FEC.v2.ipynb

{
 "metadata": {
  "name": "FEC"
 },
 "nbformat": 2,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import *",
      "import matplotlib as mpl",
      "mpl.rc('figure', figsize=(12, 6))",
      "set_printoptions(max_columns=18)",
      "months = {'JAN' : 1, 'FEB' : 2, 'MAR' : 3, 'APR' : 4, 'MAY' : 5, 'JUN' : 6,",
      "          'JUL' : 7, 'AUG' : 8, 'SEP' : 9, 'OCT': 10, 'NOV': 11, 'DEC' : 12}",
      "of_interest = ['Obama, Barack', 'Romney, Mitt', 'Santorum, Rick', ",
      "               'Paul, Ron', 'Gingrich, Newt']",
      "parties = {",
      "  'Bachmann, Michelle': 'Republican',",
      "  'Romney, Mitt': 'Republican',",
      "  'Obama, Barack': 'Democrat',",
      "  \"Roemer, Charles E. 'Buddy' III\": 'Reform',",
      "  'Pawlenty, Timothy': 'Republican',",
      "  'Johnson, Gary Earl': 'Libertarian',",
      "  'Paul, Ron': 'Republican',",
      "  'Santorum, Rick': 'Republican',",
      "  'Cain, Herman': 'Republican',",
      "  'Gingrich, Newt': 'Republican',",
      "  'McCotter, Thaddeus G': 'Republican',",
      "  'Huntsman, Jon': 'Republican',",
      "  'Perry, Rick': 'Republican'           ",
      " }"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "DataFrame.add?"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 207
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "fec = read_csv('P00000001-ALL.txt')",
      "# this takes a long time",
      "# fec['contb_receipt_dt'] = fec.contb_receipt_dt.map(datetools.to_datetime)",
      "",
      "# pickle as 'fec_data' then use this next time",
      "#fec = load('fec_data')"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def convert_date(datestr):",
      "    d, m, y = datestr.split('-')",
      "    m = months[m]",
      "    return datetime(int('20' + y), int(m), int(d))",
      "fec['contb_receipt_dt'] = fec.contb_receipt_dt.map(convert_date)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "dtypes: float64(1), int64(1), object(14)"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "import pandas",
      "pandas."
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 50,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "dtypes: float64(1), int64(1), object(14)"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "df = DataFrame(np.random.randn(50, "
     ],
     "language": "python",
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "foo = fec.cand_nm.copy()",
      "res = foo[np.random.permutation(len(foo))]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "DataFrame({'foo' : {'a': 1, 'b':2}, 'bar': {'a':np.zeros(5), 'b':1, 'c':2}}, index=['c', 'b', 'a', 'd'], columns=['foo', 'bar'])"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>foo</th>",
        "      <th>bar</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>c</strong></td>",
        "      <td>NaN</td>",
        "      <td>                     2</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>b</strong></td>",
        "      <td>  2</td>",
        "      <td>                     1</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>a</strong></td>",
        "      <td>  1</td>",
        "      <td> [ 0.  0.  0.  0.  0.]</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>d</strong></td>",
        "      <td>NaN</td>",
        "      <td>                   NaN</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 75,
       "text": [
        "   foo                    bar",
        "c  NaN                      2",
        "b    2                      1",
        "a    1  [ 0.  0.  0.  0.  0.]",
        "d  NaN                    NaN"
       ]
      }
     ],
     "prompt_number": 75
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "del fec['foo']"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 70
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 71,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "dtypes: float64(1), int64(1), object(14)"
       ]
      }
     ],
     "prompt_number": 71
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [],
     "language": "python",
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "parties"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 78,
       "text": [
        "{'Bachmann, Michelle': 'Republican',",
        " 'Cain, Herman': 'Republican',",
        " 'Gingrich, Newt': 'Republican',",
        " 'Huntsman, Jon': 'Republican',",
        " 'Johnson, Gary Earl': 'Libertarian',",
        " 'McCotter, Thaddeus G': 'Republican',",
        " 'Obama, Barack': 'Democrat',",
        " 'Paul, Ron': 'Republican',",
        " 'Pawlenty, Timothy': 'Republican',",
        " 'Perry, Rick': 'Republican',",
        " \"Roemer, Charles E. 'Buddy' III\": 'Reform',",
        " 'Romney, Mitt': 'Republican',",
        " 'Santorum, Rick': 'Republican'}"
       ]
      }
     ],
     "prompt_number": 78
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec.cand_nm.map(parties).value_counts()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 220,
       "text": [
        "Democrat       292400",
        "Republican     237575",
        "Reform           5364",
        "Libertarian       702"
       ]
      }
     ],
     "prompt_number": 220
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "[parties[name] for name in fec.cand_nm]",
      "fec.cand_nm.map(parties).value_counts()",
      "# fec.cand_nm.map(parties).value_counts()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 83,
       "text": [
        "Democrat       292400",
        "Republican     237575",
        "Reform           5364",
        "Libertarian       702"
       ]
      }
     ],
     "prompt_number": 83
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "fec['party'] = fec.cand_nm.map(parties)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 221
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "set_printoptions(max_rows=500)",
      "grouped = fec.groupby(['cand_nm', 'contb_receipt_dt'])",
      "result = grouped['contb_receipt_amt'].sum()",
      "result.unstack('cand_nm').cumsum().plot()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 235,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x13b686b50>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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X0jTw+XojhBDSuJycnDBixAhMmzZN2qHUuzqPqT148CCcnZ3rNShpEggELW6c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\nSdJzT1ZqJUmSJEmSpOfe/wIJI04cjpGRrQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 235
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "set_printoptions(notebook_repr_html=False)",
      "df = DataFrame(randn(10, 4), index=DateRange('1/1/2000', periods=10))",
      "Panel({'item1':df, 'item2':df}).to_frame().ix[datetime(2000, 1, 5):datetime(2000, 1, 10)]"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 241,
       "text": [
        "                     item1     item2",
        "major      minor                    ",
        "2000-01-05 0     -0.304216 -0.304216",
        "           1      0.175020  0.175020",
        "           2     -1.825847 -1.825847",
        "           3      0.616144  0.616144",
        "2000-01-06 0     -1.187492 -1.187492",
        "           1      0.304283  0.304283",
        "           2     -0.739825 -0.739825",
        "           3     -2.686096 -2.686096",
        "2000-01-07 0      0.475826  0.475826",
        "           1     -0.359847 -0.359847",
        "           2      0.525797  0.525797",
        "           3      1.047955  1.047955",
        "2000-01-10 0     -1.446176 -1.446176",
        "           1     -2.554074 -2.554074",
        "           2      0.905620  0.905620",
        "           3      1.389884  1.389884"
       ]
      }
     ],
     "prompt_number": 241
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 85,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "party                536041  non-null values",
        "dtypes: float64(1), int64(1), object(15)"
       ]
      }
     ],
     "prompt_number": 85
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec.cand_nm.unique()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 86,
       "text": [
        "array([Bachmann, Michelle, Romney, Mitt, Obama, Barack,",
        "       Roemer, Charles E. 'Buddy' III, Pawlenty, Timothy,",
        "       Johnson, Gary Earl, Paul, Ron, Santorum, Rick, Cain, Herman,",
        "       Gingrich, Newt, McCotter, Thaddeus G, Huntsman, Jon, Perry, Rick], dtype=object)"
       ]
      }
     ],
     "prompt_number": 86
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 87,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "party                536041  non-null values",
        "dtypes: float64(1), int64(1), object(15)"
       ]
      }
     ],
     "prompt_number": 87
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grouped = fec.groupby(['cand_nm', 'contb_receipt_dt'])",
      "",
      "by_date = grouped['contb_receipt_amt'].sum()",
      "by_date = by_date.unstack(0)",
      "by_date[of_interest].cumsum().plot()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 136,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Int64Index: 536041 entries, 0 to 536040",
        "Data columns:",
        "cmte_id              536041  non-null values",
        "cand_id              536041  non-null values",
        "cand_nm              536041  non-null values",
        "contbr_nm            536041  non-null values",
        "contbr_city          536026  non-null values",
        "contbr_st            536040  non-null values",
        "contbr_zip           535973  non-null values",
        "contbr_employer      531417  non-null values",
        "contbr_occupation    531448  non-null values",
        "contb_receipt_amt    536041  non-null values",
        "contb_receipt_dt     536041  non-null values",
        "receipt_desc         8479  non-null values",
        "memo_cd              49718  non-null values",
        "memo_text            52740  non-null values",
        "form_tp              536041  non-null values",
        "file_num             536041  non-null values",
        "party                536041  non-null values",
        "dtypes: float64(1), int64(1), object(15)"
       ]
      }
     ],
     "prompt_number": 136
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = fec.groupby('cand_nm')['contb_receipt_amt'].apply(lambda x: Series(x.order()[-5:].values))"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 163
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df1 = DataFrame({'k1' : ['a', 'b', 'c', 'a', 'b', 'c'], ",
      "                'k2':['one', 'one', 'one', 'two', 'two', 'two'], 'v1':randn(6), 'v2':randn(6)})",
      "df2 = DataFrame({'k1' : ['a', 'b', 'c', 'a', 'b', 'c'], ",
      "                'k2':['one', 'one', 'one', 'two', 'two', 'two'], 'v1':randn(6), 'v2':randn(6)})",
      "df3 = DataFrame({'k1' : ['a', 'b', 'c', 'a', 'b', 'c'], ",
      "                'k2':['one', 'one', 'one', 'two', 'two', 'two'], 'v1':randn(6), 'v2':randn(6)})",
      "df = concat([df1, df2, df3])",
      "def f(group):",
      "    return group['v1'].corr(group['v2'])",
      "# df.groupby(['k1', 'k2']).apply(f).unstack()",
      "df.pivot_table(['v1', 'v2'], rows='k1', cols='k2', aggfunc=f)"
     ],
     "language": "python",
     "outputs": [
      {
       "ename": "Exception",
       "evalue": "Index cannot contain duplicate values!",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m/Users/wesm/Dropbox/talks/pandas_tutorial_pycon/tut_files/<ipython-input-183-bb746168c69f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'v1'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'v2'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;31m# df.groupby(['k1', 'k2']).apply(f).unstack()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpivot_table\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'v1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'v2'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'k1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcols\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'k2'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maggfunc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/tools/pivot.pyc\u001b[0m in \u001b[0;36mpivot_table\u001b[0;34m(data, values, rows, cols, aggfunc, fill_value, margins)\u001b[0m\n\u001b[1;32m     87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m     \u001b[0mgrouped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m     \u001b[0magged\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgrouped\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0magg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maggfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m     \u001b[0mtable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0magged\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36magg\u001b[0;34m(self, func, *args, **kwargs)\u001b[0m\n\u001b[1;32m    238\u001b[0m         \u001b[0mSee\u001b[0m \u001b[0mdocstring\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0maggregate\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    239\u001b[0m         \"\"\"\n\u001b[0;32m--> 240\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maggregate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_iterate_slices\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36maggregate\u001b[0;34m(self, arg, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1151\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1152\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrouper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupings\u001b[0m\u001b[0;34m)\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[0;32m-> 1153\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_python_agg_general\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1154\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1155\u001b[0m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_aggregate_generic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36m_python_agg_general\u001b[0;34m(self, func, *args, **kwargs)\u001b[0m\n\u001b[1;32m    316\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterate_slices\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    317\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 318\u001b[0;31m                 \u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcounts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrouper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0magg_series\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0magg_func\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    319\u001b[0m                 \u001b[0moutput\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    320\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36magg_series\u001b[0;34m(self, obj, func)\u001b[0m\n\u001b[1;32m    594\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_aggregate_series_fast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    595\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 596\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_aggregate_series_pure_python\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    597\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    598\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_aggregate_series_fast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36m_aggregate_series_pure_python\u001b[0;34m(self, obj, func)\u001b[0m\n\u001b[1;32m    621\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    622\u001b[0m         for label, group in _generate_groups(obj, group_index, ngroups,\n\u001b[0;32m--> 623\u001b[0;31m                                              axis=self.axis):\n\u001b[0m\u001b[1;32m    624\u001b[0m             \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    625\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/groupby.pyc\u001b[0m in \u001b[0;36mgenerate_groups\u001b[0;34m(data, group_index, ngroups, axis, factory)\u001b[0m\n\u001b[1;32m   1447\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1448\u001b[0m         \u001b[0msorted_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1449\u001b[0;31m         \u001b[0msorted_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msorted_axis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1450\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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[1;32m   1451\u001b[0m         \u001b[0msorted_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/series.pyc\u001b[0m in \u001b[0;36mreindex\u001b[0;34m(self, index, method, level, fill_value, copy)\u001b[0m\n\u001b[1;32m   1888\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1889\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\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[0;32m-> 1890\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnan\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1891\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1892\u001b[0m         new_index, fill_vec = self.index.reindex(index, method=method,\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/index.pyc\u001b[0m in \u001b[0;36mreindex\u001b[0;34m(self, target, method, level)\u001b[0m\n\u001b[1;32m    648\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    649\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 650\u001b[0;31m                 \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[0mtarget\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    651\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    652\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/index.pyc\u001b[0m in \u001b[0;36mget_indexer\u001b[0;34m(self, target, method)\u001b[0m\n\u001b[1;32m    586\u001b[0m                                      target.indexMap)\n\u001b[1;32m    587\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 588\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_indexer_standard\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    589\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    590\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'unrecognized method: %s'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/index.pyc\u001b[0m in \u001b[0;36m_get_indexer_standard\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m    596\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_left_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    597\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 598\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_merge_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindexMap\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    599\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    600\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mto_groupby\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/core/index.pyc\u001b[0m in \u001b[0;36mindexMap\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    164\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mindexMap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    165\u001b[0m         \u001b[0;34m\"{label -> location}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 166\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_mapping\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    167\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    168\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_cleanup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/_engines.so\u001b[0m in \u001b[0;36mpandas._engines.DictIndexEngine.get_mapping (pandas/src/engines.c:2157)\u001b[0;34m()\u001b[0m\n",
        "\u001b[0;32m/Users/wesm/code/pandas/pandas/_engines.so\u001b[0m in \u001b[0;36mpandas._engines.DictIndexEngine.get_mapping (pandas/src/engines.c:2088)\u001b[0;34m()\u001b[0m\n",
        "\u001b[0;31mException\u001b[0m: Index cannot contain duplicate values!"
