Source

talks / pandas / Data2-Solution.ipynb

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{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<style>\n",
      "img[alt=Miki], img[alt=Eric] {\n",
      "    width: 50px;\n",
      "}\n",
      "</style>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Second Data Set\n",
      "We'll use a [csv](http://en.wikipedia.org/wiki/Comma-separated_values) file in this second part of the workshop. Pandas has a [read_csv](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) function that get data from an SQL connection to a [DataFrame](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html).\n",
      "\n",
      "This data is generated by the following SQL:\n",
      "\n",
      "`\n",
      "SELECT\n",
      "    Date(Convert_tz(From_unixtime(o.order_time), 'UTC', 'US/Pacific')) AS date\n",
      "    ,Ifnull(p.product_name, 'GiftCard') AS product\n",
      "    ,Ifnull(c.country_name, '-') AS country\n",
      "\t,oi.order_item_amount AS price\n",
      "    ,oi.order_item_cost AS cost\n",
      "    ,SUM(oi.order_item_quantity) AS qty\n",
      "    ,SUM(oi.order_item_quantity * oi.order_item_amount) AS rev\n",
      "    ,SUM((oi.order_item_amount - oi.order_item_cost) * oi.order_item_quantity) AS gm\n",
      "FROM\n",
      "    orders AS o\n",
      "    JOIN orders_items AS oi USING(order_id)\n",
      "            -- ON o.order_id = oi.order_id\n",
      "    LEFT JOIN products AS p  USING(product_id)\n",
      "           -- ON oi.product_id = p.product_id\n",
      "    LEFT JOIN countries c\n",
      "            ON o.order_shipping_country = c.country_code\n",
      "WHERE\n",
      "    o.order_time >= Unix_timestamp(Convert_tz('2013-01-01','US/Pacific', 'UTC'))\n",
      "    AND o.order_time < Unix_timestamp(\n",
      "                                Convert_tz(\n",
      "                                Date(Convert_tz(now(), 'UTC', 'US/Pacific')),\n",
      "                                'US/Pacific', 'UTC')\n",
      "                                )\n",
      "    AND o.order_type IN (0, 12) -- 0    TYPE_STANDARD, 12    TYPE_SPLIT_PARENT\n",
      "    AND o.order_status NOT IN (0, 11, 12) -- 0 PENDING,11 CANCELLED,12 RETURNED\n",
      "GROUP BY 1,2,3,4,5`\n",
      "\n",
      "\n",
      "\n",
      "The data file is `product_country.sql.csv.bz2`, in the directory you cloned `miki/talks/pandas` into, or download it from [Amazon S3](http://dm-miki.s3.amazonaws.com/talks/product_country.sql.csv.bz2).  \n",
      "\n",
      "Use [read_csv](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) to load the data file to a DataFrame called `df2`.  Set the index columns to `date`, `product`, `country`, `price`, and `cost`, and specify that `date` is to be parsed into proper datetime date values.  Don't forget to specify that the data file is bzip2-compressed."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# You code goes here\n",
      "rcParams['figure.figsize'] = 20, 10  # makes the graphs larger\n",
      "\n",
      "import pandas as pd\n",
      "df2 = pd.read_csv('product_country.sql.csv.bz2',\n",
      "                  index_col=['date', 'product', 'country', 'price', 'cost'],\n",
      "                  parse_dates='date',\n",
      "                  compression='bz2')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# First Look at the Data\n",
      "\n",
      "## `df2` as a Value\n",
      "Since we're in IPython, we can just evaluate `df2` to see what it is."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# You code goes here\n",
      "df2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<pre>\n",
        "&lt;class 'pandas.core.frame.DataFrame'&gt;\n",
        "MultiIndex: 221847 entries, (2013-01-01 00:00:00, Art Print, Australia, 18.0, 4.25) to (2014-02-04 00:00:00, Wall Clock, United States, 30.0, 14.25)\n",
        "Data columns (total 3 columns):\n",
        "qty    221847  non-null values\n",
        "rev    221847  non-null values\n",
        "gm     221847  non-null values\n",
        "dtypes: float64(2), int64(1)\n",
        "</pre>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "MultiIndex: 221847 entries, (2013-01-01 00:00:00, Art Print, Australia, 18.0, 4.25) to (2014-02-04 00:00:00, Wall Clock, United States, 30.0, 14.25)\n",
        "Data columns (total 3 columns):\n",
        "qty    221847  non-null values\n",
        "rev    221847  non-null values\n",
        "gm     221847  non-null values\n",
        "dtypes: float64(2), int64(1)"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## `df2` as Data\n",
