From 31efb770d8fdd5846a0b33aaff40cadbaf98f0d4 Mon Sep 17 00:00:00 2001
From: SorenOlegnowicz <soren.olegnowicz@gmail.com>
Date: Mon, 22 Jun 2015 00:27:23 -0400
Subject: [PATCH 1/4] First stab

---
 Data Analysis.ipynb | 1568 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 1568 insertions(+)
 create mode 100644 Data Analysis.ipynb

diff --git a/Data Analysis.ipynb b/Data Analysis.ipynb
new file mode 100644
index 0000000..0527488
--- /dev/null
+++ b/Data Analysis.ipynb	
@@ -0,0 +1,1568 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 409,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import re"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 410,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "% matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "datum = pd.read_csv('atusdata/atussum_2013.dat')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tucaseid</th>\n",
+       "      <th>TUFINLWGT</th>\n",
+       "      <th>TRYHHCHILD</th>\n",
+       "      <th>TEAGE</th>\n",
+       "      <th>TESEX</th>\n",
+       "      <th>PEEDUCA</th>\n",
+       "      <th>PTDTRACE</th>\n",
+       "      <th>PEHSPNON</th>\n",
+       "      <th>GTMETSTA</th>\n",
+       "      <th>TELFS</th>\n",
+       "      <th>...</th>\n",
+       "      <th>t181501</th>\n",
+       "      <th>t181599</th>\n",
+       "      <th>t181601</th>\n",
+       "      <th>t181801</th>\n",
+       "      <th>t189999</th>\n",
+       "      <th>t500101</th>\n",
+       "      <th>t500103</th>\n",
+       "      <th>t500105</th>\n",
+       "      <th>t500106</th>\n",
+       "      <th>t500107</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>20130101130004</td>\n",
+       "      <td>11899905.662034</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>2</td>\n",
+       "      <td>40</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>20130101130112</td>\n",
+       "      <td>4447638.009513</td>\n",
+       "      <td>1</td>\n",
+       "      <td>39</td>\n",
+       "      <td>1</td>\n",
+       "      <td>43</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>20130101130123</td>\n",
+       "      <td>10377056.507734</td>\n",
+       "      <td>-1</td>\n",
+       "      <td>47</td>\n",
+       "      <td>2</td>\n",
+       "      <td>40</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>25</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>20130101130611</td>\n",
+       "      <td>7731257.992805</td>\n",
+       "      <td>-1</td>\n",
+       "      <td>50</td>\n",
+       "      <td>2</td>\n",
+       "      <td>40</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>20130101130616</td>\n",
+       "      <td>4725269.227067</td>\n",
+       "      <td>-1</td>\n",
+       "      <td>45</td>\n",
+       "      <td>2</td>\n",
+       "      <td>40</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 413 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         tucaseid        TUFINLWGT  TRYHHCHILD  TEAGE  TESEX  PEEDUCA  \\\n",
+       "0  20130101130004  11899905.662034          12     22      2       40   \n",
+       "1  20130101130112   4447638.009513           1     39      1       43   \n",
+       "2  20130101130123  10377056.507734          -1     47      2       40   \n",
+       "3  20130101130611   7731257.992805          -1     50      2       40   \n",
+       "4  20130101130616   4725269.227067          -1     45      2       40   \n",
+       "\n",
+       "   PTDTRACE  PEHSPNON  GTMETSTA  TELFS   ...     t181501  t181599  t181601  \\\n",
+       "0         8         2         1      5   ...           0        0        0   \n",
+       "1         1         2         1      1   ...           0        0        0   \n",
+       "2         1         2         1      4   ...          25        0        0   \n",
+       "3         1         1         1      1   ...           0        0        0   \n",
+       "4         2         2         1      1   ...           0        0        0   \n",
+       "\n",
+       "   t181801  t189999  t500101  t500103  t500105  t500106  t500107  \n",
+       "0        0        0        0        0        0        0        0  \n",
+       "1        0        0        0        0        0        0        0  \n",
+       "2        0        0        0        0        0        0        0  \n",
+       "3        0        0        0        0        0        0        0  \n",
+       "4        0        0        0        0        0        0        0  \n",
+       "\n",
+       "[5 rows x 413 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datum.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##Pertinent columns:\n",
+    "###TUFINLWGT - statistical weight of respondent\n",
+    "###TRYHHCHILD - age of youngest child in household\n",
+    "###TEAGE - age of respondent\n",
+    "###TESEX - sex of respondent\n",
+    "###TELFS - working status of respondent\n",
+    "###TRCHILDNUM - number of children in household"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 408,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/sorenolegnowicz/cs/python/projects/atus-analysis/.direnv/python-3.4.3/lib/python3.4/site-packages/IPython/core/interactiveshell.py:3035: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
+      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
+     ]
+    }
+   ],
+   "source": [
+    "age = datum['TEAGE'].to_frame()\n",
+    "sexy_age = datum[['TEAGE', 'TESEX']]\n",
+    "master = datum[['TEAGE', 't010101', 'TESEX', 'TUFINLWGT','t050101', 't120303']]\n",
+    "master.TEAGE.update((master.TEAGE // 10) * 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on method plot_frame in module pandas.tools.plotting:\n",
+      "\n",
+      "plot_frame(x=None, y=None, kind='line', ax=None, subplots=False, sharex=None, sharey=False, layout=None, figsize=None, use_index=True, title=None, grid=None, legend=True, style=None, logx=False, logy=False, loglog=False, xticks=None, yticks=None, xlim=None, ylim=None, rot=None, fontsize=None, colormap=None, table=False, yerr=None, xerr=None, secondary_y=False, sort_columns=False, **kwds) method of pandas.core.frame.DataFrame instance\n",
+      "    Make plots of DataFrame using matplotlib / pylab.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "    data : DataFrame\n",
+      "    x : label or position, default None\n",
+      "    y : label or position, default None\n",
+      "        Allows plotting of one column versus another\n",
+      "    kind : str\n",
+      "        - 'line' : line plot (default)\n",
+      "        - 'bar' : vertical bar plot\n",
+      "        - 'barh' : horizontal bar plot\n",
+      "        - 'hist' : histogram\n",
+      "        - 'box' : boxplot\n",
+      "        - 'kde' : Kernel Density Estimation plot\n",
+      "        - 'density' : same as 'kde'\n",
+      "        - 'area' : area plot\n",
+      "        - 'pie' : pie plot\n",
+      "        - 'scatter' : scatter plot\n",
+      "        - 'hexbin' : hexbin plot\n",
+      "    ax : matplotlib axes object, default None\n",
+      "    subplots : boolean, default False\n",
+      "        Make separate subplots for each column\n",
+      "    sharex : boolean, default True if ax is None else False\n",
+      "        In case subplots=True, share x axis and set some x axis labels to\n",
+      "        invisible; defaults to True if ax is None otherwise False if an ax\n",
+      "        is passed in; Be aware, that passing in both an ax and sharex=True\n",
+      "        will alter all x axis labels for all axis in a figure!\n",
+      "    sharey : boolean, default False\n",
+      "        In case subplots=True, share y axis and set some y axis labels to\n",
+      "        invisible\n",
+      "    layout : tuple (optional)\n",
+      "        (rows, columns) for the layout of subplots\n",
+      "    figsize : a tuple (width, height) in inches\n",
+      "    use_index : boolean, default True\n",
+      "        Use index as ticks for x axis\n",
+      "    title : string\n",
+      "        Title to use for the plot\n",
+      "    grid : boolean, default None (matlab style default)\n",
+      "        Axis grid lines\n",
+      "    legend : False/True/'reverse'\n",
+      "        Place legend on axis subplots\n",
+      "    style : list or dict\n",
+      "        matplotlib line style per column\n",
+      "    logx : boolean, default False\n",
+      "        Use log scaling on x axis\n",
+      "    logy : boolean, default False\n",
+      "        Use log scaling on y axis\n",
+      "    loglog : boolean, default False\n",
+      "        Use log scaling on both x and y axes\n",
+      "    xticks : sequence\n",
+      "        Values to use for the xticks\n",
+      "    yticks : sequence\n",
+      "        Values to use for the yticks\n",
+      "    xlim : 2-tuple/list\n",
+      "    ylim : 2-tuple/list\n",
+      "    rot : int, default None\n",
+      "        Rotation for ticks (xticks for vertical, yticks for horizontal plots)\n",
+      "    fontsize : int, default None\n",
+      "        Font size for xticks and yticks\n",
+      "    colormap : str or matplotlib colormap object, default None\n",
+      "        Colormap to select colors from. If string, load colormap with that name\n",
+      "        from matplotlib.\n",
+      "    colorbar : boolean, optional\n",
+      "        If True, plot colorbar (only relevant for 'scatter' and 'hexbin' plots)\n",
+      "    position : float\n",
+      "        Specify relative alignments for bar plot layout.\n",
+      "        From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)\n",
+      "    layout : tuple (optional)\n",
+      "        (rows, columns) for the layout of the plot\n",
+      "    table : boolean, Series or DataFrame, default False\n",
+      "        If True, draw a table using the data in the DataFrame and the data will\n",
+      "        be transposed to meet matplotlib's default layout.\n",
+      "        If a Series or DataFrame is passed, use passed data to draw a table.\n",
+      "    yerr : DataFrame, Series, array-like, dict and str\n",
+      "        See :ref:`Plotting with Error Bars <visualization.errorbars>` for detail.\n",
+      "    xerr : same types as yerr.\n",
+      "    stacked : boolean, default False in line and\n",
+      "        bar plots, and True in area plot. If True, create stacked plot.\n",
+      "    sort_columns : boolean, default False\n",
+      "        Sort column names to determine plot ordering\n",
+      "    secondary_y : boolean or sequence, default False\n",
+      "        Whether to plot on the secondary y-axis\n",
+      "        If a list/tuple, which columns to plot on secondary y-axis\n",
+      "    mark_right : boolean, default True\n",
+      "        When using a secondary_y axis, automatically mark the column\n",
+      "        labels with \"(right)\" in the legend\n",
+      "    kwds : keywords\n",
+      "        Options to pass to matplotlib plotting method\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    axes : matplotlib.AxesSubplot or np.array of them\n",
+      "    \n",
+      "    Notes\n",
+      "    -----\n",
+      "    \n",
+      "    - See matplotlib documentation online for more on this subject\n",
+      "    - If `kind` = 'bar' or 'barh', you can specify relative alignments\n",
+      "      for bar plot layout by `position` keyword.\n",
+      "      From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)\n",
+      "    - If `kind` = 'scatter' and the argument `c` is the name of a dataframe\n",
+      "      column, the values of that column are used to color each point.\n",
+      "    - If `kind` = 'hexbin', you can control the size of the bins with the\n",
+      "      `gridsize` argument. By default, a histogram of the counts around each\n",
+      "      `(x, y)` point is computed. You can specify alternative aggregations\n",
+      "      by passing values to the `C` and `reduce_C_function` arguments.\n",
+      "      `C` specifies the value at each `(x, y)` point and `reduce_C_function`\n",
+      "      is a function of one argument that reduces all the values in a bin to\n",
+      "      a single number (e.g. `mean`, `max`, `sum`, `std`).\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(age.plot)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 243,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "520.779678623\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(average_minutes(agesleep, '010101'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x1232233c8>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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HJE/pe992wHPbff3ltgIO7Su3JfBi4PT2HrPSRPECf0nSYpith26PJBf2vd6l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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x1231f8470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "age_plot = age['TEAGE'].plot(kind='hist', bins=70, figsize=(10,8), \n",
+    "                             title='Ages of Respondents', fontsize=16, color='k')\n",
+    "age_plot.set_xlabel(\"AGE\")\n",
+    "age_plot.set_ylabel(\"Number of Respondents\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "female_age = sexy_age[sexy_age.TESEX == 2]\n",
+    "male_age = sexy_age[sexy_age.TESEX == 1]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 356,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total number of males: 5082\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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N2XUqaXH6RqZ1M4+TvGIxrzdKoFvUCUZwGrMsZwLsBvywHz83c9xBSdYMjaPb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\nDHSSJEmNM9BJkiQ1zkAnSZLUuP8P+a/LmvprLOkAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x11ee41d68>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"Total number of males: {}\".format(male_age.shape[0]))\n",
+    "male_plot = male_age['TEAGE'].plot(kind='hist', ylim=(0,250), bins=70, figsize=(10,8), \n",
+    "                                   title='Ages of Respondents', fontsize=16, color='b')\n",
+    "male_plot.set_xlabel(\"AGE\")\n",
+    "male_plot.set_ylabel(\"Number of Respondents\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total number of Females: 6303\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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e3Q7ADcAPh19AkjR/1vYEh7met7Zz4TzZQtNmtYFuHg5THgvsl+RxVXUyQJLN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\nJEmNM9BJkiQ1zkAnSZLUuP8PBY4qhGPqcC4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12a561080>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"Total number of Females: {}\".format(female_age.shape[0]))\n",
+    "female_plot = female_age['TEAGE'].plot(kind='hist', bins=70, figsize=(10,8), \n",
+    "                                       title='Ages of Respondents', fontsize=16, color='m')\n",
+    "female_plot.set_xlabel(\"AGE\")\n",
+    "female_plot.set_ylabel(\"Number of Respondents\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 237,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def average_minutes(data, activity_code):\n",
+    "    activity_col = \"t{}\".format(activity_code)\n",
+    "    data = data[['TUFINLWGT', activity_col]]\n",
+    "    data = data.rename(columns={\"TUFINLWGT\": \"weight\", activity_col: \"minutes\"})\n",
+    "    data['weighted_minutes'] = data.weight * data.minutes\n",
+    "    return data.weighted_minutes.sum() / data.weight.sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above function returns the weighted average."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 376,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def all_time(data, desire_name, desire_code, duty):\n",