       ]
      }
     ],
     "prompt_number": 183
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>k1</th>",
        "      <th>k2</th>",
        "      <th>v1</th>",
        "      <th>v2</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>0</strong></td>",
        "      <td> a</td>",
        "      <td> one</td>",
        "      <td> 1.428155</td>",
        "      <td> 0.803457</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>1</strong></td>",
        "      <td> b</td>",
        "      <td> one</td>",
        "      <td> 0.174513</td>",
        "      <td>-0.163652</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2</strong></td>",
        "      <td> c</td>",
        "      <td> one</td>",
        "      <td> 0.491576</td>",
        "      <td>-1.615540</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>3</strong></td>",
        "      <td> a</td>",
        "      <td> two</td>",
        "      <td> 0.335232</td>",
        "      <td> 0.021276</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>4</strong></td>",
        "      <td> b</td>",
        "      <td> two</td>",
        "      <td>-1.817989</td>",
        "      <td>-1.588397</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>5</strong></td>",
        "      <td> c</td>",
        "      <td> two</td>",
        "      <td>-0.437044</td>",
        "      <td>-0.228216</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>0</strong></td>",
        "      <td> a</td>",
        "      <td> one</td>",
        "      <td> 1.033687</td>",
        "      <td>-2.246327</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>1</strong></td>",
        "      <td> b</td>",
        "      <td> one</td>",
        "      <td> 1.290898</td>",
        "      <td>-0.323642</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2</strong></td>",
        "      <td> c</td>",
        "      <td> one</td>",
        "      <td> 2.175360</td>",
        "      <td> 0.097117</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>3</strong></td>",
        "      <td> a</td>",
        "      <td> two</td>",
        "      <td>-0.798585</td>",
        "      <td>-1.231085</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>4</strong></td>",
        "      <td> b</td>",
        "      <td> two</td>",
        "      <td>-0.844068</td>",
        "      <td>-1.008117</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>5</strong></td>",
        "      <td> c</td>",
        "      <td> two</td>",
        "      <td> 0.920177</td>",
        "      <td>-0.295157</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
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       "output_type": "pyout",
       "prompt_number": 177,
       "text": [
        "  k1   k2        v1        v2",
        "0  a  one  1.428155  0.803457",
        "1  b  one  0.174513 -0.163652",
        "2  c  one  0.491576 -1.615540",
        "3  a  two  0.335232  0.021276",
        "4  b  two -1.817989 -1.588397",
        "5  c  two -0.437044 -0.228216",
        "0  a  one  1.033687 -2.246327",
        "1  b  one  1.290898 -0.323642",
        "2  c  one  2.175360  0.097117",
        "3  a  two -0.798585 -1.231085",
        "4  b  two -0.844068 -1.008117",
        "5  c  two  0.920177 -0.295157"
       ]
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     ],
     "prompt_number": 177
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [],
     "language": "python",
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "set_printoptions(notebook_repr_html=True)",
      "fec.pivot_table('contb_receipt_amt', rows='contbr_st', cols='cand_nm', aggfunc=np.sum, fill_value=0)"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th>cand_nm</th>",
        "      <th>Bachmann, Michelle</th>",
        "      <th>Cain, Herman</th>",
        "      <th>Gingrich, Newt</th>",
        "      <th>Huntsman, Jon</th>",
        "      <th>Johnson, Gary Earl</th>",
        "      <th>McCotter, Thaddeus G</th>",
        "      <th>Obama, Barack</th>",
        "      <th>Paul, Ron</th>",
        "      <th>Pawlenty, Timothy</th>",
        "      <th>Perry, Rick</th>",
        "      <th>Roemer, Charles E. 'Buddy' III</th>",
        "      <th>Romney, Mitt</th>",
        "      <th>Santorum, Rick</th>",
        "    </tr>",
        "    <tr>",
        "      <th>contbr_st</th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>AA</strong></td>",
        "      <td>      0.00</td>",
        "      <td>    250.00</td>",
        "      <td>       0.00</td>",
        "      <td>    275.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    28645.00</td>",
        "      <td>     650.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AB</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     1536.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AE</strong></td>",
        "      <td>   1750.00</td>",
        "      <td>   1005.00</td>",
        "      <td>    4675.00</td>",
        "      <td>    300.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    18708.00</td>",
        "      <td>   40365.35</td>",
        "      <td>       0.00</td>",
        "      <td>     1550.00</td>",
        "      <td>   310.00</td>",
        "      <td>    4380.00</td>",
        "      <td>    500.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AK</strong></td>",
        "      <td>   7890.50</td>",
        "      <td>  30503.92</td>",
        "      <td>   23530.00</td>",
        "      <td>   2500.00</td>",
        "      <td>  1900.00</td>",
        "      <td>     0</td>",
        "      <td>   159447.40</td>",
        "      <td>   96261.18</td>",
        "      <td>     250.00</td>",
        "      <td>     3900.00</td>",
        "      <td>   705.00</td>",
        "      <td>   54110.24</td>",
        "      <td>   4984.74</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AL</strong></td>",
        "      <td>  24932.00</td>",
        "      <td>  93936.87</td>",
        "      <td>  122833.00</td>",
        "      <td>   4500.00</td>",
        "      <td>   600.00</td>",
        "      <td>     0</td>",
        "      <td>   273970.37</td>",
        "      <td>  169820.99</td>",
        "      <td>   15300.00</td>",
        "      <td>    30999.96</td>",
        "      <td>  5700.24</td>",
        "      <td>  289743.48</td>",
        "      <td>  27856.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AP</strong></td>",
        "      <td>   1000.00</td>",
        "      <td>    500.00</td>",
        "      <td>    1800.00</td>",
        "      <td>    625.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    27620.00</td>",
        "      <td>   25074.08</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>   220.00</td>",
        "      <td>     600.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AR</strong></td>",
        "      <td>  18350.00</td>",
        "      <td>  54711.02</td>",
        "      <td>   49465.00</td>",
        "      <td>  13604.00</td>",
        "      <td>   250.00</td>",
        "      <td>     0</td>",
        "      <td>   160254.33</td>",
        "      <td>   85272.56</td>",
        "      <td>   13350.00</td>",
        "      <td>    29565.00</td>",
        "      <td>  1611.00</td>",
        "      <td>   57110.50</td>",
        "      <td>   8275.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AS</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     1750.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>AZ</strong></td>",
        "      <td>  63427.00</td>",
        "      <td> 241891.63</td>",
        "      <td>  169083.00</td>",
        "      <td>  60618.00</td>",
        "      <td>  8900.00</td>",
        "      <td>     0</td>",
        "      <td>   756441.19</td>",
        "      <td>  362187.89</td>",
        "      <td>   90075.00</td>",
        "      <td>    79099.00</td>",
        "      <td>  6181.12</td>",
        "      <td> 1139583.82</td>",
        "      <td>  45505.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>BR</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     -500.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>CA</strong></td>",
        "      <td> 343130.77</td>",
        "      <td> 562920.91</td>",
        "      <td>  899405.08</td>",
        "      <td> 403495.00</td>",
        "      <td> 71460.88</td>",
        "      <td>  1030</td>",
        "      <td> 15446278.66</td>",
        "      <td> 1987962.47</td>",
        "      <td>  777830.00</td>",
        "      <td>  1592930.60</td>",
        "      <td> 35840.05</td>",
        "      <td> 6930695.27</td>",
        "      <td> 200257.65</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>CO</strong></td>",
        "      <td>  59144.65</td>",
        "      <td> 126109.66</td>",
        "      <td>  150867.01</td>",
        "      <td>  20525.00</td>",
        "      <td> 27170.00</td>",
        "      <td>     0</td>",
        "      <td>  1278124.98</td>",
        "      <td>  335301.56</td>",
        "      <td>   75168.36</td>",
        "      <td>   228033.33</td>",
        "      <td>  4145.00</td>",
        "      <td>  847365.20</td>",
        "      <td>  67254.34</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>CT</strong></td>",
        "      <td>  31690.00</td>",
        "      <td>  67519.12</td>",
        "      <td>  125595.00</td>",
        "      <td>  93498.00</td>",
        "      <td>  2500.00</td>",
        "      <td>     0</td>",
        "      <td>  1264462.23</td>",
        "      <td>  212306.16</td>",
        "      <td>   68300.00</td>",
        "      <td>    60750.00</td>",
        "      <td>  4035.00</td>",
        "      <td> 2394681.72</td>",
        "      <td>  34074.45</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>DC</strong></td>",
        "      <td>   2985.00</td>",
        "      <td>   9970.00</td>",
        "      <td>   30995.00</td>",
        "      <td>  94263.50</td>",
        "      <td>  5725.00</td>",
        "      <td>     0</td>",
        "      <td>  2822874.00</td>",
        "      <td>   32284.02</td>",
        "      <td>   34490.00</td>",
        "      <td>    73900.00</td>",
        "      <td>  1910.00</td>",
        "      <td>  615536.38</td>",
        "      <td>  14001.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>DE</strong></td>",
        "      <td>   3685.00</td>",
        "      <td>  14115.00</td>",
        "      <td>    7515.00</td>",
        "      <td>   7353.00</td>",
        "      <td>  2850.00</td>",
        "      <td>     0</td>",
        "      <td>   204406.59</td>",
        "      <td>   43819.63</td>",
        "      <td>     800.00</td>",
        "      <td>     4450.00</td>",
        "      <td>   765.00</td>",
        "      <td>   44245.00</td>",
        "      <td>   3545.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>FF</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>   5500.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>    1500.00</td>",
        "      <td>     1000.00</td>",
        "      <td>     0.00</td>",
        "      <td>   83000.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>FL</strong></td>",
        "      <td> 185890.00</td>",
        "      <td> 686522.82</td>",
        "      <td> 1417740.34</td>",
        "      <td> 283224.19</td>",
        "      <td> 21455.00</td>",
        "      <td>   250</td>",
        "      <td>  4254393.29</td>",
        "      <td>  992851.71</td>",
        "      <td>  278678.92</td>",
        "      <td>   791036.89</td>",
        "      <td> 15266.35</td>",
        "      <td> 5612898.13</td>",
        "      <td> 284128.56</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>FM</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>      400.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>GA</strong></td>",
        "      <td>  41921.25</td>",
        "      <td> 863369.30</td>",
        "      <td>  876409.02</td>",
        "      <td>  47277.50</td>",
        "      <td>  6274.00</td>",
        "      <td>     0</td>",
        "      <td>  1219130.47</td>",
        "      <td>  361461.13</td>",
        "      <td>   88870.00</td>",
        "      <td>   187036.00</td>",
        "      <td>  7691.00</td>",
        "      <td> 1249731.12</td>",
        "      <td>  77029.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>GU</strong></td>",
        "      <td>   1249.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>    150.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     8601.50</td>",
        "      <td>    1829.40</td>",
        "      <td>    1000.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>    2250.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>HI</strong></td>",
        "      <td>   5522.00</td>",
        "      <td>  40139.39</td>",
        "      <td>   17875.00</td>",
        "      <td>    250.00</td>",
        "      <td>   500.00</td>",
        "      <td>     0</td>",
        "      <td>   579267.69</td>",
        "      <td>   88385.63</td>",
        "      <td>    3500.00</td>",
        "      <td>     2250.00</td>",
        "      <td>  1060.00</td>",
        "      <td>   69743.00</td>",
        "      <td>   5300.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>IA</strong></td>",
        "      <td>  45444.89</td>",
        "      <td>  56409.89</td>",
        "      <td>  101144.00</td>",
        "      <td>    900.00</td>",
        "      <td>   800.00</td>",
        "      <td>     0</td>",
        "      <td>   333515.55</td>",
        "      <td>  217711.06</td>",
        "      <td>   18030.00</td>",
        "      <td>    16000.00</td>",
        "      <td>  1445.00</td>",
        "      <td>  134496.13</td>",
        "      <td> 104826.45</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>ID</strong></td>",
        "      <td>  13318.00</td>",
        "      <td>  29131.35</td>",
        "      <td>   29270.00</td>",
        "      <td>  21500.00</td>",
        "      <td>   750.00</td>",
        "      <td>     0</td>",
        "      <td>   107863.94</td>",
        "      <td>  113518.96</td>",
        "      <td>    7950.00</td>",
        "      <td>     2250.00</td>",
        "      <td>   495.00</td>",
        "      <td>  441561.62</td>",
        "      <td>  10940.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>IL</strong></td>",
        "      <td>  89430.75</td>",
        "      <td> 177478.28</td>",
        "      <td>  247621.14</td>",
        "      <td> 151506.00</td>",
        "      <td>  9200.00</td>",
        "      <td>  2500</td>",
        "      <td>  9057090.30</td>",
        "      <td>  451800.86</td>",
        "      <td>  207691.14</td>",
        "      <td>   396185.00</td>",
        "      <td>  7911.00</td>",
        "      <td> 1943287.44</td>",
        "      <td> 106108.35</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>IN</strong></td>",
        "      <td>  33631.00</td>",
        "      <td>  97950.11</td>",
        "      <td>  116940.00</td>",
        "      <td>   8525.00</td>",
        "      <td>  2692.76</td>",
        "      <td>   100</td>",
        "      <td>   463689.81</td>",
        "      <td>  240972.32</td>",
        "      <td>   16600.00</td>",
        "      <td>    58350.00</td>",
        "      <td>  3220.12</td>",
        "      <td>  292439.23</td>",
        "      <td>  30785.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>KS</strong></td>",
        "      <td>  28984.25</td>",
        "      <td>  92904.54</td>",
        "      <td>   79807.76</td>",
        "      <td>   2400.00</td>",
        "      <td>     0.00</td>",
        "      <td>   275</td>",
        "      <td>   209137.57</td>",
        "      <td>  127160.84</td>",
        "      <td>   64000.00</td>",
        "      <td>    40850.00</td>",
        "      <td>  1625.00</td>",
        "      <td>   96770.12</td>",
        "      <td>  26630.80</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>KY</strong></td>",
        "      <td>  13186.00</td>",
        "      <td>  57846.90</td>",
        "      <td>   63789.88</td>",
        "      <td>   4870.00</td>",
        "      <td>  1000.00</td>",
        "      <td>  2500</td>",
        "      <td>   368299.03</td>",
        "      <td>  137683.48</td>",
        "      <td>    2800.00</td>",
        "      <td>    61550.00</td>",
        "      <td>  2365.00</td>",
        "      <td>  356545.35</td>",
        "      <td>  24840.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>LA</strong></td>",
        "      <td>  47483.00</td>",
        "      <td>  82851.23</td>",
        "      <td>  231468.82</td>",
        "      <td>   4500.00</td>",
        "      <td>  2650.00</td>",
        "      <td>     0</td>",
        "      <td>   344313.67</td>",
        "      <td>  208530.73</td>",
        "      <td>    9900.00</td>",
        "      <td>   604391.02</td>",
        "      <td> 78717.36</td>",
        "      <td>  382952.35</td>",
        "      <td>  42225.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MA</strong></td>",
        "      <td>  17202.25</td>",
        "      <td>  50846.51</td>",
        "      <td>  111995.00</td>",
        "      <td> 144673.50</td>",
        "      <td>  3250.00</td>",
        "      <td>     0</td>",
        "      <td>  4328768.70</td>",
        "      <td>  283619.35</td>",
        "      <td>   97850.00</td>",
        "      <td>    49949.00</td>",
        "      <td> 10263.12</td>",
        "      <td> 3522190.40</td>",
        "      <td>  28130.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MD</strong></td>",
        "      <td>  63463.25</td>",
        "      <td>  72640.66</td>",
        "      <td>  106087.00</td>",
        "      <td>  55323.00</td>",
        "      <td>  4800.00</td>",
        "      <td>     0</td>",
        "      <td>  2908630.05</td>",
        "      <td>  279740.25</td>",
        "      <td>   35815.00</td>",