      "Use the [head](http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.head.html) method of the `df2` DataFrame to see some actual data."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# You code goes here\n",
      "df2.head(20)"
     ],
     "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></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th>qty</th>\n",
        "      <th>rev</th>\n",
        "      <th>gm</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th>product</th>\n",
        "      <th>country</th>\n",
        "      <th>price</th>\n",
        "      <th>cost</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th rowspan=\"20\" valign=\"top\">2013-01-01</th>\n",
        "      <th rowspan=\"20\" valign=\"top\">Art Print</th>\n",
        "      <th rowspan=\"7\" valign=\"top\">Australia</th>\n",
        "      <th>18.00</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 3</td>\n",
        "      <td> 54.00</td>\n",
        "      <td> 41.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18.72</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 3</td>\n",
        "      <td> 56.16</td>\n",
        "      <td> 43.41</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 21.00</td>\n",
        "      <td> 16.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21.84</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 21.84</td>\n",
        "      <td> 17.09</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22.99</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 22.99</td>\n",
        "      <td> 18.24</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 25.00</td>\n",
        "      <td> 20.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30.00</th>\n",
        "      <th>9.60 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 30.00</td>\n",
        "      <td> 20.40</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Brazil</th>\n",
        "      <th>26.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 26.00</td>\n",
        "      <td> 21.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th rowspan=\"9\" valign=\"top\">Canada</th>\n",
        "      <th>16.00</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 16.00</td>\n",
        "      <td> 11.75</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17.08</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 17.08</td>\n",
        "      <td> 12.83</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 18.00</td>\n",
        "      <td> 13.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19.76</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 19.76</td>\n",
        "      <td> 15.51</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 24.00</td>\n",
        "      <td> 19.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25.00</th>\n",
        "      <th>9.60 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 25.00</td>\n",
        "      <td> 15.40</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28.00</th>\n",
        "      <th>4.25 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 28.00</td>\n",
        "      <td> 23.75</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>35.00</th>\n",
        "      <th>16.20</th>\n",
        "      <td> 2</td>\n",
        "      <td> 70.00</td>\n",
        "      <td> 37.60</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>37.00</th>\n",
        "      <th>16.20</th>\n",
        "      <td> 1</td>\n",
        "      <td> 37.00</td>\n",
        "      <td> 20.80</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Denmark</th>\n",
        "      <th>22.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 22.00</td>\n",
        "      <td> 17.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th rowspan=\"2\" valign=\"top\">France</th>\n",
        "      <th>22.00</th>\n",
        "      <th>4.75 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 22.00</td>\n",
        "      <td> 17.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>40.00</th>\n",
        "      <th>9.60 </th>\n",
        "      <td> 1</td>\n",
        "      <td> 40.00</td>\n",
        "      <td> 30.40</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "                                            qty    rev     gm\n",
        "date       product   country   price cost                    \n",
        "2013-01-01 Art Print Australia 18.00 4.25     3  54.00  41.25\n",
        "                               18.72 4.25     3  56.16  43.41\n",
        "                               21.00 4.75     1  21.00  16.25\n",
        "                               21.84 4.75     1  21.84  17.09\n",
        "                               22.99 4.75     1  22.99  18.24\n",
        "                               25.00 4.75     1  25.00  20.25\n",
