td>0.023430</td>\n",
       "      <td>0.1566</td>\n",
       "      <td>0.05708</td>\n",
       "      <td>...</td>\n",
       "      <td>35.74</td>\n",
       "      <td>88.84</td>\n",
       "      <td>595.7</td>\n",
       "      <td>0.12270</td>\n",
       "      <td>0.16200</td>\n",
       "      <td>0.24390</td>\n",
       "      <td>0.06493</td>\n",
       "      <td>0.2372</td>\n",
       "      <td>0.07242</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>10.290</td>\n",
       "      <td>27.61</td>\n",
       "      <td>65.67</td>\n",
       "      <td>321.4</td>\n",
       "      <td>0.09030</td>\n",
       "      <td>0.07658</td>\n",
       "      <td>0.059990</td>\n",
       "      <td>0.027380</td>\n",
       "      <td>0.1593</td>\n",
       "      <td>0.06127</td>\n",
       "      <td>...</td>\n",
       "      <td>34.91</td>\n",
       "      <td>69.57</td>\n",
       "      <td>357.6</td>\n",
       "      <td>0.13840</td>\n",
       "      <td>0.17100</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>0.09127</td>\n",
       "      <td>0.2226</td>\n",
       "      <td>0.08283</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>10.160</td>\n",
       "      <td>19.59</td>\n",
       "      <td>64.73</td>\n",
       "      <td>311.7</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.07504</td>\n",
       "      <td>0.005025</td>\n",
       "      <td>0.011160</td>\n",
       "      <td>0.1791</td>\n",
       "      <td>0.06331</td>\n",
       "      <td>...</td>\n",
       "      <td>22.88</td>\n",
       "      <td>67.88</td>\n",
       "      <td>347.3</td>\n",
       "      <td>0.12650</td>\n",
       "      <td>0.12000</td>\n",
       "      <td>0.01005</td>\n",
       "      <td>0.02232</td>\n",
       "      <td>0.2262</td>\n",
       "      <td>0.06742</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>9.423</td>\n",
       "      <td>27.88</td>\n",
       "      <td>59.26</td>\n",
       "      <td>271.3</td>\n",
       "      <td>0.08123</td>\n",
       "      <td>0.04971</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1742</td>\n",
       "      <td>0.06059</td>\n",
       "      <td>...</td>\n",
       "      <td>34.24</td>\n",
       "      <td>66.50</td>\n",
       "      <td>330.6</td>\n",
       "      <td>0.10730</td>\n",
       "      <td>0.07158</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.06969</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>14.590</td>\n",
       "      <td>22.68</td>\n",
       "      <td>96.39</td>\n",
       "      <td>657.1</td>\n",
       "      <td>0.08473</td>\n",
       "      <td>0.13300</td>\n",
       "      <td>0.102900</td>\n",
       "      <td>0.037360</td>\n",
       "      <td>0.1454</td>\n",
       "      <td>0.06147</td>\n",
       "      <td>...</td>\n",
       "      <td>27.27</td>\n",
       "      <td>105.90</td>\n",
       "      <td>733.5</td>\n",
       "      <td>0.10260</td>\n",
       "      <td>0.31710</td>\n",
       "      <td>0.36620</td>\n",
       "      <td>0.11050</td>\n",
       "      <td>0.2258</td>\n",
       "      <td>0.08004</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>11.510</td>\n",
       "      <td>23.93</td>\n",
       "      <td>74.52</td>\n",
       "      <td>403.5</td>\n",
       "      <td>0.09261</td>\n",
       "      <td>0.10210</td>\n",
       "      <td>0.111200</td>\n",
       "      <td>0.041050</td>\n",
       "      <td>0.1388</td>\n",
       "      <td>0.06570</td>\n",
       "      <td>...</td>\n",
       "      <td>37.16</td>\n",
       "      <td>82.28</td>\n",
       "      <td>474.2</td>\n",
       "      <td>0.12980</td>\n",
       "      <td>0.25170</td>\n",
       "      <td>0.36300</td>\n",
       "      <td>0.09653</td>\n",
       "      <td>0.2112</td>\n",
       "      <td>0.08732</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>14.050</td>\n",
       "      <td>27.15</td>\n",
       "      <td>91.38</td>\n",
       "      <td>600.4</td>\n",
       "      <td>0.09929</td>\n",
       "      <td>0.11260</td>\n",
       "      <td>0.044620</td>\n",
       "      <td>0.043040</td>\n",
       "      <td>0.1537</td>\n",
       "      <td>0.06171</td>\n",
       "      <td>...</td>\n",
       "      <td>33.17</td>\n",
       "      <td>100.20</td>\n",
       "      <td>706.7</td>\n",
       "      <td>0.12410</td>\n",
       "      <td>0.22640</td>\n",
       "      <td>0.13260</td>\n",
       "      <td>0.10480</td>\n",
       "      <td>0.2250</td>\n",
       "      <td>0.08321</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>11.200</td>\n",
       "      <td>29.37</td>\n",
       "      <td>70.67</td>\n",
       "      <td>386.0</td>\n",
       "      <td>0.07449</td>\n",
       "      <td>0.03558</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1060</td>\n",
       "      <td>0.05502</td>\n",
       "      <td>...</td>\n",
       "      <td>38.30</td>\n",
       "      <td>75.19</td>\n",
       "      <td>439.6</td>\n",
       "      <td>0.09267</td>\n",
       "      <td>0.05494</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.1566</td>\n",
       "      <td>0.05905</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562</th>\n",
       "      <td>15.220</td>\n",
       "      <td>30.62</td>\n",
       "      <td>103.40</td>\n",
       "      <td>716.9</td>\n",
       "      <td>0.10480</td>\n",
       "      <td>0.20870</td>\n",
       "      <td>0.255000</td>\n",
       "      <td>0.094290</td>\n",
       "      <td>0.2128</td>\n",
       "      <td>0.07152</td>\n",
       "      <td>...</td>\n",
       "      <td>42.79</td>\n",
       "      <td>128.70</td>\n",
       "      <td>915.0</td>\n",
       "      <td>0.14170</td>\n",
       "      <td>0.79170</td>\n",
       "      <td>1.17000</td>\n",
       "      <td>0.23560</td>\n",
       "      <td>0.4089</td>\n",
       "      <td>0.14090</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>20.920</td>\n",
       "      <td>25.09</td>\n",
       "      <td>143.00</td>\n",
       "      <td>1347.0</td>\n",
       "      <td>0.10990</td>\n",
       "      <td>0.22360</td>\n",
       "      <td>0.317400</td>\n",
       "      <td>0.147400</td>\n",
       "      <td>0.2149</td>\n",
       "      <td>0.06879</td>\n",
       "      <td>...</td>\n",
       "      <td>29.41</td>\n",
       "      <td>179.10</td>\n",
       "      <td>1819.0</td>\n",
       "      <td>0.14070</td>\n",
       "      <td>0.41860</td>\n",
       "      <td>0.65990</td>\n",
       "      <td>0.25420</td>\n",
       "      <td>0.2929</td>\n",
       "      <td>0.09873</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>21.560</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>0.243900</td>\n",
       "      <td>0.138900</td>\n",
       "      <td>0.1726</td>\n",
       "      <td>0.05623</td>\n",
       "      <td>...</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>0.41070</td>\n",
       "      <td>0.22160</td>\n",
       "      <td>0.2060</td>\n",
       "      <td>0.07115</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>20.130</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>0.144000</td>\n",
       "      <td>0.097910</td>\n",
       "      <td>0.1752</td>\n",
       "      <td>0.05533</td>\n",
       "      <td>...</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>0.32150</td>\n",
       "      <td>0.16280</td>\n",
       "      <td>0.2572</td>\n",
       "      <td>0.06637</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>16.600</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>0.092510</td>\n",
       "      <td>0.053020</td>\n",
       "      <td>0.1590</td>\n",
       "      <td>0.05648</td>\n",
       "      <td>...</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>0.34030</td>\n",
       "      <td>0.14180</td>\n",
       "      <td>0.2218</td>\n",
       "      <td>0.07820</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>20.600</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>0.351400</td>\n",
       "      <td>0.152000</td>\n",
       "      <td>0.2397</td>\n",
       "      <td>0.07016</td>\n",
       "      <td>...</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>0.93870</td>\n",
       "      <td>0.26500</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.12400</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>7.760</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1587</td>\n",
       "      <td>0.05884</td>\n",
       "      <td>...</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>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.2871</td>\n",
       "      <td>0.07039</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>569 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0         17.990         10.38          122.80     1001.0          0.11840   \n",
       "1         20.570         17.77          132.90     1326.0          0.08474   \n",
       "2         19.690         21.25          130.00     1203.0          0.10960   \n",
       "3         11.420         20.38           77.58      386.1          0.14250   \n",
       "4         20.290         14.34          135.10     1297.0          0.10030   \n",
       "5         12.450         15.70           82.57      477.1          0.12780   \n",
       "6         18.250         19.98          119.60     1040.0          0.09463   \n",
       "7         13.710         20.83           90.20      577.9          0.11890   \n",
       "8         13.000         21.82           87.50      519.8          0.12730   \n",
       "9         12.460         24.04           83.97      475.9          0.11860   \n",
       "10        16.020         23.24          102.70      797.8          0.08206   \n",
       "11        15.780         17.89          103.60      781.0          0.09710   \n",
       "12        19.170         24.80          132.40     1123.0          0.09740   \n",
       "13        15.850         23.95          103.70      782.7          0.08401   \n",
       "14        13.730         22.61           93.60      578.3          0.11310   \n",
       "15        14.540         27.54           96.73      658.8          0.11390   \n",
       "16        14.680         20.13           94.74      684.5          0.09867   \n",
       "17        16.130         20.68          108.10      798.8          0.11700   \n",
       "18        19.810         22.15          130.00     1260.0          0.09831   \n",
       "19        13.540         14.36           87.46      566.3          0.09779   \n",
       "20        13.080         15.71           85.63      520.0          0.10750   \n",
       "21         9.504         12.44           60.34      273.9          0.10240   \n",
       "22        15.340         14.26          102.50      704.4          0.10730   \n",
       "23        21.160         23.04          137.20     1404.0          0.09428   \n",
       "24        16.650         21.38          110.00      904.6          0.11210   \n",
       "25        17.140         16.40          116.00      912.7          0.11860   \n",
       "26        14.580         21.53           97.41      644.8          0.10540   \n",
       "27        18.610         20.25          122.10     1094.0          0.09440   \n",
       "28        15.300         25.27          102.40      732.4          0.10820   \n",
       "29        17.570         15.05          115.00      955.1          0.09847   \n",
       "..           ...           ...             ...        ...              ...   \n",
       "539        7.691         25.44           48.34      170.4          0.08668   \n",
       "540       11.540         14.44           74.65      402.9          0.09984   \n",
       "541       14.470         24.99           95.81      656.4          0.08837   \n",
       "542       14.740         25.42           94.70      668.6          0.08275   \n",
       "543       13.210         28.06           84.88      538.4          0.08671   \n",
       "544       13.870         20.70           89.77      584.8          0.09578   \n",
       "545       13.620         23.23           87.19      573.2          0.09246   \n",
       "546       10.320         16.35           65.31      324.9          0.09434   \n",
       "547       10.260         16.58           65.85      320.8          0.08877   \n",
       "548        9.683         19.34           61.05      285.7          0.08491   \n",
       "549       10.820         24.21           68.89      361.6          0.08192   \n",
       "550       10.860         21.48           68.51      360.5          0.07431   \n",
       "551       11.130         22.44           71.49      378.4          0.09566   \n",
       "552       12.770         29.43           81.35      507.9          0.08276   \n",
       "553        9.333         21.94           59.01      264.0          0.09240   \n",
       "554       12.880         28.92           82.50      514.3          0.08123   \n",
       "555       10.290         27.61           65.67      321.4          0.09030   \n",
       "556       10.160         19.59           64.73      311.7          0.10030   \n",
       "557        9.423         27.88           59.26      271.3          0.08123   \n",
       "558       14.590         22.68           96.39      657.1          0.08473   \n",
       "559       11.510         23.93           74.52      403.5          0.09261   \n",
       "560       14.050         27.15           91.38      600.4          0.09929   \n",
       "561       11.200         29.37           70.67      386.0          0.07449   \n",
       "562       15.220         30.62          103.40      716.9          0.10480   \n",
       "563       20.920         25.09          143.00     1347.0          0.10990   \n",
       "564       21.560         22.39          142.00     1479.0          0.11100   \n",
       "565       20.130         28.25          131.20     1261.0          0.09780   \n",
       "566       16.600         28.08          108.30      858.1          0.08455   \n",
       "567       20.600         29.33          140.10     1265.0          0.11780   \n",
       "568        7.760         24.54           47.92      181.0          0.05263   \n",
       "\n",
       "     mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0             0.27760        0.300100             0.147100         0.2419   \n",
       "1             0.07864        0.086900             0.070170         0.1812   \n",
       "2             0.15990        0.197400             0.127900         0.2069   \n",
       "3             0.28390        0.241400             0.105200         0.2597   \n",
       "4             0.13280        0.198000             0.104300         0.1809   \n",
       "5             0.17000        0.157800             0.080890         0.2087   \n",
       "6             0.10900        0.112700             0.074000         0.1794   \n",
       "7             0.16450        0.093660             0.059850         0.2196   \n",
       "8             0.19320        0.185900             0.093530         0.2350   \n",
       "9             0.23960        0.227300             0.085430         0.2030   \n",
       "10            0.06669        0.032990             0.033230         0.1528   \n",
       "11            0.12920        0.099540             0.066060         0.1842   \n",
       "12            0.24580        0.206500             0.111800         0.2397   \n",
       "13            0.10020        0.099380             0.053640         0.1847   \n",
       "14            0.22930        0.212800             0.080250         0.2069   \n",
       "15            0.15950        0.163900             0.073640         0.2303   \n",
       "16            0.07200        0.073950             0.052590         0.1586   \n",
       "17            0.20220        0.172200             0.102800         0.2164   \n",
       "18            0.10270        0.147900             0.094980         0.1582   \n",
       "19            0.08129        0.066640             0.047810         0.1885   \n",
       "20            0.12700        0.045680             0.031100         0.1967   \n",
       "21            0.06492        0.029560             0.020760         0.1815   \n",
       "22            0.21350        0.207700             0.097560         0.2521   \n",
       "23            0.10220        0.109700             0.086320         0.1769   \n",
       "24            0.14570        0.152500             0.091700         0.1995   \n",
       "25            0.22760        0.222900             0.140100         0.3040   \n",
       "26            0.18680        0.142500             0.087830         0.2252   \n",
       "27            0.10660        0.149000             0.077310         0.1697   \n",
       "28            0.16970        0.168300             0.087510         0.1926   \n",
       "29            0.11570        0.098750             0.079530         0.1739   \n",
       "..                ...             ...                  ...            ...   \n",
       "539           0.11990        0.092520             0.013640         0.2037   \n",
       "540           0.11200        0.067370             0.025940         0.1818   \n",
       "541           0.12300        0.100900             0.038900         0.1872   \n",
       "542           0.07214        0.041050             0.030270         0.1840   \n",