        "      <td>   139620.00</td>",
        "      <td>  6586.56</td>",
        "      <td>  999304.79</td>",
        "      <td>  49551.22</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>ME</strong></td>",
        "      <td>   7272.00</td>",
        "      <td>  14413.99</td>",
        "      <td>   16965.00</td>",
        "      <td>   3204.00</td>",
        "      <td>   500.00</td>",
        "      <td>     0</td>",
        "      <td>   623131.70</td>",
        "      <td>   78844.10</td>",
        "      <td>    3000.00</td>",
        "      <td>      125.00</td>",
        "      <td>  1325.00</td>",
        "      <td>   82341.36</td>",
        "      <td>   3075.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MI</strong></td>",
        "      <td>  50332.72</td>",
        "      <td>  98023.72</td>",
        "      <td>  142101.60</td>",
        "      <td>  55042.00</td>",
        "      <td>  4545.00</td>",
        "      <td> 18200</td>",
        "      <td>  1363338.43</td>",
        "      <td>  354073.99</td>",
        "      <td>   62480.00</td>",
        "      <td>    28175.00</td>",
        "      <td>  6620.00</td>",
        "      <td> 1643083.84</td>",
        "      <td>  50128.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MN</strong></td>",
        "      <td> 253003.75</td>",
        "      <td>  68742.80</td>",
        "      <td>   96875.00</td>",
        "      <td>  11830.00</td>",
        "      <td>  2450.00</td>",
        "      <td>     0</td>",
        "      <td>   875186.25</td>",
        "      <td>  230372.21</td>",
        "      <td> 1046673.23</td>",
        "      <td>    11400.00</td>",
        "      <td>  3563.12</td>",
        "      <td>  163755.68</td>",
        "      <td>  47092.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MO</strong></td>",
        "      <td>  51446.00</td>",
        "      <td> 105258.54</td>",
        "      <td>  149845.00</td>",
        "      <td>   7542.00</td>",
        "      <td>  4545.00</td>",
        "      <td>     0</td>",
        "      <td>   839167.69</td>",
        "      <td>  216636.65</td>",
        "      <td>   46100.00</td>",
        "      <td>    68300.00</td>",
        "      <td>  4073.12</td>",
        "      <td> 1083215.24</td>",
        "      <td>  35608.10</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MP</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     2375.00</td>",
        "      <td>     250.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MS</strong></td>",
        "      <td>  18286.00</td>",
        "      <td>  23839.90</td>",
        "      <td>   51574.00</td>",
        "      <td>   2375.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>   102443.30</td>",
        "      <td>  117282.68</td>",
        "      <td>    2175.00</td>",
        "      <td>    93313.62</td>",
        "      <td>  1800.00</td>",
        "      <td>  202165.00</td>",
        "      <td>   7603.50</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>MT</strong></td>",
        "      <td>   8371.00</td>",
        "      <td>  36400.00</td>",
        "      <td>   26210.00</td>",
        "      <td>   3175.00</td>",
        "      <td>   100.00</td>",
        "      <td>     0</td>",
        "      <td>   175074.54</td>",
        "      <td>   98807.91</td>",
        "      <td>    3950.00</td>",
        "      <td>      450.50</td>",
        "      <td>   850.00</td>",
        "      <td>   63547.00</td>",
        "      <td>   5800.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NC</strong></td>",
        "      <td>  79697.25</td>",
        "      <td> 165586.98</td>",
        "      <td>  218934.94</td>",
        "      <td>  23266.00</td>",
        "      <td>  2865.00</td>",
        "      <td>     0</td>",
        "      <td>  1252353.66</td>",
        "      <td>  380139.64</td>",
        "      <td>    4650.00</td>",
        "      <td>    77025.00</td>",
        "      <td>  7383.05</td>",
        "      <td>  446364.34</td>",
        "      <td>  63720.75</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>ND</strong></td>",
        "      <td>  17595.00</td>",
        "      <td>  12789.00</td>",
        "      <td>   16495.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    31989.27</td>",
        "      <td>   50135.75</td>",
        "      <td>    5700.00</td>",
        "      <td>     3500.00</td>",
        "      <td>   265.00</td>",
        "      <td>    8339.00</td>",
        "      <td>   5375.33</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NE</strong></td>",
        "      <td>  13724.00</td>",
        "      <td>  92547.90</td>",
        "      <td>   46244.00</td>",
        "      <td>   3129.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>   128361.47</td>",
        "      <td>   67869.69</td>",
        "      <td>   24000.00</td>",
        "      <td>     9200.00</td>",
        "      <td>   835.00</td>",
        "      <td>  112848.50</td>",
        "      <td>  25151.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NH</strong></td>",
        "      <td>  11322.00</td>",
        "      <td>  42541.10</td>",
        "      <td>   47935.00</td>",
        "      <td>  29253.00</td>",
        "      <td> 10550.00</td>",
        "      <td>  1000</td>",
        "      <td>   354590.45</td>",
        "      <td>  202843.12</td>",
        "      <td>   21635.00</td>",
        "      <td>    38058.00</td>",
        "      <td>  6890.00</td>",
        "      <td>  317665.11</td>",
        "      <td>  18825.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NJ</strong></td>",
        "      <td>  47388.00</td>",
        "      <td> 112610.80</td>",
        "      <td>  153066.00</td>",
        "      <td>  65172.00</td>",
        "      <td>  2000.00</td>",
        "      <td>   250</td>",
        "      <td>  1979577.16</td>",
        "      <td>  393937.71</td>",
        "      <td>   56885.00</td>",
        "      <td>   115985.00</td>",
        "      <td>  7471.00</td>",
        "      <td> 2553088.20</td>",
        "      <td>  76391.80</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NM</strong></td>",
        "      <td>  11571.00</td>",
        "      <td>  53825.99</td>",
        "      <td>   64030.00</td>",
        "      <td>   2905.00</td>",
        "      <td> 70369.00</td>",
        "      <td>     0</td>",
        "      <td>   460400.46</td>",
        "      <td>   99414.97</td>",
        "      <td>   10500.00</td>",
        "      <td>    55100.00</td>",
        "      <td>  1940.00</td>",
        "      <td>   72211.36</td>",
        "      <td>  11623.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NS</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>   1000.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NV</strong></td>",
        "      <td>  38936.00</td>",
        "      <td> 124973.78</td>",
        "      <td>  185617.56</td>",
        "      <td> 160140.00</td>",
        "      <td>  7450.00</td>",
        "      <td>   250</td>",
        "      <td>   455645.74</td>",
        "      <td>  292082.15</td>",
        "      <td>   57899.88</td>",
        "      <td>   143500.00</td>",
        "      <td>  2255.00</td>",
        "      <td>  415985.36</td>",
        "      <td>  15890.40</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>NY</strong></td>",
        "      <td> 102814.37</td>",
        "      <td> 178938.53</td>",
        "      <td>  349029.79</td>",
        "      <td> 403003.00</td>",
        "      <td> 29430.00</td>",
        "      <td>  3900</td>",
        "      <td>  9463595.60</td>",
        "      <td>  762521.13</td>",
        "      <td>  219325.00</td>",
        "      <td>   461250.00</td>",
        "      <td> 14761.36</td>",
        "      <td> 7600646.59</td>",
        "      <td> 122360.68</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>OH</strong></td>",
        "      <td>  72738.72</td>",
        "      <td> 213268.85</td>",
        "      <td>  205533.00</td>",
        "      <td>  23571.00</td>",
        "      <td>  5500.00</td>",
        "      <td>  3210</td>",
        "      <td>   951562.85</td>",
        "      <td>  386991.08</td>",
        "      <td>   42500.00</td>",
        "      <td>   310680.00</td>",
        "      <td>  7611.12</td>",
        "      <td>  622796.18</td>",
        "      <td>  81412.52</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>OK</strong></td>",
        "      <td>  27032.00</td>",
        "      <td> 137607.79</td>",
        "      <td>  118447.76</td>",
        "      <td>  38248.00</td>",
        "      <td>  2000.00</td>",
        "      <td>     0</td>",
        "      <td>   361652.33</td>",
        "      <td>  154896.74</td>",
        "      <td>    7850.00</td>",
        "      <td>   463650.00</td>",
        "      <td>  2240.00</td>",
        "      <td>  225689.60</td>",
        "      <td>  30095.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>ON</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>  -2500.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>      250.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>OR</strong></td>",
        "      <td>  26462.50</td>",
        "      <td>  64856.87</td>",
        "      <td>   59015.00</td>",
        "      <td>   9679.00</td>",
        "      <td>  2250.00</td>",
        "      <td>     0</td>",
        "      <td>   665863.41</td>",
        "      <td>  231343.94</td>",
        "      <td>    3850.00</td>",
        "      <td>    26617.00</td>",
        "      <td>  3610.24</td>",
        "      <td>  367828.73</td>",
        "      <td>  30387.45</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>PA</strong></td>",
        "      <td>  75557.00</td>",
        "      <td> 151688.93</td>",
        "      <td>  181254.21</td>",
        "      <td>  90050.00</td>",
        "      <td> 10425.00</td>",
        "      <td>     0</td>",
        "      <td>  2236879.70</td>",
        "      <td>  528918.45</td>",
        "      <td>   14080.00</td>",
        "      <td>   321002.12</td>",
        "      <td>  9134.12</td>",
        "      <td>  995025.87</td>",
        "      <td> 727571.91</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>PR</strong></td>",
        "      <td>    300.00</td>",
        "      <td>      0.00</td>",
        "      <td>    1250.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>   192597.00</td>",
        "      <td>    1202.40</td>",
        "      <td>   72000.00</td>",
        "      <td>     2800.00</td>",
        "      <td>   350.00</td>",
        "      <td>    8574.00</td>",
        "      <td>    550.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>QU</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>      500.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>RI</strong></td>",
        "      <td>   2700.00</td>",
        "      <td>   8700.00</td>",
        "      <td>    8180.00</td>",
        "      <td>   9800.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>   331534.42</td>",
        "      <td>   46521.12</td>",
        "      <td>     800.00</td>",
        "      <td>     6750.00</td>",
        "      <td>   895.00</td>",
        "      <td>  144419.56</td>",
        "      <td>  10565.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>SC</strong></td>",
        "      <td>  29782.00</td>",
        "      <td>  97883.56</td>",
        "      <td>  190451.00</td>",
        "      <td>   9513.00</td>",
        "      <td>   701.41</td>",
        "      <td>     0</td>",
        "      <td>   387606.80</td>",
        "      <td>  166527.72</td>",
        "      <td>    2800.00</td>",
        "      <td>   128050.00</td>",
        "      <td>  2910.40</td>",
        "      <td>  216514.36</td>",
        "      <td> 137532.22</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>SD</strong></td>",
        "      <td>   9394.00</td>",
        "      <td>  17869.99</td>",
        "      <td>   58495.00</td>",
        "      <td>   1000.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    47996.76</td>",
        "      <td>   26158.34</td>",
        "      <td>   24000.00</td>",
        "      <td>     6505.00</td>",
        "      <td>   440.00</td>",
        "      <td>  119655.00</td>",
        "      <td>  11975.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>SO</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     250.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>TE</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      265.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>TN</strong></td>",
        "      <td>  67555.50</td>",
        "      <td> 214197.53</td>",
        "      <td>  159025.00</td>",
        "      <td>  54900.00</td>",
        "      <td>   250.00</td>",
        "      <td>   290</td>",
        "      <td>   547884.51</td>",
        "      <td>  268961.06</td>",
        "      <td>   10105.00</td>",
        "      <td>   375752.00</td>",
        "      <td>  5905.12</td>",
        "      <td>  932656.04</td>",
        "      <td>  38366.76</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>TX</strong></td>",
        "      <td> 239951.75</td>",
        "      <td> 945768.02</td>",
        "      <td> 1040215.99</td>",
        "      <td> 186887.00</td>",
        "      <td> 48165.00</td>",
        "      <td>  1925</td>",
        "      <td>  4115801.40</td>",
        "      <td> 1905487.24</td>",
        "      <td>  370825.24</td>",
        "      <td> 10933923.75</td>",
        "      <td> 20218.35</td>",
        "      <td> 3267924.28</td>",
        "      <td> 307520.15</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>UK</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>UT</strong></td>",
        "      <td>   7213.00</td>",
        "      <td>  16539.99</td>",
        "      <td>   16615.00</td>",
        "      <td> 364273.00</td>",
        "      <td>  2400.00</td>",
        "      <td>     0</td>",
        "      <td>   359324.64</td>",
        "      <td>  145292.54</td>",
        "      <td>   29000.00</td>",
        "      <td>    22400.00</td>",
        "      <td>  1790.00</td>",
        "      <td> 2566763.17</td>",
        "      <td>   6235.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>VA</strong></td>",
        "      <td>  73363.66</td>",
        "      <td> 192593.56</td>",
        "      <td>  354018.54</td>",
        "      <td> 115863.79</td>",
        "      <td>  9276.29</td>",
        "      <td>   250</td>",
        "      <td>  2532165.45</td>",
        "      <td>  469936.64</td>",
        "      <td>  127862.17</td>",
        "      <td>   234171.12</td>",
        "      <td> 10202.50</td>",
        "      <td> 2266563.08</td>",
        "      <td> 178131.95</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>VI</strong></td>",
        "      <td>      0.00</td>",
        "      <td>   2500.00</td>",
        "      <td>     850.00</td>",
        "      <td>    250.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>    59964.00</td>",
        "      <td>       0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      209.00</td>",
        "      <td>   200.00</td>",
        "      <td>    3500.00</td>",
        "      <td>    500.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>VT</strong></td>",
        "      <td>   9495.00</td>",
        "      <td>  13660.00</td>",
        "      <td>    9785.00</td>",
        "      <td>   4850.00</td>",
        "      <td>   950.00</td>",
        "      <td>     0</td>",
        "      <td>   479321.80</td>",
        "      <td>   37498.27</td>",
        "      <td>    1750.00</td>",
        "      <td>     3800.00</td>",
        "      <td>   536.00</td>",
        "      <td>   41405.00</td>",
        "      <td>   2450.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>WA</strong></td>",
        "      <td>  55981.50</td>",
        "      <td> 113476.87</td>",
        "      <td>  198036.60</td>",
        "      <td>  40235.00</td>",
        "      <td> 21275.00</td>",
        "      <td>   500</td>",
        "      <td>  2187551.83</td>",
        "      <td>  471366.00</td>",
        "      <td>   21125.00</td>",
        "      <td>    38335.00</td>",
        "      <td>  9370.24</td>",
        "      <td>  639183.26</td>",
        "      <td>  48887.45</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>WI</strong></td>",
        "      <td>  31464.00</td>",
        "      <td> 123267.89</td>",
        "      <td>   67364.94</td>",
        "      <td>  16763.00</td>",
        "      <td>   277.55</td>",
        "      <td>   100</td>",
        "      <td>   655354.82</td>",
        "      <td>  178446.56</td>",
        "      <td>   19090.00</td>",
        "      <td>    10885.00</td>",
        "      <td>  4161.12</td>",
        "      <td>  156813.48</td>",
        "      <td>  29741.01</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>WV</strong></td>",
        "      <td>   9488.78</td>",
        "      <td>  14014.00</td>",
        "      <td>   21265.00</td>",
        "      <td>   5119.00</td>",
        "      <td>     0.00</td>",
        "      <td>   500</td>",
        "      <td>   100951.55</td>",
        "      <td>   64700.18</td>",
        "      <td>       0.00</td>",
        "      <td>   170025.00</td>",
        "      <td>   643.00</td>",
        "      <td>   73589.12</td>",
        "      <td>   5400.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>WY</strong></td>",
        "      <td>  12967.00</td>",
        "      <td>  40535.00</td>",
        "      <td>   30865.00</td>",
        "      <td>   6500.00</td>",
        "      <td>   275.00</td>",
        "      <td>     0</td>",
        "      <td>   101826.50</td>",
        "      <td>   85315.25</td>",
        "      <td>   15000.00</td>",
        "      <td>    13400.00</td>",
        "      <td>   615.00</td>",
        "      <td>  164660.24</td>",
