Analyzing_US_Thanksgiving_Dinner.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Analyzing U.S. Thanksgiving Dinner \n",
    "## Open, Read, and Display First Five Rows of DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>RespondentID</th>\n",
       "      <th>Do you celebrate Thanksgiving?</th>\n",
       "      <th>What is typically the main dish at your Thanksgiving dinner?</th>\n",
       "      <th>What is typically the main dish at your Thanksgiving dinner? - Other (please specify)</th>\n",
       "      <th>How is the main dish typically cooked?</th>\n",
       "      <th>How is the main dish typically cooked? - Other (please specify)</th>\n",
       "      <th>What kind of stuffing/dressing do you typically have?</th>\n",
       "      <th>What kind of stuffing/dressing do you typically have? - Other (please specify)</th>\n",
       "      <th>What type of cranberry saucedo you typically have?</th>\n",
       "      <th>What type of cranberry saucedo you typically have? - Other (please specify)</th>\n",
       "      <th>...</th>\n",
       "      <th>Have you ever tried to meet up with hometown friends on Thanksgiving night?</th>\n",
       "      <th>Have you ever attended a \"Friendsgiving?\"</th>\n",
       "      <th>Will you shop any Black Friday sales on Thanksgiving Day?</th>\n",
       "      <th>Do you work in retail?</th>\n",
       "      <th>Will you employer make you work on Black Friday?</th>\n",
       "      <th>How would you describe where you live?</th>\n",
       "      <th>Age</th>\n",
       "      <th>What is your gender?</th>\n",
       "      <th>How much total combined money did all members of your HOUSEHOLD earn last year?</th>\n",
       "      <th>US Region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4337954960</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Baked</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bread-based</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>18 - 29</td>\n",
       "      <td>Male</td>\n",
       "      <td>$75,000 to $99,999</td>\n",
       "      <td>Middle Atlantic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4337951949</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Baked</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bread-based</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other (please specify)</td>\n",
       "      <td>Homemade cranberry gelatin ring</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rural</td>\n",
       "      <td>18 - 29</td>\n",
       "      <td>Female</td>\n",
       "      <td>$50,000 to $74,999</td>\n",
       "      <td>East South Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4337935621</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Roasted</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rice-based</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Homemade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>18 - 29</td>\n",
       "      <td>Male</td>\n",
       "      <td>$0 to $9,999</td>\n",
       "      <td>Mountain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4337933040</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Baked</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bread-based</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Homemade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Urban</td>\n",
       "      <td>30 - 44</td>\n",
       "      <td>Male</td>\n",
       "      <td>$200,000 and up</td>\n",
       "      <td>Pacific</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4337931983</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Tofurkey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Baked</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bread-based</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Canned</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Urban</td>\n",
       "      <td>30 - 44</td>\n",
       "      <td>Male</td>\n",
       "      <td>$100,000 to $124,999</td>\n",
       "      <td>Pacific</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 65 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RespondentID Do you celebrate Thanksgiving?  \\\n",
       "0    4337954960                            Yes   \n",
       "1    4337951949                            Yes   \n",
       "2    4337935621                            Yes   \n",
       "3    4337933040                            Yes   \n",
       "4    4337931983                            Yes   \n",
       "\n",
       "  What is typically the main dish at your Thanksgiving dinner?  \\\n",
       "0                                             Turkey             \n",
       "1                                             Turkey             \n",
       "2                                             Turkey             \n",
       "3                                             Turkey             \n",
       "4                                           Tofurkey             \n",
       "\n",
       "  What is typically the main dish at your Thanksgiving dinner? - Other (please specify)  \\\n",
       "0                                                NaN                                      \n",
       "1                                                NaN                                      \n",
       "2                                                NaN                                      \n",
       "3                                                NaN                                      \n",
       "4                                                NaN                                      \n",
       "\n",
       "  How is the main dish typically cooked?  \\\n",
       "0                                  Baked   \n",
       "1                                  Baked   \n",
       "2                                Roasted   \n",
       "3                                  Baked   \n",
       "4                                  Baked   \n",
       "\n",
       "  How is the main dish typically cooked? - Other (please specify)  \\\n",
       "0                                                NaN                \n",
       "1                                                NaN                \n",
       "2                                                NaN                \n",
       "3                                                NaN                \n",
       "4                                                NaN                \n",
       "\n",
       "  What kind of stuffing/dressing do you typically have?  \\\n",
       "0                                        Bread-based      \n",
       "1                                        Bread-based      \n",
       "2                                         Rice-based      \n",
       "3                                        Bread-based      \n",
       "4                                        Bread-based      \n",