       "543           0.06877        0.029870             0.032750         0.1628   \n",
       "544           0.10180        0.036880             0.023690         0.1620   \n",
       "545           0.06747        0.029740             0.024430         0.1664   \n",
       "546           0.04994        0.010120             0.005495         0.1885   \n",
       "547           0.08066        0.043580             0.024380         0.1669   \n",
       "548           0.05030        0.023370             0.009615         0.1580   \n",
       "549           0.06602        0.015480             0.008160         0.1976   \n",
       "550           0.04227        0.000000             0.000000         0.1661   \n",
       "551           0.08194        0.048240             0.022570         0.2030   \n",
       "552           0.04234        0.019970             0.014990         0.1539   \n",
       "553           0.05605        0.039960             0.012820         0.1692   \n",
       "554           0.05824        0.061950             0.023430         0.1566   \n",
       "555           0.07658        0.059990             0.027380         0.1593   \n",
       "556           0.07504        0.005025             0.011160         0.1791   \n",
       "557           0.04971        0.000000             0.000000         0.1742   \n",
       "558           0.13300        0.102900             0.037360         0.1454   \n",
       "559           0.10210        0.111200             0.041050         0.1388   \n",
       "560           0.11260        0.044620             0.043040         0.1537   \n",
       "561           0.03558        0.000000             0.000000         0.1060   \n",
       "562           0.20870        0.255000             0.094290         0.2128   \n",
       "563           0.22360        0.317400             0.147400         0.2149   \n",
       "564           0.11590        0.243900             0.138900         0.1726   \n",
       "565           0.10340        0.144000             0.097910         0.1752   \n",
       "566           0.10230        0.092510             0.053020         0.1590   \n",
       "567           0.27700        0.351400             0.152000         0.2397   \n",
       "568           0.04362        0.000000             0.000000         0.1587   \n",
       "\n",
       "     mean fractal dimension   ...    worst texture  worst perimeter  \\\n",
       "0                   0.07871   ...            17.33           184.60   \n",
       "1                   0.05667   ...            23.41           158.80   \n",
       "2                   0.05999   ...            25.53           152.50   \n",
       "3                   0.09744   ...            26.50            98.87   \n",
       "4                   0.05883   ...            16.67           152.20   \n",
       "5                   0.07613   ...            23.75           103.40   \n",
       "6                   0.05742   ...            27.66           153.20   \n",
       "7                   0.07451   ...            28.14           110.60   \n",
       "8                   0.07389   ...            30.73           106.20   \n",
       "9                   0.08243   ...            40.68            97.65   \n",
       "10                  0.05697   ...            33.88           123.80   \n",
       "11                  0.06082   ...            27.28           136.50   \n",
       "12                  0.07800   ...            29.94           151.70   \n",
       "13                  0.05338   ...            27.66           112.00   \n",
       "14                  0.07682   ...            32.01           108.80   \n",
       "15                  0.07077   ...            37.13           124.10   \n",
       "16                  0.05922   ...            30.88           123.40   \n",
       "17                  0.07356   ...            31.48           136.80   \n",
       "18                  0.05395   ...            30.88           186.80   \n",
       "19                  0.05766   ...            19.26            99.70   \n",
       "20                  0.06811   ...            20.49            96.09   \n",
       "21                  0.06905   ...            15.66            65.13   \n",
       "22                  0.07032   ...            19.08           125.10   \n",
       "23                  0.05278   ...            35.59           188.00   \n",
       "24                  0.06330   ...            31.56           177.00   \n",
       "25                  0.07413   ...            21.40           152.40   \n",
       "26                  0.06924   ...            33.21           122.40   \n",
       "27                  0.05699   ...            27.26           139.90   \n",
       "28                  0.06540   ...            36.71           149.30   \n",
       "29                  0.06149   ...            19.52           134.90   \n",
       "..                      ...   ...              ...              ...   \n",
       "539                 0.07751   ...            31.89            54.49   \n",
       "540                 0.06782   ...            19.68            78.78   \n",
       "541                 0.06341   ...            31.73           113.50   \n",
       "542                 0.05680   ...            32.29           107.40   \n",
       "543                 0.05781   ...            37.17            92.48   \n",
       "544                 0.06688   ...            24.75            99.17   \n",
       "545                 0.05801   ...            29.09            97.58   \n",
       "546                 0.06201   ...            21.77            71.12   \n",
       "547                 0.06714   ...            22.04            71.08   \n",
       "548                 0.06235   ...            25.59            69.10   \n",
       "549                 0.06328   ...            31.45            83.90   \n",
       "550                 0.05948   ...            24.77            74.08   \n",
       "551                 0.06552   ...            28.26            77.80   \n",
       "552                 0.05637   ...            36.00            88.10   \n",
       "553                 0.06576   ...            25.05            62.86   \n",
       "554                 0.05708   ...            35.74            88.84   \n",
       "555                 0.06127   ...            34.91            69.57   \n",
       "556                 0.06331   ...            22.88            67.88   \n",
       "557                 0.06059   ...            34.24            66.50   \n",
       "558                 0.06147   ...            27.27           105.90   \n",
       "559                 0.06570   ...            37.16            82.28   \n",
       "560                 0.06171   ...            33.17           100.20   \n",
       "561                 0.05502   ...            38.30            75.19   \n",
       "562                 0.07152   ...            42.79           128.70   \n",
       "563                 0.06879   ...            29.41           179.10   \n",
       "564                 0.05623   ...            26.40           166.10   \n",
       "565                 0.05533   ...            38.25           155.00   \n",
       "566                 0.05648   ...            34.12           126.70   \n",
       "567                 0.07016   ...            39.42           184.60   \n",
       "568                 0.05884   ...            30.37            59.16   \n",
       "\n",
       "     worst area  worst smoothness  worst compactness  worst concavity  \\\n",
       "0        2019.0           0.16220            0.66560          0.71190   \n",
       "1        1956.0           0.12380            0.18660          0.24160   \n",
       "2        1709.0           0.14440            0.42450          0.45040   \n",
       "3         567.7           0.20980            0.86630          0.68690   \n",
       "4        1575.0           0.13740            0.20500          0.40000   \n",
       "5         741.6           0.17910            0.52490          0.53550   \n",
       "6        1606.0           0.14420            0.25760          0.37840   \n",
       "7         897.0           0.16540            0.36820          0.26780   \n",
       "8         739.3           0.17030            0.54010          0.53900   \n",
       "9         711.4           0.18530            1.05800          1.10500   \n",
       "10       1150.0           0.11810            0.15510          0.14590   \n",
       "11       1299.0           0.13960            0.56090          0.39650   \n",
       "12       1332.0           0.10370            0.39030          0.36390   \n",
       "13        876.5           0.11310            0.19240          0.23220   \n",
       "14        697.7           0.16510            0.77250          0.69430   \n",
       "15        943.2           0.16780            0.65770          0.70260   \n",
       "16       1138.0           0.14640            0.18710          0.29140   \n",
       "17       1315.0           0.17890            0.42330          0.47840   \n",
       "18       2398.0           0.15120            0.31500          0.53720   \n",
       "19        711.2           0.14400            0.17730          0.23900   \n",
       "20        630.5           0.13120            0.27760          0.18900   \n",
       "21        314.9           0.13240            0.11480          0.08867   \n",
       "22        980.9           0.13900            0.59540          0.63050   \n",
       "23       2615.0           0.14010            0.26000          0.31550   \n",
       "24       2215.0           0.18050            0.35780          0.46950   \n",
       "25       1461.0           0.15450            0.39490          0.38530   \n",
       "26        896.9           0.15250            0.66430          0.55390   \n",
       "27       1403.0           0.13380            0.21170          0.34460   \n",
       "28       1269.0           0.16410            0.61100          0.63350   \n",
       "29       1227.0           0.12550            0.28120          0.24890   \n",
       "..          ...               ...                ...              ...   \n",
       "539       223.6           0.15960            0.30640          0.33930   \n",
       "540       457.8           0.13450            0.21180          0.17970   \n",
       "541       808.9           0.13400            0.42020          0.40400   \n",
       "542       826.4           0.10600            0.13760          0.16110   \n",
       "543       629.6           0.10720            0.13810          0.10620   \n",
       "544       688.6           0.12640            0.20370          0.13770   \n",
       "545       729.8           0.12160            0.15170          0.10490   \n",
       "546       384.9           0.12850            0.08842          0.04384   \n",
       "547       357.4           0.14610            0.22460          0.17830   \n",
       "548       364.2           0.11990            0.09546          0.09350   \n",
       "549       505.6           0.12040            0.16330          0.06194   \n",
       "550       412.3           0.10010            0.07348          0.00000   \n",
       "551       436.6           0.10870            0.17820          0.15640   \n",
       "552       594.7           0.12340            0.10640          0.08653   \n",
       "553       295.8           0.11030            0.08298          0.07993   \n",
       "554       595.7           0.12270            0.16200          0.24390   \n",
       "555       357.6           0.13840            0.17100          0.20000   \n",
       "556       347.3           0.12650            0.12000          0.01005   \n",
       "557       330.6           0.10730            0.07158          0.00000   \n",
       "558       733.5           0.10260            0.31710          0.36620   \n",
       "559       474.2           0.12980            0.25170          0.36300   \n",
       "560       706.7           0.12410            0.22640          0.13260   \n",
       "561       439.6           0.09267            0.05494          0.00000   \n",
       "562       915.0           0.14170            0.79170          1.17000   \n",
       "563      1819.0           0.14070            0.41860          0.65990   \n",
       "564      2027.0           0.14100            0.21130          0.41070   \n",
       "565      1731.0           0.11660            0.19220          0.32150   \n",
       "566      1124.0           0.11390            0.30940          0.34030   \n",
       "567      1821.0           0.16500            0.86810          0.93870   \n",
       "568       268.6           0.08996            0.06444          0.00000   \n",
       "\n",
       "     worst concave points  worst symmetry  worst fractal dimension  target  \n",
       "0                 0.26540          0.4601                  0.11890     0.0  \n",
       "1                 0.18600          0.2750                  0.08902     0.0  \n",
       "2                 0.24300          0.3613                  0.08758     0.0  \n",
       "3                 0.25750          0.6638                  0.17300     0.0  \n",
       "4                 0.16250          0.2364                  0.07678     0.0  \n",
       "5                 0.17410          0.3985                  0.12440     0.0  \n",
       "6                 0.19320          0.3063                  0.08368     0.0  \n",
       "7                 0.15560          0.3196                  0.11510     0.0  \n",
       "8                 0.20600          0.4378                  0.10720     0.0  \n",
       "9                 0.22100          0.4366                  0.20750     0.0  \n",
       "10                0.09975          0.2948                  0.08452     0.0  \n",
       "11                0.18100          0.3792                  0.10480     0.0  \n",
       "12                0.17670          0.3176                  0.10230     0.0  \n",
       "13                0.11190          0.2809                  0.06287     0.0  \n",
       "14                0.22080          0.3596                  0.14310     0.0  \n",
       "15                0.17120          0.4218                  0.13410     0.0  \n",
       "16                0.16090          0.3029                  0.08216     0.0  \n",
       "17                0.20730          0.3706                  0.11420     0.0  \n",
       "18                0.23880          0.2768                  0.07615     0.0  \n",
       "19                0.12880          0.2977                  0.07259     1.0  \n",
       "20                0.07283          0.3184                  0.08183     1.0  \n",
       "21                0.06227          0.2450                  0.07773     1.0  \n",
       "22                0.23930          0.4667                  0.09946     0.0  \n",
       "23                0.20090          0.2822                  0.07526     0.0  \n",
       "24                0.20950          0.3613                  0.09564     0.0  \n",
       "25                0.25500          0.4066                  0.10590     0.0  \n",
       "26                0.27010          0.4264                  0.12750     0.0  \n",
       "27                0.14900          0.2341                  0.07421     0.0  \n",
       "28                0.20240          0.4027                  0.09876     0.0  \n",
       "29                0.14560          0.2756                  0.07919     0.0  \n",
       "..                    ...             ...                      ...     ...  \n",
       "539               0.05000          0.2790                  0.10660     1.0  \n",
       "540               0.06918          0.2329                  0.08134     1.0  \n",
       "541               0.12050          0.3187                  0.10230     1.0  \n",
       "542               0.10950          0.2722                  0.06956     1.0  \n",
       "543               0.07958          0.2473                  0.06443     1.0  \n",
       "544               0.06845          0.2249                  0.08492     1.0  \n",
       "545               0.07174          0.2642                  0.06953     1.0  \n",
       "546               0.02381          0.2681                  0.07399     1.0  \n",
       "547               0.08333          0.2691                  0.09479     1.0  \n",
       "548               0.03846          0.2552                  0.07920     1.0  \n",
       "549               0.03264          0.3059                  0.07626     1.0  \n",
       "550               0.00000          0.2458                  0.06592     1.0  \n",
       "551               0.06413          0.3169                  0.08032     1.0  \n",
       "552               0.06498          0.2407                  0.06484     1.0  \n",
       "553               0.02564          0.2435                  0.07393     1.0  \n",
       "554               0.06493          0.2372                  0.07242     1.0  \n",
       "555               0.09127          0.2226                  0.08283     1.0  \n",
       "556               0.02232          0.2262                  0.06742     1.0  \n",
       "557               0.00000          0.2475                  0.06969     1.0  \n",
       "558               0.11050          0.2258                  0.08004     1.0  \n",