        "      <td>  17726.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>XX</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>  23500.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>        0.00</td>",
        "      <td>       0.00</td>",
        "      <td>    1500.00</td>",
        "      <td>    14000.00</td>",
        "      <td>   102.00</td>",
        "      <td>  283300.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>ZZ</strong></td>",
        "      <td>      0.00</td>",
        "      <td>      0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "      <td>     0.00</td>",
        "      <td>     0</td>",
        "      <td>     5638.00</td>",
        "      <td>   24415.53</td>",
        "      <td>       0.00</td>",
        "      <td>        0.00</td>",
        "      <td>     0.00</td>",
        "      <td>       0.00</td>",
        "      <td>      0.00</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 242,
       "text": [
        "cand_nm    Bachmann, Michelle  Cain, Herman  Gingrich, Newt  Huntsman, Jon  Johnson, Gary Earl  McCotter, Thaddeus G  Obama, Barack   Paul, Ron  Pawlenty, Timothy  Perry, Rick  Roemer, Charles E. 'Buddy' III  Romney, Mitt  Santorum, Rick",
        "contbr_st                                                                                                                                                                                                                                    ",
        "AA                       0.00        250.00            0.00         275.00                0.00                     0       28645.00      650.00               0.00         0.00                            0.00          0.00            0.00",
        "AB                       0.00          0.00            0.00           0.00                0.00                     0        1536.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "AE                    1750.00       1005.00         4675.00         300.00                0.00                     0       18708.00    40365.35               0.00      1550.00                          310.00       4380.00          500.00",
        "AK                    7890.50      30503.92        23530.00        2500.00             1900.00                     0      159447.40    96261.18             250.00      3900.00                          705.00      54110.24         4984.74",
        "AL                   24932.00      93936.87       122833.00        4500.00              600.00                     0      273970.37   169820.99           15300.00     30999.96                         5700.24     289743.48        27856.00",
        "AP                    1000.00        500.00         1800.00         625.00                0.00                     0       27620.00    25074.08               0.00         0.00                          220.00        600.00            0.00",
        "AR                   18350.00      54711.02        49465.00       13604.00              250.00                     0      160254.33    85272.56           13350.00     29565.00                         1611.00      57110.50         8275.00",
        "AS                       0.00          0.00            0.00           0.00                0.00                     0        1750.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "AZ                   63427.00     241891.63       169083.00       60618.00             8900.00                     0      756441.19   362187.89           90075.00     79099.00                         6181.12    1139583.82        45505.00",
        "BR                       0.00          0.00            0.00           0.00                0.00                     0        -500.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "CA                  343130.77     562920.91       899405.08      403495.00            71460.88                  1030    15446278.66  1987962.47          777830.00   1592930.60                        35840.05    6930695.27       200257.65",
        "CO                   59144.65     126109.66       150867.01       20525.00            27170.00                     0     1278124.98   335301.56           75168.36    228033.33                         4145.00     847365.20        67254.34",
        "CT                   31690.00      67519.12       125595.00       93498.00             2500.00                     0     1264462.23   212306.16           68300.00     60750.00                         4035.00    2394681.72        34074.45",
        "DC                    2985.00       9970.00        30995.00       94263.50             5725.00                     0     2822874.00    32284.02           34490.00     73900.00                         1910.00     615536.38        14001.00",
        "DE                    3685.00      14115.00         7515.00        7353.00             2850.00                     0      204406.59    43819.63             800.00      4450.00                          765.00      44245.00         3545.00",
        "FF                       0.00          0.00            0.00        5500.00                0.00                     0           0.00        0.00            1500.00      1000.00                            0.00      83000.00            0.00",
        "FL                  185890.00     686522.82      1417740.34      283224.19            21455.00                   250     4254393.29   992851.71          278678.92    791036.89                        15266.35    5612898.13       284128.56",
        "FM                       0.00          0.00            0.00           0.00                0.00                     0         400.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "GA                   41921.25     863369.30       876409.02       47277.50             6274.00                     0     1219130.47   361461.13           88870.00    187036.00                         7691.00    1249731.12        77029.00",
        "GU                    1249.00          0.00            0.00         150.00                0.00                     0        8601.50     1829.40            1000.00         0.00                            0.00       2250.00            0.00",
        "HI                    5522.00      40139.39        17875.00         250.00              500.00                     0      579267.69    88385.63            3500.00      2250.00                         1060.00      69743.00         5300.00",
        "IA                   45444.89      56409.89       101144.00         900.00              800.00                     0      333515.55   217711.06           18030.00     16000.00                         1445.00     134496.13       104826.45",
        "ID                   13318.00      29131.35        29270.00       21500.00              750.00                     0      107863.94   113518.96            7950.00      2250.00                          495.00     441561.62        10940.00",
        "IL                   89430.75     177478.28       247621.14      151506.00             9200.00                  2500     9057090.30   451800.86          207691.14    396185.00                         7911.00    1943287.44       106108.35",
        "IN                   33631.00      97950.11       116940.00        8525.00             2692.76                   100      463689.81   240972.32           16600.00     58350.00                         3220.12     292439.23        30785.00",
        "KS                   28984.25      92904.54        79807.76        2400.00                0.00                   275      209137.57   127160.84           64000.00     40850.00                         1625.00      96770.12        26630.80",
        "KY                   13186.00      57846.90        63789.88        4870.00             1000.00                  2500      368299.03   137683.48            2800.00     61550.00                         2365.00     356545.35        24840.00",
        "LA                   47483.00      82851.23       231468.82        4500.00             2650.00                     0      344313.67   208530.73            9900.00    604391.02                        78717.36     382952.35        42225.00",
        "MA                   17202.25      50846.51       111995.00      144673.50             3250.00                     0     4328768.70   283619.35           97850.00     49949.00                        10263.12    3522190.40        28130.00",
        "MD                   63463.25      72640.66       106087.00       55323.00             4800.00                     0     2908630.05   279740.25           35815.00    139620.00                         6586.56     999304.79        49551.22",
        "ME                    7272.00      14413.99        16965.00        3204.00              500.00                     0      623131.70    78844.10            3000.00       125.00                         1325.00      82341.36         3075.00",
        "MI                   50332.72      98023.72       142101.60       55042.00             4545.00                 18200     1363338.43   354073.99           62480.00     28175.00                         6620.00    1643083.84        50128.00",
        "MN                  253003.75      68742.80        96875.00       11830.00             2450.00                     0      875186.25   230372.21         1046673.23     11400.00                         3563.12     163755.68        47092.00",
        "MO                   51446.00     105258.54       149845.00        7542.00             4545.00                     0      839167.69   216636.65           46100.00     68300.00                         4073.12    1083215.24        35608.10",
        "MP                       0.00          0.00            0.00           0.00                0.00                     0        2375.00      250.00               0.00         0.00                            0.00          0.00            0.00",
        "MS                   18286.00      23839.90        51574.00        2375.00                0.00                     0      102443.30   117282.68            2175.00     93313.62                         1800.00     202165.00         7603.50",
        "MT                    8371.00      36400.00        26210.00        3175.00              100.00                     0      175074.54    98807.91            3950.00       450.50                          850.00      63547.00         5800.00",
        "NC                   79697.25     165586.98       218934.94       23266.00             2865.00                     0     1252353.66   380139.64            4650.00     77025.00                         7383.05     446364.34        63720.75",
        "ND                   17595.00      12789.00        16495.00           0.00                0.00                     0       31989.27    50135.75            5700.00      3500.00                          265.00       8339.00         5375.33",
        "NE                   13724.00      92547.90        46244.00        3129.00                0.00                     0      128361.47    67869.69           24000.00      9200.00                          835.00     112848.50        25151.00",
        "NH                   11322.00      42541.10        47935.00       29253.00            10550.00                  1000      354590.45   202843.12           21635.00     38058.00                         6890.00     317665.11        18825.00",
        "NJ                   47388.00     112610.80       153066.00       65172.00             2000.00                   250     1979577.16   393937.71           56885.00    115985.00                         7471.00    2553088.20        76391.80",
        "NM                   11571.00      53825.99        64030.00        2905.00            70369.00                     0      460400.46    99414.97           10500.00     55100.00                         1940.00      72211.36        11623.00",
        "NS                       0.00          0.00            0.00           0.00                0.00                     0           0.00        0.00               0.00         0.00                            0.00          0.00         1000.00",
        "NV                   38936.00     124973.78       185617.56      160140.00             7450.00                   250      455645.74   292082.15           57899.88    143500.00                         2255.00     415985.36        15890.40",
        "NY                  102814.37     178938.53       349029.79      403003.00            29430.00                  3900     9463595.60   762521.13          219325.00    461250.00                        14761.36    7600646.59       122360.68",
        "OH                   72738.72     213268.85       205533.00       23571.00             5500.00                  3210      951562.85   386991.08           42500.00    310680.00                         7611.12     622796.18        81412.52",
        "OK                   27032.00     137607.79       118447.76       38248.00             2000.00                     0      361652.33   154896.74            7850.00    463650.00                         2240.00     225689.60        30095.00",
        "ON                       0.00          0.00            0.00       -2500.00                0.00                     0         250.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "OR                   26462.50      64856.87        59015.00        9679.00             2250.00                     0      665863.41   231343.94            3850.00     26617.00                         3610.24     367828.73        30387.45",
        "PA                   75557.00     151688.93       181254.21       90050.00            10425.00                     0     2236879.70   528918.45           14080.00    321002.12                         9134.12     995025.87       727571.91",
        "PR                     300.00          0.00         1250.00           0.00                0.00                     0      192597.00     1202.40           72000.00      2800.00                          350.00       8574.00          550.00",
        "QU                       0.00          0.00            0.00           0.00                0.00                     0         500.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "RI                    2700.00       8700.00         8180.00        9800.00                0.00                     0      331534.42    46521.12             800.00      6750.00                          895.00     144419.56        10565.00",
        "SC                   29782.00      97883.56       190451.00        9513.00              701.41                     0      387606.80   166527.72            2800.00    128050.00                         2910.40     216514.36       137532.22",
        "SD                    9394.00      17869.99        58495.00        1000.00                0.00                     0       47996.76    26158.34           24000.00      6505.00                          440.00     119655.00        11975.00",
        "SO                       0.00          0.00          250.00           0.00                0.00                     0           0.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "TE                       0.00          0.00            0.00           0.00                0.00                     0           0.00        0.00               0.00       265.00                            0.00          0.00            0.00",
        "TN                   67555.50     214197.53       159025.00       54900.00              250.00                   290      547884.51   268961.06           10105.00    375752.00                         5905.12     932656.04        38366.76",
        "TX                  239951.75     945768.02      1040215.99      186887.00            48165.00                  1925     4115801.40  1905487.24          370825.24  10933923.75                        20218.35    3267924.28       307520.15",
        "UK                       0.00          0.00            0.00           0.00                0.00                     0           0.00        0.00               0.00         0.00                            0.00          0.00            0.00",
        "UT                    7213.00      16539.99        16615.00      364273.00             2400.00                     0      359324.64   145292.54           29000.00     22400.00                         1790.00    2566763.17         6235.00",
        "VA                   73363.66     192593.56       354018.54      115863.79             9276.29                   250     2532165.45   469936.64          127862.17    234171.12                        10202.50    2266563.08       178131.95",
        "VI                       0.00       2500.00          850.00         250.00                0.00                     0       59964.00        0.00               0.00       209.00                          200.00       3500.00          500.00",
        "VT                    9495.00      13660.00         9785.00        4850.00              950.00                     0      479321.80    37498.27            1750.00      3800.00                          536.00      41405.00         2450.00",
        "WA                   55981.50     113476.87       198036.60       40235.00            21275.00                   500     2187551.83   471366.00           21125.00     38335.00                         9370.24     639183.26        48887.45",
        "WI                   31464.00     123267.89        67364.94       16763.00              277.55                   100      655354.82   178446.56           19090.00     10885.00                         4161.12     156813.48        29741.01",
        "WV                    9488.78      14014.00        21265.00        5119.00                0.00                   500      100951.55    64700.18               0.00    170025.00                          643.00      73589.12         5400.00",
        "WY                   12967.00      40535.00        30865.00        6500.00              275.00                     0      101826.50    85315.25           15000.00     13400.00                          615.00     164660.24        17726.00",