       "\n",
       "  What kind of stuffing/dressing do you typically have? - Other (please specify)  \\\n",
       "0                                                NaN                               \n",
       "1                                                NaN                               \n",
       "2                                                NaN                               \n",
       "3                                                NaN                               \n",
       "4                                                NaN                               \n",
       "\n",
       "  What type of cranberry saucedo you typically have?  \\\n",
       "0                                               None   \n",
       "1                             Other (please specify)   \n",
       "2                                           Homemade   \n",
       "3                                           Homemade   \n",
       "4                                             Canned   \n",
       "\n",
       "  What type of cranberry saucedo you typically have? - Other (please specify)  \\\n",
       "0                                                NaN                            \n",
       "1                    Homemade cranberry gelatin ring                            \n",
       "2                                                NaN                            \n",
       "3                                                NaN                            \n",
       "4                                                NaN                            \n",
       "\n",
       "          ...          \\\n",
       "0         ...           \n",
       "1         ...           \n",
       "2         ...           \n",
       "3         ...           \n",
       "4         ...           \n",
       "\n",
       "  Have you ever tried to meet up with hometown friends on Thanksgiving night?  \\\n",
       "0                                                Yes                            \n",
       "1                                                 No                            \n",
       "2                                                Yes                            \n",
       "3                                                Yes                            \n",
       "4                                                Yes                            \n",
       "\n",
       "  Have you ever attended a \"Friendsgiving?\"  \\\n",
       "0                                        No   \n",
       "1                                        No   \n",
       "2                                       Yes   \n",
       "3                                        No   \n",
       "4                                        No   \n",
       "\n",
       "  Will you shop any Black Friday sales on Thanksgiving Day?  \\\n",
       "0                                                 No          \n",
       "1                                                Yes          \n",
       "2                                                Yes          \n",
       "3                                                 No          \n",
       "4                                                 No          \n",
       "\n",
       "  Do you work in retail? Will you employer make you work on Black Friday?  \\\n",
       "0                     No                                              NaN   \n",
       "1                     No                                              NaN   \n",
       "2                     No                                              NaN   \n",
       "3                     No                                              NaN   \n",
       "4                     No                                              NaN   \n",
       "\n",
       "  How would you describe where you live?      Age What is your gender?  \\\n",
       "0                               Suburban  18 - 29                 Male   \n",
       "1                                  Rural  18 - 29               Female   \n",
       "2                               Suburban  18 - 29                 Male   \n",
       "3                                  Urban  30 - 44                 Male   \n",
       "4                                  Urban  30 - 44                 Male   \n",
       "\n",
       "  How much total combined money did all members of your HOUSEHOLD earn last year?  \\\n",
       "0                                 $75,000 to $99,999                                \n",
       "1                                 $50,000 to $74,999                                \n",
       "2                                       $0 to $9,999                                \n",
       "3                                    $200,000 and up                                \n",
       "4                               $100,000 to $124,999                                \n",
       "\n",
       "            US Region  \n",
       "0     Middle Atlantic  \n",
       "1  East South Central  \n",
       "2            Mountain  \n",
       "3             Pacific  \n",
       "4             Pacific  \n",
       "\n",
       "[5 rows x 65 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv(\"thanksgiving.csv\",encoding=\"Latin-1\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Columns to Obtain Sense of Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['RespondentID', 'Do you celebrate Thanksgiving?',\n",
       "       'What is typically the main dish at your Thanksgiving dinner?',\n",
       "       'What is typically the main dish at your Thanksgiving dinner? - Other (please specify)',\n",
       "       'How is the main dish typically cooked?',\n",
       "       'How is the main dish typically cooked? - Other (please specify)',\n",
       "       'What kind of stuffing/dressing do you typically have?',\n",
       "       'What kind of stuffing/dressing do you typically have? - Other (please specify)',\n",
       "       'What type of cranberry saucedo you typically have?',\n",
       "       'What type of cranberry saucedo you typically have? - Other (please specify)',\n",
       "       'Do you typically have gravy?',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Brussel sprouts',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Carrots',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Cauliflower',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Corn',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Cornbread',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Fruit salad',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Green beans/green bean casserole',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Macaroni and cheese',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Mashed potatoes',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Rolls/biscuits',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Squash',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Vegetable salad',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Yams/sweet potato casserole',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify)',\n",