       "559               0.09653          0.2112                  0.08732     1.0  \n",
       "560               0.10480          0.2250                  0.08321     1.0  \n",
       "561               0.00000          0.1566                  0.05905     1.0  \n",
       "562               0.23560          0.4089                  0.14090     0.0  \n",
       "563               0.25420          0.2929                  0.09873     0.0  \n",
       "564               0.22160          0.2060                  0.07115     0.0  \n",
       "565               0.16280          0.2572                  0.06637     0.0  \n",
       "566               0.14180          0.2218                  0.07820     0.0  \n",
       "567               0.26500          0.4087                  0.12400     0.0  \n",
       "568               0.00000          0.2871                  0.07039     1.0  \n",
       "\n",
       "[569 rows x 31 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_one():\n",
    "    df = pd.DataFrame(cancer['data'], columns=cancer['feature_names'])\n",
    "    df['target'] = cancer['target']\n",
    "    df['target'] = df['target'].astype(np.float)\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "    return df\n",
    "\n",
    "\n",
    "answer_one()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 2\n",
    "What is the class distribution? (i.e. how many instances of `malignant` (encoded 0) and how many `benign` (encoded 1)?)\n",
    "\n",
    "*This function should return a Series named `target` of length 2 with integer values and index =* `['malignant', 'benign']`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "malignant    212\n",
       "benign       357\n",
       "Name: target, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_two():\n",
    "    cancerdf = answer_one()\n",
    "    index = ['malignant', 'benign']\n",
    "    target = cancerdf['target'].value_counts().sort_values(ascending=True)\n",
    "    target.index = index\n",
    "\n",
    "    \n",
    "    return target\n",
    "\n",
    "\n",
    "answer_two()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 3\n",
    "Split the DataFrame into `X` (the data) and `y` (the labels).\n",
    "\n",
    "*This function should return a tuple of length 2:* `(X, y)`*, where* \n",
    "* `X`*, a pandas DataFrame, has shape* `(569, 30)`\n",
    "* `y`*, a pandas Series, has shape* `(569,)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(     mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       " 0         17.990         10.38          122.80     1001.0          0.11840   \n",
       " 1         20.570         17.77          132.90     1326.0          0.08474   \n",
       " 2         19.690         21.25          130.00     1203.0          0.10960   \n",
       " 3         11.420         20.38           77.58      386.1          0.14250   \n",
       " 4         20.290         14.34          135.10     1297.0          0.10030   \n",
       " 5         12.450         15.70           82.57      477.1          0.12780   \n",
       " 6         18.250         19.98          119.60     1040.0          0.09463   \n",
       " 7         13.710         20.83           90.20      577.9          0.11890   \n",
       " 8         13.000         21.82           87.50      519.8          0.12730   \n",
       " 9         12.460         24.04           83.97      475.9          0.11860   \n",
       " 10        16.020         23.24          102.70      797.8          0.08206   \n",
       " 11        15.780         17.89          103.60      781.0          0.09710   \n",
       " 12        19.170         24.80          132.40     1123.0          0.09740   \n",
       " 13        15.850         23.95          103.70      782.7          0.08401   \n",
       " 14        13.730         22.61           93.60      578.3          0.11310   \n",
       " 15        14.540         27.54           96.73      658.8          0.11390   \n",
       " 16        14.680         20.13           94.74      684.5          0.09867   \n",
       " 17        16.130         20.68          108.10      798.8          0.11700   \n",
       " 18        19.810         22.15          130.00     1260.0          0.09831   \n",
       " 19        13.540         14.36           87.46      566.3          0.09779   \n",
       " 20        13.080         15.71           85.63      520.0          0.10750   \n",
       " 21         9.504         12.44           60.34      273.9          0.10240   \n",
       " 22        15.340         14.26          102.50      704.4          0.10730   \n",
       " 23        21.160         23.04          137.20     1404.0          0.09428   \n",
       " 24        16.650         21.38          110.00      904.6          0.11210   \n",
       " 25        17.140         16.40          116.00      912.7          0.11860   \n",
       " 26        14.580         21.53           97.41      644.8          0.10540   \n",
       " 27        18.610         20.25          122.10     1094.0          0.09440   \n",
       " 28        15.300         25.27          102.40      732.4          0.10820   \n",
       " 29        17.570         15.05          115.00      955.1          0.09847   \n",
       " ..           ...           ...             ...        ...              ...   \n",
       " 539        7.691         25.44           48.34      170.4          0.08668   \n",
       " 540       11.540         14.44           74.65      402.9          0.09984   \n",
       " 541       14.470         24.99           95.81      656.4          0.08837   \n",
       " 542       14.740         25.42           94.70      668.6          0.08275   \n",
       " 543       13.210         28.06           84.88      538.4          0.08671   \n",
       " 544       13.870         20.70           89.77      584.8          0.09578   \n",
       " 545       13.620         23.23           87.19      573.2          0.09246   \n",
       " 546       10.320         16.35           65.31      324.9          0.09434   \n",
       " 547       10.260         16.58           65.85      320.8          0.08877   \n",
       " 548        9.683         19.34           61.05      285.7          0.08491   \n",
       " 549       10.820         24.21           68.89      361.6          0.08192   \n",
       " 550       10.860         21.48           68.51      360.5          0.07431   \n",
       " 551       11.130         22.44           71.49      378.4          0.09566   \n",
       " 552       12.770         29.43           81.35      507.9          0.08276   \n",
       " 553        9.333         21.94           59.01      264.0          0.09240   \n",
       " 554       12.880         28.92           82.50      514.3          0.08123   \n",
       " 555       10.290         27.61           65.67      321.4          0.09030   \n",
       " 556       10.160         19.59           64.73      311.7          0.10030   \n",
       " 557        9.423         27.88           59.26      271.3          0.08123   \n",
       " 558       14.590         22.68           96.39      657.1          0.08473   \n",
       " 559       11.510         23.93           74.52      403.5          0.09261   \n",
       " 560       14.050         27.15           91.38      600.4          0.09929   \n",
       " 561       11.200         29.37           70.67      386.0          0.07449   \n",
       " 562       15.220         30.62          103.40      716.9          0.10480   \n",
       " 563       20.920         25.09          143.00     1347.0          0.10990   \n",
       " 564       21.560         22.39          142.00     1479.0          0.11100   \n",
       " 565       20.130         28.25          131.20     1261.0          0.09780   \n",
       " 566       16.600         28.08          108.30      858.1          0.08455   \n",
       " 567       20.600         29.33          140.10     1265.0          0.11780   \n",
       " 568        7.760         24.54           47.92      181.0          0.05263   \n",
       " \n",
       "      mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       " 0             0.27760        0.300100             0.147100         0.2419   \n",
       " 1             0.07864        0.086900             0.070170         0.1812   \n",
       " 2             0.15990        0.197400             0.127900         0.2069   \n",
       " 3             0.28390        0.241400             0.105200         0.2597   \n",
       " 4             0.13280        0.198000             0.104300         0.1809   \n",
       " 5             0.17000        0.157800             0.080890         0.2087   \n",
       " 6             0.10900        0.112700             0.074000         0.1794   \n",
       " 7             0.16450        0.093660             0.059850         0.2196   \n",
       " 8             0.19320        0.185900             0.093530         0.2350   \n",
       " 9             0.23960        0.227300             0.085430         0.2030   \n",
       " 10            0.06669        0.032990             0.033230         0.1528   \n",
       " 11            0.12920        0.099540             0.066060         0.1842   \n",
       " 12            0.24580        0.206500             0.111800         0.2397   \n",
       " 13            0.10020        0.099380             0.053640         0.1847   \n",
       " 14            0.22930        0.212800             0.080250         0.2069   \n",
       " 15            0.15950        0.163900             0.073640         0.2303   \n",
       " 16            0.07200        0.073950             0.052590         0.1586   \n",
       " 17            0.20220        0.172200             0.102800         0.2164   \n",
       " 18            0.10270        0.147900             0.094980         0.1582   \n",
       " 19            0.08129        0.066640             0.047810         0.1885   \n",
       " 20            0.12700        0.045680             0.031100         0.1967   \n",
       " 21            0.06492        0.029560             0.020760         0.1815   \n",
       " 22            0.21350        0.207700             0.097560         0.2521   \n",
       " 23            0.10220        0.109700             0.086320         0.1769   \n",
       " 24            0.14570        0.152500             0.091700         0.1995   \n",
       " 25            0.22760        0.222900             0.140100         0.3040   \n",
       " 26            0.18680        0.142500             0.087830         0.2252   \n",
       " 27            0.10660        0.149000             0.077310         0.1697   \n",
       " 28            0.16970        0.168300             0.087510         0.1926   \n",
       " 29            0.11570        0.098750             0.079530         0.1739   \n",
       " ..                ...             ...                  ...            ...   \n",
       " 539           0.11990        0.092520             0.013640         0.2037   \n",
       " 540           0.11200        0.067370             0.025940         0.1818   \n",
       " 541           0.12300        0.100900             0.038900         0.1872   \n",
       " 542           0.07214        0.041050             0.030270         0.1840   \n",
       " 543           0.06877        0.029870             0.032750         0.1628   \n",
       " 544           0.10180        0.036880             0.023690         0.1620   \n",
       " 545           0.06747        0.029740             0.024430         0.1664   \n",
       " 546           0.04994        0.010120             0.005495         0.1885   \n",
       " 547           0.08066        0.043580             0.024380         0.1669   \n",
       " 548           0.05030        0.023370             0.009615         0.1580   \n",
       " 549           0.06602        0.015480             0.008160         0.1976   \n",
       " 550           0.04227        0.000000             0.000000         0.1661   \n",
       " 551           0.08194        0.048240             0.022570         0.2030   \n",
       " 552           0.04234        0.019970             0.014990         0.1539   \n",
       " 553           0.05605        0.039960             0.012820         0.1692   \n",
       " 554           0.05824        0.061950             0.023430         0.1566   \n",
       " 555           0.07658        0.059990             0.027380         0.1593   \n",
       " 556           0.07504        0.005025             0.011160         0.1791   \n",
       " 557           0.04971        0.000000             0.000000         0.1742   \n",
       " 558           0.13300        0.102900             0.037360         0.1454   \n",
       " 559           0.10210        0.111200             0.041050         0.1388   \n",
       " 560           0.11260        0.044620             0.043040         0.1537   \n",
       " 561           0.03558        0.000000             0.000000         0.1060   \n",
       " 562           0.20870        0.255000             0.094290         0.2128   \n",
       " 563           0.22360        0.317400             0.147400         0.2149   \n",
       " 564           0.11590        0.243900             0.138900         0.1726   \n",
       " 565           0.10340        0.144000             0.097910         0.1752   \n",
       " 566           0.10230        0.092510             0.053020         0.1590   \n",
       " 567           0.27700        0.351400             0.152000         0.2397   \n",
       " 568           0.04362        0.000000             0.000000         0.1587   \n",
       " \n",
       "      mean fractal dimension           ...             worst radius  \\\n",
       " 0                   0.07871           ...                   25.380   \n",
       " 1                   0.05667           ...                   24.990   \n",
       " 2                   0.05999           ...                   23.570   \n",
       " 3                   0.09744           ...                   14.910   \n",
       " 4                   0.05883           ...                   22.540   \n",
       " 5                   0.07613           ...                   15.470   \n",
       " 6                   0.05742           ...                   22.880   \n",
       " 7                   0.07451           ...                   17.060   \n",
       " 8                   0.07389           ...                   15.490   \n",
       " 9                   0.08243           ...                   15.090   \n",
       " 10                  0.05697           ...                   19.190   \n",
       " 11                  0.06082           ...                   20.420   \n",
       " 12                  0.07800           ...                   20.960   \n",
       " 13                  0.05338           ...                   16.840   \n",
       " 14                  0.07682           ...                   15.030   \n",
       " 15                  0.07077           ...                   17.460   \n",
       " 16                  0.05922           ...                   19.070   \n",
       " 17                  0.07356           ...                   20.960   \n",
       " 18                  0.05395           ...                   27.320   \n",
       " 19                  0.05766           ...                   15.110   \n",
       " 20                  0.06811           ...                   14.500   \n",
       " 21                  0.06905           ...                   10.230   \n",
       " 22                  0.07032           ...                   18.070   \n",
       " 23                  0.05278           ...                   29.170   \n",
       " 24                  0.06330           ...                   26.460   \n",
       " 25                  0.07413           ...                   22.250   \n",
       " 26                  0.06924           ...                   17.620   \n",
       " 27                  0.05699           ...                   21.310   \n",
       " 28                  0.06540           ...                   20.270   \n",
       " 29                  0.06149           ...                   20.010   \n",
       " ..                      ...           ...                      ...   \n",
       " 539                 0.07751           ...                    8.678   \n",
       " 540                 0.06782           ...                   12.260   \n",
       " 541                 0.06341           ...                   16.220   \n",
       " 542                 0.05680           ...                   16.510   \n",
       " 543                 0.05781           ...                   14.370   \n",
       " 544                 0.06688           ...                   15.050   \n",
       " 545                 0.05801           ...                   15.350   \n",
       " 546                 0.06201           ...                   11.250   \n",
       " 547                 0.06714           ...                   10.830   \n",
       " 548                 0.06235           ...                   10.930   \n",
       " 549                 0.06328           ...                   13.030   \n",
       " 550                 0.05948           ...                   11.660   \n",
       " 551                 0.06552           ...                   12.020   \n",
       " 552                 0.05637           ...                   13.870   \n",