        "                               30.00 9.60     1  30.00  20.40\n",
        "                     Brazil    26.00 4.75     1  26.00  21.25\n",
        "                     Canada    16.00 4.25     1  16.00  11.75\n",
        "                               17.08 4.25     1  17.08  12.83\n",
        "                               18.00 4.75     1  18.00  13.25\n",
        "                               19.76 4.25     1  19.76  15.51\n",
        "                               24.00 4.75     1  24.00  19.25\n",
        "                               25.00 9.60     1  25.00  15.40\n",
        "                               28.00 4.25     1  28.00  23.75\n",
        "                               35.00 16.20    2  70.00  37.60\n",
        "                               37.00 16.20    1  37.00  20.80\n",
        "                     Denmark   22.00 4.75     1  22.00  17.25\n",
        "                     France    22.00 4.75     1  22.00  17.25\n",
        "                               40.00 9.60     1  40.00  30.40"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Plot the Revenue Series by Day\n",
      "\n",
      "## First, summarize the data\n",
      "\n",
      "Take the `sum()` of revenue per day by using the [groupby](http://pandas.pydata.org/pandas-docs/dev/groupby.html) method on the `df2` Data Frame, to make a new Data Frame named `df3`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Your code goes here\n",
      "df3 = df2.groupby(level='date').sum()\n",
      "print(df3)\n",
      "df3.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "DatetimeIndex: 400 entries, 2013-01-01 00:00:00 to 2014-02-04 00:00:00\n",
        "Data columns (total 3 columns):\n",
        "qty    400  non-null values\n",
        "rev    400  non-null values\n",
        "gm     400  non-null values\n",
        "dtypes: float64(2), int64(1)\n"
       ]
      },
      {
       "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>qty</th>\n",
        "      <th>rev</th>\n",
        "      <th>gm</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2013-01-01</th>\n",
        "      <td> 1374</td>\n",
        "      <td> 44752.34</td>\n",
        "      <td> 25554.79</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02</th>\n",
        "      <td> 1696</td>\n",
        "      <td> 53025.65</td>\n",
        "      <td> 30038.49</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-03</th>\n",
        "      <td> 1660</td>\n",
        "      <td> 50173.92</td>\n",
        "      <td> 29041.58</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-04</th>\n",
        "      <td> 1631</td>\n",
        "      <td> 49603.00</td>\n",
        "      <td> 28173.89</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-05</th>\n",
        "      <td> 1437</td>\n",
        "      <td> 43324.95</td>\n",
        "      <td> 24926.86</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "             qty       rev        gm\n",
        "date                                \n",
        "2013-01-01  1374  44752.34  25554.79\n",
        "2013-01-02  1696  53025.65  30038.49\n",
        "2013-01-03  1660  50173.92  29041.58\n",
        "2013-01-04  1631  49603.00  28173.89\n",
        "2013-01-05  1437  43324.95  24926.86"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Now, plot the data\n",
      "\n",
      "Find the total revenue per day by calling the [plot](http://pandas.pydata.org/pandas-docs/stable/visualization.html) method on the `df3.rev` Series."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Your code goes here\n",
      "df3.rev.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x109cec8d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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fkyZNkr7+demqq6Rf/lIqLEz2qoD4MTMJAAAAAABDzExCb8JmEqLi2dT40M0O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K9Txp07d0ahZvpkx44d6NKlCzp37owdO3ZEvS+/U/BrCrS2thYHDx5EO4NlLf72t+vR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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105ac8ed0>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Plot Gross Margin (gm) by Product by Date\n",
      "##First summarize the data\n",
      "`sum()` the data to the level of `date` and `product` using the [groupby](http://pandas.pydata.org/pandas-docs/dev/groupby.html) method on the `df2` Data Frame."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Your code goes here\n",
      "product_by_date = df2.groupby(level=['date', 'product']).sum()\n",
      "product_by_date.head()"
     ],
     "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>qty</th>\n",
        "      <th>rev</th>\n",