        "XX                       0.00          0.00            0.00       23500.00                0.00                     0           0.00        0.00            1500.00     14000.00                          102.00     283300.00            0.00",
        "ZZ                       0.00          0.00            0.00           0.00                0.00                     0        5638.00    24415.53               0.00         0.00                            0.00          0.00            0.00"
       ]
      }
     ],
     "prompt_number": 242
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [],
     "language": "python",
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grouped = fec.groupby(['cand_nm', 'contb_receipt_dt'])",
      "# grouped = fec.groupby(['cand_nm', 'contbr_st'])",
      "grouped['contb_receipt_amt'].apply(lambda x: x.order()[-5:])"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 139,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
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        "    <tr>",
        "      <th></th>",
        "      <th>cmte_id</th>",
        "      <th>cand_id</th>",
        "      <th>cand_nm</th>",
        "      <th>contbr_nm</th>",
        "      <th>contbr_city</th>",
        "      <th>contbr_st</th>",
        "      <th>contbr_zip</th>",
        "      <th>contbr_employer</th>",
        "      <th>contbr_occupation</th>",
        "      <th>contb_receipt_amt</th>",
        "      <th>contb_receipt_dt</th>",
        "      <th>receipt_desc</th>",
        "      <th>memo_cd</th>",
        "      <th>memo_text</th>",
        "      <th>form_tp</th>",
        "      <th>file_num</th>",
        "      <th>party</th>",
        "    </tr>",
        "    <tr>",
        "      <th>cand_nm</th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "      <th></th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>Bachmann, Michelle</strong></td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>  12321</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>  12257</td>",
        "      <td>  12303</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>   12</td>",
        "      <td>     0</td>",
        "      <td>     0</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "      <td>  12322</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Cain, Herman</strong></td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19797</td>",
        "      <td>  19840</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>   41</td>",
        "      <td>    26</td>",
        "      <td>    22</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "      <td>  19924</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Gingrich, Newt</strong></td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "      <td>  27739</td>",
        "      <td>  27740</td>",
        "      <td>  27739</td>",
        "      <td>  27684</td>",
        "      <td>  27681</td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "      <td>  819</td>",
        "      <td>   673</td>",
        "      <td>   912</td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "      <td>  27740</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Huntsman, Jon</strong></td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "      <td>   4141</td>",
        "      <td>   4143</td>",
        "      <td>   4140</td>",
        "      <td>   4119</td>",
        "      <td>   4123</td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "      <td>  182</td>",
        "      <td>   139</td>",
        "      <td>   205</td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "      <td>   4143</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Johnson, Gary Earl</strong></td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    642</td>",
        "      <td>    692</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    0</td>",
        "      <td>     0</td>",
        "      <td>     0</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "      <td>    702</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>McCotter, Thaddeus G</strong></td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     62</td>",
        "      <td>     63</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>    0</td>",
        "      <td>     0</td>",
        "      <td>     0</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "      <td>     74</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Obama, Barack</strong></td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 292399</td>",
        "      <td> 292378</td>",
        "      <td> 289875</td>",
        "      <td> 289802</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 2303</td>",
        "      <td> 46155</td>",
        "      <td> 46718</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "      <td> 292400</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Paul, Ron</strong></td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87664</td>",
        "      <td>  87324</td>",
        "      <td>  87305</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  398</td>",
        "      <td>   107</td>",
        "      <td>   150</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "      <td>  87697</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Pawlenty, Timothy</strong></td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4182</td>",
        "      <td>   4182</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td> 1199</td>",
        "      <td>   729</td>",
        "      <td>   913</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "      <td>   4532</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Perry, Rick</strong></td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td>  13340</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td>  13121</td>",
        "      <td>  13123</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td> 1688</td>",
        "      <td>  1122</td>",
        "      <td>  1765</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "      <td>  13341</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Roemer, Charles E. 'Buddy' III</strong></td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   5357</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   5327</td>",
        "      <td>   5187</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   36</td>",
        "      <td>    29</td>",
        "      <td>     0</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "      <td>   5364</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Romney, Mitt</strong></td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "      <td>  58417</td>",
        "      <td>  58420</td>",
        "      <td>  58411</td>",
        "      <td>  57781</td>",
        "      <td>  57784</td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "      <td> 1785</td>",
        "      <td>   721</td>",
        "      <td>  2029</td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "      <td>  58420</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>Santorum, Rick</strong></td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9246</td>",
        "      <td>   9363</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   16</td>",
        "      <td>    17</td>",
        "      <td>    26</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "      <td>   9382</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 150,
       "text": [
        "                                cmte_id  cand_id  cand_nm  contbr_nm  contbr_city  contbr_st  contbr_zip  contbr_employer  contbr_occupation  contb_receipt_amt  contb_receipt_dt  receipt_desc  memo_cd  memo_text  form_tp  file_num   party",
        "cand_nm                                                                                                                                                                                                                                       ",
        "Bachmann, Michelle                12322    12322    12322      12322        12321      12322       12322            12257              12303              12322             12322            12        0          0    12322     12322   12322",
        "Cain, Herman                      19924    19924    19924      19924        19924      19924       19924            19797              19840              19924             19924            41       26         22    19924     19924   19924",
        "Gingrich, Newt                    27740    27740    27740      27740        27739      27740       27739            27684              27681              27740             27740           819      673        912    27740     27740   27740",
        "Huntsman, Jon                      4143     4143     4143       4143         4141       4143        4140             4119               4123               4143              4143           182      139        205     4143      4143    4143",
        "Johnson, Gary Earl                  702      702      702        702          702        702         702              642                692                702               702             0        0          0      702       702     702",
        "McCotter, Thaddeus G                 74       74       74         74           74         74          74               62                 63                 74                74             0        0          0       74        74      74",
        "Obama, Barack                    292400   292400   292400     292400       292400     292399      292378           289875             289802             292400            292400          2303    46155      46718   292400    292400  292400",
        "Paul, Ron                         87697    87697    87697      87697        87697      87697       87664            87324              87305              87697             87697           398      107        150    87697     87697   87697",
        "Pawlenty, Timothy                  4532     4532     4532       4532         4532       4532        4532             4182               4182               4532              4532          1199      729        913     4532      4532    4532",
        "Perry, Rick                       13341    13341    13341      13341        13340      13341       13341            13121              13123              13341             13341          1688     1122       1765    13341     13341   13341",
        "Roemer, Charles E. 'Buddy' III     5364     5364     5364       5364         5357       5364        5364             5327               5187               5364              5364            36       29          0     5364      5364    5364",
        "Romney, Mitt                      58420    58420    58420      58420        58417      58420       58411            57781              57784              58420             58420          1785      721       2029    58420     58420   58420",
        "Santorum, Rick                     9382     9382     9382       9382         9382       9382        9382             9246               9363               9382              9382            16       17         26     9382      9382    9382"
       ]
      }
     ],
     "prompt_number": 150
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec.sort_index(by='contb_receipt_amt')[-10:]"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>cmte_id</th>",
        "      <th>cand_id</th>",
        "      <th>cand_nm</th>",
        "      <th>contbr_nm</th>",
        "      <th>contbr_city</th>",
        "      <th>contbr_st</th>",
        "      <th>contbr_zip</th>",
        "      <th>contbr_employer</th>",
        "      <th>contbr_occupation</th>",
        "      <th>contb_receipt_amt</th>",
        "      <th>contb_receipt_dt</th>",
        "      <th>receipt_desc</th>",
        "      <th>memo_cd</th>",
        "      <th>memo_text</th>",
        "      <th>form_tp</th>",
        "      <th>file_num</th>",
        "      <th>party</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>359998</strong></td>",
        "      <td> C00494393</td>",
        "      <td> P20002556</td>",
        "      <td> Pawlenty, Timothy</td>",
        "      <td>                   HUBBARD, R. D. MR.</td>",
        "      <td>          RUIDOSO</td>",
        "      <td> NM</td>",
        "      <td> 883457700</td>",
        "      <td>               RETIRED</td>",
        "      <td>               RETIRED</td>",
        "      <td>   10000.00</td>",
        "      <td> 2011-05-03 00:00:00</td>",
        "      <td> SEE REATTRIBUTION</td>",
        "      <td> NaN</td>",
        "      <td>                    SEE REATTRIBUTION</td>",
        "      <td> SA17A</td>",
        "      <td> 748365</td>",
        "      <td> Republican</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>359005</strong></td>",
        "      <td> C00494393</td>",
        "      <td> P20002556</td>",
        "      <td> Pawlenty, Timothy</td>",
        "      <td>                 DAVIS, MARTIN E. MR.</td>",
        "      <td>        SHOREWOOD</td>",
        "      <td> MN</td>",
        "      <td> 553318321</td>",
        "      <td>               CAMBRIA</td>",
        "      <td>       GENERAL MANAGER</td>",
        "      <td>   10000.00</td>",
        "      <td> 2011-06-22 00:00:00</td>",
        "      <td> SEE REATTRIBUTION</td>",
        "      <td> NaN</td>",
        "      <td>                    SEE REATTRIBUTION</td>",
        "      <td> SA17A</td>",
        "      <td> 748365</td>",
        "      <td> Republican</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>478807</strong></td>",
        "      <td> C00496067</td>",
        "      <td> P00003608</td>",
        "      <td>      Cain, Herman</td>",
        "      <td>                            HILDE, AL</td>",
        "      <td>          JACKSON</td>",
        "      <td> WY</td>",
        "      <td> 830019347</td>",
        "      <td> INFORMATION REQUESTED</td>",
        "      <td> INFORMATION REQUESTED</td>",
        "      <td>   10000.00</td>",
        "      <td> 2011-10-25 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td> NaN</td>",
        "      <td>                                  NaN</td>",
        "      <td> SA17A</td>",
        "      <td> 763621</td>",
        "      <td> Republican</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>35412</strong></td>",
        "      <td> C00431171</td>",
        "      <td> P80003353</td>",
        "      <td>      Romney, Mitt</td>",
        "      <td>                               NORPAC</td>",
        "      <td> ENGLEWOOD CLIFFS</td>",
        "      <td> NJ</td>",
        "      <td>     07632</td>",
        "      <td>                   NaN</td>",
        "      <td>                   NaN</td>",
        "      <td>   12700.00</td>",
        "      <td> 2011-09-29 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td>   X</td>",
        "      <td> EARMARKED CONTRIBUTIONS FROM CONDUIT</td>",
        "      <td> SA17A</td>",
        "      <td> 760261</td>",
        "      <td> Republican</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>71379</strong></td>",
        "      <td> C00431445</td>",
        "      <td> P80003338</td>",
        "      <td>     Obama, Barack</td>",
        "      <td>                 DAVIS, STEPHEN JAMES</td>",
        "      <td>    SAN FRANCISCO</td>",
        "      <td> CA</td>",
        "      <td> 941151123</td>",
        "      <td>     BANNEKER PARTNERS</td>",
        "      <td>              ATTORNEY</td>",
        "      <td>   25800.00</td>",
        "      <td> 2011-05-10 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td> NaN</td>",
        "      <td>      CONTRIBUTION REFUNDED ON 7/8/11</td>",
        "      <td> SA17A</td>",
        "      <td> 756214</td>",
        "      <td>   Democrat</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>61937</strong></td>",
        "      <td> C00431445</td>",
        "      <td> P80003338</td>",
        "      <td>     Obama, Barack</td>",
        "      <td>                   MURPHY, CYNTHIA C.</td>",
        "      <td>      LITTLE ROCK</td>",
        "      <td> AR</td>",
        "      <td> 722075462</td>",
        "      <td>          MURPHY GROUP</td>",
        "      <td>      PUBLIC RELATIONS</td>",
        "      <td>   33300.00</td>",
        "      <td> 2011-05-25 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td> NaN</td>",
        "      <td>                                  NaN</td>",
        "      <td> SA17A</td>",
        "      <td> 756214</td>",
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        "      <td><strong>133568</strong></td>",
        "      <td> C00431445</td>",
        "      <td> P80003338</td>",
        "      <td>     Obama, Barack</td>",
        "      <td> OBAMA VICTORY FUND 2012 - UNITEMIZED</td>",
        "      <td>       WASHINGTON</td>",
        "      <td> DC</td>",
        "      <td>     20003</td>",
        "      <td>                   NaN</td>",
        "      <td>                   NaN</td>",
        "      <td>  451726.00</td>",
        "      <td> 2011-06-30 00:00:00</td>",
        "      <td>               NaN</td>",
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        "      <td>                                    *</td>",
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        "      <td> 756214</td>",
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        "      <td><strong>177473</strong></td>",
        "      <td> C00431445</td>",
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        "      <td>     Obama, Barack</td>",
        "      <td> OBAMA VICTORY FUND 2012 - UNITEMIZED</td>",
        "      <td>          CHICAGO</td>",
        "      <td> IL</td>",
        "      <td>     60680</td>",
        "      <td>                   NaN</td>",