       " 553                 0.06576           ...                    9.845   \n",
       " 554                 0.05708           ...                   13.890   \n",
       " 555                 0.06127           ...                   10.840   \n",
       " 556                 0.06331           ...                   10.650   \n",
       " 557                 0.06059           ...                   10.490   \n",
       " 558                 0.06147           ...                   15.480   \n",
       " 559                 0.06570           ...                   12.480   \n",
       " 560                 0.06171           ...                   15.300   \n",
       " 561                 0.05502           ...                   11.920   \n",
       " 562                 0.07152           ...                   17.520   \n",
       " 563                 0.06879           ...                   24.290   \n",
       " 564                 0.05623           ...                   25.450   \n",
       " 565                 0.05533           ...                   23.690   \n",
       " 566                 0.05648           ...                   18.980   \n",
       " 567                 0.07016           ...                   25.740   \n",
       " 568                 0.05884           ...                    9.456   \n",
       " \n",
       "      worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       " 0            17.33           184.60      2019.0           0.16220   \n",
       " 1            23.41           158.80      1956.0           0.12380   \n",
       " 2            25.53           152.50      1709.0           0.14440   \n",
       " 3            26.50            98.87       567.7           0.20980   \n",
       " 4            16.67           152.20      1575.0           0.13740   \n",
       " 5            23.75           103.40       741.6           0.17910   \n",
       " 6            27.66           153.20      1606.0           0.14420   \n",
       " 7            28.14           110.60       897.0           0.16540   \n",
       " 8            30.73           106.20       739.3           0.17030   \n",
       " 9            40.68            97.65       711.4           0.18530   \n",
       " 10           33.88           123.80      1150.0           0.11810   \n",
       " 11           27.28           136.50      1299.0           0.13960   \n",
       " 12           29.94           151.70      1332.0           0.10370   \n",
       " 13           27.66           112.00       876.5           0.11310   \n",
       " 14           32.01           108.80       697.7           0.16510   \n",
       " 15           37.13           124.10       943.2           0.16780   \n",
       " 16           30.88           123.40      1138.0           0.14640   \n",
       " 17           31.48           136.80      1315.0           0.17890   \n",
       " 18           30.88           186.80      2398.0           0.15120   \n",
       " 19           19.26            99.70       711.2           0.14400   \n",
       " 20           20.49            96.09       630.5           0.13120   \n",
       " 21           15.66            65.13       314.9           0.13240   \n",
       " 22           19.08           125.10       980.9           0.13900   \n",
       " 23           35.59           188.00      2615.0           0.14010   \n",
       " 24           31.56           177.00      2215.0           0.18050   \n",
       " 25           21.40           152.40      1461.0           0.15450   \n",
       " 26           33.21           122.40       896.9           0.15250   \n",
       " 27           27.26           139.90      1403.0           0.13380   \n",
       " 28           36.71           149.30      1269.0           0.16410   \n",
       " 29           19.52           134.90      1227.0           0.12550   \n",
       " ..             ...              ...         ...               ...   \n",
       " 539          31.89            54.49       223.6           0.15960   \n",
       " 540          19.68            78.78       457.8           0.13450   \n",
       " 541          31.73           113.50       808.9           0.13400   \n",
       " 542          32.29           107.40       826.4           0.10600   \n",
       " 543          37.17            92.48       629.6           0.10720   \n",
       " 544          24.75            99.17       688.6           0.12640   \n",
       " 545          29.09            97.58       729.8           0.12160   \n",
       " 546          21.77            71.12       384.9           0.12850   \n",
       " 547          22.04            71.08       357.4           0.14610   \n",
       " 548          25.59            69.10       364.2           0.11990   \n",
       " 549          31.45            83.90       505.6           0.12040   \n",
       " 550          24.77            74.08       412.3           0.10010   \n",
       " 551          28.26            77.80       436.6           0.10870   \n",
       " 552          36.00            88.10       594.7           0.12340   \n",
       " 553          25.05            62.86       295.8           0.11030   \n",
       " 554          35.74            88.84       595.7           0.12270   \n",
       " 555          34.91            69.57       357.6           0.13840   \n",
       " 556          22.88            67.88       347.3           0.12650   \n",
       " 557          34.24            66.50       330.6           0.10730   \n",
       " 558          27.27           105.90       733.5           0.10260   \n",
       " 559          37.16            82.28       474.2           0.12980   \n",
       " 560          33.17           100.20       706.7           0.12410   \n",
       " 561          38.30            75.19       439.6           0.09267   \n",
       " 562          42.79           128.70       915.0           0.14170   \n",
       " 563          29.41           179.10      1819.0           0.14070   \n",
       " 564          26.40           166.10      2027.0           0.14100   \n",
       " 565          38.25           155.00      1731.0           0.11660   \n",
       " 566          34.12           126.70      1124.0           0.11390   \n",
       " 567          39.42           184.60      1821.0           0.16500   \n",
       " 568          30.37            59.16       268.6           0.08996   \n",
       " \n",
       "      worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       " 0              0.66560          0.71190               0.26540          0.4601   \n",
       " 1              0.18660          0.24160               0.18600          0.2750   \n",
       " 2              0.42450          0.45040               0.24300          0.3613   \n",
       " 3              0.86630          0.68690               0.25750          0.6638   \n",
       " 4              0.20500          0.40000               0.16250          0.2364   \n",
       " 5              0.52490          0.53550               0.17410          0.3985   \n",
       " 6              0.25760          0.37840               0.19320          0.3063   \n",
       " 7              0.36820          0.26780               0.15560          0.3196   \n",
       " 8              0.54010          0.53900               0.20600          0.4378   \n",
       " 9              1.05800          1.10500               0.22100          0.4366   \n",
       " 10             0.15510          0.14590               0.09975          0.2948   \n",
       " 11             0.56090          0.39650               0.18100          0.3792   \n",
       " 12             0.39030          0.36390               0.17670          0.3176   \n",
       " 13             0.19240          0.23220               0.11190          0.2809   \n",
       " 14             0.77250          0.69430               0.22080          0.3596   \n",
       " 15             0.65770          0.70260               0.17120          0.4218   \n",
       " 16             0.18710          0.29140               0.16090          0.3029   \n",
       " 17             0.42330          0.47840               0.20730          0.3706   \n",
       " 18             0.31500          0.53720               0.23880          0.2768   \n",
       " 19             0.17730          0.23900               0.12880          0.2977   \n",
       " 20             0.27760          0.18900               0.07283          0.3184   \n",
       " 21             0.11480          0.08867               0.06227          0.2450   \n",
       " 22             0.59540          0.63050               0.23930          0.4667   \n",
       " 23             0.26000          0.31550               0.20090          0.2822   \n",
       " 24             0.35780          0.46950               0.20950          0.3613   \n",
       " 25             0.39490          0.38530               0.25500          0.4066   \n",
       " 26             0.66430          0.55390               0.27010          0.4264   \n",
       " 27             0.21170          0.34460               0.14900          0.2341   \n",
       " 28             0.61100          0.63350               0.20240          0.4027   \n",
       " 29             0.28120          0.24890               0.14560          0.2756   \n",
       " ..                 ...              ...                   ...             ...   \n",
       " 539            0.30640          0.33930               0.05000          0.2790   \n",
       " 540            0.21180          0.17970               0.06918          0.2329   \n",
       " 541            0.42020          0.40400               0.12050          0.3187   \n",
       " 542            0.13760          0.16110               0.10950          0.2722   \n",
       " 543            0.13810          0.10620               0.07958          0.2473   \n",
       " 544            0.20370          0.13770               0.06845          0.2249   \n",
       " 545            0.15170          0.10490               0.07174          0.2642   \n",
       " 546            0.08842          0.04384               0.02381          0.2681   \n",
       " 547            0.22460          0.17830               0.08333          0.2691   \n",
       " 548            0.09546          0.09350               0.03846          0.2552   \n",
       " 549            0.16330          0.06194               0.03264          0.3059   \n",
       " 550            0.07348          0.00000               0.00000          0.2458   \n",
       " 551            0.17820          0.15640               0.06413          0.3169   \n",
       " 552            0.10640          0.08653               0.06498          0.2407   \n",
       " 553            0.08298          0.07993               0.02564          0.2435   \n",
       " 554            0.16200          0.24390               0.06493          0.2372   \n",
       " 555            0.17100          0.20000               0.09127          0.2226   \n",
       " 556            0.12000          0.01005               0.02232          0.2262   \n",
       " 557            0.07158          0.00000               0.00000          0.2475   \n",
       " 558            0.31710          0.36620               0.11050          0.2258   \n",
       " 559            0.25170          0.36300               0.09653          0.2112   \n",
       " 560            0.22640          0.13260               0.10480          0.2250   \n",
       " 561            0.05494          0.00000               0.00000          0.1566   \n",
       " 562            0.79170          1.17000               0.23560          0.4089   \n",
       " 563            0.41860          0.65990               0.25420          0.2929   \n",
       " 564            0.21130          0.41070               0.22160          0.2060   \n",
       " 565            0.19220          0.32150               0.16280          0.2572   \n",
       " 566            0.30940          0.34030               0.14180          0.2218   \n",
       " 567            0.86810          0.93870               0.26500          0.4087   \n",
       " 568            0.06444          0.00000               0.00000          0.2871   \n",
       " \n",
       "      worst fractal dimension  \n",
       " 0                    0.11890  \n",
       " 1                    0.08902  \n",
       " 2                    0.08758  \n",
       " 3                    0.17300  \n",
       " 4                    0.07678  \n",
       " 5                    0.12440  \n",
       " 6                    0.08368  \n",
       " 7                    0.11510  \n",
       " 8                    0.10720  \n",
       " 9                    0.20750  \n",
       " 10                   0.08452  \n",
       " 11                   0.10480  \n",
       " 12                   0.10230  \n",
       " 13                   0.06287  \n",
       " 14                   0.14310  \n",
       " 15                   0.13410  \n",
       " 16                   0.08216  \n",
       " 17                   0.11420  \n",
       " 18                   0.07615  \n",
       " 19                   0.07259  \n",
       " 20                   0.08183  \n",
       " 21                   0.07773  \n",
       " 22                   0.09946  \n",
       " 23                   0.07526  \n",
       " 24                   0.09564  \n",
       " 25                   0.10590  \n",
       " 26                   0.12750  \n",
       " 27                   0.07421  \n",
       " 28                   0.09876  \n",
       " 29                   0.07919  \n",
       " ..                       ...  \n",
       " 539                  0.10660  \n",
       " 540                  0.08134  \n",
       " 541                  0.10230  \n",
       " 542                  0.06956  \n",
       " 543                  0.06443  \n",
       " 544                  0.08492  \n",
       " 545                  0.06953  \n",
       " 546                  0.07399  \n",
       " 547                  0.09479  \n",
       " 548                  0.07920  \n",
       " 549                  0.07626  \n",
       " 550                  0.06592  \n",
       " 551                  0.08032  \n",
       " 552                  0.06484  \n",
       " 553                  0.07393  \n",
       " 554                  0.07242  \n",
       " 555                  0.08283  \n",
       " 556                  0.06742  \n",
       " 557                  0.06969  \n",
       " 558                  0.08004  \n",
       " 559                  0.08732  \n",
       " 560                  0.08321  \n",
       " 561                  0.05905  \n",
       " 562                  0.14090  \n",
       " 563                  0.09873  \n",
       " 564                  0.07115  \n",
       " 565                  0.06637  \n",
       " 566                  0.07820  \n",
       " 567                  0.12400  \n",
       " 568                  0.07039  \n",
       " \n",
       " [569 rows x 30 columns], 0      0.0\n",
       " 1      0.0\n",
       " 2      0.0\n",
       " 3      0.0\n",
       " 4      0.0\n",
       " 5      0.0\n",
       " 6      0.0\n",
       " 7      0.0\n",
       " 8      0.0\n",
       " 9      0.0\n",
       " 10     0.0\n",
       " 11     0.0\n",
       " 12     0.0\n",
       " 13     0.0\n",
       " 14     0.0\n",
       " 15     0.0\n",
       " 16     0.0\n",
       " 17     0.0\n",
       " 18     0.0\n",
       " 19     1.0\n",
       " 20     1.0\n",
       " 21     1.0\n",
       " 22     0.0\n",
       " 23     0.0\n",
       " 24     0.0\n",
       " 25     0.0\n",
       " 26     0.0\n",
       " 27     0.0\n",
       " 28     0.0\n",
       " 29     0.0\n",
       "       ... \n",
       " 539    1.0\n",
       " 540    1.0\n",
       " 541    1.0\n",
       " 542    1.0\n",
       " 543    1.0\n",
       " 544    1.0\n",
       " 545    1.0\n",
       " 546    1.0\n",
       " 547    1.0\n",
       " 548    1.0\n",
       " 549    1.0\n",
       " 550    1.0\n",
       " 551    1.0\n",
       " 552    1.0\n",
       " 553    1.0\n",
       " 554    1.0\n",
       " 555    1.0\n",
       " 556    1.0\n",
       " 557    1.0\n",
       " 558    1.0\n",
       " 559    1.0\n",
       " 560    1.0\n",
       " 561    1.0\n",
       " 562    0.0\n",
       " 563    0.0\n",
       " 564    0.0\n",
       " 565    0.0\n",
       " 566    0.0\n",
       " 567    0.0\n",
       " 568    1.0\n",
       " Name: target, dtype: float64)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_three():\n",
    "    cancerdf = answer_one()\n",
    "    y = cancerdf['target']\n",
    "    X = cancerdf.drop('target', axis=1)\n",
    "    \n",
    "    return X, y\n",
    "answer_three()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 4\n",
    "Using `train_test_split`, split `X` and `y` into training and test sets `(X_train, X_test, y_train, and y_test)`.\n",
    "\n",
    "**Set the random number generator state to 0 using `random_state=0` to make sure your results match the autograder!**\n",
    "\n",
    "*This function should return a tuple of length 4:* `(X_train, X_test, y_train, y_test)`*, where* \n",
    "* `X_train` *has shape* `(426, 30)`\n",
    "* `X_test` *has shape* `(143, 30)`\n",
    "* `y_train` *has shape* `(426,)`\n",