        "      <th>gm</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th>product</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th rowspan=\"5\" valign=\"top\">2013-01-01</th>\n",
        "      <th>Art Print</th>\n",
        "      <td> 240</td>\n",
        "      <td> 6694.74</td>\n",
        "      <td> 4695.89</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Framed Art Print</th>\n",
        "      <td>  95</td>\n",
        "      <td> 4775.50</td>\n",
        "      <td> 2684.55</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>GiftCard</th>\n",
        "      <td>   8</td>\n",
        "      <td>  500.00</td>\n",
        "      <td>  500.00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Hoody</th>\n",
        "      <td>  26</td>\n",
        "      <td> 1044.00</td>\n",
        "      <td>  346.55</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Laptop &amp; iPad Skin</th>\n",
        "      <td>  43</td>\n",
        "      <td> 1185.00</td>\n",
        "      <td>  773.75</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "                               qty      rev       gm\n",
        "date       product                                  \n",
        "2013-01-01 Art Print           240  6694.74  4695.89\n",
        "           Framed Art Print     95  4775.50  2684.55\n",
        "           GiftCard              8   500.00   500.00\n",
        "           Hoody                26  1044.00   346.55\n",
        "           Laptop & iPad Skin   43  1185.00   773.75"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Put the `product` names into the column headings\n",
      "Use the [unstack](http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.unstack.html) method of the `product_by_date` Data Frame to move the product names from the row labels into the column headings."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date = product_by_date.unstack()\n",
      "product_by_date.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<pre>\n",
        "&lt;class 'pandas.core.frame.DataFrame'&gt;\n",
        "DatetimeIndex: 5 entries, 2013-01-01 00:00:00 to 2013-01-05 00:00:00\n",
        "Data columns (total 57 columns):\n",
        "(qty, Art Print)             5  non-null values\n",
        "(qty, Framed Art Print)      5  non-null values\n",
        "(qty, GiftCard)              5  non-null values\n",
        "(qty, Hoody)                 5  non-null values\n",
        "(qty, Kids T-Shirt)          0  non-null values\n",
        "(qty, Laptop &amp; iPad Skin)    5  non-null values\n",
        "(qty, Mug)                   0  non-null values\n",
        "(qty, Onesie)                0  non-null values\n",
        "(qty, Stationery Cards)      5  non-null values\n",
        "(qty, Stretched Canvas)      5  non-null values\n",
        "(qty, T-shirt)               5  non-null values\n",
        "(qty, Throw Pillow)          5  non-null values\n",
        "(qty, Tote Bag)              0  non-null values\n",
        "(qty, Tote Bag (old))        5  non-null values\n",
        "(qty, Unisex Tank Top)       0  non-null values\n",
        "(qty, Wall Clock)            0  non-null values\n",
        "(qty, iPad Case)             0  non-null values\n",
        "(qty, iPhone &amp; iPod Case)    5  non-null values\n",
        "(qty, iPhone &amp; iPod Skin)    5  non-null values\n",
        "(rev, Art Print)             5  non-null values\n",
        "(rev, Framed Art Print)      5  non-null values\n",
        "(rev, GiftCard)              5  non-null values\n",
        "(rev, Hoody)                 5  non-null values\n",
        "(rev, Kids T-Shirt)          0  non-null values\n",
        "(rev, Laptop &amp; iPad Skin)    5  non-null values\n",
        "(rev, Mug)                   0  non-null values\n",
        "(rev, Onesie)                0  non-null values\n",
        "(rev, Stationery Cards)      5  non-null values\n",
        "(rev, Stretched Canvas)      5  non-null values\n",
        "(rev, T-shirt)               5  non-null values\n",
        "(rev, Throw Pillow)          5  non-null values\n",
        "(rev, Tote Bag)              0  non-null values\n",
        "(rev, Tote Bag (old))        5  non-null values\n",
        "(rev, Unisex Tank Top)       0  non-null values\n",
        "(rev, Wall Clock)            0  non-null values\n",
        "(rev, iPad Case)             0  non-null values\n",
        "(rev, iPhone &amp; iPod Case)    5  non-null values\n",
        "(rev, iPhone &amp; iPod Skin)    5  non-null values\n",
        "(gm, Art Print)              5  non-null values\n",
        "(gm, Framed Art Print)       5  non-null values\n",
        "(gm, GiftCard)               5  non-null values\n",
        "(gm, Hoody)                  5  non-null values\n",
