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",
   "execution_count": 4,
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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": 5,
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    {
     "data": {
      "text/plain": [
       "dict_keys(['target_names', 'feature_names', 'data', 'DESCR', 'target'])"
      ]
     },
     "execution_count": 5,
     "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": 6,
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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": 7,
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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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_one():\n",
    "    \n",
    "    # Your code here\n",
    "    \n",
    "    return pd.DataFrame(np.c_[cancer['data'], cancer['target']],\n",
    "                  columns= np.append(cancer['feature_names'], ['target']))\n",
    "\n",
    "\n",
    "answer_one()"
   ]
  },
  {
   "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": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "malignant    212\n",
       "benign       357\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def answer_two():\n",
    "    cancerdf = answer_one()\n",
    "    \n",
    "    # Your code here\n",
    "    malignant = len(cancerdf[cancerdf['target'] == 0])\n",
    "    benign = len(cancerdf[cancerdf['target'] == 1])\n",
    "    target = pd.Series(data = [malignant, benign], index = ['malignant', 'benign'])\n",
    "    return target\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": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def answer_three():\n",
    "    cancerdf = answer_one()\n",
    "    \n",
    "    X = cancerdf.iloc[:, :30]\n",
    "    y = cancerdf.iloc[:, 30]\n",
    "    \n",
    "    return  X, y"
   ]
  },
  {
   "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": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "def answer_four():\n",
    "    X, y = answer_three()\n",
    "    \n",
    "    # Your code here\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "    return X_train, X_test, y_train, y_test"
   ]
  },
  {
   "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": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "def answer_five():\n",
    "    X_train, X_test, y_train, y_test = answer_four()\n",
    "    \n",
    "    # Your code here\n",
    "    knn = KNeighborsClassifier(n_neighbors = 1)\n",
    "    return knn.fit(X_train, y_train)"
   ]
  },
  {
   "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",
    "    means = cancerdf.mean()[:-1].values.reshape(1, -1)\n",
    "    \n",
    "    # Your code here\n",
    "    predict = answer_five()\n",
    "    label = predict.predict(means)\n",
    "    return label\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": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(143,)"
      ]
     },
     "execution_count": 26,
     "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",
    "    \n",
    "    # Your code here\n",
    "    \n",
    "    return knn.predict(X_test)\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": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.91608391608391604"
      ]
     },
     "execution_count": 27,
     "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",
    "    \n",
    "    # Your code here\n",
    "    \n",
    "    return knn.score(X_test, y_test)\n",
    "\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": 28,
   "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": 29,
   "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}