    "* `y_test` *has shape* `(143,)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(     mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       " 293       11.850         17.46           75.54      432.7          0.08372   \n",
       " 332       11.220         19.86           71.94      387.3          0.10540   \n",
       " 565       20.130         28.25          131.20     1261.0          0.09780   \n",
       " 278       13.590         17.84           86.24      572.3          0.07948   \n",
       " 489       16.690         20.20          107.10      857.6          0.07497   \n",
       " 346       12.060         18.90           76.66      445.3          0.08386   \n",
       " 357       13.870         16.21           88.52      593.7          0.08743   \n",
       " 355       12.560         19.07           81.92      485.8          0.08760   \n",
       " 112       14.260         19.65           97.83      629.9          0.07837   \n",
       " 68         9.029         17.33           58.79      250.5          0.10660   \n",
       " 526       13.460         18.75           87.44      551.1          0.10750   \n",
       " 206        9.876         17.27           62.92      295.4          0.10890   \n",
       " 65        14.780         23.94           97.40      668.3          0.11720   \n",
       " 437       14.040         15.98           89.78      611.2          0.08458   \n",
       " 126       13.610         24.69           87.76      572.6          0.09258   \n",
       " 429       12.720         17.67           80.98      501.3          0.07896   \n",
       " 392       15.490         19.97          102.40      744.7          0.11600   \n",
       " 343       19.680         21.68          129.90     1194.0          0.09797   \n",
       " 334       12.300         19.02           77.88      464.4          0.08313   \n",
       " 440       10.970         17.20           71.73      371.5          0.08915   \n",
       " 441       17.270         25.42          112.40      928.8          0.08331   \n",
       " 137       11.430         15.39           73.06      399.8          0.09639   \n",
       " 230       17.050         19.08          113.40      895.0          0.11410   \n",
       " 7         13.710         20.83           90.20      577.9          0.11890   \n",
       " 408       17.990         20.66          117.80      991.7          0.10360   \n",
       " 523       13.710         18.68           88.73      571.0          0.09916   \n",
       " 361       13.300         21.57           85.24      546.1          0.08582   \n",
       " 553        9.333         21.94           59.01      264.0          0.09240   \n",
       " 478       11.490         14.59           73.99      404.9          0.10460   \n",
       " 303       10.490         18.61           66.86      334.3          0.10680   \n",
       " ..           ...           ...             ...        ...              ...   \n",
       " 459        9.755         28.20           61.68      290.9          0.07984   \n",
       " 510       11.740         14.69           76.31      426.0          0.08099   \n",
       " 151        8.219         20.70           53.27      203.9          0.09405   \n",
       " 244       19.400         23.50          129.10     1155.0          0.10270   \n",
       " 543       13.210         28.06           84.88      538.4          0.08671   \n",
       " 544       13.870         20.70           89.77      584.8          0.09578   \n",
       " 265       20.730         31.12          135.70     1419.0          0.09469   \n",
       " 288       11.260         19.96           73.72      394.1          0.08020   \n",
       " 423       13.660         19.13           89.46      575.3          0.09057   \n",
       " 147       14.950         18.77           97.84      689.5          0.08138   \n",
       " 177       16.460         20.11          109.30      832.9          0.09831   \n",
       " 99        14.420         19.77           94.48      642.5          0.09752   \n",
       " 448       14.530         19.34           94.25      659.7          0.08388   \n",
       " 431       12.400         17.68           81.47      467.8          0.10540   \n",
       " 115       11.930         21.53           76.53      438.6          0.09768   \n",
       " 72        17.200         24.52          114.20      929.4          0.10710   \n",
       " 537       11.690         24.44           76.37      406.4          0.12360   \n",
       " 174       10.660         15.15           67.49      349.6          0.08792   \n",
       " 87        19.020         24.59          122.00     1076.0          0.09029   \n",
       " 551       11.130         22.44           71.49      378.4          0.09566   \n",
       " 486       14.640         16.85           94.21      666.0          0.08641   \n",
       " 314        8.597         18.60           54.09      221.2          0.10740   \n",
       " 396       13.510         18.89           88.10      558.1          0.10590   \n",
       " 472       14.920         14.93           96.45      686.9          0.08098   \n",
       " 70        18.940         21.31          123.60     1130.0          0.09009   \n",
       " 277       18.810         19.98          120.90     1102.0          0.08923   \n",
       " 9         12.460         24.04           83.97      475.9          0.11860   \n",
       " 359        9.436         18.32           59.82      278.6          0.10090   \n",
       " 192        9.720         18.22           60.73      288.1          0.06950   \n",
       " 559       11.510         23.93           74.52      403.5          0.09261   \n",
       " \n",
       "      mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       " 293           0.05642        0.026880             0.022800         0.1875   \n",
       " 332           0.06779        0.005006             0.007583         0.1940   \n",
       " 565           0.10340        0.144000             0.097910         0.1752   \n",
       " 278           0.04052        0.019970             0.012380         0.1573   \n",
       " 489           0.07112        0.036490             0.023070         0.1846   \n",
       " 346           0.05794        0.007510             0.008488         0.1555   \n",
       " 357           0.05492        0.015020             0.020880         0.1424   \n",
       " 355           0.10380        0.103000             0.043910         0.1533   \n",
       " 112           0.22330        0.300300             0.077980         0.1704   \n",
       " 68            0.14130        0.313000             0.043750         0.2111   \n",
       " 526           0.11380        0.042010             0.031520         0.1723   \n",
       " 206           0.07232        0.017560             0.019520         0.1934   \n",
       " 65            0.14790        0.126700             0.090290         0.1953   \n",
       " 437           0.05895        0.035340             0.029440         0.1714   \n",
       " 126           0.07862        0.052850             0.030850         0.1761   \n",
       " 429           0.04522        0.014020             0.018350         0.1459   \n",
       " 392           0.15620        0.189100             0.091130         0.1929   \n",
       " 343           0.13390        0.186300             0.110300         0.2082   \n",
       " 334           0.04202        0.007756             0.008535         0.1539   \n",
       " 440           0.11130        0.094570             0.036130         0.1489   \n",
       " 441           0.11090        0.120400             0.057360         0.1467   \n",
       " 137           0.06889        0.035030             0.028750         0.1734   \n",
       " 230           0.15720        0.191000             0.109000         0.2131   \n",
       " 7             0.16450        0.093660             0.059850         0.2196   \n",
       " 408           0.13040        0.120100             0.088240         0.1992   \n",
       " 523           0.10700        0.053850             0.037830         0.1714   \n",
       " 361           0.06373        0.033440             0.024240         0.1815   \n",
       " 553           0.05605        0.039960             0.012820         0.1692   \n",
       " 478           0.08228        0.053080             0.019690         0.1779   \n",
       " 303           0.06678        0.022970             0.017800         0.1482   \n",
       " ..                ...             ...                  ...            ...   \n",
       " 459           0.04626        0.015410             0.010430         0.1621   \n",
       " 510           0.09661        0.067260             0.026390         0.1499   \n",
       " 151           0.13050        0.132100             0.021680         0.2222   \n",
       " 244           0.15580        0.204900             0.088860         0.1978   \n",
       " 543           0.06877        0.029870             0.032750         0.1628   \n",
       " 544           0.10180        0.036880             0.023690         0.1620   \n",
       " 265           0.11430        0.136700             0.086460         0.1769   \n",
       " 288           0.11810        0.092740             0.055880         0.2595   \n",
       " 423           0.11470        0.096570             0.048120         0.1848   \n",
       " 147           0.11670        0.090500             0.035620         0.1744   \n",
       " 177           0.15560        0.179300             0.088660         0.1794   \n",
       " 99            0.11410        0.093880             0.058390         0.1879   \n",
       " 448           0.07800        0.088170             0.029250         0.1473   \n",
       " 431           0.13160        0.077410             0.027990         0.1811   \n",
       " 115           0.07849        0.033280             0.020080         0.1688   \n",
       " 72            0.18300        0.169200             0.079440         0.1927   \n",
       " 537           0.15520        0.045150             0.045310         0.2131   \n",
       " 174           0.04302        0.000000             0.000000         0.1928   \n",
       " 87            0.12060        0.146800             0.082710         0.1953   \n",
       " 551           0.08194        0.048240             0.022570         0.2030   \n",
       " 486           0.06698        0.051920             0.027910         0.1409   \n",
       " 314           0.05847        0.000000             0.000000         0.2163   \n",
       " 396           0.11470        0.085800             0.053810         0.1806   \n",
       " 472           0.08549        0.055390             0.032210         0.1687   \n",
       " 70            0.10290        0.108000             0.079510         0.1582   \n",
       " 277           0.05884        0.080200             0.058430         0.1550   \n",
       " 9             0.23960        0.227300             0.085430         0.2030   \n",
       " 359           0.05956        0.027100             0.014060         0.1506   \n",
       " 192           0.02344        0.000000             0.000000         0.1653   \n",
       " 559           0.10210        0.111200             0.041050         0.1388   \n",
       " \n",
       "      mean fractal dimension           ...             worst radius  \\\n",
       " 293                 0.05715           ...                   13.060   \n",
       " 332                 0.06028           ...                   11.980   \n",
       " 565                 0.05533           ...                   23.690   \n",
       " 278                 0.05520           ...                   15.500   \n",
       " 489                 0.05325           ...                   19.180   \n",
       " 346                 0.06048           ...                   13.640   \n",
       " 357                 0.05883           ...                   15.110   \n",
       " 355                 0.06184           ...                   13.370   \n",
       " 112                 0.07769           ...                   15.300   \n",
       " 68                  0.08046           ...                   10.310   \n",
       " 526                 0.06317           ...                   15.350   \n",
       " 206                 0.06285           ...                   10.420   \n",
       " 65                  0.06654           ...                   17.310   \n",
       " 437                 0.05898           ...                   15.660   \n",
       " 126                 0.06130           ...                   16.890   \n",
       " 429                 0.05544           ...                   13.820   \n",
       " 392                 0.06744           ...                   21.200   \n",
       " 343                 0.05715           ...                   22.750   \n",
       " 334                 0.05945           ...                   13.350   \n",
       " 440                 0.06640           ...                   12.360   \n",
       " 441                 0.05407           ...                   20.380   \n",
       " 137                 0.05865           ...                   12.320   \n",
       " 230                 0.06325           ...                   19.590   \n",
       " 7                   0.07451           ...                   17.060   \n",
       " 408                 0.06069           ...                   21.080   \n",
       " 523                 0.06843           ...                   15.110   \n",
       " 361                 0.05696           ...                   14.200   \n",
       " 553                 0.06576           ...                    9.845   \n",
       " 478                 0.06574           ...                   12.400   \n",
       " 303                 0.06600           ...                   11.060   \n",
       " ..                      ...           ...                      ...   \n",
       " 459                 0.05952           ...                   10.670   \n",
       " 510                 0.06758           ...                   12.450   \n",
       " 151                 0.08261           ...                    9.092   \n",
       " 244                 0.06000           ...                   21.650   \n",
       " 543                 0.05781           ...                   14.370   \n",
       " 544                 0.06688           ...                   15.050   \n",
       " 265                 0.05674           ...                   32.490   \n",
       " 288                 0.06233           ...                   11.860   \n",
       " 423                 0.06181           ...                   15.140   \n",
       " 147                 0.06493           ...                   16.250   \n",
       " 177                 0.06323           ...                   17.790   \n",
       " 99                  0.06390           ...                   16.330   \n",
       " 448                 0.05746           ...                   16.300   \n",
       " 431                 0.07102           ...                   12.880   \n",
       " 115                 0.06194           ...                   13.670   \n",
       " 72                  0.06487           ...                   23.320   \n",
       " 537                 0.07405           ...                   12.980   \n",
       " 174                 0.05975           ...                   11.540   \n",
       " 87                  0.05629           ...                   24.560   \n",
       " 551                 0.06552           ...                   12.020   \n",
       " 486                 0.05355           ...                   16.460   \n",
       " 314                 0.07359           ...                    8.952   \n",
       " 396                 0.06079           ...                   14.800   \n",
       " 472                 0.05669           ...                   17.180   \n",
       " 70                  0.05461           ...                   24.860   \n",
       " 277                 0.04996           ...                   19.960   \n",
       " 9                   0.08243           ...                   15.090   \n",
       " 359                 0.06959           ...                   12.020   \n",
       " 192                 0.06447           ...                    9.968   \n",
       " 559                 0.06570           ...                   12.480   \n",
       " \n",
       "      worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       " 293          25.75            84.35       517.8           0.13690   \n",
       " 332          25.78            76.91       436.1           0.14240   \n",
       " 565          38.25           155.00      1731.0           0.11660   \n",
       " 278          26.10            98.91       739.1           0.10500   \n",
       " 489          26.56           127.30      1084.0           0.10090   \n",
       " 346          27.06            86.54       562.6           0.12890   \n",
       " 357          25.58            96.74       694.4           0.11530   \n",
       " 355          22.43            89.02       547.4           0.10960   \n",
       " 112          23.73           107.00       709.0           0.08949   \n",
       " 68           22.65            65.50       324.7           0.14820   \n",
       " 526          25.16           101.90       719.8           0.16240   \n",
       " 206          23.22            67.08       331.6           0.14150   \n",