        "(gm, Kids T-Shirt)           0  non-null values\n",
        "(gm, Laptop &amp; iPad Skin)     5  non-null values\n",
        "(gm, Mug)                    0  non-null values\n",
        "(gm, Onesie)                 0  non-null values\n",
        "(gm, Stationery Cards)       5  non-null values\n",
        "(gm, Stretched Canvas)       5  non-null values\n",
        "(gm, T-shirt)                5  non-null values\n",
        "(gm, Throw Pillow)           5  non-null values\n",
        "(gm, Tote Bag)               0  non-null values\n",
        "(gm, Tote Bag (old))         5  non-null values\n",
        "(gm, Unisex Tank Top)        0  non-null values\n",
        "(gm, Wall Clock)             0  non-null values\n",
        "(gm, iPad Case)              0  non-null values\n",
        "(gm, iPhone &amp; iPod Case)     5  non-null values\n",
        "(gm, iPhone &amp; iPod Skin)     5  non-null values\n",
        "dtypes: float64(57)\n",
        "</pre>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "DatetimeIndex: 5 entries, 2013-01-01 00:00:00 to 2013-01-05 00:00:00\n",
        "Data columns (total 57 columns):\n",
        "(qty, Art Print)             5  non-null values\n",
        "(qty, Framed Art Print)      5  non-null values\n",
        "(qty, GiftCard)              5  non-null values\n",
        "(qty, Hoody)                 5  non-null values\n",
        "(qty, Kids T-Shirt)          0  non-null values\n",
        "(qty, Laptop & iPad Skin)    5  non-null values\n",
        "(qty, Mug)                   0  non-null values\n",
        "(qty, Onesie)                0  non-null values\n",
        "(qty, Stationery Cards)      5  non-null values\n",
        "(qty, Stretched Canvas)      5  non-null values\n",
        "(qty, T-shirt)               5  non-null values\n",
        "(qty, Throw Pillow)          5  non-null values\n",
        "(qty, Tote Bag)              0  non-null values\n",
        "(qty, Tote Bag (old))        5  non-null values\n",
        "(qty, Unisex Tank Top)       0  non-null values\n",
        "(qty, Wall Clock)            0  non-null values\n",
        "(qty, iPad Case)             0  non-null values\n",
        "(qty, iPhone & iPod Case)    5  non-null values\n",
        "(qty, iPhone & iPod Skin)    5  non-null values\n",
        "(rev, Art Print)             5  non-null values\n",
        "(rev, Framed Art Print)      5  non-null values\n",
        "(rev, GiftCard)              5  non-null values\n",
        "(rev, Hoody)                 5  non-null values\n",
        "(rev, Kids T-Shirt)          0  non-null values\n",
        "(rev, Laptop & iPad Skin)    5  non-null values\n",
        "(rev, Mug)                   0  non-null values\n",
        "(rev, Onesie)                0  non-null values\n",
        "(rev, Stationery Cards)      5  non-null values\n",
        "(rev, Stretched Canvas)      5  non-null values\n",
        "(rev, T-shirt)               5  non-null values\n",
        "(rev, Throw Pillow)          5  non-null values\n",
        "(rev, Tote Bag)              0  non-null values\n",
        "(rev, Tote Bag (old))        5  non-null values\n",
        "(rev, Unisex Tank Top)       0  non-null values\n",
        "(rev, Wall Clock)            0  non-null values\n",
        "(rev, iPad Case)             0  non-null values\n",
        "(rev, iPhone & iPod Case)    5  non-null values\n",
        "(rev, iPhone & iPod Skin)    5  non-null values\n",
        "(gm, Art Print)              5  non-null values\n",
        "(gm, Framed Art Print)       5  non-null values\n",
        "(gm, GiftCard)               5  non-null values\n",
        "(gm, Hoody)                  5  non-null values\n",
        "(gm, Kids T-Shirt)           0  non-null values\n",
        "(gm, Laptop & iPad Skin)     5  non-null values\n",
        "(gm, Mug)                    0  non-null values\n",
        "(gm, Onesie)                 0  non-null values\n",
        "(gm, Stationery Cards)       5  non-null values\n",
        "(gm, Stretched Canvas)       5  non-null values\n",
        "(gm, T-shirt)                5  non-null values\n",
        "(gm, Throw Pillow)           5  non-null values\n",
        "(gm, Tote Bag)               0  non-null values\n",
        "(gm, Tote Bag (old))         5  non-null values\n",
        "(gm, Unisex Tank Top)        0  non-null values\n",
        "(gm, Wall Clock)             0  non-null values\n",
        "(gm, iPad Case)              0  non-null values\n",
        "(gm, iPhone & iPod Case)     5  non-null values\n",
        "(gm, iPhone & iPod Skin)     5  non-null values\n",
        "dtypes: float64(57)"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Keep just the Gross Margin\n",
