file reading.ipynb

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  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!cat pydata-book/ch06/ex7.csv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\"a\",\"b\",\"c\"\r\n",
        "\"1\",\"2\",\"3\"\r\n",
        "\"1\",\"2\",\"3\",\"4\"\r\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f = open('pydata-book/ch06/ex7.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import csv\n",
      "reader = csv.reader(f)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for line in reader:\n",
      "    print line"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "['a', 'b', 'c']\n",
        "['1', '2', '3']\n",
        "['1', '2', '3', '4']\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lines = list(csv.reader(open('pydata-book/ch06/ex7.csv')))\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "header = lines[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "values = lines[1:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "zip(header,zip(*values))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "[('a', ('1', '1')), ('b', ('2', '2')), ('c', ('3', '3'))]"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import Series\n",
      "Series(np.arange(5)).apply()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "0    0\n",
        "1    1\n",
        "2    2\n",
        "3    3\n",
        "4    4\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df1 = pd.DataFrame(np.arange(10).reshape(5,2), columns=['a','key1'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2 = pd.DataFrame(np.arange(10).reshape(5,2), columns=['b','key2'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df1.merge(df2, left_on='key1', right_on='key2')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>a</th>\n",
        "      <th>key1</th>\n",
        "      <th>b</th>\n",
        "      <th>key2</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 4</td>\n",
        "      <td> 5</td>\n",
        "      <td> 4</td>\n",
        "      <td> 5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 6</td>\n",
        "      <td> 7</td>\n",
        "      <td> 6</td>\n",
        "      <td> 7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 8</td>\n",
        "      <td> 9</td>\n",
        "      <td> 8</td>\n",
        "      <td> 9</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 4 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "   a  key1  b  key2\n",
        "0  0     1  0     1\n",
        "1  2     3  2     3\n",
        "2  4     5  4     5\n",
        "3  6     7  6     7\n",
        "4  8     9  8     9\n",
        "\n",
        "[5 rows x 4 columns]"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df3 = pd.DataFrame({'lkey': ['b', 'b', 'a', 'c', 'a', 'a', 'b'],'data1': range(7)})\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df4 = pd.DataFrame({'rkey': ['a', 'b', 'd'],'data2': range(3)})\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df4"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>data2</th>\n",
        "      <th>rkey</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 0</td>\n",
        "      <td> a</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1</td>\n",
        "      <td> b</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 2</td>\n",
        "      <td> d</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>3 rows \u00d7 2 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 67,
       "text": [
        "   data2 rkey\n",
        "0      0    a\n",
        "1      1    b\n",
        "2      2    d\n",
        "\n",
        "[3 rows x 2 columns]"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A =pd.merge(df3,df4,left_on='lkey', right_on='rkey', how = 'outer')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 70
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A.drop('rkey',axis=1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>data1</th>\n",
        "      <th>lkey</th>\n",
        "      <th>data2</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  0</td>\n",
        "      <td>   b</td>\n",
        "      <td>  1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  1</td>\n",
        "      <td>   b</td>\n",
        "      <td>  1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>  6</td>\n",
        "      <td>   b</td>\n",
        "      <td>  1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>  2</td>\n",
        "      <td>   a</td>\n",
        "      <td>  0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>  4</td>\n",
        "      <td>   a</td>\n",
        "      <td>  0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>  5</td>\n",
        "      <td>   a</td>\n",
        "      <td>  0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>  3</td>\n",
        "      <td>   c</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>8 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 77,
       "text": [
        "   data1 lkey  data2\n",
        "0      0    b      1\n",
        "1      1    b      1\n",
        "2      6    b      1\n",
        "3      2    a      0\n",
        "4      4    a      0\n",
        "5      5    a      0\n",
        "6      3    c    NaN\n",
        "7    NaN  NaN      2\n",
        "\n",
        "[8 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 77
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "left = pd.DataFrame(np.arange(6).reshape(3,2),columns=['Ohio','Nevada'],index=['a','b','c'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 84
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "right = pd.DataFrame(np.arange(8).reshape(4,2),columns=['Mis','Ala'],index=['b','c','d','e'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 85
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.merge(left,right,how='outer',left_index=True,right_index=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Ohio</th>\n",
        "      <th>Nevada</th>\n",
        "      <th>Mis</th>\n",
        "      <th>Ala</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>a</th>\n",
        "      <td>  0</td>\n",
        "      <td>  1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>b</th>\n",
        "      <td>  2</td>\n",
        "      <td>  3</td>\n",
        "      <td>  0</td>\n",
        "      <td>  1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>c</th>\n",
        "      <td>  4</td>\n",
        "      <td>  5</td>\n",
        "      <td>  2</td>\n",
        "      <td>  3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>d</th>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>  5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>e</th>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>  7</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 4 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 86,
       "text": [
        "   Ohio  Nevada  Mis  Ala\n",
        "a     0       1  NaN  NaN\n",
        "b     2       3    0    1\n",
        "c     4       5    2    3\n",
        "d   NaN     NaN    4    5\n",
        "e   NaN     NaN    6    7\n",
        "\n",
        "[5 rows x 4 columns]"
       ]
      }
     ],
     "prompt_number": 86
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = pd.DataFrame({'food': ['bacon', 'pulled pork', 'bacon', 'Pastrami','corned beef', 'Bacon', 'pastrami', 'honey ham','nova lox'],\n",
      "'ounces': [4, 3, 12, 6, 7.5, 8, 3, 5, 6]})\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 88
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>food</th>\n",
        "      <th>ounces</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>       bacon</td>\n",
        "      <td>  4.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> pulled pork</td>\n",
        "      <td>  3.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>       bacon</td>\n",
        "      <td> 12.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>    Pastrami</td>\n",
        "      <td>  6.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> corned beef</td>\n",
