clean_team_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-15T18:23:14.077362",
     "start_time": "2017-02-15T18:23:13.720918"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "pd.set_option(\"display.notebook_repr_html\", False)\n",
    "#pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-14T17:36:12.734193",
     "start_time": "2017-02-14T17:36:12.707969"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8708 entries, 0 to 8707\n",
      "Columns: 225 entries, (Person.ID, 1) to (C, 15)\n",
      "dtypes: float64(105), object(120)\n",
      "memory usage: 14.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-14T17:36:13.280022",
     "start_time": "2017-02-14T17:36:13.276969"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "matplotlib.rcParams['figure.figsize'] = [12, 8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-14T17:15:53.263044",
     "start_time": "2017-02-14T17:15:49.308226"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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bpX098D3gUw3IO65OOeWUZkcYwJlq40zDSy2PWVmR+maR2gJujxXTli3T+Od//qdmx9gl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\nBRCnn356tLa2Rmtraxx//PF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twEtA+fqtq4BLJLVKegvZJ8HfAHfCrvF2LXClpJMktQA3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h5IM5NNfJ103jlrezhr2hQx1AWcziJpDtADnwQ+w0TZLzNrXm9vL11dXZA1TnuLzjMUSZuBN0XE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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ea15e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hists = df.hist([f + str(1) for f in p1_features_cont], bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-14T17:16:15.864140",
     "start_time": "2017-02-14T17:15:53.267752"
    },
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAMC0Gekr36WU9yb5SDpf8744yXuSHE7ye90mdya5pZSyI8lTSW5LsivJPWOqFwAAAKbC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\n7PPH4SR/muTf5fhnjv7t9u5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iZNNdINtpd39f8TijkT99CG3onIU2wxei+PhhtDn6SpQn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\nb+CiGA6MDSE0FEVxPKpH/aD//gnVFlvm/5ehmr97IoaX+/O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CaOiGh+HAPiGEhbXOu83x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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11810df98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AAAB0Jr4BAACgM/ENAAAAnYlvAAAA6Ex8AwAAQGfiGwAAADoT3wAAANCZ+AYA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\nvgEAAGCwX4kCDIlw/W9FAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11943efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Ydvjw4RO+/1rPfO9O8u8m2VdVNW07K8lVVfW2JD+apDI7uz1/9ntbkqMvIX8kyZaqumDV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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c5d9240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1AAAANAhrAAAAaBDWAAAA0CCsAQAAoEFYAwAAQEMrrKvqnVX1RFVdtmL84qq6p6oeqqqP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\nP8gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11cf54c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oQMAGAACADgRsAAAA6EDABgAAgA4EbAAAAOhAwAYAAIAOBGwAAADoQMAGAACADgRsAAAA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\nQYIECRIkiAD/H3ic1BSGmP+vAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11def2b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AADoT3wAAANCZ+AYAAIDOxDcAAAB0Jr4BAACgM/ENAAAAnYlvAAAA6Ex8AwAAQGfiGwAA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\nSWs+naxoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d2159b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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bp4c+l+TxuZnTkpyS5JbpoVuSbKiql8+89rZMwv7WBdcMAAAAS7XQzvcY4+EkX5w9VlUP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\n0Oz/Aj+bE8YxLQusAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11eff6d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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JcsfMmk1Vde7c2e8t031H1sxf/fwpSc6fWfO49uzZkx07dqzuBwIAAIBjeLyTuvv27cvO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\nNNA8GTiuqk7rLp00GEkuB/6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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e289e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#f, axarr = plt.subplots(len(p1_features_cat))\n",
    "#f, ax = plt.subplots()\n",
    "for i, feat in enumerate(p1_features_cat):\n",
    "    col = feat + str(1)\n",
    "    s = df[col].value_counts()\n",
    "    plt.figure()\n",
    "    s.plot(kind=\"bar\")\n",
    "    #axarr[i].bar(s.index, s.values)\n",
    "    #ax.bar(df[feat + str(1)].value_counts())\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-15T18:35:48.638240",
     "start_time": "2017-02-15T18:35:46.434437"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/core/indexing.py:141: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "/Users/markhashimoto/Documents/data_science/data_science_retreat/work/classes/mini_competition/DSR_minicompetition/clean_team_data.py:111: PerformanceWarning: dropping on a non-lexsorted multi-index without a level parameter may impact performance.\n",
      "  # drop Person.ID column for now\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'Grant.Application.ID'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2133\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2134\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2135\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4433)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4279)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13742)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13696)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Grant.Application.ID'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/Users/markhashimoto/Documents/data_science/data_science_retreat/work/classes/mini_competition/DSR_minicompetition/clean_team_data.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    117\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m \u001b[0mX_team\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 119\u001b[0;31m \u001b[0mX_team\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mX_team\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Grant.Application.ID\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    120\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    121\u001b[0m \u001b[0;31m######################################################################\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2055\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2056\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mis_mi_columns\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2057\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2058\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2059\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_multilevel\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2099\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2100\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2101\u001b[0;31m         \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2102\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2103\u001b[0m             \u001b[0mnew_columns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/multi.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method)\u001b[0m\n\u001b[1;32m   1641\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1642\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1643\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_level_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1644\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0m_maybe_to_slice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1645\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/multi.py\u001b[0m in \u001b[0;36m_get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m   1903\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1904\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1905\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlevel_index\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1906\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlevel\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlexsort_depth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1907\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbool\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2134\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2135\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2136\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2138\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4433)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4279)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13742)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13696)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Grant.Application.ID'"
     ]
    }
   ],
   "source": [
    "%run clean_team_data.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-02-15T18:36:25.616236",
     "start_time": "2017-02-15T18:36:25.544281"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Grant.Application.ID'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2133\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2134\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2135\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4433)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4279)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13742)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13696)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Grant.Application.ID'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-11-df42588254ac>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Grant.Application.ID\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2055\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2056\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mis_mi_columns\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2057\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2058\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2059\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_multilevel\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2099\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2100\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2101\u001b[0;31m         \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2102\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2103\u001b[0m             \u001b[0mnew_columns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/multi.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method)\u001b[0m\n\u001b[1;32m   1641\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1642\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1643\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_level_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1644\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0m_maybe_to_slice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1645\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/multi.py\u001b[0m in \u001b[0;36m_get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m   1903\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1904\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1905\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlevel_index\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1906\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlevel\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlexsort_depth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1907\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbool\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/markhashimoto/anaconda/lib/python3.5/site-packages/pandas/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2134\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2135\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2136\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2138\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4433)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/index.pyx\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas/index.c:4279)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13742)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/src/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13696)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Grant.Application.ID'"
     ]
    }
   ],
   "source": [
    "df[\"Grant.Application.ID\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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