        "      <td>                   NaN</td>",
        "      <td>  512710.91</td>",
        "      <td> 2012-01-31 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td>   X</td>",
        "      <td>                                    *</td>",
        "      <td>  SA18</td>",
        "      <td> 766535</td>",
        "      <td>   Democrat</td>",
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        "    <tr>",
        "      <td><strong>162313</strong></td>",
        "      <td> C00431445</td>",
        "      <td> P80003338</td>",
        "      <td>     Obama, Barack</td>",
        "      <td> OBAMA VICTORY FUND 2012 - UNITEMIZED</td>",
        "      <td>          CHICAGO</td>",
        "      <td> IL</td>",
        "      <td>     60680</td>",
        "      <td>                   NaN</td>",
        "      <td>                   NaN</td>",
        "      <td> 1511192.17</td>",
        "      <td> 2011-09-30 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td>   X</td>",
        "      <td>                                    *</td>",
        "      <td>  SA18</td>",
        "      <td> 756218</td>",
        "      <td>   Democrat</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>176127</strong></td>",
        "      <td> C00431445</td>",
        "      <td> P80003338</td>",
        "      <td>     Obama, Barack</td>",
        "      <td> OBAMA VICTORY FUND 2012 - UNITEMIZED</td>",
        "      <td>          CHICAGO</td>",
        "      <td> IL</td>",
        "      <td>     60680</td>",
        "      <td>                   NaN</td>",
        "      <td>                   NaN</td>",
        "      <td> 1944042.43</td>",
        "      <td> 2011-12-31 00:00:00</td>",
        "      <td>               NaN</td>",
        "      <td>   X</td>",
        "      <td>                                    *</td>",
        "      <td>  SA18</td>",
        "      <td> 763233</td>",
        "      <td>   Democrat</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 147,
       "text": [
        "          cmte_id    cand_id            cand_nm                             contbr_nm       contbr_city contbr_st contbr_zip        contbr_employer      contbr_occupation  contb_receipt_amt     contb_receipt_dt       receipt_desc memo_cd                             memo_text form_tp  file_num       party",
        "359998  C00494393  P20002556  Pawlenty, Timothy                    HUBBARD, R. D. MR.           RUIDOSO        NM  883457700                RETIRED                RETIRED           10000.00  2011-05-03 00:00:00  SEE REATTRIBUTION     NaN                     SEE REATTRIBUTION   SA17A    748365  Republican",
        "359005  C00494393  P20002556  Pawlenty, Timothy                  DAVIS, MARTIN E. MR.         SHOREWOOD        MN  553318321                CAMBRIA        GENERAL MANAGER           10000.00  2011-06-22 00:00:00  SEE REATTRIBUTION     NaN                     SEE REATTRIBUTION   SA17A    748365  Republican",
        "478807  C00496067  P00003608       Cain, Herman                             HILDE, AL           JACKSON        WY  830019347  INFORMATION REQUESTED  INFORMATION REQUESTED           10000.00  2011-10-25 00:00:00                NaN     NaN                                   NaN   SA17A    763621  Republican",
        "35412   C00431171  P80003353       Romney, Mitt                                NORPAC  ENGLEWOOD CLIFFS        NJ      07632                    NaN                    NaN           12700.00  2011-09-29 00:00:00                NaN       X  EARMARKED CONTRIBUTIONS FROM CONDUIT   SA17A    760261  Republican",
        "71379   C00431445  P80003338      Obama, Barack                  DAVIS, STEPHEN JAMES     SAN FRANCISCO        CA  941151123      BANNEKER PARTNERS               ATTORNEY           25800.00  2011-05-10 00:00:00                NaN     NaN       CONTRIBUTION REFUNDED ON 7/8/11   SA17A    756214    Democrat",
        "61937   C00431445  P80003338      Obama, Barack                    MURPHY, CYNTHIA C.       LITTLE ROCK        AR  722075462           MURPHY GROUP       PUBLIC RELATIONS           33300.00  2011-05-25 00:00:00                NaN     NaN                                   NaN   SA17A    756214    Democrat",
        "133568  C00431445  P80003338      Obama, Barack  OBAMA VICTORY FUND 2012 - UNITEMIZED        WASHINGTON        DC      20003                    NaN                    NaN          451726.00  2011-06-30 00:00:00                NaN       X                                     *    SA18    756214    Democrat",
        "177473  C00431445  P80003338      Obama, Barack  OBAMA VICTORY FUND 2012 - UNITEMIZED           CHICAGO        IL      60680                    NaN                    NaN          512710.91  2012-01-31 00:00:00                NaN       X                                     *    SA18    766535    Democrat",
        "162313  C00431445  P80003338      Obama, Barack  OBAMA VICTORY FUND 2012 - UNITEMIZED           CHICAGO        IL      60680                    NaN                    NaN         1511192.17  2011-09-30 00:00:00                NaN       X                                     *    SA18    756218    Democrat",
        "176127  C00431445  P80003338      Obama, Barack  OBAMA VICTORY FUND 2012 - UNITEMIZED           CHICAGO        IL      60680                    NaN                    NaN         1944042.43  2011-12-31 00:00:00                NaN       X                                     *    SA18    763233    Democrat"
       ]
      }
     ],
     "prompt_number": 147
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "res = _"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 140
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "res[:100].stack()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 142,
       "text": [
        "cand_nm             contb_receipt_dt        ",
        "Bachmann, Michelle  2011-06-13        76        2500",
        "                                      80        2500",
        "                                      84        2500",
        "                                      360       1000",
        "                                      509162    1000",
        "                    2011-06-14        509845    2500",
        "                                      511239    2500",
        "                                      514049    2500",
        "                                      514998    2500",
        "                                      517908    2500",
        "                    2011-06-15        513424    2500",
        "                                      514103    2500",
        "                                      514396    2500",
        "                                      517373    2500",
        "                                      517839    2500",
        "...",
        "Bachmann, Michelle  2011-09-19        506718     501",
        "                                      509493    2500",
        "                                      511088    2500",
        "                                      514192     501",
        "                                      515692     601",
        "                    2011-09-20        507905     501",
        "                                      513293     500",
        "                                      516792     500",
        "                                      516885    1000",
        "                                      518130     501",
        "                    2011-09-21        509569    1000",
        "                                      513289    2500",
        "                                      514202     501",
        "                                      516407    1001",
        "                                      516905    1000",
        "Length: 486"
       ]
      }
     ],
     "prompt_number": 142
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result.unstack('cand_nm').unstack('contbr_st').median(axis=1, level='cand_nm')"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 134,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Index: 376 entries, 2011-01-01 00:00:00 to 2012-01-31 00:00:00",
        "Data columns:",
        "Bachmann, Michelle                200  non-null values",
        "Cain, Herman                      319  non-null values",
        "Gingrich, Newt                    317  non-null values",
        "Huntsman, Jon                     213  non-null values",
        "Johnson, Gary Earl                190  non-null values",
        "McCotter, Thaddeus G              38  non-null values",
        "Obama, Barack                     303  non-null values",
        "Paul, Ron                         281  non-null values",
        "Pawlenty, Timothy                 216  non-null values",
        "Perry, Rick                       160  non-null values",
        "Roemer, Charles E. 'Buddy' III    314  non-null values",
        "Romney, Mitt                      296  non-null values",
        "Santorum, Rick                    255  non-null values",
        "dtypes: float64(13)"
       ]
      }
     ],
     "prompt_number": 134
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "babies = read_csv('baby-names2.csv')",
      "births = read_csv('births.csv')"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 184
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "babies[:50]"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>year</th>",
        "      <th>name</th>",
        "      <th>prop</th>",
        "      <th>sex</th>",
        "      <th>soundex</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>0</strong></td>",
        "      <td> 1880</td>",
        "      <td>      John</td>",
        "      <td> 0.081541</td>",
        "      <td> boy</td>",
        "      <td> J500</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>1</strong></td>",
        "      <td> 1880</td>",
        "      <td>   William</td>",
        "      <td> 0.080511</td>",
        "      <td> boy</td>",
        "      <td> W450</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2</strong></td>",
        "      <td> 1880</td>",
        "      <td>     James</td>",
        "      <td> 0.050057</td>",
        "      <td> boy</td>",
        "      <td> J520</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>3</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Charles</td>",
        "      <td> 0.045167</td>",
        "      <td> boy</td>",
        "      <td> C642</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>4</strong></td>",
        "      <td> 1880</td>",
        "      <td>    George</td>",
        "      <td> 0.043292</td>",
        "      <td> boy</td>",
        "      <td> G620</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>5</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Frank</td>",
        "      <td> 0.027380</td>",
        "      <td> boy</td>",
        "      <td> F652</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>6</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Joseph</td>",
        "      <td> 0.022229</td>",
        "      <td> boy</td>",
        "      <td> J210</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>7</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Thomas</td>",
        "      <td> 0.021401</td>",
        "      <td> boy</td>",
        "      <td> T520</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>8</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Henry</td>",
        "      <td> 0.020641</td>",
        "      <td> boy</td>",
        "      <td> H560</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>9</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Robert</td>",
        "      <td> 0.020404</td>",
        "      <td> boy</td>",
        "      <td> R163</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>10</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Edward</td>",
        "      <td> 0.019965</td>",
        "      <td> boy</td>",
        "      <td> E363</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>11</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Harry</td>",
        "      <td> 0.018175</td>",
        "      <td> boy</td>",
        "      <td> H600</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>12</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Walter</td>",
        "      <td> 0.014822</td>",
        "      <td> boy</td>",
        "      <td> W436</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>13</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Arthur</td>",
        "      <td> 0.013504</td>",
        "      <td> boy</td>",
        "      <td> A636</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>14</strong></td>",
        "      <td> 1880</td>",
        "      <td>      Fred</td>",
        "      <td> 0.013251</td>",
        "      <td> boy</td>",
        "      <td> F630</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>15</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Albert</td>",
        "      <td> 0.012609</td>",
        "      <td> boy</td>",
        "      <td> A416</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>16</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Samuel</td>",
        "      <td> 0.008648</td>",
        "      <td> boy</td>",
        "      <td> S540</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>17</strong></td>",
        "      <td> 1880</td>",
        "      <td>     David</td>",
        "      <td> 0.007339</td>",
        "      <td> boy</td>",
        "      <td> D130</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>18</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Louis</td>",
        "      <td> 0.006993</td>",
        "      <td> boy</td>",
        "      <td> L200</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>19</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Joe</td>",
        "      <td> 0.006174</td>",
        "      <td> boy</td>",
        "      <td> J000</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>20</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Charlie</td>",
        "      <td> 0.006165</td>",
        "      <td> boy</td>",
        "      <td> C640</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>21</strong></td>",
        "      <td> 1880</td>",
        "      <td>  Clarence</td>",
        "      <td> 0.006165</td>",
        "      <td> boy</td>",
        "      <td> C465</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>22</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Richard</td>",
        "      <td> 0.006148</td>",
        "      <td> boy</td>",
        "      <td> R263</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>23</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Andrew</td>",
        "      <td> 0.005439</td>",
        "      <td> boy</td>",
        "      <td> A536</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>24</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Daniel</td>",
        "      <td> 0.005430</td>",
        "      <td> boy</td>",
        "      <td> D540</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>25</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Ernest</td>",
        "      <td> 0.005194</td>",
        "      <td> boy</td>",
        "      <td> E652</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>26</strong></td>",
        "      <td> 1880</td>",
        "      <td>      Will</td>",
        "      <td> 0.004966</td>",
        "      <td> boy</td>",
        "      <td> W400</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>27</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Jesse</td>",
        "      <td> 0.004805</td>",
        "      <td> boy</td>",
        "      <td> J200</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>28</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Oscar</td>",
        "      <td> 0.004594</td>",
        "      <td> boy</td>",
        "      <td> O260</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>29</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Lewis</td>",
        "      <td> 0.004366</td>",
        "      <td> boy</td>",
        "      <td> L200</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>30</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Peter</td>",
        "      <td> 0.004189</td>",
        "      <td> boy</td>",
        "      <td> P360</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>31</strong></td>",
        "      <td> 1880</td>",
        "      <td>  Benjamin</td>",
        "      <td> 0.004138</td>",
        "      <td> boy</td>",
        "      <td> B525</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>32</strong></td>",
        "      <td> 1880</td>",
        "      <td> Frederick</td>",
        "      <td> 0.004079</td>",
        "      <td> boy</td>",
        "      <td> F636</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>33</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Willie</td>",
        "      <td> 0.004020</td>",
        "      <td> boy</td>",
        "      <td> W400</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>34</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Alfred</td>",
        "      <td> 0.003961</td>",
        "      <td> boy</td>",
        "      <td> A416</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>35</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Sam</td>",
        "      <td> 0.003860</td>",
        "      <td> boy</td>",
        "      <td> S500</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>36</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Roy</td>",
        "      <td> 0.003716</td>",
        "      <td> boy</td>",
        "      <td> R000</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>37</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Herbert</td>",
        "      <td> 0.003581</td>",
        "      <td> boy</td>",
        "      <td> H616</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>38</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Jacob</td>",