      "Set the `product_by_date` DataFrame to just the subset of columns that hold gross margin (`gm`)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date = product_by_date['gm']\n",
      "product_by_date.head()                           "
     ],
     "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>product</th>\n",
        "      <th>Art Print</th>\n",
        "      <th>Framed Art Print</th>\n",
        "      <th>GiftCard</th>\n",
        "      <th>Hoody</th>\n",
        "      <th>Kids T-Shirt</th>\n",
        "      <th>Laptop &amp; iPad Skin</th>\n",
        "      <th>Mug</th>\n",
        "      <th>Onesie</th>\n",
        "      <th>Stationery Cards</th>\n",
        "      <th>Stretched Canvas</th>\n",
        "      <th>T-shirt</th>\n",
        "      <th>Throw Pillow</th>\n",
        "      <th>Tote Bag</th>\n",
        "      <th>Tote Bag (old)</th>\n",
        "      <th>Unisex Tank Top</th>\n",
        "      <th>Wall Clock</th>\n",
        "      <th>iPad Case</th>\n",
        "      <th>iPhone &amp; iPod Case</th>\n",
        "      <th>iPhone &amp; iPod Skin</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2013-01-01</th>\n",
        "      <td> 4695.89</td>\n",
        "      <td> 2684.55</td>\n",
        "      <td> 500</td>\n",
        "      <td> 346.55</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 773.75</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 127.08</td>\n",
        "      <td> 1186.38</td>\n",
        "      <td> 1337.00</td>\n",
        "      <td> 1491.54</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 127.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 11868.0</td>\n",
        "      <td> 416.25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02</th>\n",
        "      <td> 6151.93</td>\n",
        "      <td> 2588.52</td>\n",
        "      <td>  75</td>\n",
        "      <td> 316.75</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 666.25</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  91.72</td>\n",
        "      <td> 1008.32</td>\n",
        "      <td> 1531.35</td>\n",
        "      <td> 1915.55</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 155.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15038.5</td>\n",
        "      <td> 499.50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-03</th>\n",
        "      <td> 6457.19</td>\n",
        "      <td> 2484.98</td>\n",
        "      <td>  97</td>\n",
        "      <td> 385.35</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 742.50</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 356.08</td>\n",
        "      <td>  591.16</td>\n",
        "      <td> 1404.60</td>\n",
        "      <td> 1824.42</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 220.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13794.5</td>\n",
        "      <td> 683.00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-04</th>\n",
        "      <td> 6761.30</td>\n",
        "      <td> 2125.80</td>\n",
        "      <td>  75</td>\n",
        "      <td> 429.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 531.75</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 251.68</td>\n",
        "      <td>  779.87</td>\n",
        "      <td> 1683.10</td>\n",
        "      <td> 1710.44</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 252.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12999.5</td>\n",
        "      <td> 573.50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-05</th>\n",
        "      <td> 5561.05</td>\n",
        "      <td> 2215.95</td>\n",
        "      <td>  50</td>\n",
        "      <td> 438.20</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 730.50</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  91.60</td>\n",
        "      <td>  486.88</td>\n",
        "      <td> 1366.00</td>\n",
        "      <td> 1918.33</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 128.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 11338.5</td>\n",
        "      <td> 601.25</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "product     Art Print  Framed Art Print  GiftCard   Hoody  Kids T-Shirt  \\\n",
        "date                                                                      \n",
        "2013-01-01    4695.89           2684.55       500  346.55           NaN   \n",
        "2013-01-02    6151.93           2588.52        75  316.75           NaN   \n",
        "2013-01-03    6457.19           2484.98        97  385.35           NaN   \n",
        "2013-01-04    6761.30           2125.80        75  429.15           NaN   \n",
        "2013-01-05    5561.05           2215.95        50  438.20           NaN   \n",
        "\n",