+    "    data_group = data.groupby(duty)\n",
+    "    data_time = {i: average_minutes(k, desire_code) for i, k in data_group}\n",
+    "    data_df = pd.DataFrame(data_time, index=[desire_name])\n",
+    "    data_df = data_df.T\n",
+    "    return data_df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above function will return the averages of the given parts of a dataframe using '.groupby'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 329,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "master_group = master.groupby('TEAGE')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 382,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Sleep</th>\n",
+       "      <th>Work</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>572.874959</td>\n",
+       "      <td>51.847874</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>532.986603</td>\n",
+       "      <td>218.561638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>510.443990</td>\n",
+       "      <td>251.044129</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>512.147604</td>\n",
+       "      <td>247.786269</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>501.802848</td>\n",
+       "      <td>233.328555</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>507.882861</td>\n",
+       "      <td>128.834603</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>70</th>\n",
+       "      <td>520.346491</td>\n",
+       "      <td>37.429498</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>558.167498</td>\n",
+       "      <td>16.443226</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Sleep        Work\n",
+       "10  572.874959   51.847874\n",
+       "20  532.986603  218.561638\n",
+       "30  510.443990  251.044129\n",
+       "40  512.147604  247.786269\n",
+       "50  501.802848  233.328555\n",
+       "60  507.882861  128.834603\n",
+       "70  520.346491   37.429498\n",
+       "80  558.167498   16.443226"
+      ]
+     },
+     "execution_count": 382,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sleep_time = {i: average_minutes(k, '010101') for i, k in master_group}\n",
+    "work_time = {i: average_minutes(k, '050101') for i, k in master_group}\n",
+    "    \n",
+    "sleeper = all_time(master, 'Sleep', '010101', 'TEAGE')\n",
+    "worker = all_time(master, 'Work','050101', 'TEAGE')\n",
+    "sleep_work = sleeper.join(worker)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 375,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>10</th>\n",
+       "      <th>20</th>\n",
+       "      <th>30</th>\n",
+       "      <th>40</th>\n",
+       "      <th>50</th>\n",
+       "      <th>60</th>\n",
+       "      <th>70</th>\n",
+       "      <th>80</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>hello</th>\n",
+       "      <td>572.874959</td>\n",
+       "      <td>532.986603</td>\n",
+       "      <td>510.44399</td>\n",
+       "      <td>512.147604</td>\n",
+       "      <td>501.802848</td>\n",
+       "      <td>507.882861</td>\n",
+       "      <td>520.346491</td>\n",
+       "      <td>558.167498</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               10          20         30          40          50          60  \\\n",
+       "hello  572.874959  532.986603  510.44399  512.147604  501.802848  507.882861   \n",
+       "\n",
+       "               70          80  \n",
+       "hello  520.346491  558.167498  "
+      ]
+     },
+     "execution_count": 375,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sleep_df = pd.DataFrame(sleep_time, index=['sleep'])\n",
+    "work_df = pd.DataFrame(work_time, index=['work'])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 332,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "sleep_df = sleep_df.T\n",
+    "work_df = work_df.T"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "'sleep_df' is now equivalent to 'all_time(master, '010101', 'TEAGE')'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 387,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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YamuNUYCZjS07FN09Djna9joGuNZiPC1feLg4ZoHOz1fnUv4ap9ylUf7SKH9p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\n/w+Nef5vTfUATwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12cb52a20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "sleep_plot = sleeper.plot(figsize=(10,6), color='c', title=\"Time slept per Age\",\n",
+    "                               marker='o', markerfacecolor='b', markersize=3,\n",
+    "                               fontsize=16)\n",
+    "sleep_plot.set_xlabel(\"Age Group\")\n",
+    "sleep_plot.set_ylabel(\"Average Time Slept\")\n",
+    "sleep_plot.legend(['1 Year'])\n",
+    "sleep_plot.grid(axis='x',color='r')\n",
+    "#decades = [\"{}'s\".format(i) for i in range(10,81,10)]\n",
+    "#sleep_plot.set_xticks(range(10,81,10), decades)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 391,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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KXZ4W5y94eDhaPAA4K1pcsxpt0jv0+cuj/NXN0tnM0LTjubfmqqeZzUJahboZ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\ngg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12be50e80>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "work_plot = worker.plot(figsize=(10,6), color='m', title=\"Time Worked per Age\",\n",
+    "                               marker='o', markerfacecolor='k', markersize=3,\n",
+    "                               fontsize=16)\n",
+    "work_plot.set_xlabel(\"Age Group\")\n",
+    "work_plot.set_ylabel(\"Average Time Worked\")\n",
+    "work_plot.legend(['1 Year'])\n",
+    "work_plot.grid(axis='x',color='r')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above two plots suggest that Time worked is inversely proportional to Time slept."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 398,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x12d063400>"
+      ]
+     },
+     "execution_count": 398,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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cjp1tt5NkedfTlVW1co5ZJI2ZhB2ALwDnAn9fhfM6JfVNkqXA0jm/vmrmgaUk\nOwNnV9UenedHAdtX1RuS7AacX1X36ExoP4lmntUOwPnAfWrCmySpqspcQ0saXwn3pSlWHwDeVuXo\nuKSFNdveMuPIVZIVwH7AXZNcDbweOAE4obM8wy3AcwGqalWSU4BVwK3A0ROLlSTNVcJDgbOB11Rx\nQtt5JGkyPY1c9f1NHbmSNEsJjwVWAEdW8Zm280gaH7PtLa7QLmngJTyDZsrB0yxWkgad9xaUNNAS\njgZeAzyuiovbziNJM7FcSRpICaG5lc0RNIuD/rDlSJLUE8uVpIGTsCHwHppV1x9VxXUtR5Kknlmu\nJA2UhE2BTwB3o7kB869bjiRJs+KEdkkDI+FOwGeBDYHHW6wkDSPLlaSBkHA34ALgB8Azqri55UiS\nNCeWK0mtS9gZ+CrweeDFVdzWbiJJmjvLlaRWJewBfAV4XxWv83Y2koadE9oltSbhUTQ3gT+uipPa\nziNJ/WC5ktSKhIOAjwJHVPGFtvNIUr94WVDSokt4LvBh4CCLlaRR48iVpEWV8PfAMcCjq7i87TyS\n1G+WK0mLonM7m7cCB9Gsun51y5EkaUFYriQtuISNgA8B96e5T+AvW44kSQvGciVpQSVsBnwK2AR4\nTBW/azmSJC0oJ7RLWjAJWwPnAr8FDrZYSRoHlitJCyJhe+BLwLeA51RxS8uRJGlRWK4k9V3CrjS3\ns1lBs0DoupYjSdKicc6VpL5K+Cvg34HXV/HhtvNI0mKzXEnqm4T9gZOBo6o4o+08ktQGLwtK6ouE\nQ2mK1dMtVpLGmSNXkuYt4cXA64ADqrio7TyS1CbLlaQ566y6/lrg+cC+Vfyg3USS1D7LlaQ5SdgA\neA+wN83tbK5tOZIkDQTLlaRZS9gE+Dhwd2C/Kn7dciRJGhhOaJc0Kwlb0Cy1sCnw1xYrSfpLlitJ\nPUvYBvgi8BOaTwXe3HIkSRo4litJPUnYhWbV9fOBF1Vxa8uRJGkgWa4kTSth24R3Af8NvK+KV1dR\nbeeSpEFluZI0qYS7JrwFWNXZ9IAq3ttmJkkaBpYrSX8hYcuE5cD3gK2AB1fxMpdakKTeWK4kAZBw\nx4RXAVcCuwBLqnhxFVe3HE2ShorrXEljLuEOwFHA8cCXadaturzdVJI0vCxX0pjqLAT6Aprb13wb\nOLCKi9tNJUnDz3IljZmEDYFnA8tpLgE+rYoLWw0lSSPEciWNic69AA8F/gG4Hnh+FV9uN5UkjR7L\nlTTiEgJmCXmmAAAKV0lEQVQ8CXgj8EfgWOA816qSpIVhuZJGVKdUPQ54E819AF8HnG2pkqSFNeNS\nDElOSHJdkksn2ffyJOuS3KVr27IkVya5IskB/Q4saWYJ+wJfAt4DvB3Ys4qzLFaStPB6Wefqo8CB\nEzcm2Ynm/4p/3LVtd+AwYPfOa96fxLW0pEWSsCThC8DHgI8A/7OKU6pY124ySRofMxafqvoKcMMk\nu94BvHLCtkOAFVW1tqpWA1cBS+YbUtL0Eh6U8BngNOB04H5VnOjNlSVp8c1pVCnJIcCaqrpkwq7t\ngTVdz9cAO8wxm6QZJNwv4VPAOcAXgV2r+GAVt7QcTZLG1qzLVZLNgVcDb+jePM1LnOMh9VnCvRJO\npFlR/dvAfap4dxU3txxNksbeXD4teG9gZ+DiJAA7At9K8jDgp8BOXcfu2Nl2O0mWdz1dWVUr55BF\nGisJO9KsqH4o8P9oRqp+3W4qSRotSZYCS+f8+qqZB5aS7AycXVV7TLLvR8BDqupXnQntJ9HMs9oB\nOB+4T014kyRVVdONdknqkrAtsAx4DvAh4J+q+GW7qSRpPMy2t/SyFMMK4GvAbkmuTvKCCYf8qThV\n1SrgFGAV8Hng6InFSlLvEu6a8Baav1MAD6jieIuVJA2unkau+v6mjlxJ00rYEjgO+DvgVOD/VnF1\nu6kkaTz1feRK0uJJuGPCq2huqLwLsKSKF1usJGl4ePsbaQAk3AE4Cjie5hOA+1VxebupJElzYbmS\nWpSwCfACmk8Afhs4sIqL200lSZoPy5XUgoQNgWcDy2kuAT6tigtbDSVJ6gvLlbSIEjagWaPqH4Dr\ngedX8eV2U0mS+slyJS2ChABPAt4I/BE4FjivyjsYSNKosVxJC6hTqh4HvAnYFHgdcLalSpJGl+VK\nWiAJ+9KUqv8BvB44tYp17aaSJC00y5XUZwlLaC7/7Uozt+rfqri13VSSpMXiIqJSnyQ8KOEzwGnA\n6cD9qjjRYiVJ48VyJc1Twv0SPgWcA3wR2LWKD1ZxS8vRJEktsFxJc5Rwr4QTaVZU/zZwnyreXcXN\nLUeTJLXIciXNUsKOCf8CXAj8iGak6q1V/K7laJKkAWC5knqUsG3Cu4CLgRuB+1axvIpftxxNkjRA\nLFfSDBLumvAWYFVn0wOqOL6KX7aZS5I0mCxX0hQStkxYDnwP2Ap4cBUvq+LadpNJkgaZ5UqaIOGO\nCa+iuaHyLsCSKl5cxdUtR5MkDQEXEZU6Eu4AHAUcT/MJwP2quLzdVJKkYWO50thL2AR4AfBamiUV\nDqzi4nZTSZKGVWvlKmENcCuwdorfp9vXyzGL+nrvGTd8EjYEng0sp7kE+LQqLmw1lCRp6LU5cvVw\nYONOhom/T7ZtNsdsBGw2z9fP6v0T1rH45W6y3xdsXxU1xZ/lUEnYADiU5r5/1wPPr+LL7aaSJI2K\nVC3+v5dJqqqy6G+8QBJC8+GABS1w0/zez33TZbmNRShxC7zvgcD/Af5IcxnwvFEpjZKkhTHb3uKc\nqz7o/ON8W+fXSOoUyOkK30KUvs36+LXW/34d8DrgbEuVJGkhOHIlSZI0jdn2Fte5kiRJ6iPLlSRJ\nUh9ZriRJkvrIciVJktRHlitJkqQ+slxJkiT1keVKkiSpjyxXkiRJfWS5kiRJ6iPLlSRJUh9ZriRJ\nkvrIciVJktRHlitJkqQ+slxJkiT1keVKkiSpj2YsV0lOSHJdkku7tv1TksuTXJzk9CRbdu1bluTK\nJFckOWChgkuSJA2iXkauPgocOGHbucADqupBwPeBZQBJdgcOA3bvvOb9SRwd67MkS9vOMKw8d/Pj\n+Zsfz9/cee7mx/O3uGYsPlX1FeCGCdvOq6p1naffAHbsPD4EWFFVa6tqNXAVsKR/cdWxtO0AQ2xp\n2wGG3NK2Awy5pW0HGGJL2w4w5Ja2HWCc9GNU6YXA5zqPtwfWdO1bA+zQh/eQJEkaCvMqV0leA9xS\nVSdNc1jN5z0kSZKGSapm7j5JdgbOrqo9urY9H3gR8Jiqurmz7XiAqnpL5/k5wBuq6hsTvp6FS5Ik\nDY2qSq/HbjSXN0hyIPAKYL/1xarjLOCkJO+guRy4K3DhfAJKkiQNkxnLVZIVwH7ANkmuBt5A8+nA\nTYDzkgD8V1UdXVWrkpwCrAJuBY6uXobGJEmSRkRPlwUlSZLUmwVdg2qKBUjvkuS8JN9Pcm6SrRYy\nwzBLslOSC5JcluS7SY7pbPcc9iDJHZJ8I8lFSVYleXNnu+evR0k2TPKdJGd3nnvuepRkdZJLOufv\nws42z1+PkmyV5NTOgtWrkjzM89ebJPft/Nyt//XrJMd4/nrTWQz9siSXJjkpyaazPXcLvcDnZAuQ\nHg+cV1W7Af/Rea7JrQWOq6oHAA8HXpLk/ngOe9KZD/joqnow8EDg0Un2xvM3G8fSXOZfP8Ttuetd\nAUuras+qWr/en+evd+8GPldV96f5+3sFnr+eVNX3Oj93ewIPAX4PnIHnb0adD/C9CPirzof4NgSe\nyWzPXVUt6C9gZ+DSrudXANt2Hm8HXLHQGUblF3Am8FjP4ZzO3ebAN4EHeP56Pmc7AucDj6b5tLB/\nf2d3/n4E3HXCNs9fb+duS+CHk2z3/M3+XB4AfMXz1/P5ugvwPWBrmnnpZwOPm+25a+PWNNtW1XWd\nx9cB27aQYeh02vSeNCview57lGSDJBfRnKcLquoyPH+9eifNp4LXdW3z3PWugPOT/HeSF3W2ef56\nswtwfZKPJvl2kg8luSOev7l4JrCi89jzN4Oq+hXwz8BPgGuAG6vqPGZ57lq97181FdAZ9TNIsgVw\nGnBsVf22e5/ncHpVta6ay4I7AvsmefSE/Z6/SSQ5CPh5VX0HmHTpFM/djB5VzWWZx9Nc0t+ne6fn\nb1obAX8FvL+q/gr4HRMuw3j+ZpZkE+BJwKcn7vP8TS7JvYGX0Vx12x7YIskR3cf0cu7aKFfXJdkO\nIMndgZ+3kGFoJNmYplh9oqrO7Gz2HM5SVf0a+CzN/APP38weCRyc5Ec0/9e7f5JP4LnrWVX9rPP7\n9TTzXZbg+evVGmBNVX2z8/xUmrJ1redvVh4PfKvzMwj+/PXiocDXquqXVXUrcDrwCGb5s9dGuToL\neF7n8fNo5hFpEmkWEfsIsKqq3tW1y3PYgyTbrP9ER5LNaK6bfwfP34yq6tVVtVNV7UJzWeGLVfUc\nPHc9SbJ5kjt1Ht+RZt7LpXj+elJV1wJXJ9mts+mxwGU08188f707nD9fEgR//npxBfDwJJt1/g1+\nLM2Hemb1s7eg61ylawFSmmuUrwc+A5wC3ANYDTyjqm5csBBDrPPJti8Dl/DnIchlNKveew5nkGQP\n4ESa/4nYgGb075+S3AXPX8+S7Ae8vKoO9tz1JskuNKNV0Fzi+reqerPnr3dJHgR8mGbB6h8AL6D5\n5JbnrwedUv9jYJf100n8+etNklfSFKh1wLeBI4E7MYtz5yKikiRJfdTqhHZJkqRRY7mSJEnqI8uV\nJElSH1muJEmS+shyJUmS1EeWK0mSpD6yXEmSJPWR5UqSJKmP/j/bCegYYcwiNwAAAABJRU5ErkJg\ngg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12c3b5668>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "watcher = all_time(master, 'Televisioning', '120303', 'TEAGE')\n",
+    "watcher.plot(figsize=(10,6))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Televsion usage increases with age. Why?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 403,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def activity_columns(data, activity_code):\n",
+    "    col_prefix = \"t{}\".format(activity_code)\n",
+    "    return [column for column in data.columns if re.match(col_prefix, column)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 411,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "exercise_list = datum[activity_columns(datum, '1301')]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 440,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          0\n",
+       "1          0\n",
+       "2        260\n",
+       "3          0\n",
+       "4         60\n",
+       "5          0\n",
+       "6          0\n",
+       "7          0\n",
+       "8          0\n",
+       "9          0\n",
+       "10         0\n",
+       "11         0\n",
+       "12         0\n",
+       "13         0\n",
+       "14         0\n",
+       "15         0\n",
+       "16         0\n",
+       "17         0\n",
+       "18        60\n",
+       "19         0\n",
+       "20        30\n",
+       "21         0\n",
+       "22         0\n",
+       "23         0\n",
+       "24         0\n",
+       "25       120\n",
+       "26         0\n",
+       "27         0\n",
+       "28         0\n",
+       "29         0\n",
+       "        ... \n",
+       "11355    315\n",
+       "11356     30\n",
+       "11357      0\n",
+       "11358      0\n",
+       "11359      0\n",
+       "11360      0\n",
+       "11361      0\n",
+       "11362      0\n",
+       "11363      0\n",
+       "11364      0\n",
+       "11365      0\n",
+       "11366      0\n",
+       "11367      0\n",
+       "11368      0\n",
+       "11369      0\n",
+       "11370      0\n",
+       "11371      0\n",
+       "11372      0\n",
+       "11373      0\n",
+       "11374      0\n",
+       "11375      0\n",
+       "11376      0\n",
+       "11377      0\n",
+       "11378      0\n",
+       "11379      0\n",
+       "11380      0\n",
+       "11381      0\n",
+       "11382      0\n",
+       "11383      0\n",
+       "11384      0\n",
+       "Name: exercise, dtype: float64"
+      ]
+     },
+     "execution_count": 440,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "e_df = exercise_list.sum(axis=1).to_frame(name='exercise')\n",
+    "deef = master.append(e_df)\n",
+    "derf = deef.exercise.dropna()\n",
+    "derf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 432,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "doop = master.groupby('TEAGE')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 434,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "39        10      610      1   7325390.733778        0      330\n",
+      "49        10      480      1  17284603.689761        0      165\n",
+      "61        10      450      2  23220400.569550        0      125\n",
+      "88        10      480      1  13186606.269365        0        0\n",
+      "95        10      465      2  23498429.630321        0        0\n",
+      "126       10      520      2   5111724.936207        0      385\n",
+      "127       10      555      1  18246566.290865        0        0\n",
+      "136       10      455      2  26050136.903249        0      120\n",
+      "156       10      470      1  12032854.019376      409      200\n",
+      "168       10      690      1   9776548.777139        0      570\n",
+      "176       10      810      2  12258183.437851        0      590\n",
+      "182       10      645      2  14853183.882684        0       60\n",
+      "188       10      600      1   7930671.840137        0        0\n",
+      "192       10      590      1  15331577.262264        0       60\n",
+      "220       10      810      1   3747644.368693        0        0\n",
+      "284       10      632      1   8322956.232154        0        0\n",
+      "291       10      450      2  21332472.568844        0        0\n",
+      "309       10      525      2  21219988.363132        0        0\n",
+      "400       10      570      2  13160459.620726        0       20\n",
+      "419       10      660      2   6502054.294583        0      120\n",
