Pandas_selecting data with expressions.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "}\n",
       "table.dataframe {\n",
       "    border-collapse: collapse;\n",
       "    border: none;\n",
       "}\n",
       "table.dataframe tr {\n",
       "    border: none;\n",
       "}\n",
       "table.dataframe td, table.dataframe th {\n",
       "    margin: 0;\n",
       "    border: 1px solid white;\n",
       "    padding-left: 0.25em;\n",
       "    padding-right: 0.25em;\n",
       "}\n",
       "table.dataframe th:not(:empty) {\n",
       "    background-color: #fec;\n",
       "    text-align: left;\n",
       "    font-weight: normal;\n",
       "}\n",
       "table.dataframe tr:nth-child(2) th:empty {\n",
       "    border-left: none;\n",
       "    border-right: 1px dashed #888;\n",
       "}\n",
       "table.dataframe td {\n",
       "    border: 2px solid #ccf;\n",
       "    background-color: #f4f4ff;\n",
       "}\n",
       "h3 {\n",
       "    color: white;\n",
       "    background-color: black;\n",
       "    padding: 0.5em;\n",
       "}\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import HTML, Image\n",
    "css = open('style/style-table.css').read() + open('style/style-notebook.css').read()\n",
    "HTML('<style>{}</style>'.format(css))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('data/inflammation.csv',header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60, 40)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa0aad45be0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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1t6vil//HfpaeXip6Xi7KVrLC02Y2s5RMikFRC3UMitIRbYPVgKnFRGJeNNjk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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa0aa96fba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample = [1,4,7,10,20]\n",
    "data.iloc[sample,:].T.plot(legend=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa0aa8bdbe0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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P2JxElLs2nme6f3TbPqQ8SXngkB35rI8iMu0zKwfMqz631Yiz5oSz5gFnxQM2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SnHZzeEbkY4yRiLORNnRt9Z0SiL2WbMr64/5ucvPuONPsdyS+xRiV2XWNRIGiwUR8wwjMc+BT6V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\nwjODVTCv8MxgFcwrPDNYBfMKzwz+D9n+6gJCPtVHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa0aa977828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60, 40)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.values.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>8</th>\n",
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       "      <th>31</th>\n",
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       "      <th>33</th>\n",
       "      <th>34</th>\n",
       "      <th>35</th>\n",
       "      <th>36</th>\n",
       "      <th>37</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>60 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    0   1   2   3   4   5    6    7    8    9  ...    30   31   32   33   34  \\\n",
       "0  NaN NaN NaN NaN NaN NaN  NaN  7.0  8.0  NaN ...   NaN  NaN  NaN  7.0  NaN   \n",
       "1  NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  6.0 ...   NaN  NaN  NaN  NaN  NaN   \n",
       "2  NaN NaN NaN NaN NaN NaN  6.0  NaN  NaN  9.0 ...  10.0  NaN  NaN  NaN  NaN   \n",
       "3  NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  7.0 ...   NaN  NaN  6.0  NaN  NaN   \n",
       "4  NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   9.0  6.0  NaN  NaN  NaN   \n",
       "5  NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  NaN ...   8.0  NaN  7.0  NaN  NaN   \n",
       "6  NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  8.0 ...   8.0  8.0  NaN  NaN  NaN   \n",
       "7  NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   NaN  9.0  NaN  NaN  NaN   \n",
       "8  NaN NaN NaN NaN NaN NaN  6.0  NaN  NaN  8.0 ...   NaN  6.0  NaN  7.0  6.0   \n",
       "9  NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  8.0 ...   NaN  NaN  NaN  NaN  NaN   \n",
       "10 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   NaN  NaN  NaN  NaN  NaN   \n",
       "11 NaN NaN NaN NaN NaN NaN  NaN  7.0  8.0  NaN ...   8.0  NaN  NaN  NaN  NaN   \n",
       "12 NaN NaN NaN NaN NaN NaN  6.0  NaN  6.0  7.0 ...   NaN  NaN  7.0  NaN  NaN   \n",