        "      <td> 0.003412</td>",
        "      <td> boy</td>",
        "      <td> J210</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>39</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Tom</td>",
        "      <td> 0.003370</td>",
        "      <td> boy</td>",
        "      <td> T500</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>40</strong></td>",
        "      <td> 1880</td>",
        "      <td>     Elmer</td>",
        "      <td> 0.003150</td>",
        "      <td> boy</td>",
        "      <td> E456</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>41</strong></td>",
        "      <td> 1880</td>",
        "      <td>      Carl</td>",
        "      <td> 0.003142</td>",
        "      <td> boy</td>",
        "      <td> C640</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>42</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Lee</td>",
        "      <td> 0.003049</td>",
        "      <td> boy</td>",
        "      <td> L000</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>43</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Howard</td>",
        "      <td> 0.003015</td>",
        "      <td> boy</td>",
        "      <td> H630</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>44</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Martin</td>",
        "      <td> 0.003015</td>",
        "      <td> boy</td>",
        "      <td> M635</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>45</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Michael</td>",
        "      <td> 0.002990</td>",
        "      <td> boy</td>",
        "      <td> M240</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>46</strong></td>",
        "      <td> 1880</td>",
        "      <td>      Bert</td>",
        "      <td> 0.002939</td>",
        "      <td> boy</td>",
        "      <td> B630</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>47</strong></td>",
        "      <td> 1880</td>",
        "      <td>    Herman</td>",
        "      <td> 0.002931</td>",
        "      <td> boy</td>",
        "      <td> H655</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>48</strong></td>",
        "      <td> 1880</td>",
        "      <td>       Jim</td>",
        "      <td> 0.002914</td>",
        "      <td> boy</td>",
        "      <td> J500</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>49</strong></td>",
        "      <td> 1880</td>",
        "      <td>   Francis</td>",
        "      <td> 0.002905</td>",
        "      <td> boy</td>",
        "      <td> F652</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 129,
       "text": [
        "    year       name      prop  sex soundex",
        "0   1880       John  0.081541  boy    J500",
        "1   1880    William  0.080511  boy    W450",
        "2   1880      James  0.050057  boy    J520",
        "3   1880    Charles  0.045167  boy    C642",
        "4   1880     George  0.043292  boy    G620",
        "5   1880      Frank  0.027380  boy    F652",
        "6   1880     Joseph  0.022229  boy    J210",
        "7   1880     Thomas  0.021401  boy    T520",
        "8   1880      Henry  0.020641  boy    H560",
        "9   1880     Robert  0.020404  boy    R163",
        "10  1880     Edward  0.019965  boy    E363",
        "11  1880      Harry  0.018175  boy    H600",
        "12  1880     Walter  0.014822  boy    W436",
        "13  1880     Arthur  0.013504  boy    A636",
        "14  1880       Fred  0.013251  boy    F630",
        "15  1880     Albert  0.012609  boy    A416",
        "16  1880     Samuel  0.008648  boy    S540",
        "17  1880      David  0.007339  boy    D130",
        "18  1880      Louis  0.006993  boy    L200",
        "19  1880        Joe  0.006174  boy    J000",
        "20  1880    Charlie  0.006165  boy    C640",
        "21  1880   Clarence  0.006165  boy    C465",
        "22  1880    Richard  0.006148  boy    R263",
        "23  1880     Andrew  0.005439  boy    A536",
        "24  1880     Daniel  0.005430  boy    D540",
        "25  1880     Ernest  0.005194  boy    E652",
        "26  1880       Will  0.004966  boy    W400",
        "27  1880      Jesse  0.004805  boy    J200",
        "28  1880      Oscar  0.004594  boy    O260",
        "29  1880      Lewis  0.004366  boy    L200",
        "30  1880      Peter  0.004189  boy    P360",
        "31  1880   Benjamin  0.004138  boy    B525",
        "32  1880  Frederick  0.004079  boy    F636",
        "33  1880     Willie  0.004020  boy    W400",
        "34  1880     Alfred  0.003961  boy    A416",
        "35  1880        Sam  0.003860  boy    S500",
        "36  1880        Roy  0.003716  boy    R000",
        "37  1880    Herbert  0.003581  boy    H616",
        "38  1880      Jacob  0.003412  boy    J210",
        "39  1880        Tom  0.003370  boy    T500",
        "40  1880      Elmer  0.003150  boy    E456",
        "41  1880       Carl  0.003142  boy    C640",
        "42  1880        Lee  0.003049  boy    L000",
        "43  1880     Howard  0.003015  boy    H630",
        "44  1880     Martin  0.003015  boy    M635",
        "45  1880    Michael  0.002990  boy    M240",
        "46  1880       Bert  0.002939  boy    B630",
        "47  1880     Herman  0.002931  boy    H655",
        "48  1880        Jim  0.002914  boy    J500",
        "49  1880    Francis  0.002905  boy    F652"
       ]
      }
     ],
     "prompt_number": 129
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas.util.testing as tm",
      "df = tm.makeTimeDataFrame()",
      "ts = df['A']"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 187
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ts1 = ts[:7]",
      "ts2 = ts[:9]"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 193,
       "text": [
        "2000-01-03    2.196900",
        "2000-01-04   -0.999768",
        "2000-01-05    1.690059",
        "2000-01-06    1.119271",
        "2000-01-07   -1.587614",
        "2000-01-10   -2.199279",
        "2000-01-11   -2.254439",
        "2000-01-12    1.157619",
        "2000-01-13    0.780915",
        "Name: A"
       ]
      }
     ],
     "prompt_number": 193
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Factor(fec.cand_nm)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 197,
       "text": [
        "Factor:",
        "array([Bachmann, Michelle, Bachmann, Michelle, Bachmann, Michelle, ...,",
        "       Perry, Rick, Perry, Rick, Perry, Rick], dtype=object)",
        "Levels (13): array([Bachmann, Michelle, Cain, Herman, Gingrich, Newt, Huntsman, Jon,",
        "       Johnson, Gary Earl, McCotter, Thaddeus G, Obama, Barack, Paul, Ron,",
        "       Pawlenty, Timothy, Perry, Rick, Roemer, Charles E. 'Buddy' III,",
        "       Romney, Mitt, Santorum, Rick], dtype=object)"
       ]
      }
     ],
     "prompt_number": 197
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>B</th>",
        "      <th>C</th>",
        "      <th>D</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>2000-01-03 00:00:00</strong></td>",
        "      <td>-0.779028</td>",
        "      <td>-0.721610</td>",
        "      <td>-1.528296</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-04 00:00:00</strong></td>",
        "      <td>-1.621385</td>",
        "      <td>-0.773365</td>",
        "      <td> 0.875603</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-05 00:00:00</strong></td>",
        "      <td>-0.034184</td>",
        "      <td>-0.401620</td>",
        "      <td>-0.131541</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-06 00:00:00</strong></td>",
        "      <td> 1.220423</td>",
        "      <td>-0.031725</td>",
        "      <td> 1.520886</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-07 00:00:00</strong></td>",
        "      <td> 2.840327</td>",
        "      <td>-0.716051</td>",
        "      <td> 1.749560</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-10 00:00:00</strong></td>",
        "      <td> 0.321776</td>",
        "      <td> 0.699181</td>",
        "      <td>-1.103870</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-11 00:00:00</strong></td>",
        "      <td> 0.465374</td>",
        "      <td> 0.246970</td>",
        "      <td> 0.356292</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-12 00:00:00</strong></td>",
        "      <td>-0.182423</td>",
        "      <td>-1.742033</td>",
        "      <td>-1.533021</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-13 00:00:00</strong></td>",
        "      <td> 1.006741</td>",
        "      <td> 0.064173</td>",
        "      <td>-1.229465</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-14 00:00:00</strong></td>",
        "      <td>-0.793282</td>",
        "      <td>-0.924148</td>",
        "      <td> 0.634416</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-17 00:00:00</strong></td>",
        "      <td> 1.650775</td>",
        "      <td> 0.445637</td>",
        "      <td> 0.316600</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-18 00:00:00</strong></td>",
        "      <td>-0.605736</td>",
        "      <td> 2.426416</td>",
        "      <td>-0.355462</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-19 00:00:00</strong></td>",
        "      <td>-1.067655</td>",
        "      <td> 0.029917</td>",
        "      <td>-0.802377</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-20 00:00:00</strong></td>",
        "      <td> 0.072785</td>",
        "      <td>-2.527968</td>",
        "      <td> 0.983527</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-21 00:00:00</strong></td>",
        "      <td>-0.059629</td>",
        "      <td>-0.696293</td>",
        "      <td>-0.463731</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-24 00:00:00</strong></td>",
        "      <td>-1.313752</td>",
        "      <td> 0.017138</td>",
        "      <td> 0.590519</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-25 00:00:00</strong></td>",
        "      <td>-0.469022</td>",
        "      <td>-2.783043</td>",
        "      <td>-0.676610</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-26 00:00:00</strong></td>",
        "      <td>-0.664583</td>",
        "      <td> 0.885575</td>",
        "      <td>-1.316099</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-27 00:00:00</strong></td>",
        "      <td>-0.417425</td>",
        "      <td> 1.321704</td>",
        "      <td> 0.200258</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-28 00:00:00</strong></td>",
        "      <td>-0.208437</td>",
        "      <td> 0.645996</td>",
        "      <td> 0.257645</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-31 00:00:00</strong></td>",
        "      <td> 0.423154</td>",
        "      <td>-0.151050</td>",
        "      <td> 0.278508</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-01 00:00:00</strong></td>",
        "      <td>-1.267921</td>",
        "      <td>-0.287300</td>",
        "      <td>-1.575588</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-02 00:00:00</strong></td>",
        "      <td>-1.231242</td>",
        "      <td>-0.509735</td>",
        "      <td>-0.345767</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-03 00:00:00</strong></td>",
        "      <td> 0.185326</td>",
        "      <td> 0.807050</td>",
        "      <td> 0.457551</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-04 00:00:00</strong></td>",
        "      <td> 0.542608</td>",
        "      <td>-0.141204</td>",
        "      <td> 0.518549</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-07 00:00:00</strong></td>",
        "      <td> 1.559418</td>",
        "      <td>-0.134254</td>",
        "      <td>-0.002082</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-08 00:00:00</strong></td>",
        "      <td> 1.189163</td>",
        "      <td> 0.107255</td>",
        "      <td> 0.512349</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-09 00:00:00</strong></td>",
        "      <td>-2.802906</td>",
        "      <td>-1.054708</td>",
        "      <td> 0.534505</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-10 00:00:00</strong></td>",
        "      <td> 0.419311</td>",
        "      <td>-0.072897</td>",
        "      <td>-0.235556</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-11 00:00:00</strong></td>",
        "      <td> 0.084953</td>",
        "      <td>-0.143175</td>",
        "      <td>-0.065602</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 202,
       "text": [
        "                   B         C         D",
        "2000-01-03 -0.779028 -0.721610 -1.528296",
        "2000-01-04 -1.621385 -0.773365  0.875603",
        "2000-01-05 -0.034184 -0.401620 -0.131541",
        "2000-01-06  1.220423 -0.031725  1.520886",
        "2000-01-07  2.840327 -0.716051  1.749560",
        "2000-01-10  0.321776  0.699181 -1.103870",
        "2000-01-11  0.465374  0.246970  0.356292",
        "2000-01-12 -0.182423 -1.742033 -1.533021",
        "2000-01-13  1.006741  0.064173 -1.229465",
        "2000-01-14 -0.793282 -0.924148  0.634416",
        "2000-01-17  1.650775  0.445637  0.316600",
        "2000-01-18 -0.605736  2.426416 -0.355462",
        "2000-01-19 -1.067655  0.029917 -0.802377",
        "2000-01-20  0.072785 -2.527968  0.983527",
        "2000-01-21 -0.059629 -0.696293 -0.463731",
        "2000-01-24 -1.313752  0.017138  0.590519",
        "2000-01-25 -0.469022 -2.783043 -0.676610",
        "2000-01-26 -0.664583  0.885575 -1.316099",
        "2000-01-27 -0.417425  1.321704  0.200258",
        "2000-01-28 -0.208437  0.645996  0.257645",
        "2000-01-31  0.423154 -0.151050  0.278508",
        "2000-02-01 -1.267921 -0.287300 -1.575588",
        "2000-02-02 -1.231242 -0.509735 -0.345767",
        "2000-02-03  0.185326  0.807050  0.457551",
        "2000-02-04  0.542608 -0.141204  0.518549",
        "2000-02-07  1.559418 -0.134254 -0.002082",
        "2000-02-08  1.189163  0.107255  0.512349",
        "2000-02-09 -2.802906 -1.054708  0.534505",
        "2000-02-10  0.419311 -0.072897 -0.235556",
        "2000-02-11  0.084953 -0.143175 -0.065602"
       ]
      }
     ],
     "prompt_number": 202
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "import scikits.statsmodels.api as sm",
      "y = df.pop('A')",
      "x = df",
      "res = sm.OLS(y, x).fit()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 198
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>B</th>",
        "      <th>C</th>",
        "      <th>D</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>2000-01-03 00:00:00</strong></td>",
        "      <td>-0.779028</td>",
        "      <td>-0.721610</td>",
        "      <td>-1.528296</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-04 00:00:00</strong></td>",
        "      <td>-1.621385</td>",
        "      <td>-0.773365</td>",
        "      <td> 0.875603</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-05 00:00:00</strong></td>",
        "      <td>-0.034184</td>",
        "      <td>-0.401620</td>",
        "      <td>-0.131541</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-06 00:00:00</strong></td>",
        "      <td> 1.220423</td>",
        "      <td>-0.031725</td>",
        "      <td> 1.520886</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-07 00:00:00</strong></td>",
        "      <td> 2.840327</td>",
        "      <td>-0.716051</td>",
        "      <td> 1.749560</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-10 00:00:00</strong></td>",
        "      <td> 0.321776</td>",
        "      <td> 0.699181</td>",
        "      <td>-1.103870</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-11 00:00:00</strong></td>",
        "      <td> 0.465374</td>",
        "      <td> 0.246970</td>",
        "      <td> 0.356292</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-12 00:00:00</strong></td>",
        "      <td>-0.182423</td>",
        "      <td>-1.742033</td>",
        "      <td>-1.533021</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-13 00:00:00</strong></td>",
        "      <td> 1.006741</td>",
        "      <td> 0.064173</td>",
        "      <td>-1.229465</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-14 00:00:00</strong></td>",
        "      <td>-0.793282</td>",
        "      <td>-0.924148</td>",
        "      <td> 0.634416</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-17 00:00:00</strong></td>",
        "      <td> 1.650775</td>",
        "      <td> 0.445637</td>",
        "      <td> 0.316600</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-18 00:00:00</strong></td>",
        "      <td>-0.605736</td>",
        "      <td> 2.426416</td>",
        "      <td>-0.355462</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-19 00:00:00</strong></td>",
        "      <td>-1.067655</td>",
        "      <td> 0.029917</td>",
        "      <td>-0.802377</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-20 00:00:00</strong></td>",
        "      <td> 0.072785</td>",
        "      <td>-2.527968</td>",
        "      <td> 0.983527</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-21 00:00:00</strong></td>",
        "      <td>-0.059629</td>",
        "      <td>-0.696293</td>",
        "      <td>-0.463731</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-24 00:00:00</strong></td>",
        "      <td>-1.313752</td>",
        "      <td> 0.017138</td>",
        "      <td> 0.590519</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-25 00:00:00</strong></td>",
        "      <td>-0.469022</td>",
        "      <td>-2.783043</td>",
        "      <td>-0.676610</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-26 00:00:00</strong></td>",
        "      <td>-0.664583</td>",
        "      <td> 0.885575</td>",
        "      <td>-1.316099</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-27 00:00:00</strong></td>",
        "      <td>-0.417425</td>",