       " 65           33.39           114.60       925.1           0.16480   \n",
       " 437          21.58           101.20       750.0           0.11950   \n",
       " 126          35.64           113.20       848.7           0.14710   \n",
       " 429          20.96            88.87       586.8           0.10680   \n",
       " 392          29.41           142.10      1359.0           0.16810   \n",
       " 343          34.66           157.60      1540.0           0.12180   \n",
       " 334          28.46            84.53       544.3           0.12220   \n",
       " 440          26.87            90.14       476.4           0.13910   \n",
       " 441          35.46           132.80      1284.0           0.14360   \n",
       " 137          22.02            79.93       462.0           0.11900   \n",
       " 230          24.89           133.50      1189.0           0.17030   \n",
       " 7            28.14           110.60       897.0           0.16540   \n",
       " 408          25.41           138.10      1349.0           0.14820   \n",
       " 523          25.63            99.43       701.9           0.14250   \n",
       " 361          29.20            92.94       621.2           0.11400   \n",
       " 553          25.05            62.86       295.8           0.11030   \n",
       " 478          21.90            82.04       467.6           0.13520   \n",
       " 303          24.54            70.76       375.4           0.14130   \n",
       " ..             ...              ...         ...               ...   \n",
       " 459          36.92            68.03       349.9           0.11100   \n",
       " 510          17.60            81.25       473.8           0.10730   \n",
       " 151          29.72            58.08       249.8           0.16300   \n",
       " 244          30.53           144.90      1417.0           0.14630   \n",
       " 543          37.17            92.48       629.6           0.10720   \n",
       " 544          24.75            99.17       688.6           0.12640   \n",
       " 265          47.16           214.00      3432.0           0.14010   \n",
       " 288          22.33            78.27       437.6           0.10280   \n",
       " 423          25.50           101.40       708.8           0.11470   \n",
       " 147          25.47           107.10       809.7           0.09970   \n",
       " 177          28.45           123.50       981.2           0.14150   \n",
       " 99           30.86           109.50       826.4           0.14310   \n",
       " 448          28.39           108.10       830.5           0.10890   \n",
       " 431          22.91            89.61       515.8           0.14500   \n",
       " 115          26.15            87.54       583.0           0.15000   \n",
       " 72           33.82           151.60      1681.0           0.15850   \n",
       " 537          32.19            86.12       487.7           0.17680   \n",
       " 174          19.20            73.20       408.3           0.10760   \n",
       " 87           30.41           152.90      1623.0           0.12490   \n",
       " 551          28.26            77.80       436.6           0.10870   \n",
       " 486          25.44           106.00       831.0           0.11420   \n",
       " 314          22.44            56.65       240.1           0.13470   \n",
       " 396          27.20            97.33       675.2           0.14280   \n",
       " 472          18.22           112.00       906.6           0.10650   \n",
       " 70           26.58           165.90      1866.0           0.11930   \n",
       " 277          24.30           129.00      1236.0           0.12430   \n",
       " 9            40.68            97.65       711.4           0.18530   \n",
       " 359          25.02            75.79       439.6           0.13330   \n",
       " 192          20.83            62.25       303.8           0.07117   \n",
       " 559          37.16            82.28       474.2           0.12980   \n",
       " \n",
       "      worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       " 293            0.17580          0.13160               0.09140          0.3101   \n",
       " 332            0.09669          0.01335               0.02022          0.3292   \n",
       " 565            0.19220          0.32150               0.16280          0.2572   \n",
       " 278            0.07622          0.10600               0.05185          0.2335   \n",
       " 489            0.29200          0.24770               0.08737          0.4677   \n",
       " 346            0.13520          0.04506               0.05093          0.2880   \n",
       " 357            0.10080          0.05285               0.05556          0.2362   \n",
       " 355            0.20020          0.23880               0.09265          0.2121   \n",
       " 112            0.41930          0.67830               0.15050          0.2398   \n",
       " 68             0.43650          1.25200               0.17500          0.4228   \n",
       " 526            0.31240          0.26540               0.14270          0.3518   \n",
       " 206            0.12470          0.06213               0.05588          0.2989   \n",
       " 65             0.34160          0.30240               0.16140          0.3321   \n",
       " 437            0.12520          0.11170               0.07453          0.2725   \n",
       " 126            0.28840          0.37960               0.13290          0.3470   \n",
       " 429            0.09605          0.03469               0.03612          0.2165   \n",
       " 392            0.39130          0.55530               0.21210          0.3187   \n",
       " 343            0.34580          0.47340               0.22550          0.4045   \n",
       " 334            0.09052          0.03619               0.03983          0.2554   \n",
       " 440            0.40820          0.47790               0.15550          0.2540   \n",
       " 441            0.41220          0.50360               0.17390          0.2500   \n",
       " 137            0.16480          0.13990               0.08476          0.2676   \n",
       " 230            0.39340          0.50180               0.25430          0.3109   \n",
       " 7              0.36820          0.26780               0.15560          0.3196   \n",
       " 408            0.37350          0.33010               0.19740          0.3060   \n",
       " 523            0.25660          0.19350               0.12840          0.2849   \n",
       " 361            0.16670          0.12120               0.05614          0.2637   \n",
       " 553            0.08298          0.07993               0.02564          0.2435   \n",
       " 478            0.20100          0.25960               0.07431          0.2941   \n",
       " 303            0.10440          0.08423               0.06528          0.2213   \n",
       " ..                 ...              ...                   ...             ...   \n",
       " 459            0.11090          0.07190               0.04866          0.2321   \n",
       " 510            0.27930          0.26900               0.10560          0.2604   \n",
       " 151            0.43100          0.53810               0.07879          0.3322   \n",
       " 244            0.29680          0.34580               0.15640          0.2920   \n",
       " 543            0.13810          0.10620               0.07958          0.2473   \n",
       " 544            0.20370          0.13770               0.06845          0.2249   \n",
       " 265            0.26440          0.34420               0.16590          0.2868   \n",
       " 288            0.18430          0.15460               0.09314          0.2955   \n",
       " 423            0.31670          0.36600               0.14070          0.2744   \n",
       " 147            0.25210          0.25000               0.08405          0.2852   \n",
       " 177            0.46670          0.58620               0.20350          0.3054   \n",
       " 99             0.30260          0.31940               0.15650          0.2718   \n",
       " 448            0.26490          0.37790               0.09594          0.2471   \n",
       " 431            0.26290          0.24030               0.07370          0.2556   \n",
       " 115            0.23990          0.15030               0.07247          0.2438   \n",
       " 72             0.73940          0.65660               0.18990          0.3313   \n",
       " 537            0.32510          0.13950               0.13080          0.2803   \n",
       " 174            0.06791          0.00000               0.00000          0.2710   \n",
       " 87             0.32060          0.57550               0.19560          0.3956   \n",
       " 551            0.17820          0.15640               0.06413          0.3169   \n",
       " 486            0.20700          0.24370               0.07828          0.2455   \n",
       " 314            0.07767          0.00000               0.00000          0.3142   \n",
       " 396            0.25700          0.34380               0.14530          0.2666   \n",
       " 472            0.27910          0.31510               0.11470          0.2688   \n",
       " 70             0.23360          0.26870               0.17890          0.2551   \n",
       " 277            0.11600          0.22100               0.12940          0.2567   \n",
       " 9              1.05800          1.10500               0.22100          0.4366   \n",
       " 359            0.10490          0.11440               0.05052          0.2454   \n",
       " 192            0.02729          0.00000               0.00000          0.1909   \n",
       " 559            0.25170          0.36300               0.09653          0.2112   \n",
       " \n",
       "      worst fractal dimension  \n",
       " 293                  0.07007  \n",
       " 332                  0.06522  \n",
       " 565                  0.06637  \n",
       " 278                  0.06263  \n",
       " 489                  0.07623  \n",
       " 346                  0.08083  \n",
       " 357                  0.07113  \n",
       " 355                  0.07188  \n",
       " 112                  0.10820  \n",
       " 68                   0.11750  \n",
       " 526                  0.08665  \n",
       " 206                  0.07380  \n",
       " 65                   0.08911  \n",
       " 437                  0.07234  \n",
       " 126                  0.07900  \n",
       " 429                  0.06025  \n",
       " 392                  0.10190  \n",
       " 343                  0.07918  \n",
       " 334                  0.07207  \n",
       " 440                  0.09532  \n",
       " 441                  0.07944  \n",
       " 137                  0.06765  \n",
       " 230                  0.09061  \n",
       " 7                    0.11510  \n",
       " 408                  0.08503  \n",
       " 523                  0.09031  \n",
       " 361                  0.06658  \n",
       " 553                  0.07393  \n",
       " 478                  0.09180  \n",
       " 303                  0.07842  \n",
       " ..                       ...  \n",
       " 459                  0.07211  \n",
       " 510                  0.09879  \n",
       " 151                  0.14860  \n",
       " 244                  0.07614  \n",
       " 543                  0.06443  \n",
       " 544                  0.08492  \n",
       " 265                  0.08218  \n",
       " 288                  0.07009  \n",
       " 423                  0.08839  \n",
       " 147                  0.09218  \n",
       " 177                  0.09519  \n",
       " 99                   0.09353  \n",
       " 448                  0.07463  \n",
       " 431                  0.09359  \n",
       " 115                  0.08541  \n",
       " 72                   0.13390  \n",
       " 537                  0.09970  \n",
       " 174                  0.06164  \n",
       " 87                   0.09288  \n",
       " 551                  0.08032  \n",
       " 486                  0.06596  \n",
       " 314                  0.08116  \n",
       " 396                  0.07686  \n",
       " 472                  0.08273  \n",
       " 70                   0.06589  \n",
       " 277                  0.05737  \n",
       " 9                    0.20750  \n",
       " 359                  0.08136  \n",
       " 192                  0.06559  \n",
       " 559                  0.08732  \n",
       " \n",
       " [426 rows x 30 columns],\n",
       "      mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       " 512       13.400         20.52           88.64      556.7          0.11060   \n",
       " 457       13.210         25.25           84.10      537.9          0.08791   \n",
       " 439       14.020         15.66           89.59      606.5          0.07966   \n",
       " 298       14.260         18.17           91.22      633.1          0.06576   \n",
       " 37        13.030         18.42           82.61      523.8          0.08983   \n",
       " 515       11.340         18.61           72.76      391.2          0.10490   \n",
       " 382       12.050         22.72           78.75      447.8          0.06935   \n",
       " 310       11.700         19.11           74.33      418.7          0.08814   \n",
       " 538        7.729         25.49           47.98      178.8          0.08098   \n",
       " 345       10.260         14.71           66.20      321.6          0.09882   \n",
       " 421       14.690         13.98           98.22      656.1          0.10310   \n",
       " 90        14.620         24.02           94.57      662.7          0.08974   \n",
       " 412        9.397         21.68           59.75      268.8          0.07969   \n",
       " 157       16.840         19.46          108.40      880.2          0.07445   \n",
       " 89        14.640         15.24           95.77      651.9          0.11320   \n",
       " 172       15.460         11.89          102.50      736.9          0.12570   \n",
       " 318        9.042         18.90           60.07      244.5          0.09968   \n",
       " 233       20.510         27.81          134.40     1319.0          0.09159   \n",
       " 389       19.550         23.21          128.90     1174.0          0.10100   \n",
       " 250       20.940         23.56          138.90     1364.0          0.10070   \n",
       " 31        11.840         18.70           77.93      440.6          0.11090   \n",
       " 283       16.240         18.77          108.80      805.1          0.10660   \n",
       " 482       13.470         14.06           87.32      546.3          0.10710   \n",
       " 211       11.840         18.94           75.51      428.0          0.08871   \n",
       " 372       21.370         15.10          141.30     1386.0          0.10010   \n",
       " 401       11.930         10.91           76.14      442.7          0.08872   \n",
       " 159       10.900         12.96           68.69      366.8          0.07515   \n",
       " 14        13.730         22.61           93.60      578.3          0.11310   \n",
       " 364       13.400         16.95           85.48      552.4          0.07937   \n",
       " 337       18.770         21.43          122.90     1092.0          0.09116   \n",
       " ..           ...           ...             ...        ...              ...   \n",
       " 500       15.040         16.74           98.73      689.4          0.09883   \n",
       " 338       10.050         17.53           64.41      310.8          0.10070   \n",
       " 427       10.800         21.98           68.79      359.9          0.08801   \n",
       " 406       16.140         14.86          104.30      800.0          0.09495   \n",
       " 96        12.180         17.84           77.79      451.1          0.10450   \n",
       " 490       12.250         22.44           78.18      466.5          0.08192   \n",
       " 384       13.280         13.72           85.79      541.8          0.08363   \n",
       " 281       11.740         14.02           74.24      427.3          0.07813   \n",
       " 325       12.670         17.30           81.25      489.9          0.10280   \n",
       " 190       14.220         23.12           94.37      609.9          0.10750   \n",
       " 380       11.270         12.96           73.16      386.3          0.12370   \n",
       " 366       20.200         26.83          133.70     1234.0          0.09905   \n",
       " 469       11.620         18.18           76.38      408.8          0.11750   \n",
       " 225       14.340         13.47           92.51      641.2          0.09906   \n",
       " 271       11.290         13.04           72.23      388.0          0.09834   \n",
       " 547       10.260         16.58           65.85      320.8          0.08877   \n",
       " 550       10.860         21.48           68.51      360.5          0.07431   \n",
       " 492       18.010         20.56          118.40     1007.0          0.10010   \n",
       " 185       10.080         15.11           63.76      317.5          0.09267   \n",
       " 306       13.200         15.82           84.07      537.3          0.08511   \n",
       " 208       13.110         22.54           87.02      529.4          0.10020   \n",