       "       'Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify).1',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Apple',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Buttermilk',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Cherry',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Chocolate',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Coconut cream',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Key lime',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Peach',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pecan',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pumpkin',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Sweet Potato',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - None',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify)',\n",
       "       'Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify).1',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Apple cobbler',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Blondies',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Brownies',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Carrot cake',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Cheesecake',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Cookies',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Fudge',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Ice cream',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Peach cobbler',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - None',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Other (please specify)',\n",
       "       'Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Other (please specify).1',\n",
       "       'Do you typically pray before or after the Thanksgiving meal?',\n",
       "       'How far will you travel for Thanksgiving?',\n",
       "       'Will you watch any of the following programs on Thanksgiving? Please select all that apply. - Macy's Parade',\n",
       "       'What's the age cutoff at your \"kids' table\" at Thanksgiving?',\n",
       "       'Have you ever tried to meet up with hometown friends on Thanksgiving night?',\n",
       "       'Have you ever attended a \"Friendsgiving?\"',\n",
       "       'Will you shop any Black Friday sales on Thanksgiving Day?',\n",
       "       'Do you work in retail?',\n",
       "       'Will you employer make you work on Black Friday?',\n",
       "       'How would you describe where you live?', 'Age', 'What is your gender?',\n",
       "       'How much total combined money did all members of your HOUSEHOLD earn last year?',\n",
       "       'US Region'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Responses to 'Do you celebrate Thanksgiving?' and Display Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    980\n",
       "No      78\n",
       "Name: Do you celebrate Thanksgiving?, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yes_no = data[\"Do you celebrate Thanksgiving?\"]\n",
    "\n",
    "yes_no.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create New DataFrame by Filtering Out Non-'Yes' Responses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = data[yes_no == \"Yes\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Counts Again to Confirm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    980\n",
       "Name: Do you celebrate Thanksgiving?, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Do you celebrate Thanksgiving?\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Extract Responses to 'What is typically the main dish at your Thanksgiving dinner?' and Display Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Turkey                    859\n",
       "Other (please specify)     35\n",
       "Ham/Pork                   29\n",
       "Tofurkey                   20\n",
       "Chicken                    12\n",
       "Roast beef                 11\n",
       "I don't know                5\n",
       "Turducken                   3\n",
       "Name: What is typically the main dish at your Thanksgiving dinner?, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_dish = data[\"What is typically the main dish at your Thanksgiving dinner?\"]\n",
    "\n",
    "main_dish.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter Out Non-'Tofurkey' Responses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Tofurkey = data[main_dish == \"Tofurkey\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Counts Again to Confirm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tofurkey    20\n",
       "Name: What is typically the main dish at your Thanksgiving dinner?, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tofurkey[\"What is typically the main dish at your Thanksgiving dinner?\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Responses to 'Do you typically have gravy?' for 'Tofurkey' DataFrame and Display Column and Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4      Yes\n",
       "33     Yes\n",
       "69      No\n",
       "72      No\n",
       "77     Yes\n",
       "145    Yes\n",
       "175    Yes\n",
       "218     No\n",
       "243    Yes\n",
       "275     No\n",
       "393    Yes\n",
       "399    Yes\n",
       "571    Yes\n",
       "594    Yes\n",
       "628     No\n",
       "774     No\n",
       "820     No\n",
       "837    Yes\n",
       "860     No\n",
       "953    Yes\n",
       "Name: Do you typically have gravy?, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tofurkey_with_gravy = Tofurkey[\"Do you typically have gravy?\"]\n",
    "\n",
    "Tofurkey_with_gravy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    12\n",
       "No      8\n",
       "Name: Do you typically have gravy?, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tofurkey_with_gravy.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Generate Boolean Series for 'Apple Pie', 'Pumpkin Pie', and 'Pecan Pie' Desserts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "apple_isnull = pd.isnull(data[\"Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Apple\"])\n",
    "\n",
    "pumpkin_isnull = pd.isnull(data[\"Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pumpkin\"])\n",
    "\n",
    "pecan_isnull = pd.isnull(data[\"Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pecan\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Join All Three Series Using & Operator and Display Column and Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "5        True\n",
       "6       False\n",
       "7        True\n",
       "8       False\n",
       "9       False\n",
       "11      False\n",
       "12      False\n",
       "13      False\n",