+      "427       10      730      1  13157528.323440      300       30\n",
+      "432       10      840      2   3768668.700901        0       60\n",
+      "496       10      474      2   3507471.522710        0       90\n",
+      "505       10      560      2   3603916.045809      300      120\n",
+      "509       10      715      1  20356012.578093        0      180\n",
+      "541       10      630      1  18799348.384743        0       30\n",
+      "578       10      780      1  12191930.254770        0      210\n",
+      "606       10      710      2   4665918.270500        0        0\n",
+      "612       10      636      2   5037604.070669        0        0\n",
+      "630       10      720      1  24041924.750143        0      307\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "10796     10      490      2  18209729.433285        0        0\n",
+      "10801     10      765      1   4875879.589655        0      650\n",
+      "10833     10      390      2  26144413.637180        0      150\n",
+      "10883     10      660      2  35667226.493369        0      180\n",
+      "10922     10      540      2   4545756.211734        0        0\n",
+      "10930     10      760      2   9885479.091282        0       60\n",
+      "10949     10      540      2  35448170.998971        0       60\n",
+      "10976     10      420      1   3421902.779792        0       90\n",
+      "11006     10      480      2  33307622.668722        0      350\n",
+      "11015     10      395      1   8129213.691383      550       65\n",
+      "11017     10      428      1  13705057.110350        0        0\n",
+      "11034     10      750      1   6600534.628853        0        0\n",
+      "11037     10     1015      1   3179278.177192        0        0\n",
+      "11040     10      540      1  14029146.125332        0      246\n",
+      "11046     10      660      1   8302324.206821      550        0\n",
+      "11066     10      845      2  27830450.004867        0       45\n",
+      "11089     10      480      2  29061771.051207        0       40\n",
+      "11112     10      660      1   6980159.305555        0       90\n",
+      "11131     10      540      1   7466666.661487        0      160\n",
+      "11143     10      750      1   7656954.649078        0        0\n",
+      "11146     10      370      2  24711609.273728        0       90\n",
+      "11165     10      458      1   9101434.668713        0      210\n",
+      "11212     10      630      2  10176221.842711        0      135\n",
+      "11263     10      720      1   6242106.101312        0       60\n",
+      "11277     10      780      2  11219480.404516        0       90\n",
+      "11281     10      825      1   6900488.424996        0      240\n",
+      "11299     10      930      1  33045801.921894        0       60\n",
+      "11305     10      420      1  10161375.748248      406      105\n",
+      "11336     10      750      1   3124126.590468        0      190\n",
+      "11337     10      660      1   5424512.023010        0        0\n",
+      "\n",
+      "[630 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "0         20      540      2  11899905.662034        0      330\n",
+      "9         20      520      2   3905483.253032      450        0\n",
+      "22        20      540      1   5767745.700187      470        0\n",
+      "28        20      150      2   7823574.493908        0      240\n",
+      "48        20      195      1  47558174.916715      535       75\n",
+      "69        20      520      1   7610347.321442      650       50\n",
+      "72        20      750      2   2475227.649477        0       30\n",
+      "80        20      390      2   2902362.038320        0      165\n",
+      "97        20      490      2  10406697.968610      494       60\n",
+      "113       20      615      1  22263548.185123      440      195\n",
+      "118       20      420      1  25569487.580622      680      200\n",
+      "132       20      600      1  10024101.613130        0      497\n",
+      "140       20      480      2  15446029.125408      558      218\n",
+      "142       20      390      2  16793383.462384      635       90\n",
+      "163       20      240      1  13507907.871520      436      120\n",
+      "170       20      660      1   5395994.974214        0      180\n",
+      "178       20      575      2  28729454.031678      435      120\n",
+      "181       20      540      2   4446148.674191      270      270\n",
+      "185       20      715      2  31396108.581758        0      150\n",
+      "186       20      390      1   6934967.010339      500      185\n",
+      "194       20      660      1  15650915.300098        0      280\n",
+      "210       20      570      2   4977342.447970        0       50\n",
+      "242       20      510      2   9450898.245420        0      120\n",
+      "247       20      420      2   1929271.112057        0       90\n",
+      "249       20      690      2   2596206.638998        0        0\n",
+      "250       20      465      2  12400702.893819        0       90\n",
+      "257       20      505      2   5717246.257594      660        0\n",
+      "267       20      645      1   8206748.617891      300       45\n",
+      "271       20      600      1  13356790.759873        0      320\n",
+      "277       20      465      1  49531689.248070      525        0\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11081     20      495      2  21051663.239670      600        0\n",
+      "11082     20      894      1   4498295.055811        0       90\n",
+      "11086     20      630      2  27329574.632137      430      180\n",
+      "11104     20      715      1  13382246.454755        0      420\n",
+      "11108     20      695      1  19105527.989516      120        0\n",
+      "11113     20      720      1   8596232.621229      300        0\n",
+      "11117     20      585      2   5864959.847693      489        0\n",
+      "11118     20      315      1   4095785.607304        0        0\n",
+      "11125     20      310      1  49960437.222844        0      105\n",
+      "11161     20      295      1  32070013.095155      500      180\n",
+      "11166     20      452      1  13960000.231074      466      195\n",
+      "11180     20      450      2  52632328.828751        0      411\n",
+      "11181     20      595      1   5782659.310700        0      180\n",
+      "11194     20      540      2  35060245.775690      225       60\n",
+      "11214     20      510      1   2192707.928641        0      240\n",
+      "11226     20      930      1   7322035.974241        0      360\n",
+      "11237     20      599      2   4436344.008165        0      188\n",
+      "11243     20      570      2   2143529.961279        0      143\n",
+      "11246     20      450      1   7706183.754778      540        0\n",
+      "11247     20      690      1   7217195.241209      510        0\n",
+      "11266     20      600      1   4197057.643162        0      300\n",
+      "11285     20      640      1  11597353.199992        0      178\n",
+      "11287     20      630      2   7936784.277661      310      125\n",
+      "11306     20      310      1  44748973.969384        0        0\n",
+      "11314     20      545      2   3302644.755483       20      120\n",
+      "11319     20      427      2   3705680.234096      794        0\n",
+      "11335     20      420      1  32218669.402973      435        0\n",
+      "11348     20      510      2  25858850.521863        0        0\n",
+      "11360     20      500      2   9075032.448859        0       60\n",
+      "11368     20      435      2   6753944.494461      483      180\n",
+      "\n",
+      "[1227 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "1         30      580      1   4447638.009513        0       95\n",
+      "11        30      500      1   6755514.216327      520       60\n",
+      "20        30      680      2   1102916.898147        0        0\n",
+      "36        30      427      2  12247497.817496      417      120\n",
+      "44        30      495      2  17663714.149234      425       60\n",
+      "52        30      600      2   2545139.512357        0      172\n",
+      "60        30      480      2   6824541.014325      420      195\n",
+      "62        30      585      1   7766675.451508        0       88\n",
+      "67        30      550      2   3292976.630328       90       30\n",
+      "73        30      599      2   2077845.156239        0       24\n",
+      "79        30      385      1   2292542.682742      310        0\n",
+      "84        30      571      2  10195964.532553        0        0\n",
+      "85        30      400      1   7411953.861404      505      110\n",
+      "91        30      515      1  19579904.656459      555       30\n",
+      "93        30      360      1  19702245.941487        0      360\n",
+      "99        30      210      1   7828544.773423      795      210\n",
+      "102       30      660      2   2010358.767744      685        0\n",
+      "111       30      960      2  12080068.852012        0      400\n",
+      "115       30      510      1   3171595.802118        0       60\n",
+      "116       30      420      2  13243599.712815      480        0\n",
+      "117       30      580      1   9195857.630884       10      410\n",
+      "121       30      390      1   2932486.383661        0      298\n",
+      "123       30      480      1   2578796.440520        0      620\n",
+      "124       30      450      2  11864076.858080      486      229\n",
+      "133       30      600      2   3044119.177159        0      555\n",
+      "148       30      360      2   3290041.071775        0      265\n",
+      "152       30      510      2   7354890.565325        0      183\n",
+      "164       30      520      1  21645455.510258      465      100\n",
+      "165       30      578      2  19880864.002577      493       90\n",
+      "166       30      420      2   2329178.869577      755       20\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11217     30      480      1   3029264.490944      540        0\n",
+      "11221     30      510      2   2678242.860944        0        0\n",
+      "11222     30      360      1   2783248.883993      710       60\n",
+      "11224     30      490      2   3954988.563090        0        0\n",
+      "11240     30      420      1  12925321.152796      495      180\n",
+      "11248     30      384      1   6033256.735098        0      544\n",
+      "11250     30      510      1   4135572.525678        0      389\n",
+      "11252     30      585      1  21980509.138592      660        0\n",
+      "11253     30      575      1   2551214.599892        0      603\n",
+      "11257     30      445      1   7834085.666400      450        0\n",
+      "11262     30      480      2   1985563.638093        0      200\n",
+      "11274     30      450      2   8401493.274954        0        0\n",
+      "11276     30      675      2   3633735.472181        0      120\n",
+      "11280     30      760      1  21373128.933256        0       90\n",
+      "11283     30      660      2   5817911.706809        0        0\n",
+      "11293     30      554      2   2355872.045471      105        0\n",
+      "11295     30      720      1   3264654.964583        0      120\n",
+      "11297     30      725      2   2286079.651766        0      180\n",
+      "11307     30      660      1   6455713.879513        0      415\n",
+      "11316     30       95      2   4434448.973399        0       60\n",
+      "11323     30      660      1  11670465.506146        0      490\n",
+      "11329     30      390      2   2691814.008463      575       90\n",
+      "11330     30      450      1   6319173.000529      475      413\n",
+      "11339     30      360      2   4338027.600369        0       60\n",
+      "11342     30      660      1   5920576.231175        0        0\n",
+      "11346     30      420      2   2309394.161367        0      118\n",
+      "11361     30      540      1  26070055.668273        0      175\n",
+      "11363     30      810      1   1661291.183740        0      400\n",
+      "11371     30      444      2   8820012.063839      480       60\n",
+      "11374     30      660      1   7697603.816560      400      180\n",
+      "\n",
+      "[2135 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "2         40      450      2  10377056.507734        0       60\n",
+      "4         40      570      2   4725269.227067        0       90\n",
+      "13        40      480      2   5521732.162587      505       15\n",
+      "16        40      450      1   6884215.057542      490       70\n",
+      "19        40      405      2  12301142.559951        0      120\n",
+      "25        40      528      1   3157926.871281        0        0\n",
+      "29        40      420      2   9061749.751818      282       90\n",
+      "31        40      480      1  17897951.662710        0      287\n",
+      "34        40     1108      1   9872318.115406        0      268\n",
+      "45        40      500      1   2630800.468761      490       20\n",
+      "46        40      570      2   2037394.470956        0      288\n",
+      "50        40      755      1   7487792.888126        0      268\n",
+      "70        40      387      2   7791711.857311      465       60\n",
+      "77        40      600      2  10954496.632411       20      165\n",
+      "78        40      600      2   6052110.766297      495       30\n",
+      "86        40     1005      2   6118133.026524        0        0\n",
+      "89        40      570      1  10610185.315550        0      550\n",
+      "90        40      395      1   4479189.671498      615       80\n",
+      "98        40      540      1  13367259.660653      465      225\n",
+      "110       40      750      1   3097491.070263       10      270\n",
+      "129       40      615      2   3161004.079121        0        0\n",
+      "130       40      555      1   7108775.747053      425       50\n",
+      "131       40      420      1   6405218.894362      760       60\n",
+      "135       40      450      1   7691516.119898      772      120\n",
+      "137       40      420      1   3571102.552099        0      150\n",
+      "144       40      500      1   7595798.145121      520      120\n",
+      "146       40      530      2   8502848.723099        0        0\n",
+      "147       40      450      1   6047088.987427      683        0\n",
+      "154       40      510      2   1591781.156326        0        0\n",
+      "158       40      725      1  12007283.051748      380      240\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11265     40      540      1  15695072.236362        0      690\n",
+      "11269     40      600      2   1311156.259538       10      144\n",
+      "11279     40      500      1  30008989.260705        0       80\n",
+      "11284     40      540      1  10623228.616852        0      520\n",
+      "11288     40      555      2   6316426.665632        0      275\n",
+      "11290     40      610      1   5979163.598864        0      289\n",
+      "11291     40      510      2   4165611.110828        0      385\n",
+      "11302     40      510      1   7265481.594943        0      120\n",
+      "11303     40      690      1   2396136.831248        0      130\n",
+      "11308     40      545      2   3393501.331304        0       60\n",
+      "11315     40      575      2   1191105.800719       80       90\n",
+      "11320     40      550      1   5384630.528194      495       75\n",