        "      <td>  7.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>       Bacon</td>\n",
        "      <td>  8.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>    pastrami</td>\n",
        "      <td>  3.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>   honey ham</td>\n",
        "      <td>  5.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>    nova lox</td>\n",
        "      <td>  6.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>9 rows \u00d7 2 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 90,
       "text": [
        "          food  ounces\n",
        "0        bacon     4.0\n",
        "1  pulled pork     3.0\n",
        "2        bacon    12.0\n",
        "3     Pastrami     6.0\n",
        "4  corned beef     7.5\n",
        "5        Bacon     8.0\n",
        "6     pastrami     3.0\n",
        "7    honey ham     5.0\n",
        "8     nova lox     6.0\n",
        "\n",
        "[9 rows x 2 columns]"
       ]
      }
     ],
     "prompt_number": 90
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "meat_to_animal = {\n",
      "'bacon': 'pig',\n",
      "'pulled pork': 'pig',\n",
      "'pastrami': 'cow',\n",
      "'corned beef': 'cow',\n",
      "'honey ham': 'pig',\n",
      "'nova lox': 'salmon'\n",
      "}\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 91
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data['animal'] = data['food'].map(str.lower).map(meat_to_animal)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 92
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>food</th>\n",
        "      <th>ounces</th>\n",
        "      <th>animal</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>       bacon</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>    pig</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> pulled pork</td>\n",
        "      <td>  3.0</td>\n",
        "      <td>    pig</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>       bacon</td>\n",
        "      <td> 12.0</td>\n",
        "      <td>    pig</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>    Pastrami</td>\n",
        "      <td>  6.0</td>\n",
        "      <td>    cow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> corned beef</td>\n",
        "      <td>  7.5</td>\n",
        "      <td>    cow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>       Bacon</td>\n",
        "      <td>  8.0</td>\n",
        "      <td>    pig</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>    pastrami</td>\n",
        "      <td>  3.0</td>\n",
        "      <td>    cow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>   honey ham</td>\n",
        "      <td>  5.0</td>\n",
        "      <td>    pig</td>\n",
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        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>    nova lox</td>\n",
        "      <td>  6.0</td>\n",
        "      <td> salmon</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>9 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
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       "text": [
        "          food  ounces  animal\n",
        "0        bacon     4.0     pig\n",
        "1  pulled pork     3.0     pig\n",
        "2        bacon    12.0     pig\n",
        "3     Pastrami     6.0     cow\n",
        "4  corned beef     7.5     cow\n",
        "5        Bacon     8.0     pig\n",
        "6     pastrami     3.0     cow\n",
        "7    honey ham     5.0     pig\n",
        "8     nova lox     6.0  salmon\n",
        "\n",
        "[9 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 93
    },
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     "cell_type": "code",
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      "ages = [20, 22, 25, 27, 21, 23, 37, 31, 61, 45, 41, 32]"
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     "metadata": {},
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     "prompt_number": 94
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     "cell_type": "code",
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     "input": [
      "bins = [18, 25, 35, 60, 100]"
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     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 96
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cats = pd.cut(ages, bins)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 97
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame(np.arange(5 * 4).reshape(5, 4))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 100
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sampler = np.random.permutation(5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 101
    },
    {
     "cell_type": "code",
     "collapsed": false,
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     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 102,
       "text": [
        "array([1, 0, 2, 4, 3])"
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      }
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     "prompt_number": 102
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
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     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>0</th>\n",
        "      <th>1</th>\n",
        "      <th>2</th>\n",
        "      <th>3</th>\n",
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        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  0</td>\n",
        "      <td>  1</td>\n",
        "      <td>  2</td>\n",
        "      <td>  3</td>\n",
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        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  4</td>\n",
        "      <td>  5</td>\n",
        "      <td>  6</td>\n",
        "      <td>  7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>  8</td>\n",
        "      <td>  9</td>\n",
        "      <td> 10</td>\n",
        "      <td> 11</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 12</td>\n",
        "      <td> 13</td>\n",
        "      <td> 14</td>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 16</td>\n",
        "      <td> 17</td>\n",
        "      <td> 18</td>\n",
        "      <td> 19</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 4 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
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       "prompt_number": 112,
       "text": [
        "    0   1   2   3\n",
        "0   0   1   2   3\n",
        "1   4   5   6   7\n",
        "2   8   9  10  11\n",
        "3  12  13  14  15\n",
        "4  16  17  18  19\n",
        "\n",
        "[5 rows x 4 columns]"
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     "prompt_number": 112
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
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     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 123
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "str ='::'.join(list(a))"
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     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 130
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = {'Dave': 'dave@google.com', 'Steve': 'steve@gmail.com','Rob': 'rob@gmail.com', 'Wes': np.nan}\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 161
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = Series(data)"
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     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 162
    },
    {
     "cell_type": "code",
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     "input": [
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 163,
       "text": [
        "Dave      True\n",
        "Rob      False\n",
        "Steve    False\n",
        "Wes        NaN\n",
        "dtype: object"
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     ],
     "prompt_number": 163
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   "metadata": {}
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 ]
}