       " 242       11.300         18.19           73.93      389.4          0.09592   \n",
       " 313       11.540         10.72           73.73      409.1          0.08597   \n",
       " 542       14.740         25.42           94.70      668.6          0.08275   \n",
       " 514       15.050         19.07           97.26      701.9          0.09215   \n",
       " 236       23.210         26.97          153.50     1670.0          0.09509   \n",
       " 113       10.510         20.19           68.64      334.2          0.11220   \n",
       " 527       12.340         12.27           78.94      468.5          0.09003   \n",
       " 76        13.530         10.94           87.91      559.2          0.12910   \n",
       " 162       19.590         18.15          130.70     1214.0          0.11200   \n",
       " \n",
       "      mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       " 512           0.14690        0.144500             0.081720         0.2116   \n",
       " 457           0.05205        0.027720             0.020680         0.1619   \n",
       " 439           0.05581        0.020870             0.026520         0.1589   \n",
       " 298           0.05220        0.024750             0.013740         0.1635   \n",
       " 37            0.03766        0.025620             0.029230         0.1467   \n",
       " 515           0.08499        0.043020             0.025940         0.1927   \n",
       " 382           0.10730        0.079430             0.029780         0.1203   \n",
       " 310           0.05253        0.015830             0.011480         0.1936   \n",
       " 538           0.04878        0.000000             0.000000         0.1870   \n",
       " 345           0.09159        0.035810             0.020370         0.1633   \n",
       " 421           0.18360        0.145000             0.063000         0.2086   \n",
       " 90            0.08606        0.031020             0.029570         0.1685   \n",
       " 412           0.06053        0.037350             0.005128         0.1274   \n",
       " 157           0.07223        0.051500             0.027710         0.1844   \n",
       " 89            0.13390        0.099660             0.070640         0.2116   \n",
       " 172           0.15550        0.203200             0.109700         0.1966   \n",
       " 318           0.19720        0.197500             0.049080         0.2330   \n",
       " 233           0.10740        0.155400             0.083400         0.1448   \n",
       " 389           0.13180        0.185600             0.102100         0.1989   \n",
       " 250           0.16060        0.271200             0.131000         0.2205   \n",
       " 31            0.15160        0.121800             0.051820         0.2301   \n",
       " 283           0.18020        0.194800             0.090520         0.1876   \n",
       " 482           0.11550        0.057860             0.052660         0.1779   \n",
       " 211           0.06900        0.026690             0.013930         0.1533   \n",
       " 372           0.15150        0.193200             0.125500         0.1973   \n",
       " 401           0.05242        0.026060             0.017960         0.1601   \n",
       " 159           0.03718        0.003090             0.006588         0.1442   \n",
       " 14            0.22930        0.212800             0.080250         0.2069   \n",
       " 364           0.05696        0.021810             0.014730         0.1650   \n",
       " 337           0.14020        0.106000             0.060900         0.1953   \n",
       " ..                ...             ...                  ...            ...   \n",
       " 500           0.13640        0.077210             0.061420         0.1668   \n",
       " 338           0.07326        0.025110             0.017750         0.1890   \n",
       " 427           0.05743        0.036140             0.014040         0.2016   \n",
       " 406           0.08501        0.055000             0.045280         0.1735   \n",
       " 96            0.07057        0.024900             0.029410         0.1900   \n",
       " 490           0.05200        0.017140             0.012610         0.1544   \n",
       " 384           0.08575        0.050770             0.028640         0.1617   \n",
       " 281           0.04340        0.022450             0.027630         0.2101   \n",
       " 325           0.07664        0.031930             0.021070         0.1707   \n",
       " 190           0.24130        0.198100             0.066180         0.2384   \n",
       " 380           0.11110        0.079000             0.055500         0.2018   \n",
       " 366           0.16690        0.164100             0.126500         0.1875   \n",
       " 469           0.14830        0.102000             0.055640         0.1957   \n",
       " 225           0.07624        0.057240             0.046030         0.2075   \n",
       " 271           0.07608        0.032650             0.027550         0.1769   \n",
       " 547           0.08066        0.043580             0.024380         0.1669   \n",
       " 550           0.04227        0.000000             0.000000         0.1661   \n",
       " 492           0.12890        0.117000             0.077620         0.2116   \n",
       " 185           0.04695        0.001597             0.002404         0.1703   \n",
       " 306           0.05251        0.001461             0.003261         0.1632   \n",
       " 208           0.14830        0.087050             0.051020         0.1850   \n",
       " 242           0.13250        0.154800             0.028540         0.2054   \n",
       " 313           0.05969        0.013670             0.008907         0.1833   \n",
       " 542           0.07214        0.041050             0.030270         0.1840   \n",
       " 514           0.08597        0.074860             0.043350         0.1561   \n",
       " 236           0.16820        0.195000             0.123700         0.1909   \n",
       " 113           0.13030        0.064760             0.030680         0.1922   \n",
       " 527           0.06307        0.029580             0.026470         0.1689   \n",
       " 76            0.10470        0.068770             0.065560         0.2403   \n",
       " 162           0.16660        0.250800             0.128600         0.2027   \n",
       " \n",
       "      mean fractal dimension           ...             worst radius  \\\n",
       " 512                 0.07325           ...                   16.410   \n",
       " 457                 0.05584           ...                   14.350   \n",
       " 439                 0.05586           ...                   14.910   \n",
       " 298                 0.05586           ...                   16.220   \n",
       " 37                  0.05863           ...                   13.300   \n",
       " 515                 0.06211           ...                   12.470   \n",
       " 382                 0.06659           ...                   12.570   \n",
       " 310                 0.06128           ...                   12.610   \n",
       " 538                 0.07285           ...                    9.077   \n",
       " 345                 0.07005           ...                   10.880   \n",
       " 421                 0.07406           ...                   16.460   \n",
       " 90                  0.05866           ...                   16.110   \n",
       " 412                 0.06724           ...                    9.965   \n",
       " 157                 0.05268           ...                   18.220   \n",
       " 89                  0.06346           ...                   16.340   \n",
       " 172                 0.07069           ...                   18.790   \n",
       " 318                 0.08743           ...                   10.060   \n",
       " 233                 0.05592           ...                   24.470   \n",
       " 389                 0.05884           ...                   20.820   \n",
       " 250                 0.05898           ...                   25.580   \n",
       " 31                  0.07799           ...                   16.820   \n",
       " 283                 0.06684           ...                   18.550   \n",
       " 482                 0.06639           ...                   14.830   \n",
       " 211                 0.06057           ...                   13.300   \n",
       " 372                 0.06183           ...                   22.690   \n",
       " 401                 0.05541           ...                   13.800   \n",
       " 159                 0.05743           ...                   12.360   \n",
       " 14                  0.07682           ...                   15.030   \n",
       " 364                 0.05701           ...                   14.730   \n",
       " 337                 0.06083           ...                   24.540   \n",
       " ..                      ...           ...                      ...   \n",
       " 500                 0.06869           ...                   16.760   \n",
       " 338                 0.06331           ...                   11.160   \n",
       " 427                 0.05977           ...                   12.760   \n",
       " 406                 0.05875           ...                   17.710   \n",
       " 96                  0.06635           ...                   12.830   \n",
       " 490                 0.05976           ...                   14.170   \n",
       " 384                 0.05594           ...                   14.240   \n",
       " 281                 0.06113           ...                   13.310   \n",
       " 325                 0.05984           ...                   13.710   \n",
       " 190                 0.07542           ...                   15.740   \n",
       " 380                 0.06914           ...                   12.840   \n",
       " 366                 0.06020           ...                   24.190   \n",
       " 469                 0.07255           ...                   13.360   \n",
       " 225                 0.05448           ...                   16.770   \n",
       " 271                 0.06270           ...                   12.320   \n",
       " 547                 0.06714           ...                   10.830   \n",
       " 550                 0.05948           ...                   11.660   \n",
       " 492                 0.06077           ...                   21.530   \n",
       " 185                 0.06048           ...                   11.870   \n",
       " 306                 0.05894           ...                   14.410   \n",
       " 208                 0.07310           ...                   14.550   \n",
       " 242                 0.07669           ...                   12.580   \n",
       " 313                 0.06100           ...                   12.340   \n",
       " 542                 0.05680           ...                   16.510   \n",
       " 514                 0.05915           ...                   17.580   \n",
       " 236                 0.06309           ...                   31.010   \n",
       " 113                 0.07782           ...                   11.160   \n",
       " 527                 0.05808           ...                   13.610   \n",
       " 76                  0.06641           ...                   14.080   \n",
       " 162                 0.06082           ...                   26.730   \n",
       " \n",
       "      worst texture  worst perimeter  worst area  worst smoothness  \\\n",
       " 512          29.66           113.30       844.4           0.15740   \n",
       " 457          34.23            91.29       632.9           0.12890   \n",
       " 439          19.31            96.53       688.9           0.10340   \n",
       " 298          25.26           105.80       819.7           0.09445   \n",
       " 37           22.81            84.46       545.9           0.09701   \n",
       " 515          23.03            79.15       478.6           0.14830   \n",
       " 382          28.71            87.36       488.4           0.08799   \n",
       " 310          26.55            80.92       483.1           0.12230   \n",
       " 538          30.92            57.17       248.0           0.12560   \n",
       " 345          19.48            70.89       357.1           0.13600   \n",
       " 421          18.34           114.10       809.2           0.13120   \n",
       " 90           29.11           102.90       803.7           0.11150   \n",
       " 412          27.99            66.61       301.0           0.10860   \n",
       " 157          28.07           120.30      1032.0           0.08774   \n",
       " 89           18.24           109.40       803.6           0.12770   \n",
       " 172          17.04           125.00      1102.0           0.15310   \n",
       " 318          23.40            68.62       297.1           0.12210   \n",
       " 233          37.38           162.70      1872.0           0.12230   \n",
       " 389          30.44           142.00      1313.0           0.12510   \n",
       " 250          27.00           165.30      2010.0           0.12110   \n",
       " 31           28.12           119.40       888.7           0.16370   \n",
       " 283          25.09           126.90      1031.0           0.13650   \n",
       " 482          18.32            94.94       660.2           0.13930   \n",
       " 211          24.99            85.22       546.3           0.12800   \n",
       " 372          21.84           152.10      1535.0           0.11920   \n",
       " 401          20.14            87.64       589.5           0.13740   \n",
       " 159          18.20            78.07       470.0           0.11710   \n",
       " 14           32.01           108.80       697.7           0.16510   \n",
       " 364          21.70            93.76       663.5           0.12130   \n",
       " 337          34.37           161.10      1873.0           0.14980   \n",
       " ..             ...              ...         ...               ...   \n",
       " 500          20.43           109.70       856.9           0.11350   \n",
       " 338          26.84            71.98       384.0           0.14020   \n",
       " 427          32.04            83.69       489.5           0.13030   \n",
       " 406          19.58           115.90       947.9           0.12060   \n",
       " 96           20.92            82.14       495.2           0.11400   \n",
       " 490          31.99            92.74       622.9           0.12560   \n",
       " 384          17.37            96.59       623.7           0.11660   \n",
       " 281          18.26            84.70       533.7           0.10360   \n",
       " 325          21.10            88.70       574.4           0.13840   \n",
       " 190          37.18           106.40       762.4           0.15330   \n",
       " 380          20.53            84.93       476.1           0.16100   \n",
       " 366          33.81           160.00      1671.0           0.12780   \n",
       " 469          25.40            88.14       528.1           0.17800   \n",
       " 225          16.90           110.40       873.2           0.12970   \n",
       " 271          16.18            78.27       457.5           0.13580   \n",
       " 547          22.04            71.08       357.4           0.14610   \n",
       " 550          24.77            74.08       412.3           0.10010   \n",
       " 492          26.06           143.40      1426.0           0.13090   \n",
       " 185          21.18            75.39       437.0           0.15210   \n",
       " 306          20.45            92.00       636.9           0.11280   \n",
       " 208          29.16            99.48       639.3           0.13490   \n",
       " 242          27.96            87.16       472.9           0.13470   \n",
       " 313          12.87            81.23       467.8           0.10920   \n",
       " 542          32.29           107.40       826.4           0.10600   \n",
       " 514          28.06           113.80       967.0           0.12460   \n",
       " 236          34.51           206.00      2944.0           0.14810   \n",
       " 113          22.75            72.62       374.4           0.13000   \n",
       " 527          19.27            87.22       564.9           0.12920   \n",
       " 76           12.49            91.36       605.5           0.14510   \n",
       " 162          26.39           174.90      2232.0           0.14380   \n",
       " \n",
       "      worst compactness  worst concavity  worst concave points  worst symmetry  \\\n",
       " 512            0.38560          0.51060               0.20510          0.3585   \n",
       " 457            0.10630          0.13900               0.06005          0.2444   \n",
       " 439            0.10170          0.06260               0.08216          0.2136   \n",
       " 298            0.21670          0.15650               0.07530          0.2636   \n",
       " 37             0.04619          0.04833               0.05013          0.1987   \n",
       " 515            0.15740          0.16240               0.08542          0.3060   \n",
       " 382            0.32140          0.29120               0.10920          0.2191   \n",