+      "11322     40      530      1   4032736.345657        0      330\n",
+      "11326     40      490      2   3940579.188645        0       85\n",
+      "11328     40      420      2   8123410.202165        0       60\n",
+      "11334     40      585      1   5985504.301408        0       15\n",
+      "11338     40      600      2   3509393.995749        0       30\n",
+      "11345     40      612      2   2920871.517947        0       40\n",
+      "11351     40      595      1   3726657.058047        0      520\n",
+      "11352     40      499      2   8661395.066959        0        0\n",
+      "11357     40      660      2  17993815.969566        0      240\n",
+      "11358     40      493      1  10952198.773372      343        0\n",
+      "11362     40      953      2   4479526.683095      180        0\n",
+      "11365     40      370      2  29229820.168242        0        0\n",
+      "11375     40      360      2   7045546.574380      480        0\n",
+      "11376     40      505      1   3404156.995949       45      120\n",
+      "11379     40      620      2   4844414.703530        0      205\n",
+      "11382     40      645      1  23557969.110158      550        0\n",
+      "11383     40      510      1  20450051.675501        0       60\n",
+      "11384     40      385      1   3397480.288114        0      330\n",
+      "\n",
+      "[2070 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "3         50      450      2   7731257.992805      680       65\n",
+      "7         50      480      2   8608413.296903        0       90\n",
+      "8         50      930      2   1378191.194810        0      270\n",
+      "10        50      210      2   4538371.462244      540      283\n",
+      "12        50      650      1  13506297.294756        0      300\n",
+      "17        50      420      1  12569148.198194        0      660\n",
+      "18        50      300      2  14226152.054254      725       75\n",
+      "21        50      467      2   8128107.650758      265      105\n",
+      "23        50      520      2   9474271.417876        0       60\n",
+      "24        50      160      1   5960041.143926     1006        0\n",
+      "26        50      720      2   3359410.785590        0      360\n",
+      "33        50      450      2   5114237.704143      520        0\n",
+      "41        50      545      1   5672688.960360      475        0\n",
+      "42        50      860      2   4899964.175715        0      420\n",
+      "43        50      530      2   4179351.731196       30      230\n",
+      "56        50      540      1  14395170.154470        0      250\n",
+      "59        50      460      2   3899112.240048        0       90\n",
+      "63        50      420      1   4336329.296802      485      250\n",
+      "64        50      540      1   5507709.637792        0      275\n",
+      "65        50      165      2   4745076.033227      450        0\n",
+      "66        50      480      1   4780823.505048      450        0\n",
+      "71        50      470      2  17861075.311170      510      120\n",
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+      "105       50      560      1  14855319.048947      603       90\n",
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+      "120       50      510      1   4455799.336535      625       70\n",
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+      "134       50      390      2  14588052.810768      390      133\n",
+      "138       50      309      1   8269284.626159      705      200\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11175     50      420      1   5032572.030719      505      360\n",
+      "11184     50      480      1  23215583.129806        0      481\n",
+      "11185     50      540      2  21408342.414632        0      220\n",
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+      "11193     50      600      1   2539190.698246      120       60\n",
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+      "11202     50      360      2   6761594.139816      510      160\n",
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+      "11209     50      460      1  10246257.497062      660      120\n",
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+      "11378     50      480      1   7548528.958862        0      370\n",
+      "\n",
+      "[2038 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "14        60      615      1  11791654.393174        0      397\n",
+      "15        60      720      2   1801834.050978        0      130\n",
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+      "153       60      585      2   1026591.267310        0       60\n",
+      "167       60      480      1   8827580.302387      180      190\n",
+      "206       60      570      2   1495682.392854        0      447\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11201     60      635      2   1779890.726839        0        0\n",
+      "11215     60      450      2   5906807.899208        0      370\n",
+      "11216     60      445      2  11288680.932262      485        0\n",
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+      "11289     60      480      1   3165217.163949        0      637\n",
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+      "11301     60      625      2   4718692.834607        0      210\n",
+      "11304     60      565      1   1784286.956725        0      380\n",
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+      "11317     60      590      2   8762629.471153        0      152\n",
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+      "11321     60      450      1   6525607.772974        0      510\n",
+      "11331     60      720      2   3731145.590155        0      325\n",
+      "11332     60      815      1   2529983.509041        0       60\n",
+      "11353     60      450      1   4796588.887839        0      565\n",
+      "11354     60      459      2   1620251.749429        0      120\n",
+      "11359     60      510      1  10969610.362669      190      175\n",
+      "11370     60      480      2   4681607.563005      495       90\n",
+      "11373     60      450      1   6454041.312322        0      406\n",
+      "11381     60      455      1   4103676.895062      445        0\n",
+      "\n",
+      "[1719 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "6         70      290      1   5671341.270490        0      244\n",
+      "32        70      510      1   9339822.293071        0      435\n",
+      "38        70      555      1   4281464.665852        0      167\n",
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+      "47        70      450      1   7351319.132975        0      125\n",
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+      "101       70      570      1  10599708.349245        0      300\n",
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+      "162       70      480      1   5745654.098933      900        0\n",
+      "179       70      780      2   8604987.493600        0      180\n",
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+      "190       70      720      1   3914537.546553        0      580\n",
+      "199       70      615      2   5858104.695494        0      200\n",
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+      "208       70      495      2   6098490.933292        0       45\n",
+      "221       70      720      1   4071770.199139        0      225\n",
+      "233       70      784      1   1827420.031506        0      115\n",
+      "236       70      650      1   3616078.174585        0      180\n",
+      "237       70      450      2  13862088.362812        0      550\n",
+      "255       70      420      1  14049868.701988      285        0\n",
+      "260       70      540      2   1810049.688378        0      250\n",
+      "269       70      705      2   7175918.642034        0       60\n",
+      "320       70      600      1   6570729.327039        0      555\n",
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+      "349       70      510      1  10841672.060961        0      390\n",
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+      "372       70      480      1   3560186.962625        0      300\n",
+      "388       70      380      2   7035922.172183        0      210\n",
+      "389       70      510      2   9819799.461568        0       30\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "11064     70      480      2   6357041.783741        0      210\n",
+      "11065     70      420      2   6262770.278938        0       30\n",
+      "11073     70      300      1  13362800.811477        0      924\n",
+      "11078     70      540      2   6028236.406986        0      582\n",
+      "11100     70      560      1   1699946.003948        0      180\n",
+      "11103     70      450      2   4030223.088018      285       60\n",
+      "11109     70      575      2   2452262.758356      610        0\n",
+      "11111     70      300      1   2601328.326493        0      960\n",
+      "11121     70      600      2   3475303.399063        0      504\n",
+      "11129     70      500      2  14650091.205261        0       60\n",
+      "11148     70      480      1   5972292.674713      610      220\n",
+      "11155     70      540      2  16265794.894820      450        0\n",
+      "11186     70      335      1   5914189.513436        0      700\n",
+      "11196     70      465      2   5805688.661820      534      138\n",
+      "11200     70      510      1   4647609.775592        0      540\n",
+      "11210     70      540      1  13351528.691465        0      715\n",
+      "11218     70      570      1   6289319.793169        0        0\n",
+      "11239     70      630      2  12737048.679523        0        0\n",
+      "11245     70      495      1  10017639.876671        0      190\n",
+      "11255     70      677      2  12987380.212853        0      151\n",
+      "11259     70      620      1   7603251.331595       15        0\n",
+      "11286     70      600      1   6861733.718310        0      400\n",
+      "11294     70      510      2   6115763.610236        0       60\n",
+      "11300     70      540      2   6186658.115273        0       60\n",
+      "11324     70       60      2   3968824.922564        0       60\n",
+      "11325     70      540      1   4601634.758350        0      180\n",
+      "11341     70      510      2   1269938.571212        0      894\n",
+      "11343     70      630      1  32120635.161945        0      635\n",
+      "11347     70      570      1   3833098.981090        0      215\n",
+      "11366     70      545      1   2709393.926463        0      240\n",
+      "\n",
+      "[954 rows x 6 columns]\n",
+      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
+      "5         80      495      2   2372791.046351        0      270\n",
+      "27        80      510      2  17547816.572228        0      120\n",
+      "57        80      600      2   4735832.929302        0      240\n",
+      "106       80      360      2   2017395.251175        0        0\n",
+      "114       80      600      2   1672799.901193        0      490\n",
+      "128       80      660      2   1532346.930362        0      180\n",
+      "145       80      810      1  13262141.925633        0      120\n",
+      "289       80      510      2   6680427.198486        0      185\n",
+      "321       80      705      2   6006887.538735        0      165\n",
+      "333       80      330      2   1753266.894347      120      453\n",
+      "347       80      555      2  13167868.213048        0      260\n",
+      "352       80      550      2   2224067.836660        0      180\n",
+      "373       80      600      1  11156497.509749        0      165\n",
+      "376       80      525      2   7150043.663756        0      160\n",
+      "392       80      440      1   1797810.655993        0      335\n",
+      "393       80      541      2  16151260.939039        0      329\n",
+      "395       80      650      2   2016538.534295        0       45\n",
+      "421       80      540      1   4552627.002899      245      165\n",
+      "461       80      540      2   8002205.042858        0      240\n",
+      "468       80      470      1   1774410.834063      240       15\n",
+      "508       80      420      2   2272978.671553        0        0\n",
+      "519       80      570      2  15649036.558960        0      390\n",
+      "525       80      450      2   7926611.511046        0        0\n",
+      "528       80      510      2   5590727.095603        0      115\n",
+      "532       80      467      1   1833186.987661        0      240\n",
+      "543       80      540      1   1912086.105907        0      675\n",
+      "565       80      540      1   4820263.194324        0      120\n",
+      "618       80      540      2   4834649.166287        0      875\n",
+      "625       80      470      2   6381826.183586        0      190\n",
+      "711       80      720      2   6503836.965754        0      125\n",
+      "...      ...      ...    ...              ...      ...      ...\n",
+      "10908     80      450      2   3669160.142743        0      265\n",
+      "10946     80      540      2   1540997.446387        0      165\n",
+      "10967     80      720      1   5158938.664079        0      585\n",
+      "10968     80      540      1   7379338.236892        0       30\n",
+      "11022     80      630      2   3132975.049378        0        0\n",
+      "11030     80      700      1   7712442.882288        0      480\n",
+      "11033     80      506      1   5940063.907671        0       60\n",
+      "11042     80      510      1  12765353.852847        0      280\n",
+      "11099     80      810      2  11340505.719801        0       60\n",
+      "11101     80      585      1   2452363.918235        0      747\n",
+      "11122     80      540      2   1387725.018450        0        0\n",
+      "11124     80      780      1   2911306.663617        0      490\n",
+      "11142     80      480      2   4249868.979466      165      120\n",
+      "11167     80      450      2   6911348.142600        0      551\n",
+      "11198     80      560      2   3956966.489327        0        0\n",
+      "11207     80      375      2  16018203.380493        0      355\n",
+      "11227     80      420      2   3185870.710368        0      150\n",
+      "11231     80      660      1  13157418.855151        0      120\n",
+      "11235     80      810      2   6365190.049790        0      600\n",
+      "11251     80      655      1   3105983.861132        0      233\n",
+      "11258     80      510      2   3869762.971403        0        0\n",
+      "11270     80      720      1   5511908.806864        0      685\n",
+      "11278     80      510      2   4241514.318240        0      324\n",
+      "11333     80      630      2   3246491.188202        0      340\n",
+      "11340     80      640      2   2755542.631494        0      140\n",
+      "11344     80      560      1  18136091.705952        0        0\n",
+      "11350     80      520      2   6586072.883651        0      285\n",
+      "11367     80      530      2   4417006.113982        0       90\n",
+      "11369     80      700      1   3799315.033354        0      410\n",
+      "11380     80      450      2   4469643.600730        0      480\n",
+      "\n",
+      "[612 rows x 6 columns]\n"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.4.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