       "13 NaN NaN NaN NaN NaN NaN  NaN  6.0  6.0  NaN ...   NaN  8.0  7.0  NaN  6.0   \n",
       "14 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   8.0  NaN  NaN  NaN  NaN   \n",
       "15 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  NaN ...  10.0  9.0  NaN  6.0  NaN   \n",
       "16 NaN NaN NaN NaN NaN NaN  6.0  NaN  7.0  NaN ...   9.0  8.0  7.0  NaN  NaN   \n",
       "17 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  7.0 ...   NaN  NaN  6.0  NaN  NaN   \n",
       "18 NaN NaN NaN NaN NaN NaN  NaN  NaN  7.0  8.0 ...   6.0  9.0  NaN  NaN  NaN   \n",
       "19 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  7.0 ...   6.0  6.0  6.0  NaN  NaN   \n",
       "20 NaN NaN NaN NaN NaN NaN  NaN  NaN  8.0  NaN ...   NaN  NaN  NaN  NaN  NaN   \n",
       "21 NaN NaN NaN NaN NaN NaN  NaN  6.0  NaN  8.0 ...   8.0  NaN  6.0  6.0  NaN   \n",
       "22 NaN NaN NaN NaN NaN NaN  NaN  7.0  7.0  8.0 ...   NaN  NaN  8.0  NaN  6.0   \n",
       "23 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  NaN ...   NaN  NaN  NaN  NaN  NaN   \n",
       "24 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  NaN ...   NaN  NaN  6.0  NaN  NaN   \n",
       "25 NaN NaN NaN NaN NaN NaN  NaN  7.0  NaN  NaN ...   8.0  NaN  7.0  NaN  NaN   \n",
       "26 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  7.0 ...   7.0  NaN  8.0  NaN  NaN   \n",
       "27 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   9.0  NaN  NaN  NaN  NaN   \n",
       "28 NaN NaN NaN NaN NaN NaN  6.0  NaN  7.0  6.0 ...   7.0  7.0  8.0  NaN  NaN   \n",
       "29 NaN NaN NaN NaN NaN NaN  6.0  NaN  8.0  6.0 ...   6.0  9.0  NaN  NaN  NaN   \n",
       "30 NaN NaN NaN NaN NaN NaN  NaN  6.0  8.0  6.0 ...  10.0  NaN  NaN  6.0  NaN   \n",
       "31 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  7.0 ...   NaN  6.0  6.0  NaN  NaN   \n",
       "32 NaN NaN NaN NaN NaN NaN  6.0  6.0  6.0  7.0 ...   NaN  8.0  NaN  NaN  NaN   \n",
       "33 NaN NaN NaN NaN NaN NaN  6.0  7.0  NaN  8.0 ...   NaN  9.0  7.0  NaN  NaN   \n",
       "34 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   NaN  6.0  6.0  NaN  NaN   \n",
       "35 NaN NaN NaN NaN NaN NaN  6.0  NaN  NaN  NaN ...   NaN  9.0  NaN  NaN  6.0   \n",
       "36 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  6.0 ...   6.0  NaN  NaN  NaN  6.0   \n",
       "37 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   9.0  9.0  NaN  NaN  NaN   \n",
       "38 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  9.0 ...   NaN  NaN  NaN  NaN  NaN   \n",
       "39 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  7.0 ...   NaN  NaN  6.0  NaN  NaN   \n",
       "40 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   NaN  9.0  6.0  NaN  NaN   \n",
       "41 NaN NaN NaN NaN NaN NaN  NaN  NaN  8.0  9.0 ...   NaN  8.0  NaN  6.0  6.0   \n",
       "42 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  7.0 ...   NaN  8.0  NaN  NaN  6.0   \n",
       "43 NaN NaN NaN NaN NaN NaN  NaN  6.0  7.0  8.0 ...  10.0  NaN  NaN  NaN  NaN   \n",
       "44 NaN NaN NaN NaN NaN NaN  NaN  6.0  NaN  NaN ...  10.0  6.0  8.0  7.0  NaN   \n",
       "45 NaN NaN NaN NaN NaN NaN  NaN  NaN  8.0  9.0 ...   NaN  8.0  NaN  NaN  NaN   \n",
       "46 NaN NaN NaN NaN NaN NaN  NaN  6.0  NaN  9.0 ...   6.0  7.0  6.0  NaN  NaN   \n",
       "47 NaN NaN NaN NaN NaN NaN  6.0  NaN  8.0  NaN ...   6.0  9.0  NaN  6.0  NaN   \n",
       "48 NaN NaN NaN NaN NaN NaN  NaN  NaN  7.0  6.0 ...  10.0  7.0  6.0  NaN  NaN   \n",
       "49 NaN NaN NaN NaN NaN NaN  NaN  7.0  NaN  NaN ...   NaN  6.0  NaN  NaN  NaN   \n",
       "50 NaN NaN NaN NaN NaN NaN  NaN  NaN  6.0  NaN ...   7.0  9.0  NaN  NaN  6.0   \n",
       "51 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  6.0 ...   8.0  NaN  NaN  NaN  NaN   \n",
       "52 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...  10.0  8.0  7.0  NaN  NaN   \n",
       "53 NaN NaN NaN NaN NaN NaN  NaN  7.0  NaN  9.0 ...   7.0  6.0  NaN  NaN  NaN   \n",
       "54 NaN NaN NaN NaN NaN NaN  NaN  NaN  NaN  NaN ...   NaN  NaN  NaN  NaN  NaN   \n",
       "55 NaN NaN NaN NaN NaN NaN  6.0  NaN  NaN  7.0 ...   NaN  NaN  NaN  NaN  NaN   \n",
       "56 NaN NaN NaN NaN NaN NaN  NaN  7.0  NaN  NaN ...   7.0  7.0  NaN  6.0  NaN   \n",