        "product     Laptop & iPad Skin  Mug  Onesie  Stationery Cards  \\\n",
        "date                                                            \n",
        "2013-01-01              773.75  NaN     NaN            127.08   \n",
        "2013-01-02              666.25  NaN     NaN             91.72   \n",
        "2013-01-03              742.50  NaN     NaN            356.08   \n",
        "2013-01-04              531.75  NaN     NaN            251.68   \n",
        "2013-01-05              730.50  NaN     NaN             91.60   \n",
        "\n",
        "product     Stretched Canvas  T-shirt  Throw Pillow  Tote Bag  Tote Bag (old)  \\\n",
        "date                                                                            \n",
        "2013-01-01           1186.38  1337.00       1491.54       NaN           127.8   \n",
        "2013-01-02           1008.32  1531.35       1915.55       NaN           155.1   \n",
        "2013-01-03            591.16  1404.60       1824.42       NaN           220.8   \n",
        "2013-01-04            779.87  1683.10       1710.44       NaN           252.8   \n",
        "2013-01-05            486.88  1366.00       1918.33       NaN           128.6   \n",
        "\n",
        "product     Unisex Tank Top  Wall Clock  iPad Case  iPhone & iPod Case  \\\n",
        "date                                                                     \n",
        "2013-01-01              NaN         NaN        NaN             11868.0   \n",
        "2013-01-02              NaN         NaN        NaN             15038.5   \n",
        "2013-01-03              NaN         NaN        NaN             13794.5   \n",
        "2013-01-04              NaN         NaN        NaN             12999.5   \n",
        "2013-01-05              NaN         NaN        NaN             11338.5   \n",
        "\n",
        "product     iPhone & iPod Skin  \n",
        "date                            \n",
        "2013-01-01              416.25  \n",
        "2013-01-02              499.50  \n",
        "2013-01-03              683.00  \n",
        "2013-01-04              573.50  \n",
        "2013-01-05              601.25  "
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Find the top 3 products\n",
      "There are a lot of products.  Use the `sum()` method of the `product_by_date` DataFrame to find total gross margin by product."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date.sum().order(ascending=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "product\n",
        "iPhone & iPod Case    4109925.00\n",
        "Art Print             3621201.30\n",
        "Throw Pillow          1642305.62\n",
        "Framed Art Print      1368167.02\n",
        "T-shirt               1150088.78\n",
        "Stretched Canvas       455008.65\n",
        "Mug                    281916.80\n",
        "Tote Bag               281639.20\n",
        "Laptop & iPad Skin     227714.00\n",
        "iPhone & iPod Skin     218467.25\n",
        "Hoody                  173869.68\n",
        "GiftCard               135163.30\n",
        "Stationery Cards       123254.33\n",
        "Tote Bag (old)          98802.60\n",
        "Unisex Tank Top         96848.68\n",
        "iPad Case               87429.00\n",
        "Kids T-Shirt            17716.68\n",
        "Wall Clock              17569.00\n",
        "Onesie                  16625.30\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Keep just the top 3 products\n",
      "Update the `product_by_date` DataFrame by setting it to just a subset of the columns, specified as a list of column names."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date = product_by_date[['iPhone & iPod Case', 'Art Print', 'Throw Pillow']]\n",
      "product_by_date.head()"
     ],
     "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>product</th>\n",
        "      <th>iPhone &amp; iPod Case</th>\n",
        "      <th>Art Print</th>\n",
        "      <th>Throw Pillow</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2013-01-01</th>\n",
        "      <td> 11868.0</td>\n",
        "      <td> 4695.89</td>\n",
        "      <td> 1491.54</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02</th>\n",
        "      <td> 15038.5</td>\n",
        "      <td> 6151.93</td>\n",
        "      <td> 1915.55</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-03</th>\n",
        "      <td> 13794.5</td>\n",
        "      <td> 6457.19</td>\n",
        "      <td> 1824.42</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-04</th>\n",
        "      <td> 12999.5</td>\n",
        "      <td> 6761.30</td>\n",
        "      <td> 1710.44</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-05</th>\n",
        "      <td> 11338.5</td>\n",