From 0ca1d9efdc929b54441d609cd65c4916ffa38540 Mon Sep 17 00:00:00 2001
From: SorenOlegnowicz <soren.olegnowicz@gmail.com>
Date: Mon, 22 Jun 2015 09:42:27 -0400
Subject: [PATCH 2/4] Feeling pretty good

---
 Data Analysis.ipynb | 1078 +++++++++++++++++++------------------------
 1 file changed, 471 insertions(+), 607 deletions(-)

diff --git a/Data Analysis.ipynb b/Data Analysis.ipynb
index 0527488..777b5aa 100644
--- a/Data Analysis.ipynb	
+++ b/Data Analysis.ipynb	
@@ -575,7 +575,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 376,
+   "execution_count": 469,
    "metadata": {
     "collapsed": true
    },
@@ -845,26 +845,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 398,
+   "execution_count": 452,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
+      "image/png": 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kNTMXzhn+aAS/LTkks666lGlmZlYKiXlJHzbLK8qOclFmvcKF2YBxr0DznLti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\n23vMJE0ALouINSr2XUC6fculwHsi4ml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       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x12d063400>"
-      ]
-     },
-     "execution_count": 398,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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cjp1tt5NkedfTlVW1co5ZJI2ZhB2ALwDnAn9fhfM6JfVNkqXA0jm/vmrmgaUk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\ngg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x12c3b5668>"
+       "<matplotlib.figure.Figure at 0x12bf3e898>"
       ]
      },
      "metadata": {},
@@ -873,7 +864,11 @@
    ],
    "source": [
     "watcher = all_time(master, 'Televisioning', '120303', 'TEAGE')\n",
-    "watcher.plot(figsize=(10,6))"
+    "watched = watcher.plot(figsize=(10,6), title='Minutes per day spent watching Television', \n",
+    "                       linewidth=5)\n",
+    "watched.set_xlabel('AGE')\n",
+    "watched.set_ylabel('Hours watching')\n",
+    "watched.grid()"
    ]
   },
   {
@@ -898,641 +893,510 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 411,
+   "execution_count": 471,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def average_minutes_2(data, activity_code):\n",
+    "    data = data[['TUFINLWGT', activity_code]]\n",
+    "    data = data.rename(columns={\"TUFINLWGT\": \"weight\", activity_code: \"minutes\"})\n",
+    "    data['weighted_minutes'] = data.weight * data.minutes\n",
+    "    return data.weighted_minutes.sum() / data.weight.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 472,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def all_time_2(data, desire_name, desire_code, duty):\n",
+    "    data_group = data.groupby(duty)\n",
+    "    data_time = {i: average_minutes_2(k, desire_code) for i, k in data_group}\n",
+    "    data_df = pd.DataFrame(data_time, index=[desire_name])\n",
+    "    data_df = data_df.T\n",
+    "    return data_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 449,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
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+       "      <td>47</td>\n",
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+       "</table>\n",
+       "<p>5 rows × 36 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 TEAGE  t130101  t130102  t130103  t130104  t130105  t130106  \\\n",
+       "TUFINLWGT                                                                      \n",
+       "11899905.662034     22        0        0        0        0        0        0   \n",
+       "4447638.009513      39        0        0        0        0        0        0   \n",
+       "10377056.507734     47        0        0        0        0        0        0   \n",
+       "7731257.992805      50        0        0        0        0        0        0   \n",
+       "4725269.227067      45        0        0        0        0        0        0   \n",
+       "\n",
+       "                 t130107  t130108  t130109   ...     t130128  t130129  \\\n",
+       "TUFINLWGT                                    ...                        \n",
+       "11899905.662034        0        0        0   ...           0        0   \n",
+       "4447638.009513         0        0        0   ...           0        0   \n",
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+       "7731257.992805         0        0        0   ...           0        0   \n",
+       "4725269.227067         0        0        0   ...           0        0   \n",
+       "\n",
+       "                 t130130  t130131  t130132  t130133  t130134  t130135  \\\n",
+       "TUFINLWGT                                                               \n",
+       "11899905.662034        0        0        0        0        0        0   \n",
+       "4447638.009513         0        0        0        0        0        0   \n",
+       "10377056.507734        0        0        0        0        0        0   \n",
+       "7731257.992805         0        0        0        0        0        0   \n",
+       "4725269.227067         0        0        0        0        0        0   \n",
+       "\n",
+       "                 t130136  t130199  \n",
+       "TUFINLWGT                          \n",
+       "11899905.662034        0        0  \n",
+       "4447638.009513         0        0  \n",
+       "10377056.507734        0        0  \n",
+       "7731257.992805         0        0  \n",
+       "4725269.227067        60        0  \n",
+       "\n",
+       "[5 rows x 36 columns]"
+      ]
+     },
+     "execution_count": 449,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "exercise_list = datum[['TUFINLWGT', 'TEAGE'] + activity_columns(datum, '1301')]\n",
+    "exercise_list.index = exercise_list.pop('TUFINLWGT')\n",
+    "exercise_list.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 447,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "e_df = exercise_list.sum(axis=1).to_frame(name='exercise')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 463,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "o_df = e_df.reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 464,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TUFINLWGT</th>\n",
+       "      <th>exercise</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
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+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         TUFINLWGT  exercise\n",
+       "0  11899905.662034         0\n",
+       "1   4447638.009513         0\n",
+       "2  10377056.507734       260\n",
+       "3   7731257.992805         0\n",
+       "4   4725269.227067        60"
+      ]
+     },
+     "execution_count": 464,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "o_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 467,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "exercise_list = datum[activity_columns(datum, '1301')]"
+    "meester = pd.merge(master, o_df, on='TUFINLWGT')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 440,
+   "execution_count": 473,
    "metadata": {
     "collapsed": false,
     "scrolled": true
    },
+   "outputs": [],
+   "source": [
+    "exer = all_time_2(meester, 'exerts', 'exercise', 'TEAGE')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 474,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
+      "text/html": [
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
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-       "Name: exercise, dtype: float64"
+       "       exerts\n",
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+       "30  14.647323\n",
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-     "execution_count": 440,
+     "execution_count": 474,
      "metadata": {},
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    "source": [
-    "e_df = exercise_list.sum(axis=1).to_frame(name='exercise')\n",
-    "deef = master.append(e_df)\n",
-    "derf = deef.exercise.dropna()\n",
-    "derf"
+    "exer.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 432,
+   "execution_count": 476,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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kNTMXzhn+aAS/LTkks666lGlmZlYKiXlJHzbLK8qOclFmvcKF2YBxr0DznLti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\nWJhJkiSNCAszSZKkEWFhJkmSNCL+CzcTVSD+GOnAAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12bf3e5c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "doop = master.groupby('TEAGE')"
+    "watcher = all_time(master, 'Televisioning', '120303', 'TEAGE')\n",
+    "watched = watcher.plot(figsize=(10,6), title='Minutes per day spent watching Television', \n",
+    "                       linewidth=5)\n",
+    "watched.set_xlabel('AGE')\n",
+    "watched.set_ylabel('Hours watching')\n",
+    "watched.grid()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 434,
+   "execution_count": 479,
    "metadata": {
     "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "39        10      610      1   7325390.733778        0      330\n",
-      "49        10      480      1  17284603.689761        0      165\n",
-      "61        10      450      2  23220400.569550        0      125\n",
-      "88        10      480      1  13186606.269365        0        0\n",
-      "95        10      465      2  23498429.630321        0        0\n",
-      "126       10      520      2   5111724.936207        0      385\n",
-      "127       10      555      1  18246566.290865        0        0\n",
-      "136       10      455      2  26050136.903249        0      120\n",
-      "156       10      470      1  12032854.019376      409      200\n",
-      "168       10      690      1   9776548.777139        0      570\n",
-      "176       10      810      2  12258183.437851        0      590\n",
-      "182       10      645      2  14853183.882684        0       60\n",
-      "188       10      600      1   7930671.840137        0        0\n",
-      "192       10      590      1  15331577.262264        0       60\n",
-      "220       10      810      1   3747644.368693        0        0\n",
-      "284       10      632      1   8322956.232154        0        0\n",
-      "291       10      450      2  21332472.568844        0        0\n",
-      "309       10      525      2  21219988.363132        0        0\n",
-      "400       10      570      2  13160459.620726        0       20\n",
-      "419       10      660      2   6502054.294583        0      120\n",
-      "427       10      730      1  13157528.323440      300       30\n",
-      "432       10      840      2   3768668.700901        0       60\n",
-      "496       10      474      2   3507471.522710        0       90\n",
-      "505       10      560      2   3603916.045809      300      120\n",
-      "509       10      715      1  20356012.578093        0      180\n",
-      "541       10      630      1  18799348.384743        0       30\n",
-      "578       10      780      1  12191930.254770        0      210\n",
-      "606       10      710      2   4665918.270500        0        0\n",
-      "612       10      636      2   5037604.070669        0        0\n",
-      "630       10      720      1  24041924.750143        0      307\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "10796     10      490      2  18209729.433285        0        0\n",
-      "10801     10      765      1   4875879.589655        0      650\n",
-      "10833     10      390      2  26144413.637180        0      150\n",
-      "10883     10      660      2  35667226.493369        0      180\n",
-      "10922     10      540      2   4545756.211734        0        0\n",
-      "10930     10      760      2   9885479.091282        0       60\n",
-      "10949     10      540      2  35448170.998971        0       60\n",
-      "10976     10      420      1   3421902.779792        0       90\n",
-      "11006     10      480      2  33307622.668722        0      350\n",
-      "11015     10      395      1   8129213.691383      550       65\n",
-      "11017     10      428      1  13705057.110350        0        0\n",
-      "11034     10      750      1   6600534.628853        0        0\n",
-      "11037     10     1015      1   3179278.177192        0        0\n",
-      "11040     10      540      1  14029146.125332        0      246\n",
-      "11046     10      660      1   8302324.206821      550        0\n",
-      "11066     10      845      2  27830450.004867        0       45\n",
-      "11089     10      480      2  29061771.051207        0       40\n",
-      "11112     10      660      1   6980159.305555        0       90\n",
-      "11131     10      540      1   7466666.661487        0      160\n",
-      "11143     10      750      1   7656954.649078        0        0\n",
-      "11146     10      370      2  24711609.273728        0       90\n",
-      "11165     10      458      1   9101434.668713        0      210\n",
-      "11212     10      630      2  10176221.842711        0      135\n",
-      "11263     10      720      1   6242106.101312        0       60\n",
-      "11277     10      780      2  11219480.404516        0       90\n",
-      "11281     10      825      1   6900488.424996        0      240\n",
-      "11299     10      930      1  33045801.921894        0       60\n",
-      "11305     10      420      1  10161375.748248      406      105\n",
-      "11336     10      750      1   3124126.590468        0      190\n",
-      "11337     10      660      1   5424512.023010        0        0\n",
-      "\n",
-      "[630 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "0         20      540      2  11899905.662034        0      330\n",
-      "9         20      520      2   3905483.253032      450        0\n",
-      "22        20      540      1   5767745.700187      470        0\n",
-      "28        20      150      2   7823574.493908        0      240\n",
-      "48        20      195      1  47558174.916715      535       75\n",
-      "69        20      520      1   7610347.321442      650       50\n",
-      "72        20      750      2   2475227.649477        0       30\n",
-      "80        20      390      2   2902362.038320        0      165\n",
-      "97        20      490      2  10406697.968610      494       60\n",
-      "113       20      615      1  22263548.185123      440      195\n",
-      "118       20      420      1  25569487.580622      680      200\n",
-      "132       20      600      1  10024101.613130        0      497\n",
-      "140       20      480      2  15446029.125408      558      218\n",
-      "142       20      390      2  16793383.462384      635       90\n",
-      "163       20      240      1  13507907.871520      436      120\n",
-      "170       20      660      1   5395994.974214        0      180\n",
-      "178       20      575      2  28729454.031678      435      120\n",
-      "181       20      540      2   4446148.674191      270      270\n",
-      "185       20      715      2  31396108.581758        0      150\n",
-      "186       20      390      1   6934967.010339      500      185\n",
-      "194       20      660      1  15650915.300098        0      280\n",
-      "210       20      570      2   4977342.447970        0       50\n",
-      "242       20      510      2   9450898.245420        0      120\n",
-      "247       20      420      2   1929271.112057        0       90\n",
-      "249       20      690      2   2596206.638998        0        0\n",
-      "250       20      465      2  12400702.893819        0       90\n",
-      "257       20      505      2   5717246.257594      660        0\n",
-      "267       20      645      1   8206748.617891      300       45\n",
-      "271       20      600      1  13356790.759873        0      320\n",