       " 310            0.10870          0.07915               0.05741          0.3487   \n",
       " 538            0.08340          0.00000               0.00000          0.3058   \n",
       " 345            0.16360          0.07162               0.04074          0.2434   \n",
       " 421            0.36350          0.32190               0.11080          0.2827   \n",
       " 90             0.17660          0.09189               0.06946          0.2522   \n",
       " 412            0.18870          0.18680               0.02564          0.2376   \n",
       " 157            0.17100          0.18820               0.08436          0.2527   \n",
       " 89             0.30890          0.26040               0.13970          0.3151   \n",
       " 172            0.35830          0.58300               0.18270          0.3216   \n",
       " 318            0.37480          0.46090               0.11450          0.3135   \n",
       " 233            0.27610          0.41460               0.15630          0.2437   \n",
       " 389            0.24140          0.38290               0.18250          0.2576   \n",
       " 250            0.31720          0.69910               0.21050          0.3126   \n",
       " 31             0.57750          0.69560               0.15460          0.4761   \n",
       " 283            0.47060          0.50260               0.17320          0.2770   \n",
       " 482            0.24990          0.18480               0.13350          0.3227   \n",
       " 211            0.18800          0.14710               0.06913          0.2535   \n",
       " 372            0.28400          0.40240               0.19660          0.2730   \n",
       " 401            0.15750          0.15140               0.06876          0.2460   \n",
       " 159            0.08294          0.01854               0.03953          0.2738   \n",
       " 14             0.77250          0.69430               0.22080          0.3596   \n",
       " 364            0.16760          0.13640               0.06987          0.2741   \n",
       " 337            0.48270          0.46340               0.20480          0.3679   \n",
       " ..                 ...              ...                   ...             ...   \n",
       " 500            0.21760          0.18560               0.10180          0.2177   \n",
       " 338            0.14020          0.10550               0.06499          0.2894   \n",
       " 427            0.16960          0.19270               0.07485          0.2965   \n",
       " 406            0.17220          0.23100               0.11290          0.2778   \n",
       " 96             0.09358          0.04980               0.05882          0.2227   \n",
       " 490            0.18040          0.12300               0.06335          0.3100   \n",
       " 384            0.26850          0.28660               0.09173          0.2736   \n",
       " 281            0.08500          0.06735               0.08290          0.3101   \n",
       " 325            0.12120          0.10200               0.05602          0.2688   \n",
       " 190            0.93270          0.84880               0.17720          0.5166   \n",
       " 380            0.24290          0.22470               0.13180          0.3343   \n",
       " 366            0.34160          0.37030               0.21520          0.3271   \n",
       " 469            0.28780          0.31860               0.14160          0.2660   \n",
       " 225            0.15250          0.16320               0.10870          0.3062   \n",
       " 271            0.15070          0.12750               0.08750          0.2733   \n",
       " 547            0.22460          0.17830               0.08333          0.2691   \n",
       " 550            0.07348          0.00000               0.00000          0.2458   \n",
       " 492            0.23270          0.25440               0.14890          0.3251   \n",
       " 185            0.10190          0.00692               0.01042          0.2933   \n",
       " 306            0.13460          0.01120               0.02500          0.2651   \n",
       " 208            0.44020          0.31620               0.11260          0.4128   \n",
       " 242            0.48480          0.74360               0.12180          0.3308   \n",
       " 313            0.16260          0.08324               0.04715          0.3390   \n",
       " 542            0.13760          0.16110               0.10950          0.2722   \n",
       " 514            0.21010          0.28660               0.11200          0.2282   \n",
       " 236            0.41260          0.58200               0.25930          0.3103   \n",
       " 113            0.20490          0.12950               0.06136          0.2383   \n",
       " 527            0.20740          0.17910               0.10700          0.3110   \n",
       " 76             0.13790          0.08539               0.07407          0.2710   \n",
       " 162            0.38460          0.68100               0.22470          0.3643   \n",
       " \n",
       "      worst fractal dimension  \n",
       " 512                  0.11090  \n",
       " 457                  0.06788  \n",
       " 439                  0.06710  \n",
       " 298                  0.07676  \n",
       " 37                   0.06169  \n",
       " 515                  0.06783  \n",
       " 382                  0.09349  \n",
       " 310                  0.06958  \n",
       " 538                  0.09938  \n",
       " 345                  0.08488  \n",
       " 421                  0.09208  \n",
       " 90                   0.07246  \n",
       " 412                  0.09206  \n",
       " 157                  0.05972  \n",
       " 89                   0.08473  \n",
       " 172                  0.10100  \n",
       " 318                  0.10550  \n",
       " 233                  0.08328  \n",
       " 389                  0.07602  \n",
       " 250                  0.07849  \n",
       " 31                   0.14020  \n",
       " 283                  0.10630  \n",
       " 482                  0.09326  \n",
       " 211                  0.07993  \n",
       " 372                  0.08666  \n",
       " 401                  0.07262  \n",
       " 159                  0.07685  \n",
       " 14                   0.14310  \n",
       " 364                  0.07582  \n",
       " 337                  0.09870  \n",
       " ..                       ...  \n",
       " 500                  0.08549  \n",
       " 338                  0.07664  \n",
       " 427                  0.07662  \n",
       " 406                  0.07012  \n",
       " 96                   0.07376  \n",
       " 490                  0.08203  \n",
       " 384                  0.07320  \n",
       " 281                  0.06688  \n",
       " 325                  0.06888  \n",
       " 190                  0.14460  \n",
       " 380                  0.09215  \n",
       " 366                  0.07632  \n",
       " 469                  0.09270  \n",
       " 225                  0.06072  \n",
       " 271                  0.08022  \n",
       " 547                  0.09479  \n",
       " 550                  0.06592  \n",
       " 492                  0.07625  \n",
       " 185                  0.07697  \n",
       " 306                  0.08385  \n",
       " 208                  0.10760  \n",
       " 242                  0.12970  \n",
       " 313                  0.07434  \n",
       " 542                  0.06956  \n",
       " 514                  0.06954  \n",
       " 236                  0.08677  \n",
       " 113                  0.09026  \n",
       " 527                  0.07592  \n",
       " 76                   0.07191  \n",
       " 162                  0.09223  \n",
       " \n",
       " [143 rows x 30 columns],\n",
       " 293    1.0\n",
       " 332    1.0\n",
       " 565    0.0\n",
       " 278    1.0\n",
       " 489    0.0\n",
       " 346    1.0\n",
       " 357    1.0\n",
       " 355    1.0\n",
       " 112    1.0\n",
       " 68     1.0\n",
       " 526    1.0\n",
       " 206    1.0\n",
       " 65     0.0\n",
       " 437    1.0\n",
       " 126    0.0\n",
       " 429    1.0\n",
       " 392    0.0\n",
       " 343    0.0\n",
       " 334    1.0\n",
       " 440    1.0\n",
       " 441    0.0\n",
       " 137    1.0\n",
       " 230    0.0\n",
       " 7      0.0\n",
       " 408    0.0\n",
       " 523    1.0\n",
       " 361    1.0\n",
       " 553    1.0\n",
       " 478    1.0\n",
       " 303    1.0\n",
       "       ... \n",
       " 459    1.0\n",
       " 510    1.0\n",
       " 151    1.0\n",
       " 244    0.0\n",
       " 543    1.0\n",
       " 544    1.0\n",
       " 265    0.0\n",
       " 288    1.0\n",
       " 423    1.0\n",
       " 147    1.0\n",
       " 177    0.0\n",
       " 99     0.0\n",
       " 448    1.0\n",
       " 431    1.0\n",
       " 115    1.0\n",
       " 72     0.0\n",
       " 537    1.0\n",
       " 174    1.0\n",
       " 87     0.0\n",
       " 551    1.0\n",
       " 486    1.0\n",
       " 314    1.0\n",
       " 396    1.0\n",
       " 472    1.0\n",
       " 70     0.0\n",
       " 277    0.0\n",
       " 9      0.0\n",
       " 359    1.0\n",
       " 192    1.0\n",
       " 559    1.0\n",
       " Name: target, dtype: float64,\n",
       " 512    0.0\n",
       " 457    1.0\n",
       " 439    1.0\n",
       " 298    1.0\n",
       " 37     1.0\n",
       " 515    1.0\n",
       " 382    1.0\n",
       " 310    1.0\n",
       " 538    1.0\n",
       " 345    1.0\n",
       " 421    1.0\n",
       " 90     1.0\n",
       " 412    1.0\n",
       " 157    1.0\n",
       " 89     1.0\n",
       " 172    0.0\n",
       " 318    1.0\n",
       " 233    0.0\n",
       " 389    0.0\n",
       " 250    0.0\n",
       " 31     0.0\n",
       " 283    0.0\n",
       " 482    1.0\n",
       " 211    1.0\n",
       " 372    0.0\n",
       " 401    1.0\n",
       " 159    1.0\n",
       " 14     0.0\n",
       " 364    1.0\n",
       " 337    0.0\n",
       "       ... \n",
       " 500    1.0\n",
       " 338    1.0\n",
       " 427    1.0\n",
       " 406    1.0\n",
       " 96     1.0\n",
       " 490    1.0\n",
       " 384    1.0\n",
       " 281    1.0\n",
       " 325    1.0\n",
       " 190    0.0\n",
       " 380    1.0\n",
       " 366    0.0\n",
       " 469    1.0\n",
       " 225    1.0\n",
       " 271    1.0\n",
       " 547    1.0\n",
       " 550    1.0\n",
       " 492    0.0\n",
       " 185    1.0\n",
       " 306    1.0\n",
       " 208    1.0\n",
       " 242    1.0\n",
       " 313    1.0\n",
       " 542    1.0\n",
       " 514    0.0\n",
       " 236    0.0\n",
       " 113    1.0\n",
       " 527    1.0\n",
       " 76     1.0\n",
       " 162    0.0\n",
       " Name: target, dtype: float64)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "def answer_four():\n",
    "    X, y = answer_three()\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "    \n",
    "    return X_train, X_test, y_train, y_test\n",
    "answer_four()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 5\n",
    "Using KNeighborsClassifier, fit a k-nearest neighbors (knn) classifier with `X_train`, `y_train` and using one nearest neighbor (`n_neighbors = 1`).\n",
    "\n",
    "*This function should return a * `sklearn.neighbors.classification.KNeighborsClassifier`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=1, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "def answer_five():\n",
    "    X_train, X_test, y_train, y_test = answer_four()\n",
    "    knn = KNeighborsClassifier(n_neighbors = 1)\n",
    "    knn.fit(X_train, y_train)\n",
    "        \n",
    "    return knn\n",
    "answer_five()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 6\n",
    "Using your knn classifier, predict the class label using the mean value for each feature.\n",
    "\n",
    "Hint: You can use `cancerdf.mean()[:-1].values.reshape(1, -1)` which gets the mean value for each feature, ignores the target column, and reshapes the data from 1 dimension to 2 (necessary for the precict method of KNeighborsClassifier).\n",
    "\n",
    "*This function should return a numpy array either `array([ 0.])` or `array([ 1.])`*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_six():\n",
    "    cancerdf = answer_one()\n",
    "    knn = answer_five()\n",
    "    means = cancerdf.mean()[:-1].values.reshape(1, -1)\n",
    "    cancerpred = knn.predict(means)\n",
    "    \n",
    "    return cancerpred\n",
    "answer_six()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 7\n",
    "Using your knn classifier, predict the class labels for the test set `X_test`.\n",
    "\n",
    "*This function should return a numpy array with shape `(143,)` and values either `0.0` or `1.0`.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  1.,  1.,  0.,  1.,  1.,  1.,  1.,  1.,  1.,  0.,  1.,  1.,\n",
       "        1.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  1.,  1.,  1.,  0.,  1.,\n",
       "        1.,  1.,  1.,  0.,  1.,  0.,  1.,  0.,  1.,  0.,  1.,  0.,  1.,\n",
       "        0.,  0.,  1.,  0.,  1.,  0.,  0.,  1.,  1.,  1.,  0.,  0.,  1.,\n",
       "        0.,  1.,  1.,  1.,  1.,  1.,  1.,  0.,  0.,  0.,  1.,  1.,  0.,\n",
       "        1.,  0.,  0.,  0.,  1.,  1.,  0.,  1.,  1.,  0.,  1.,  1.,  1.,\n",
       "        1.,  1.,  0.,  0.,  0.,  1.,  0.,  1.,  1.,  1.,  0.,  0.,  1.,\n",
       "        0.,  1.,  0.,  1.,  1.,  0.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,\n",
       "        0.,  1.,  0.,  1.,  0.,  1.,  1.,  0.,  0.,  1.,  1.,  1.,  0.,\n",
       "        1.,  1.,  1.,  1.,  1.,  1.,  1.,  0.,  1.,  1.,  1.,  1.,  1.,\n",
       "        0.,  1.,  1.,  1.,  1.,  1.,  1.,  0.,  0.,  1.,  1.,  1.,  0.])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_seven():\n",
    "    X_train, X_test, y_train, y_test = answer_four()\n",
    "    knn = answer_five()\n",
    "    cxpred = knn.predict(X_test)\n",
    "    \n",
    "    return cxpred\n",
    "answer_seven()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 8\n",
    "Find the score (mean accuracy) of your knn classifier using `X_test` and `y_test`.\n",
    "\n",
    "*This function should return a float between 0 and 1*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.91608391608391604"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_eight():\n",
    "    X_train, X_test, y_train, y_test = answer_four()\n",
    "    knn = answer_five()\n",
    "    acc = knn.score(X_test, y_test)\n",
    "    \n",
    "    return acc\n",
    "answer_eight()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optional plot\n",
    "\n",
    "Try using the plotting function below to visualize the differet predicition scores between training and test sets, as well as malignant and benign cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def accuracy_plot():\n",
    "    import matplotlib.pyplot as plt\n",
    "\n",
    "    %matplotlib notebook\n",
    "\n",
    "    X_train, X_test, y_train, y_test = answer_four()\n",
    "\n",
    "    # Find the training and testing accuracies by target value (i.e. malignant, benign)\n",
    "    mal_train_X = X_train[y_train==0]\n",
    "    mal_train_y = y_train[y_train==0]\n",
    "    ben_train_X = X_train[y_train==1]\n",
    "    ben_train_y = y_train[y_train==1]\n",
    "\n",
    "    mal_test_X = X_test[y_test==0]\n",
    "    mal_test_y = y_test[y_test==0]\n",
    "    ben_test_X = X_test[y_test==1]\n",
    "    ben_test_y = y_test[y_test==1]\n",
    "\n",
    "    knn = answer_five()\n",
    "\n",
    "    scores = [knn.score(mal_train_X, mal_train_y), knn.score(ben_train_X, ben_train_y), \n",
    "              knn.score(mal_test_X, mal_test_y), knn.score(ben_test_X, ben_test_y)]\n",
    "\n",
    "\n",
    "    plt.figure()\n",
    "\n",
    "    # Plot the scores as a bar chart\n",
    "    bars = plt.bar(np.arange(4), scores, color=['#4c72b0','#4c72b0','#55a868','#55a868'])\n",
    "\n",
    "    # directly label the score onto the bars\n",
    "    for bar in bars:\n",
    "        height = bar.get_height()\n",
    "        plt.gca().text(bar.get_x() + bar.get_width()/2, height*.90, '{0:.{1}f}'.format(height, 2), \n",
    "                     ha='center', color='w', fontsize=11)\n",
    "\n",
    "    # remove all the ticks (both axes), and tick labels on the Y axis\n",
    "    plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')\n",
    "\n",
    "    # remove the frame of the chart\n",
    "    for spine in plt.gca().spines.values():\n",
    "        spine.set_visible(False)\n",
    "\n",
    "    plt.xticks([0,1,2,3], ['Malignant\\nTraining', 'Benign\\nTraining', 'Malignant\\nTest', 'Benign\\nTest'], alpha=0.8);\n",
    "    plt.title('Training and Test Accuracies for Malignant and Benign Cells', alpha=0.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uncomment the plotting function to see the visualization.\n",
    "\n",
    "**Comment out** the plotting function when submitting your notebook for grading. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#accuracy_plot() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "coursera": {
   "course_slug": "python-machine-learning",
   "graded_item_id": "f9SY5",
   "launcher_item_id": "oxndk",
   "part_id": "mh1Vo"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}