/lessons/06 - Lesson.ipynb

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     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Lesson 6  \n",
      "\n",
      "Lets take a look at the ***groupby*** function."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Import libraries\n",
      "from pandas import DataFrame\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print 'Pandas version: ' + pd.__version__"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Pandas version: 0.13.0\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Our small data set\n",
      "d = {'one':[1,1,1,1,1],\n",
      "     'two':[2,2,2,2,2],\n",
      "     'letter':['a','a','b','b','c']}\n",
      "\n",
      "# Create dataframe\n",
      "df = DataFrame(d)\n",
      "df"
     ],
     "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>letter</th>\n",
        "      <th>one</th>\n",
        "      <th>two</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> a</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> a</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> b</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> b</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> c</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "  letter  one  two\n",
        "0      a    1    2\n",
        "1      a    1    2\n",
        "2      b    1    2\n",
        "3      b    1    2\n",
        "4      c    1    2\n",
        "\n",
        "[5 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Create group object\n",
      "one = df.groupby('letter')\n",
      "\n",
      "# Apply sum function\n",
      "one.sum()"
     ],
     "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>one</th>\n",
        "      <th>two</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>letter</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>a</th>\n",
        "      <td> 2</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>b</th>\n",
        "      <td> 2</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>c</th>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>3 rows \u00d7 2 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "        one  two\n",
        "letter          \n",
        "a         2    4\n",
        "b         2    4\n",
        "c         1    2\n",
        "\n",
        "[3 rows x 2 columns]"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "letterone = df.groupby(['letter','one']).sum()\n",
      "letterone"
     ],
     "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></th>\n",
        "      <th>two</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>letter</th>\n",
        "      <th>one</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>a</th>\n",
        "      <th>1</th>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>b</th>\n",
        "      <th>1</th>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>c</th>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>3 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "            two\n",
        "letter one     \n",
        "a      1      4\n",
        "b      1      4\n",
        "c      1      2\n",
        "\n",
        "[3 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "letterone.index"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "MultiIndex(levels=[[u'a', u'b', u'c'], [1]],\n",
        "           labels=[[0, 1, 2], [0, 0, 0]],\n",
        "           names=[u'letter', u'one'])"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You may want to ***not*** have the columns you are grouping by become your index, this can be easily achieved as shown below."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "letterone = df.groupby(['letter','one'], as_index=False).sum()\n",
      "letterone"
     ],
     "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>letter</th>\n",
        "      <th>one</th>\n",
        "      <th>two</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> a</td>\n",
        "      <td> 1</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> b</td>\n",
        "      <td> 1</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> c</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>3 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "  letter  one  two\n",
        "0      a    1    4\n",
        "1      b    1    4\n",
        "2      c    1    2\n",
        "\n",
        "[3 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "letterone.index"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "Int64Index([0, 1, 2], dtype='int64')"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Author:** [David Rojas LLC](http://hdrojas.pythonanywhere.com/)  "
     ]
    }
   ],
   "metadata": {}
  }
 ]
}