-      "277       20      465      1  49531689.248070      525        0\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11081     20      495      2  21051663.239670      600        0\n",
-      "11082     20      894      1   4498295.055811        0       90\n",
-      "11086     20      630      2  27329574.632137      430      180\n",
-      "11104     20      715      1  13382246.454755        0      420\n",
-      "11108     20      695      1  19105527.989516      120        0\n",
-      "11113     20      720      1   8596232.621229      300        0\n",
-      "11117     20      585      2   5864959.847693      489        0\n",
-      "11118     20      315      1   4095785.607304        0        0\n",
-      "11125     20      310      1  49960437.222844        0      105\n",
-      "11161     20      295      1  32070013.095155      500      180\n",
-      "11166     20      452      1  13960000.231074      466      195\n",
-      "11180     20      450      2  52632328.828751        0      411\n",
-      "11181     20      595      1   5782659.310700        0      180\n",
-      "11194     20      540      2  35060245.775690      225       60\n",
-      "11214     20      510      1   2192707.928641        0      240\n",
-      "11226     20      930      1   7322035.974241        0      360\n",
-      "11237     20      599      2   4436344.008165        0      188\n",
-      "11243     20      570      2   2143529.961279        0      143\n",
-      "11246     20      450      1   7706183.754778      540        0\n",
-      "11247     20      690      1   7217195.241209      510        0\n",
-      "11266     20      600      1   4197057.643162        0      300\n",
-      "11285     20      640      1  11597353.199992        0      178\n",
-      "11287     20      630      2   7936784.277661      310      125\n",
-      "11306     20      310      1  44748973.969384        0        0\n",
-      "11314     20      545      2   3302644.755483       20      120\n",
-      "11319     20      427      2   3705680.234096      794        0\n",
-      "11335     20      420      1  32218669.402973      435        0\n",
-      "11348     20      510      2  25858850.521863        0        0\n",
-      "11360     20      500      2   9075032.448859        0       60\n",
-      "11368     20      435      2   6753944.494461      483      180\n",
-      "\n",
-      "[1227 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "1         30      580      1   4447638.009513        0       95\n",
-      "11        30      500      1   6755514.216327      520       60\n",
-      "20        30      680      2   1102916.898147        0        0\n",
-      "36        30      427      2  12247497.817496      417      120\n",
-      "44        30      495      2  17663714.149234      425       60\n",
-      "52        30      600      2   2545139.512357        0      172\n",
-      "60        30      480      2   6824541.014325      420      195\n",
-      "62        30      585      1   7766675.451508        0       88\n",
-      "67        30      550      2   3292976.630328       90       30\n",
-      "73        30      599      2   2077845.156239        0       24\n",
-      "79        30      385      1   2292542.682742      310        0\n",
-      "84        30      571      2  10195964.532553        0        0\n",
-      "85        30      400      1   7411953.861404      505      110\n",
-      "91        30      515      1  19579904.656459      555       30\n",
-      "93        30      360      1  19702245.941487        0      360\n",
-      "99        30      210      1   7828544.773423      795      210\n",
-      "102       30      660      2   2010358.767744      685        0\n",
-      "111       30      960      2  12080068.852012        0      400\n",
-      "115       30      510      1   3171595.802118        0       60\n",
-      "116       30      420      2  13243599.712815      480        0\n",
-      "117       30      580      1   9195857.630884       10      410\n",
-      "121       30      390      1   2932486.383661        0      298\n",
-      "123       30      480      1   2578796.440520        0      620\n",
-      "124       30      450      2  11864076.858080      486      229\n",
-      "133       30      600      2   3044119.177159        0      555\n",
-      "148       30      360      2   3290041.071775        0      265\n",
-      "152       30      510      2   7354890.565325        0      183\n",
-      "164       30      520      1  21645455.510258      465      100\n",
-      "165       30      578      2  19880864.002577      493       90\n",
-      "166       30      420      2   2329178.869577      755       20\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11217     30      480      1   3029264.490944      540        0\n",
-      "11221     30      510      2   2678242.860944        0        0\n",
-      "11222     30      360      1   2783248.883993      710       60\n",
-      "11224     30      490      2   3954988.563090        0        0\n",
-      "11240     30      420      1  12925321.152796      495      180\n",
-      "11248     30      384      1   6033256.735098        0      544\n",
-      "11250     30      510      1   4135572.525678        0      389\n",
-      "11252     30      585      1  21980509.138592      660        0\n",
-      "11253     30      575      1   2551214.599892        0      603\n",
-      "11257     30      445      1   7834085.666400      450        0\n",
-      "11262     30      480      2   1985563.638093        0      200\n",
-      "11274     30      450      2   8401493.274954        0        0\n",
-      "11276     30      675      2   3633735.472181        0      120\n",
-      "11280     30      760      1  21373128.933256        0       90\n",
-      "11283     30      660      2   5817911.706809        0        0\n",
-      "11293     30      554      2   2355872.045471      105        0\n",
-      "11295     30      720      1   3264654.964583        0      120\n",
-      "11297     30      725      2   2286079.651766        0      180\n",
-      "11307     30      660      1   6455713.879513        0      415\n",
-      "11316     30       95      2   4434448.973399        0       60\n",
-      "11323     30      660      1  11670465.506146        0      490\n",
-      "11329     30      390      2   2691814.008463      575       90\n",
-      "11330     30      450      1   6319173.000529      475      413\n",
-      "11339     30      360      2   4338027.600369        0       60\n",
-      "11342     30      660      1   5920576.231175        0        0\n",
-      "11346     30      420      2   2309394.161367        0      118\n",
-      "11361     30      540      1  26070055.668273        0      175\n",
-      "11363     30      810      1   1661291.183740        0      400\n",
-      "11371     30      444      2   8820012.063839      480       60\n",
-      "11374     30      660      1   7697603.816560      400      180\n",
-      "\n",
-      "[2135 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "2         40      450      2  10377056.507734        0       60\n",
-      "4         40      570      2   4725269.227067        0       90\n",
-      "13        40      480      2   5521732.162587      505       15\n",
-      "16        40      450      1   6884215.057542      490       70\n",
-      "19        40      405      2  12301142.559951        0      120\n",
-      "25        40      528      1   3157926.871281        0        0\n",
-      "29        40      420      2   9061749.751818      282       90\n",
-      "31        40      480      1  17897951.662710        0      287\n",
-      "34        40     1108      1   9872318.115406        0      268\n",
-      "45        40      500      1   2630800.468761      490       20\n",
-      "46        40      570      2   2037394.470956        0      288\n",
-      "50        40      755      1   7487792.888126        0      268\n",
-      "70        40      387      2   7791711.857311      465       60\n",
-      "77        40      600      2  10954496.632411       20      165\n",
-      "78        40      600      2   6052110.766297      495       30\n",
-      "86        40     1005      2   6118133.026524        0        0\n",
-      "89        40      570      1  10610185.315550        0      550\n",
-      "90        40      395      1   4479189.671498      615       80\n",
-      "98        40      540      1  13367259.660653      465      225\n",
-      "110       40      750      1   3097491.070263       10      270\n",
-      "129       40      615      2   3161004.079121        0        0\n",
-      "130       40      555      1   7108775.747053      425       50\n",
-      "131       40      420      1   6405218.894362      760       60\n",
-      "135       40      450      1   7691516.119898      772      120\n",
-      "137       40      420      1   3571102.552099        0      150\n",
-      "144       40      500      1   7595798.145121      520      120\n",
-      "146       40      530      2   8502848.723099        0        0\n",
-      "147       40      450      1   6047088.987427      683        0\n",
-      "154       40      510      2   1591781.156326        0        0\n",
-      "158       40      725      1  12007283.051748      380      240\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11265     40      540      1  15695072.236362        0      690\n",
-      "11269     40      600      2   1311156.259538       10      144\n",
-      "11279     40      500      1  30008989.260705        0       80\n",
-      "11284     40      540      1  10623228.616852        0      520\n",
-      "11288     40      555      2   6316426.665632        0      275\n",
-      "11290     40      610      1   5979163.598864        0      289\n",
-      "11291     40      510      2   4165611.110828        0      385\n",
-      "11302     40      510      1   7265481.594943        0      120\n",
-      "11303     40      690      1   2396136.831248        0      130\n",
-      "11308     40      545      2   3393501.331304        0       60\n",
-      "11315     40      575      2   1191105.800719       80       90\n",
-      "11320     40      550      1   5384630.528194      495       75\n",
-      "11322     40      530      1   4032736.345657        0      330\n",
-      "11326     40      490      2   3940579.188645        0       85\n",
-      "11328     40      420      2   8123410.202165        0       60\n",
-      "11334     40      585      1   5985504.301408        0       15\n",
-      "11338     40      600      2   3509393.995749        0       30\n",
-      "11345     40      612      2   2920871.517947        0       40\n",
-      "11351     40      595      1   3726657.058047        0      520\n",
-      "11352     40      499      2   8661395.066959        0        0\n",
-      "11357     40      660      2  17993815.969566        0      240\n",
-      "11358     40      493      1  10952198.773372      343        0\n",
-      "11362     40      953      2   4479526.683095      180        0\n",
-      "11365     40      370      2  29229820.168242        0        0\n",
-      "11375     40      360      2   7045546.574380      480        0\n",
-      "11376     40      505      1   3404156.995949       45      120\n",
-      "11379     40      620      2   4844414.703530        0      205\n",
-      "11382     40      645      1  23557969.110158      550        0\n",
-      "11383     40      510      1  20450051.675501        0       60\n",
-      "11384     40      385      1   3397480.288114        0      330\n",
-      "\n",
-      "[2070 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "3         50      450      2   7731257.992805      680       65\n",
-      "7         50      480      2   8608413.296903        0       90\n",
-      "8         50      930      2   1378191.194810        0      270\n",
-      "10        50      210      2   4538371.462244      540      283\n",
-      "12        50      650      1  13506297.294756        0      300\n",
-      "17        50      420      1  12569148.198194        0      660\n",
-      "18        50      300      2  14226152.054254      725       75\n",
-      "21        50      467      2   8128107.650758      265      105\n",
-      "23        50      520      2   9474271.417876        0       60\n",
-      "24        50      160      1   5960041.143926     1006        0\n",
-      "26        50      720      2   3359410.785590        0      360\n",
-      "33        50      450      2   5114237.704143      520        0\n",
-      "41        50      545      1   5672688.960360      475        0\n",
-      "42        50      860      2   4899964.175715        0      420\n",
-      "43        50      530      2   4179351.731196       30      230\n",
-      "56        50      540      1  14395170.154470        0      250\n",
-      "59        50      460      2   3899112.240048        0       90\n",
-      "63        50      420      1   4336329.296802      485      250\n",
-      "64        50      540      1   5507709.637792        0      275\n",
-      "65        50      165      2   4745076.033227      450        0\n",
-      "66        50      480      1   4780823.505048      450        0\n",
-      "71        50      470      2  17861075.311170      510      120\n",
-      "75        50      400      2   9673636.600841        0        0\n",
-      "105       50      560      1  14855319.048947      603       90\n",
-      "108       50      440      2   5036942.371765      450       50\n",
-      "119       50      510      2  12836583.287955      420      193\n",
-      "120       50      510      1   4455799.336535      625       70\n",
-      "125       50      590      2   3835748.221858        0        0\n",
-      "134       50      390      2  14588052.810768      390      133\n",
-      "138       50      309      1   8269284.626159      705      200\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11175     50      420      1   5032572.030719      505      360\n",
-      "11184     50      480      1  23215583.129806        0      481\n",
-      "11185     50      540      2  21408342.414632        0      220\n",
-      "11190     50      570      1   3018573.718431        0      410\n",
-      "11193     50      600      1   2539190.698246      120       60\n",
-      "11195     50      420      2  19464613.786907      555        0\n",
-      "11199     50      300      2  10683016.652875        0      320\n",
-      "11202     50      360      2   6761594.139816      510      160\n",
-      "11204     50      555      1   4333417.846295       60        0\n",
-      "11209     50      460      1  10246257.497062      660      120\n",
-      "11219     50      400      2   5648311.548884      440        0\n",
-      "11228     50      590      1  15943670.695261       15        0\n",
-      "11234     50      300      1   8025836.789506        0      190\n",
-      "11242     50      535      1   2511955.883756        0      470\n",
-      "11267     50      660      1   2424338.722845        0      120\n",
-      "11271     50      470      1  13053986.051667        0      290\n",
-      "11272     50      480      1  18459763.924574        0       60\n",
-      "11275     50      555      1   2042551.826923      200        0\n",
-      "11282     50      300      1   8723788.752799      430      407\n",
-      "11292     50      718      1   4418900.403328        0        0\n",
-      "11298     50      830      1   7865093.851106        0       30\n",
-      "11312     50      750      2   2655874.525220      120       60\n",