        "      <td> 5561.05</td>\n",
        "      <td> 1918.33</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "product     iPhone & iPod Case  Art Print  Throw Pillow\n",
        "date                                                   \n",
        "2013-01-01             11868.0    4695.89       1491.54\n",
        "2013-01-02             15038.5    6151.93       1915.55\n",
        "2013-01-03             13794.5    6457.19       1824.42\n",
        "2013-01-04             12999.5    6761.30       1710.44\n",
        "2013-01-05             11338.5    5561.05       1918.33"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Plot the gross margin for the top 3 products\n",
      "Use the [plot](http://pandas.pydata.org/pandas-docs/dev/visualization.html) method of the `product_by_date` DataFrame"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x108e335d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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TAAAAAADTEmckqm+7vnph+AsVPpefbRErp7r3yrsnaU8DAAAAAKACXM+tle1p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\nXgZ181Pbm3VmGC0hbNhA10O+fy+/bNWqLqxYAZjNnWhtBXp6u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0vHb5/FGSiqdFVIi0zz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\nMHUqK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nUms3GkgtrSpZwjW7WyfooeHMyI082bTV+3VZUU4Pzx0088rT91yrm2x8dzbXGH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\ntrZq7dq1OnjwYPZ6OBzO7hSKx+PZL9bXz33t4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       "text": [
        "<matplotlib.figure.Figure at 0x108e55190>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#If there's time\n",
      "##Pricing policies\n",
      "What is Society6's apparent pricing policy?  Is gross margin invariably a fixed share of revenue, or do, say, different products have different relative gross margins?  \n",
      "\n",
      "To take a first look, let's recreate the full `product_by_date` DataFrame from above"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "product_by_date = df2.groupby(level=['date', 'product']).sum()\n",
      "product_by_date.head()"
     ],
     "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>qty</th>\n",
        "      <th>rev</th>\n",
        "      <th>gm</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th>product</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th rowspan=\"5\" valign=\"top\">2013-01-01</th>\n",
        "      <th>Art Print</th>\n",
        "      <td> 240</td>\n",
        "      <td> 6694.74</td>\n",
        "      <td> 4695.89</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Framed Art Print</th>\n",
        "      <td>  95</td>\n",
        "      <td> 4775.50</td>\n",
        "      <td> 2684.55</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>GiftCard</th>\n",
        "      <td>   8</td>\n",
        "      <td>  500.00</td>\n",
        "      <td>  500.00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Hoody</th>\n",
        "      <td>  26</td>\n",
        "      <td> 1044.00</td>\n",
        "      <td>  346.55</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Laptop &amp; iPad Skin</th>\n",
        "      <td>  43</td>\n",
        "      <td> 1185.00</td>\n",
        "      <td>  773.75</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "                               qty      rev       gm\n",
        "date       product                                  \n",
        "2013-01-01 Art Print           240  6694.74  4695.89\n",
        "           Framed Art Print     95  4775.50  2684.55\n",
        "           GiftCard              8   500.00   500.00\n",
        "           Hoody                26  1044.00   346.55\n",
        "           Laptop & iPad Skin   43  1185.00   773.75"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, using [matplotlib.pyplot](http://matplotlib.org/api/pyplot_api.html)'s [scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) method, let's create a scatterplot of revenue vs. gross margin for each combination of day and product."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "plt.scatter(product_by_date.rev, product_by_date.gm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "<matplotlib.collections.PathCollection at 0x108e8d6d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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p/TjclClTcvbZZ6epqSmjRo3KyJEjkyTnnHNOxo0bl9ra2lRVVb1u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\nb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       "text": [
        "<matplotlib.figure.Figure at 0x108e24d10>"
       ]
      }
     ],
     "prompt_number": 13
    }
   ],
   "metadata": {}
  }
 ]
}