       "57 NaN NaN NaN NaN NaN NaN  6.0  NaN  6.0  NaN ...   8.0  6.0  6.0  NaN  NaN   \n",
       "58 NaN NaN NaN NaN NaN NaN  6.0  NaN  8.0  7.0 ...  10.0  8.0  8.0  6.0  NaN   \n",
       "59 NaN NaN NaN NaN NaN NaN  NaN  NaN  8.0  NaN ...   8.0  NaN  NaN  NaN  NaN   \n",
       "\n",
       "    35  36  37  38  39  \n",
       "0  NaN NaN NaN NaN NaN  \n",
       "1  NaN NaN NaN NaN NaN  \n",
       "2  NaN NaN NaN NaN NaN  \n",
       "3  NaN NaN NaN NaN NaN  \n",
       "4  NaN NaN NaN NaN NaN  \n",
       "5  NaN NaN NaN NaN NaN  \n",
       "6  NaN NaN NaN NaN NaN  \n",
       "7  NaN NaN NaN NaN NaN  \n",
       "8  NaN NaN NaN NaN NaN  \n",
       "9  NaN NaN NaN NaN NaN  \n",
       "10 NaN NaN NaN NaN NaN  \n",
       "11 NaN NaN NaN NaN NaN  \n",
       "12 NaN NaN NaN NaN NaN  \n",
       "13 NaN NaN NaN NaN NaN  \n",
       "14 NaN NaN NaN NaN NaN  \n",
       "15 NaN NaN NaN NaN NaN  \n",
       "16 NaN NaN NaN NaN NaN  \n",
       "17 NaN NaN NaN NaN NaN  \n",
       "18 NaN NaN NaN NaN NaN  \n",
       "19 NaN NaN NaN NaN NaN  \n",
       "20 NaN NaN NaN NaN NaN  \n",
       "21 NaN NaN NaN NaN NaN  \n",
       "22 NaN NaN NaN NaN NaN  \n",
       "23 NaN NaN NaN NaN NaN  \n",
       "24 NaN NaN NaN NaN NaN  \n",
       "25 NaN NaN NaN NaN NaN  \n",
       "26 NaN NaN NaN NaN NaN  \n",
       "27 NaN NaN NaN NaN NaN  \n",
       "28 NaN NaN NaN NaN NaN  \n",
       "29 NaN NaN NaN NaN NaN  \n",
       "30 NaN NaN NaN NaN NaN  \n",
       "31 NaN NaN NaN NaN NaN  \n",
       "32 NaN NaN NaN NaN NaN  \n",
       "33 NaN NaN NaN NaN NaN  \n",
       "34 NaN NaN NaN NaN NaN  \n",
       "35 NaN NaN NaN NaN NaN  \n",
       "36 NaN NaN NaN NaN NaN  \n",
       "37 NaN NaN NaN NaN NaN  \n",
       "38 NaN NaN NaN NaN NaN  \n",
       "39 NaN NaN NaN NaN NaN  \n",
       "40 NaN NaN NaN NaN NaN  \n",
       "41 NaN NaN NaN NaN NaN  \n",
       "42 NaN NaN NaN NaN NaN  \n",
       "43 NaN NaN NaN NaN NaN  \n",
       "44 NaN NaN NaN NaN NaN  \n",
       "45 NaN NaN NaN NaN NaN  \n",
       "46 NaN NaN NaN NaN NaN  \n",
       "47 NaN NaN NaN NaN NaN  \n",
       "48 NaN NaN NaN NaN NaN  \n",
       "49 NaN NaN NaN NaN NaN  \n",
       "50 NaN NaN NaN NaN NaN  \n",
       "51 NaN NaN NaN NaN NaN  \n",
       "52 NaN NaN NaN NaN NaN  \n",
       "53 NaN NaN NaN NaN NaN  \n",
       "54 NaN NaN NaN NaN NaN  \n",
       "55 NaN NaN NaN NaN NaN  \n",
       "56 NaN NaN NaN NaN NaN  \n",
       "57 NaN NaN NaN NaN NaN  \n",
       "58 NaN NaN NaN NaN NaN  \n",
       "59 NaN NaN NaN NaN NaN  \n",
       "\n",
       "[60 rows x 40 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[:,:][data.iloc[:,:]>5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "titanic = sns.load_dataset('titanic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(891, 15)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 15 columns):\n",
      "survived       891 non-null int64\n",
      "pclass         891 non-null int64\n",
      "sex            891 non-null object\n",
      "age            714 non-null float64\n",
      "sibsp          891 non-null int64\n",
      "parch          891 non-null int64\n",
      "fare           891 non-null float64\n",
      "embarked       889 non-null object\n",
      "class          891 non-null category\n",
      "who            891 non-null object\n",
      "adult_male     891 non-null bool\n",
      "deck           203 non-null category\n",
      "embark_town    889 non-null object\n",
      "alive          891 non-null object\n",
      "alone          891 non-null bool\n",
      "dtypes: bool(2), category(2), float64(2), int64(4), object(5)\n",
      "memory usage: 80.2+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa09e4f6160>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rGphkJvij4bAmFOQbqSVJfV2n5MTj8qZnUC+FalGPetQ7p96pTvWGjxmpJUld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\nJdOKRzEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa09e4df5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic.age[titanic.sex=='male'].plot(kind='hist',bins=16,range=(0,80),alpha=1)\n",
    "titanic.age[titanic.sex=='female'].plot(kind='hist', bins=16,range=(0,80),alpha=.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80.0"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.age[titanic.sex=='male'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}