-      "11327     50      510      1  34698751.604644      440      140\n",
-      "11349     50      720      2   6791023.432204        0      355\n",
-      "11355     50      315      1   8140631.838710       30      120\n",
-      "11356     50      540      1   7853305.097899        0      190\n",
-      "11364     50      550      2   9980183.671597        0      363\n",
-      "11372     50      655      2   4571613.779402        0        0\n",
-      "11377     50      570      2  10775395.416617      315      118\n",
-      "11378     50      480      1   7548528.958862        0      370\n",
-      "\n",
-      "[2038 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "14        60      615      1  11791654.393174        0      397\n",
-      "15        60      720      2   1801834.050978        0      130\n",
-      "30        60      470      2   5593947.004768        0      193\n",
-      "35        60      600      2   1615210.298718        0      225\n",
-      "37        60      300      1   4369661.120262        0      559\n",
-      "51        60      540      2   1155696.356453        0      390\n",
-      "54        60      495      2   1552575.923818        0      160\n",
-      "55        60      670      1   4025712.610135        0      375\n",
-      "58        60      553      1  18134702.210490        0      493\n",
-      "68        60      540      2   7246036.839990        0      120\n",
-      "74        60      495      2   1668957.316975       20      120\n",
-      "76        60      570      1   7121345.777743        0      725\n",
-      "81        60      365      1  14026843.891702        0      255\n",
-      "82        60      480      2    905491.422607        0      585\n",
-      "83        60      330      2   4949328.204808        0        0\n",
-      "87        60      600      2   7214021.670004        0      330\n",
-      "92        60      536      2   4214121.903742      535      110\n",
-      "94        60      819      2   5423281.958462        0       30\n",
-      "96        60      630      1   2378202.313739        0      750\n",
-      "100       60      660      1  16345016.144182        0      635\n",
-      "103       60      540      2   4767502.081252        0      365\n",
-      "104       60      450      2   5874564.524659        0      384\n",
-      "107       60      706      2    995946.672027        0       30\n",
-      "109       60      585      2    957202.866217        0      225\n",
-      "112       60      690      2  14250055.620988        0      395\n",
-      "122       60      490      1  19181757.762991      480       30\n",
-      "143       60      570      2   4203061.211280        0      290\n",
-      "153       60      585      2   1026591.267310        0       60\n",
-      "167       60      480      1   8827580.302387      180      190\n",
-      "206       60      570      2   1495682.392854        0      447\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11201     60      635      2   1779890.726839        0        0\n",
-      "11215     60      450      2   5906807.899208        0      370\n",
-      "11216     60      445      2  11288680.932262      485        0\n",
-      "11232     60      720      2   3784844.768038        0      660\n",
-      "11233     60      420      2   8321476.698838        0      355\n",
-      "11244     60      420      1   2656294.115735        0        0\n",
-      "11249     60      720      1   2059916.609318        0      550\n",
-      "11254     60      630      2  17732989.092974        0      165\n",
-      "11264     60      523      2  10915647.663904        0       95\n",
-      "11268     60     1376      1   8007901.668570        0       60\n",
-      "11273     60      570      1   5643283.112760        0      395\n",
-      "11289     60      480      1   3165217.163949        0      637\n",
-      "11296     60      560      2   2379662.158634        0      120\n",
-      "11301     60      625      2   4718692.834607        0      210\n",
-      "11304     60      565      1   1784286.956725        0      380\n",
-      "11309     60      345      2   8226515.613924      450        0\n",
-      "11310     60      600      1   1685062.337737        0        0\n",
-      "11311     60      540      1  13257583.342535        0       60\n",
-      "11313     60      435      2   1976427.364612      360      120\n",
-      "11317     60      590      2   8762629.471153        0      152\n",
-      "11318     60      450      2  13390317.688340      472      244\n",
-      "11321     60      450      1   6525607.772974        0      510\n",
-      "11331     60      720      2   3731145.590155        0      325\n",
-      "11332     60      815      1   2529983.509041        0       60\n",
-      "11353     60      450      1   4796588.887839        0      565\n",
-      "11354     60      459      2   1620251.749429        0      120\n",
-      "11359     60      510      1  10969610.362669      190      175\n",
-      "11370     60      480      2   4681607.563005      495       90\n",
-      "11373     60      450      1   6454041.312322        0      406\n",
-      "11381     60      455      1   4103676.895062      445        0\n",
-      "\n",
-      "[1719 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "6         70      290      1   5671341.270490        0      244\n",
-      "32        70      510      1   9339822.293071        0      435\n",
-      "38        70      555      1   4281464.665852        0      167\n",
-      "40        70      510      2   2640030.174785        0      135\n",
-      "47        70      450      1   7351319.132975        0      125\n",
-      "53        70      467      2   2302532.129170        0      205\n",
-      "101       70      570      1  10599708.349245        0      300\n",
-      "159       70      623      1   5458501.990213        0      330\n",
-      "162       70      480      1   5745654.098933      900        0\n",
-      "179       70      780      2   8604987.493600        0      180\n",
-      "189       70      360      1   5533265.788663        0       90\n",
-      "190       70      720      1   3914537.546553        0      580\n",
-      "199       70      615      2   5858104.695494        0      200\n",
-      "200       70      895      1   7955493.450767        0      180\n",
-      "208       70      495      2   6098490.933292        0       45\n",
-      "221       70      720      1   4071770.199139        0      225\n",
-      "233       70      784      1   1827420.031506        0      115\n",
-      "236       70      650      1   3616078.174585        0      180\n",
-      "237       70      450      2  13862088.362812        0      550\n",
-      "255       70      420      1  14049868.701988      285        0\n",
-      "260       70      540      2   1810049.688378        0      250\n",
-      "269       70      705      2   7175918.642034        0       60\n",
-      "320       70      600      1   6570729.327039        0      555\n",
-      "342       70      770      2   2245016.672470        0      120\n",
-      "349       70      510      1  10841672.060961        0      390\n",
-      "353       70      390      1  10323139.493818        0      320\n",
-      "361       70      300      2   7006110.116001        0      120\n",
-      "372       70      480      1   3560186.962625        0      300\n",
-      "388       70      380      2   7035922.172183        0      210\n",
-      "389       70      510      2   9819799.461568        0       30\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "11064     70      480      2   6357041.783741        0      210\n",
-      "11065     70      420      2   6262770.278938        0       30\n",
-      "11073     70      300      1  13362800.811477        0      924\n",
-      "11078     70      540      2   6028236.406986        0      582\n",
-      "11100     70      560      1   1699946.003948        0      180\n",
-      "11103     70      450      2   4030223.088018      285       60\n",
-      "11109     70      575      2   2452262.758356      610        0\n",
-      "11111     70      300      1   2601328.326493        0      960\n",
-      "11121     70      600      2   3475303.399063        0      504\n",
-      "11129     70      500      2  14650091.205261        0       60\n",
-      "11148     70      480      1   5972292.674713      610      220\n",
-      "11155     70      540      2  16265794.894820      450        0\n",
-      "11186     70      335      1   5914189.513436        0      700\n",
-      "11196     70      465      2   5805688.661820      534      138\n",
-      "11200     70      510      1   4647609.775592        0      540\n",
-      "11210     70      540      1  13351528.691465        0      715\n",
-      "11218     70      570      1   6289319.793169        0        0\n",
-      "11239     70      630      2  12737048.679523        0        0\n",
-      "11245     70      495      1  10017639.876671        0      190\n",
-      "11255     70      677      2  12987380.212853        0      151\n",
-      "11259     70      620      1   7603251.331595       15        0\n",
-      "11286     70      600      1   6861733.718310        0      400\n",
-      "11294     70      510      2   6115763.610236        0       60\n",
-      "11300     70      540      2   6186658.115273        0       60\n",
-      "11324     70       60      2   3968824.922564        0       60\n",
-      "11325     70      540      1   4601634.758350        0      180\n",
-      "11341     70      510      2   1269938.571212        0      894\n",
-      "11343     70      630      1  32120635.161945        0      635\n",
-      "11347     70      570      1   3833098.981090        0      215\n",
-      "11366     70      545      1   2709393.926463        0      240\n",
-      "\n",
-      "[954 rows x 6 columns]\n",
-      "       TEAGE  t010101  TESEX        TUFINLWGT  t050101  t120303\n",
-      "5         80      495      2   2372791.046351        0      270\n",
-      "27        80      510      2  17547816.572228        0      120\n",
-      "57        80      600      2   4735832.929302        0      240\n",
-      "106       80      360      2   2017395.251175        0        0\n",
-      "114       80      600      2   1672799.901193        0      490\n",
-      "128       80      660      2   1532346.930362        0      180\n",
-      "145       80      810      1  13262141.925633        0      120\n",
-      "289       80      510      2   6680427.198486        0      185\n",
-      "321       80      705      2   6006887.538735        0      165\n",
-      "333       80      330      2   1753266.894347      120      453\n",
-      "347       80      555      2  13167868.213048        0      260\n",
-      "352       80      550      2   2224067.836660        0      180\n",
-      "373       80      600      1  11156497.509749        0      165\n",
-      "376       80      525      2   7150043.663756        0      160\n",
-      "392       80      440      1   1797810.655993        0      335\n",
-      "393       80      541      2  16151260.939039        0      329\n",
-      "395       80      650      2   2016538.534295        0       45\n",
-      "421       80      540      1   4552627.002899      245      165\n",
-      "461       80      540      2   8002205.042858        0      240\n",
-      "468       80      470      1   1774410.834063      240       15\n",
-      "508       80      420      2   2272978.671553        0        0\n",
-      "519       80      570      2  15649036.558960        0      390\n",
-      "525       80      450      2   7926611.511046        0        0\n",
-      "528       80      510      2   5590727.095603        0      115\n",
-      "532       80      467      1   1833186.987661        0      240\n",
-      "543       80      540      1   1912086.105907        0      675\n",
-      "565       80      540      1   4820263.194324        0      120\n",
-      "618       80      540      2   4834649.166287        0      875\n",
-      "625       80      470      2   6381826.183586        0      190\n",
-      "711       80      720      2   6503836.965754        0      125\n",
-      "...      ...      ...    ...              ...      ...      ...\n",
-      "10908     80      450      2   3669160.142743        0      265\n",
-      "10946     80      540      2   1540997.446387        0      165\n",
-      "10967     80      720      1   5158938.664079        0      585\n",
-      "10968     80      540      1   7379338.236892        0       30\n",
-      "11022     80      630      2   3132975.049378        0        0\n",
-      "11030     80      700      1   7712442.882288        0      480\n",
-      "11033     80      506      1   5940063.907671        0       60\n",
-      "11042     80      510      1  12765353.852847        0      280\n",
-      "11099     80      810      2  11340505.719801        0       60\n",
-      "11101     80      585      1   2452363.918235        0      747\n",
-      "11122     80      540      2   1387725.018450        0        0\n",
-      "11124     80      780      1   2911306.663617        0      490\n",
-      "11142     80      480      2   4249868.979466      165      120\n",
-      "11167     80      450      2   6911348.142600        0      551\n",
-      "11198     80      560      2   3956966.489327        0        0\n",
-      "11207     80      375      2  16018203.380493        0      355\n",
-      "11227     80      420      2   3185870.710368        0      150\n",
-      "11231     80      660      1  13157418.855151        0      120\n",
-      "11235     80      810      2   6365190.049790        0      600\n",
-      "11251     80      655      1   3105983.861132        0      233\n",
-      "11258     80      510      2   3869762.971403        0        0\n",
-      "11270     80      720      1   5511908.806864        0      685\n",
-      "11278     80      510      2   4241514.318240        0      324\n",
-      "11333     80      630      2   3246491.188202        0      340\n",
-      "11340     80      640      2   2755542.631494        0      140\n",
-      "11344     80      560      1  18136091.705952        0        0\n",
-      "11350     80      520      2   6586072.883651        0      285\n",
-      "11367     80      530      2   4417006.113982        0       90\n",
-      "11369     80      700      1   3799315.033354        0      410\n",
-      "11380     80      450      2   4469643.600730        0      480\n",
-      "\n",
-      "[612 rows x 6 columns]\n"
-     ]
+     "data": {
+      "image/png": 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AWImI17sdj5mZmVkjg9aEvyzwiW4H0W88jl+M81eM81eM89c+564Y569avV6AARyC5Oko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\nAJMkSRozCzBJkqQxswCTJEkas/8ApzjxeMYtN3AAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12c9b1a20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
-   "source": []
+   "source": [
+    "exertion = exer.plot(figsize=(10,6), linewidth=5, color = 'r', \n",
+    "                     title='Average Total Physical Activity')\n",
+    "exertion.set_xlabel('Age')\n",
+    "exertion.set_ylabel('Minutes of activity per Day')\n",
+    "exertion.grid()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above two plots suggest that the youth might not be so inclined to watch Television as much as the elderly because they spend more time engaging in physical activity"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note: The averages are so low in this graph because I included all of the Zero Values."
+   ]
   },
   {
    "cell_type": "code",

