chap02ex01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercise 2.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>\n",
    "Allen Downey\n",
    "\n",
    "Read the female respondent file and display the variables names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "chap01soln.py: All tests passed.\n"
     ]
    }
   ],
   "source": [
    "%run chap01soln"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>caseid</th>\n",
       "      <th>rscrinf</th>\n",
       "      <th>rdormres</th>\n",
       "      <th>rostscrn</th>\n",
       "      <th>rscreenhisp</th>\n",
       "      <th>rscreenrace</th>\n",
       "      <th>age_a</th>\n",
       "      <th>age_r</th>\n",
       "      <th>cmbirth</th>\n",
       "      <th>agescrn</th>\n",
       "      <th>...</th>\n",
       "      <th>pubassis_i</th>\n",
       "      <th>basewgt</th>\n",
       "      <th>adj_mod_basewgt</th>\n",
       "      <th>finalwgt</th>\n",
       "      <th>secu_r</th>\n",
       "      <th>sest</th>\n",
       "      <th>cmintvw</th>\n",
       "      <th>cmlstyr</th>\n",
       "      <th>screentime</th>\n",
       "      <th>intvlngth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2298</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>902</td>\n",
       "      <td>27</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3247.916977</td>\n",
       "      <td>5123.759559</td>\n",
       "      <td>5556.717241</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>1234</td>\n",
       "      <td>1222</td>\n",
       "      <td>18:26:36</td>\n",
       "      <td>110.492667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5012</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>718</td>\n",
       "      <td>42</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2335.279149</td>\n",
       "      <td>2846.799490</td>\n",
       "      <td>4744.191350</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>1233</td>\n",
       "      <td>1221</td>\n",
       "      <td>16:30:59</td>\n",
       "      <td>64.294000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11586</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>708</td>\n",
       "      <td>43</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2335.279149</td>\n",
       "      <td>2846.799490</td>\n",
       "      <td>4744.191350</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>1234</td>\n",
       "      <td>1222</td>\n",
       "      <td>18:19:09</td>\n",
       "      <td>75.149167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6794</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>1042</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3783.152221</td>\n",
       "      <td>5071.464231</td>\n",
       "      <td>5923.977368</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>1234</td>\n",
       "      <td>1222</td>\n",
       "      <td>15:54:43</td>\n",
       "      <td>28.642833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>616</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>991</td>\n",
       "      <td>20</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>5341.329968</td>\n",
       "      <td>6437.335772</td>\n",
       "      <td>7229.128072</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>1233</td>\n",
       "      <td>1221</td>\n",
       "      <td>14:19:44</td>\n",
       "      <td>69.502667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 3087 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   caseid  rscrinf  rdormres  rostscrn  rscreenhisp  rscreenrace  age_a  \\\n",
       "0    2298        1         5         5            1          5.0     27   \n",
       "1    5012        1         5         1            5          5.0     42   \n",
       "2   11586        1         5         1            5          5.0     43   \n",
       "3    6794        5         5         4            1          5.0     15   \n",
       "4     616        1         5         4            1          5.0     20   \n",
       "\n",
       "   age_r  cmbirth  agescrn     ...      pubassis_i      basewgt  \\\n",
       "0     27      902       27     ...               0  3247.916977   \n",
       "1     42      718       42     ...               0  2335.279149   \n",
       "2     43      708       43     ...               0  2335.279149   \n",
       "3     15     1042       15     ...               0  3783.152221   \n",
       "4     20      991       20     ...               0  5341.329968   \n",
       "\n",
       "   adj_mod_basewgt     finalwgt  secu_r  sest  cmintvw  cmlstyr  screentime  \\\n",
       "0      5123.759559  5556.717241       2    18     1234     1222    18:26:36   \n",
       "1      2846.799490  4744.191350       2    18     1233     1221    16:30:59   \n",
       "2      2846.799490  4744.191350       2    18     1234     1222    18:19:09   \n",
       "3      5071.464231  5923.977368       2    18     1234     1222    15:54:43   \n",
       "4      6437.335772  7229.128072       2    18     1233     1221    14:19:44   \n",
       "\n",
       "    intvlngth  \n",
       "0  110.492667  \n",
       "1   64.294000  \n",
       "2   75.149167  \n",
       "3   28.642833  \n",
       "4   69.502667  \n",
       "\n",
       "[5 rows x 3087 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resp = ReadFemResp()\n",
    "# Let's take a look at our data\n",
    "resp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Write the command to look at the columns of the DataFrame \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a histogram of <tt>totincr</tt> the total income for the respondent's family.  To interpret the codes see the [codebook](http://www.icpsr.umich.edu/nsfg6/Controller?displayPage=labelDetails&fileCode=MALE&section=R&subSec=7958&srtLabel=609776)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import thinkstats2\n",
    "hist_totincr = thinkstats2.Hist(resp.totincr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kDyf5UNc+P8ndSR5N8q0kh/WtsyrJpiSPJHnHTLwASdL0DTIS2An8eVW9AXgr8MEkfwSs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\nQJIaZghIUsMMAUlq2P8H5LP2UPwdKvcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c9ac2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10aca9290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import thinkplot\n",
    "thinkplot.Hist(hist_totincr, label='totincr')\n",
    "thinkplot.Show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a histogram of <tt>age_r</tt>, the respondent's age at the time of interview."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "hist_age_r = thinkstats2.Hist(resp.age_r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a histogram of <tt>numfmhh</tt>, the number of people in the respondent's household."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Explain what is shown in the histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a histogram of <tt>numfmhh</tt>, the number of people in the respondent's household."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Explain what you see in the distribution. Remember, you can use the [codebook](http://www.icpsr.umich.edu/nsfg6/Controller?displayPage=labelDetails&fileCode=MALE&section=R&subSec=7958&srtLabel=609776) to interpret the codes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most respondents have between 1 to 3 family members their household (mening: households of 2-4 family members). The histogram has a right tail, meaning the number of respondents gradually becomes smaller the more members in a household. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a histogram of <tt>parity</tt>, the number children the respondent has."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use Hist.Largest to find the largest values of <tt>parity</tt>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the values shown in the histogram."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use <tt>totincr</tt> to select the respondents with the highest income.  Compute the distribution of <tt>parity</tt> for just the high income respondents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# creating a variable of respondents with highest income\n",
    "\n",
    "# sanity check: compare number of rows with codebook\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# compute the distribution of high income respondents\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Describe what you see in the distribution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find the largest parities for high income respondents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a histogram of the other respondents parities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find the maximum parity for other (lower) income."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the mean <tt>parity</tt> for high income respondents and others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Investigate any other variables that look interesting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}