        "      <td> 1.321704</td>",
        "      <td> 0.200258</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-28 00:00:00</strong></td>",
        "      <td>-0.208437</td>",
        "      <td> 0.645996</td>",
        "      <td> 0.257645</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-31 00:00:00</strong></td>",
        "      <td> 0.423154</td>",
        "      <td>-0.151050</td>",
        "      <td> 0.278508</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-01 00:00:00</strong></td>",
        "      <td>-1.267921</td>",
        "      <td>-0.287300</td>",
        "      <td>-1.575588</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-02 00:00:00</strong></td>",
        "      <td>-1.231242</td>",
        "      <td>-0.509735</td>",
        "      <td>-0.345767</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-03 00:00:00</strong></td>",
        "      <td> 0.185326</td>",
        "      <td> 0.807050</td>",
        "      <td> 0.457551</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-04 00:00:00</strong></td>",
        "      <td> 0.542608</td>",
        "      <td>-0.141204</td>",
        "      <td> 0.518549</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-07 00:00:00</strong></td>",
        "      <td> 1.559418</td>",
        "      <td>-0.134254</td>",
        "      <td>-0.002082</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-08 00:00:00</strong></td>",
        "      <td> 1.189163</td>",
        "      <td> 0.107255</td>",
        "      <td> 0.512349</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-09 00:00:00</strong></td>",
        "      <td>-2.802906</td>",
        "      <td>-1.054708</td>",
        "      <td> 0.534505</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-10 00:00:00</strong></td>",
        "      <td> 0.419311</td>",
        "      <td>-0.072897</td>",
        "      <td>-0.235556</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-11 00:00:00</strong></td>",
        "      <td> 0.084953</td>",
        "      <td>-0.143175</td>",
        "      <td>-0.065602</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
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       "prompt_number": 205,
       "text": [
        "                   B         C         D",
        "2000-01-03 -0.779028 -0.721610 -1.528296",
        "2000-01-04 -1.621385 -0.773365  0.875603",
        "2000-01-05 -0.034184 -0.401620 -0.131541",
        "2000-01-06  1.220423 -0.031725  1.520886",
        "2000-01-07  2.840327 -0.716051  1.749560",
        "2000-01-10  0.321776  0.699181 -1.103870",
        "2000-01-11  0.465374  0.246970  0.356292",
        "2000-01-12 -0.182423 -1.742033 -1.533021",
        "2000-01-13  1.006741  0.064173 -1.229465",
        "2000-01-14 -0.793282 -0.924148  0.634416",
        "2000-01-17  1.650775  0.445637  0.316600",
        "2000-01-18 -0.605736  2.426416 -0.355462",
        "2000-01-19 -1.067655  0.029917 -0.802377",
        "2000-01-20  0.072785 -2.527968  0.983527",
        "2000-01-21 -0.059629 -0.696293 -0.463731",
        "2000-01-24 -1.313752  0.017138  0.590519",
        "2000-01-25 -0.469022 -2.783043 -0.676610",
        "2000-01-26 -0.664583  0.885575 -1.316099",
        "2000-01-27 -0.417425  1.321704  0.200258",
        "2000-01-28 -0.208437  0.645996  0.257645",
        "2000-01-31  0.423154 -0.151050  0.278508",
        "2000-02-01 -1.267921 -0.287300 -1.575588",
        "2000-02-02 -1.231242 -0.509735 -0.345767",
        "2000-02-03  0.185326  0.807050  0.457551",
        "2000-02-04  0.542608 -0.141204  0.518549",
        "2000-02-07  1.559418 -0.134254 -0.002082",
        "2000-02-08  1.189163  0.107255  0.512349",
        "2000-02-09 -2.802906 -1.054708  0.534505",
        "2000-02-10  0.419311 -0.072897 -0.235556",
        "2000-02-11  0.084953 -0.143175 -0.065602"
       ]
      }
     ],
     "prompt_number": 205
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ols(y=y, x=x, window=10).beta"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">",
        "<table border=\"1\">",
        "  <thead>",
        "    <tr>",
        "      <th></th>",
        "      <th>B</th>",
        "      <th>C</th>",
        "      <th>D</th>",
        "      <th>intercept</th>",
        "    </tr>",
        "    </thead>",
        "    <tbody>",
        "    <tr>",
        "      <td><strong>2000-01-14 00:00:00</strong></td>",
        "      <td> 0.097849</td>",
        "      <td>-0.631871</td>",
        "      <td>-0.364008</td>",
        "      <td>-0.246238</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-17 00:00:00</strong></td>",
        "      <td> 0.044081</td>",
        "      <td>-0.761076</td>",
        "      <td>-0.307508</td>",
        "      <td>-0.436251</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-18 00:00:00</strong></td>",
        "      <td>-0.170571</td>",
        "      <td>-0.554817</td>",
        "      <td>-0.199920</td>",
        "      <td>-0.167603</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-19 00:00:00</strong></td>",
        "      <td> 0.035460</td>",
        "      <td>-0.492634</td>",
        "      <td>-0.226241</td>",
        "      <td>-0.482092</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-20 00:00:00</strong></td>",
        "      <td> 0.146031</td>",
        "      <td>-0.373458</td>",
        "      <td>-0.604335</td>",
        "      <td>-0.816768</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-21 00:00:00</strong></td>",
        "      <td>-0.079546</td>",
        "      <td>-0.467875</td>",
        "      <td>-0.815151</td>",
        "      <td>-0.622652</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-24 00:00:00</strong></td>",
        "      <td>-0.008007</td>",
        "      <td>-0.421989</td>",
        "      <td>-0.970575</td>",
        "      <td>-0.543737</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-25 00:00:00</strong></td>",
        "      <td> 0.057857</td>",
        "      <td>-0.272159</td>",
        "      <td>-0.850459</td>",
        "      <td>-0.542233</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-26 00:00:00</strong></td>",
        "      <td> 0.097036</td>",
        "      <td>-0.298163</td>",
        "      <td>-0.759791</td>",
        "      <td>-0.579624</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-27 00:00:00</strong></td>",
        "      <td> 0.007539</td>",
        "      <td>-0.327269</td>",
        "      <td>-0.700978</td>",
        "      <td>-0.693929</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-28 00:00:00</strong></td>",
        "      <td> 0.084663</td>",
        "      <td>-0.292802</td>",
        "      <td>-0.763486</td>",
        "      <td>-0.680676</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-01-31 00:00:00</strong></td>",
        "      <td> 1.284316</td>",
        "      <td>-0.174553</td>",
        "      <td>-0.797877</td>",
        "      <td> 0.032196</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-01 00:00:00</strong></td>",
        "      <td> 1.336821</td>",
        "      <td>-0.137998</td>",
        "      <td>-0.750165</td>",
        "      <td> 0.071421</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-02 00:00:00</strong></td>",
        "      <td> 0.891721</td>",
        "      <td>-0.167439</td>",
        "      <td>-0.696736</td>",
        "      <td> 0.035762</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-03 00:00:00</strong></td>",
        "      <td> 0.872023</td>",
        "      <td>-0.397233</td>",
        "      <td>-0.461721</td>",
        "      <td> 0.103032</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-04 00:00:00</strong></td>",
        "      <td> 0.362765</td>",
        "      <td>-0.259471</td>",
        "      <td>-0.251337</td>",
        "      <td>-0.375197</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-07 00:00:00</strong></td>",
        "      <td> 0.825776</td>",
        "      <td>-0.260346</td>",
        "      <td>-0.495456</td>",
        "      <td>-0.196771</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-08 00:00:00</strong></td>",
        "      <td> 0.799834</td>",
        "      <td>-0.807566</td>",
        "      <td>-0.435254</td>",
        "      <td> 0.051090</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-09 00:00:00</strong></td>",
        "      <td> 0.315662</td>",
        "      <td>-1.397948</td>",
        "      <td> 0.402500</td>",
        "      <td> 0.188222</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-10 00:00:00</strong></td>",
        "      <td> 0.372698</td>",
        "      <td>-1.506072</td>",
        "      <td> 0.340793</td>",
        "      <td> 0.245625</td>",
        "    </tr>",
        "    <tr>",
        "      <td><strong>2000-02-11 00:00:00</strong></td>",
        "      <td> 0.381912</td>",
        "      <td>-1.597330</td>",
        "      <td> 0.356361</td>",
        "      <td> 0.112097</td>",
        "    </tr>",
        "  </tbody>",
        "</table>",
        "",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 204,
       "text": [
        "                   B         C         D  intercept",
        "2000-01-14  0.097849 -0.631871 -0.364008  -0.246238",
        "2000-01-17  0.044081 -0.761076 -0.307508  -0.436251",
        "2000-01-18 -0.170571 -0.554817 -0.199920  -0.167603",
        "2000-01-19  0.035460 -0.492634 -0.226241  -0.482092",
        "2000-01-20  0.146031 -0.373458 -0.604335  -0.816768",
        "2000-01-21 -0.079546 -0.467875 -0.815151  -0.622652",
        "2000-01-24 -0.008007 -0.421989 -0.970575  -0.543737",
        "2000-01-25  0.057857 -0.272159 -0.850459  -0.542233",
        "2000-01-26  0.097036 -0.298163 -0.759791  -0.579624",
        "2000-01-27  0.007539 -0.327269 -0.700978  -0.693929",
        "2000-01-28  0.084663 -0.292802 -0.763486  -0.680676",
        "2000-01-31  1.284316 -0.174553 -0.797877   0.032196",
        "2000-02-01  1.336821 -0.137998 -0.750165   0.071421",
        "2000-02-02  0.891721 -0.167439 -0.696736   0.035762",
        "2000-02-03  0.872023 -0.397233 -0.461721   0.103032",
        "2000-02-04  0.362765 -0.259471 -0.251337  -0.375197",
        "2000-02-07  0.825776 -0.260346 -0.495456  -0.196771",
        "2000-02-08  0.799834 -0.807566 -0.435254   0.051090",
        "2000-02-09  0.315662 -1.397948  0.402500   0.188222",
        "2000-02-10  0.372698 -1.506072  0.340793   0.245625",
        "2000-02-11  0.381912 -1.597330  0.356361   0.112097"
       ]
      }
     ],
     "prompt_number": 204
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ols"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 206,
       "text": [
        "<function pandas.stats.interface.ols>"
       ]
      }
     ],
     "prompt_number": 206
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "res.params"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 200,
       "text": [
        "B    0.113124",
        "C   -0.351027",
        "D   -0.300097"
       ]
      }
     ],
     "prompt_number": 200
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -n 10 baby-names2.csv"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\"year\",\"name\",\"prop\",\"sex\",\"soundex\"",
        "1880,\"John\",0.081541,\"boy\",\"J500\"",
        "1880,\"William\",0.080511,\"boy\",\"W450\"",
        "1880,\"James\",0.050057,\"boy\",\"J520\"",
        "1880,\"Charles\",0.045167,\"boy\",\"C642\"",
        "1880,\"George\",0.043292,\"boy\",\"G620\"",
        "1880,\"Frank\",0.02738,\"boy\",\"F652\"",
        "1880,\"Joseph\",0.022229,\"boy\",\"J210\"",
        "1880,\"Thomas\",0.021401,\"boy\",\"T520\"",
        "1880,\"Henry\",0.020641,\"boy\",\"H560\""
       ]
      }
     ],
     "prompt_number": 125
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result.unstack('cand_nm').stack().swaplevel('cand_nm', 'contbr_st').sortlevel(0)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 115,
       "text": [
        "cand_nm             contbr_st",
        "Bachmann, Michelle  AE              3",
        "                    AK             54",
        "                    AL            124",
        "                    AP              1",
        "                    AR            129",
        "                    AZ            311",
        "                    CA           1748",
        "                    CO            241",
        "                    CT            141",
        "                    DC             18",
        "                    DE             37",
        "                    FL            657",
        "                    GA            236",
        "                    GU              5",
        "                    HI             26",
        "...",
        "Santorum, Rick  PA           1506",
        "                PR              2",
        "                RI             22",
        "                SC            294",
        "                SD             43",
        "                TN            135",
        "                TX            807",
        "                UT             22",
        "                VA            470",
        "                VI              2",
        "                VT             19",
        "                WA            193",
        "                WI            109",
        "                WV             12",
        "                WY             24",
        "Length: 690"
       ]
      }
     ],
     "prompt_number": 115
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result['Paul, Ron']#.cumsum().plot()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 98,
       "text": [
        "contb_receipt_dt  contbr_st",
        "2011-04-26        AL           1",
        "                  AZ           1",
        "                  CA           4",
        "                  DE           2",
        "                  FL           1",
        "                  IA           1",
        "                  MN           1",
        "                  MS           1",
        "                  NV           1",
        "                  NY           1",
        "                  PA           1",
        "                  TX           2",
        "                  VA           1",
        "                  WA           1",
        "2011-04-27        AR           1",
        "...",
        "2012-01-31        NV            1",
        "                  NY            4",
        "                  OH            5",
        "                  OK            2",
        "                  OR            3",
        "                  PA            6",
        "                  SC            2",
        "                  TN            4",
        "                  TX           19",
        "                  UT            1",
        "                  VA            2",
        "                  VT            1",
        "                  WA            5",
        "                  WI            2",
        "                  WY            1",
        "Length: 8870"
       ]
      }
     ],
     "prompt_number": 98
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "outputs": [],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grouped = fec.groupby(['cand_nm', 'contbr_occupation'])",
      "by_occupation = grouped['contb_receipt_amt'].sum()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "by_occupation.unstack(0)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "by_occupation = by_occupation.unstack(0)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "[x for x in by_occupation.index if 'ZOMBIE' in x]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "by_occupation['Obama, Barack'].dropna().order(ascending=False)[:20]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "by_occupation['Romney, Mitt'].dropna().order(ascending=False)[:20]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "by_occupation['Paul, Ron'].dropna().order(ascending=False)[:20]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = fec[(fec.contbr_occupation == 'ZOMBIE SLAYER').fillna(False)]",
      "df"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.contb_receipt_amt.sum()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fec[fec.contb_receipt_amt > 100000].T"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grouped = fec.groupby('contbr_st')",
      "result = grouped.apply(lambda x: len(x['contbr_nm'].unique()))",
      "result.order(ascending=False)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nrecords = fec.groupby(['contbr_st', 'cand_nm']).size()",
      "nrecords.groupby(level='contbr_st').apply(lambda x: x.idxmax()[1])"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(fec.contb_receipt_amt < 0).sum()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "total = fec.groupby(['contbr_st', 'cand_nm'])['contb_receipt_amt'].sum()",
      "total.groupby(level='contbr_st').apply(lambda x: x.idxmax()[1])"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nparties = fec.groupby(['contbr_nm', 'party']).size().count(level=0)",
      "multi_party = nparties[nparties > 1]"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(multi_party)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bins = [0, 1, 10, 100, 1000, 10000, 100000, 1000000, 10000000]",
      "",
      "def bucket(s, bins, closed='left', strings=True):",
      "    bins = np.asarray(bins)",
      "    labels = bins.searchsorted(s.values, side=closed)",
      "    ",
      "    if strings:",
      "        if closed == 'left':",
      "            strings = ['[%s, %s)' % tup for tup in zip(bins, bins[1:])]",
      "        else:",
      "            strings = ['(%s, %s]' % tup for tup in zip(bins, bins[1:])]",
      "        strings = np.asarray(strings, dtype=object)",
      "        return strings.take(labels - 1)",
      "    ",
      "    return labels, s.values",
      "",
      "fec.groupby(bucket(fec.contb_receipt_amt, bins))['contb_receipt_amt'].size()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 43
    }
   ]
  }
 ]
}