From c700d9ae38b34dc09b68ea1af8bd28d99553a04b Mon Sep 17 00:00:00 2001
From: SorenOlegnowicz <soren.olegnowicz@gmail.com>
Date: Fri, 21 Aug 2015 17:43:31 -0400
Subject: [PATCH 3/4] a little cleaning

---
 Data Analysis.ipynb | 48 ++++++++++++++++++++++++++++++++++++++-------
 1 file changed, 41 insertions(+), 7 deletions(-)

diff --git a/Data Analysis.ipynb b/Data Analysis.ipynb
index 777b5aa..eee3731 100644
--- a/Data Analysis.ipynb	
+++ b/Data Analysis.ipynb	
@@ -249,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 408,
+   "execution_count": 490,
    "metadata": {
     "collapsed": false
    },
@@ -268,7 +268,7 @@
    ],
    "source": [
     "age = datum['TEAGE'].to_frame()\n",
-    "sexy_age = datum[['TEAGE', 'TESEX']]\n",
+    "sexy_age = datum[['TEAGE', 'TESEX', 'tucaseid']]\n",
     "master = datum[['TEAGE', 't010101', 'TESEX', 'TUFINLWGT','t050101', 't120303']]\n",
     "master.TEAGE.update((master.TEAGE // 10) * 10)"
    ]
@@ -506,6 +506,40 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 497,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1307f0400>"
+      ]
+     },
+     "execution_count": 497,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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JN2TYo2rby8b6v7PL+kupMXEPOz2XQ42xgdzs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\nAAB07v8DSdp2yfVQT14AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x1307ab860>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "#sexy_age\n",
+    "sexy_age.pivot_table(index=[\"TEAGE\"], columns=[\"TESEX\"], values=[\"tucaseid\"], aggfunc=lambda x: len(x.unique())).plot(kind=\"bar\", figsize=(20, 20), stacked=True)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 75,
@@ -840,12 +874,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The above two plots suggest that Time worked is inversely proportional to Time slept."
+    "##^The above two plots suggest that Time worked is inversely proportional to Time slept."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 452,
+   "execution_count": 499,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -853,9 +887,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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kNTMXzhn+aAS/LTkks666lGlmZlYKiXlJHzbLK8qOclFmvcKF2YBxr0DznLti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\nWJhJkiSNCAszSZKkEWFhJkmSNCL+CzcTVSD+GOnAAAAAAElFTkSuQmCC\n",
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8H34rOj+SqcN0jYVb7Zy7bJy/bJy/mv0Qnloc/ronPHgpzNoRBnZ7YcC653Ov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\nSUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x12bf3e898>"
+       "<matplotlib.figure.Figure at 0x131037048>"
       ]
      },
      "metadata": {},
@@ -865,7 +899,7 @@
    "source": [
     "watcher = all_time(master, 'Televisioning', '120303', 'TEAGE')\n",
     "watched = watcher.plot(figsize=(10,6), title='Minutes per day spent watching Television', \n",
-    "                       linewidth=5)\n",
+    "                       linewidth=1, marker = '*')\n",
     "watched.set_xlabel('AGE')\n",
     "watched.set_ylabel('Hours watching')\n",
     "watched.grid()"

From d64ffe3a59efdac042cbfd0c8c5a486ddd785a74 Mon Sep 17 00:00:00 2001
From: SorenOlegnowicz <SorenOlegnowicz@users.noreply.github.com>
Date: Fri, 21 Aug 2015 17:56:26 -0400
Subject: [PATCH 4/4] Update README.md

---
 README.md | 22 ++--------------------
 1 file changed, 2 insertions(+), 20 deletions(-)

diff --git a/README.md b/README.md
index 88b27af..80fec6d 100644
--- a/README.md
+++ b/README.md
@@ -2,27 +2,9 @@
 
 ## Description
 
-Use the U.S. Department of Labor's data on Americans' time use for research and analysis.
+Uses Pandas and Matplotlib to analyze the U.S. Department of Labor's data on Americans' Time Use Survey.
 
-## Objectives
-
-### Learning Objectives
-
-After completing this assignment, you should understand:
-
-* How to use public data for analysis
-* How to translate data from CSVs to relational databases
-* How to publish your own data analysis as a notebook
-
-### Performance Objectives
-
-After completing this assignment, you should be able to:
-
-* Use pandas to parse and analyze data
-* Use matplotlib to chart data
-* Clean data
-
-## Details
+## Assignment Details
 
 ### Deliverables