       "14      False\n",
       "15       True\n",
       "16      False\n",
       "17      False\n",
       "18      False\n",
       "19      False\n",
       "20      False\n",
       "21       True\n",
       "23      False\n",
       "24      False\n",
       "25      False\n",
       "26      False\n",
       "27      False\n",
       "28      False\n",
       "29      False\n",
       "30      False\n",
       "32      False\n",
       "        ...  \n",
       "1024    False\n",
       "1025    False\n",
       "1026    False\n",
       "1027    False\n",
       "1029    False\n",
       "1030    False\n",
       "1031    False\n",
       "1033    False\n",
       "1034    False\n",
       "1035    False\n",
       "1037     True\n",
       "1038    False\n",
       "1039    False\n",
       "1040    False\n",
       "1041    False\n",
       "1042    False\n",
       "1043     True\n",
       "1044    False\n",
       "1045    False\n",
       "1046    False\n",
       "1047    False\n",
       "1048    False\n",
       "1049    False\n",
       "1050    False\n",
       "1051    False\n",
       "1053    False\n",
       "1054    False\n",
       "1055    False\n",
       "1056     True\n",
       "1057     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ate_pies = apple_isnull & pumpkin_isnull & pecan_isnull\n",
    "\n",
    "ate_pies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    876\n",
       "True     104\n",
       "dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ate_pies.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Function that Converts 'Age' String to Appropriate Integer while Replacing '+' in Any String with ' ' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def ageStr_to_int(string):\n",
    "    if pd.isnull(string): return None\n",
    "    first_age = string.split(\" \")[0]\n",
    "    \n",
    "    return int( first_age.replace(\"+\",\"\") )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Function to Each String of 'Age' Column of Data and Assign Result to New Column of Data Called 'int_age'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data[\"int_age\"] = data[\"Age\"].apply(ageStr_to_int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Column, Corresponding Counts, and 'Age' Column Counts to Confirm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       18.0\n",
       "1       18.0\n",
       "2       18.0\n",
       "3       30.0\n",
       "4       30.0\n",
       "5       18.0\n",
       "6       18.0\n",
       "7       18.0\n",
       "8       30.0\n",
       "9       30.0\n",
       "11      30.0\n",
       "12      18.0\n",
       "13      18.0\n",
       "14      60.0\n",
       "15      30.0\n",
       "16      30.0\n",
       "17      18.0\n",
       "18      30.0\n",
       "19      30.0\n",
       "20      30.0\n",
       "21      18.0\n",
       "23      18.0\n",
       "24      30.0\n",
       "25      18.0\n",
       "26      30.0\n",
       "27      18.0\n",
       "28      30.0\n",
       "29      30.0\n",
       "30      30.0\n",
       "32      18.0\n",
       "        ... \n",
       "1024    45.0\n",
       "1025    60.0\n",
       "1026    45.0\n",
       "1027    60.0\n",
       "1029    60.0\n",
       "1030    45.0\n",
       "1031    45.0\n",
       "1033    30.0\n",
       "1034    30.0\n",
       "1035    30.0\n",
       "1037    30.0\n",
       "1038    60.0\n",
       "1039    18.0\n",
       "1040    30.0\n",
       "1041    45.0\n",
       "1042    45.0\n",
       "1043    45.0\n",
       "1044    60.0\n",
       "1045    30.0\n",
       "1046    18.0\n",
       "1047    30.0\n",
       "1048    60.0\n",
       "1049     NaN\n",
       "1050    60.0\n",
       "1051    60.0\n",
       "1053    30.0\n",
       "1054    60.0\n",
       "1055    60.0\n",
       "1056     NaN\n",
       "1057     NaN\n",
       "Name: int_age, dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_age\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45.0    269\n",
       "60.0    258\n",
       "30.0    235\n",
       "18.0    185\n",
       "Name: int_age, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_age\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45 - 59    269\n",
       "60+        258\n",
       "30 - 44    235\n",
       "18 - 29    185\n",
       "Name: Age, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Age\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examine Statistics of 'int_age' Column of Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    947.000000\n",
       "mean      40.089757\n",
       "std       15.352014\n",
       "min       18.000000\n",
       "25%       30.000000\n",
       "50%       45.000000\n",
       "75%       60.000000\n",
       "max       60.000000\n",
       "Name: int_age, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_age\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Findings\n",
    "As respondents of age 30 are older than 25% of the population, respondents of age 45 are older than 50% of the population, and respondents of age 60 are older than 75% of the population, the distribution of respondent ages are fairly uniform.  However, because we do not know the exact age of respondents and instead chose the lower bound of each age bracket, these statistics are inadequate in truly depicting the ages of respondents.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Function that Converts Income String to Appropriate Integer while Replacing '`$`' and ',' in Any String with ' '"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def incomeStr_to_int(string):\n",
    "    if pd.isnull(string): return None\n",
    "    first_income = string.split(\" \")[0] \n",
    "    \n",
    "    if first_income == \"Prefer\": return None\n",
    "    first_income = first_income.replace(\"$\", \"\")\n",
    "    \n",
    "    return int( first_income.replace(\",\", \"\") )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Function to Each Value of 'How much total combined money did all members of your HOUSEHOLD earn last year?' Column of Data and Assign Result to New Column of Data Called 'int_income'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data[\"int_income\"] = data[\"How much total combined money did all members of your HOUSEHOLD earn last year?\"].apply(incomeStr_to_int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display Column, Corresponding Counts, and 'How much total combined money did all members of your HOUSEHOLD earn last year?' Column Counts to Confirm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        75000.0\n",
       "1        50000.0\n",
       "2            0.0\n",
       "3       200000.0\n",
       "4       100000.0\n",
       "5            0.0\n",
       "6        25000.0\n",
       "7            NaN\n",
       "8        75000.0\n",
       "9        25000.0\n",
       "11       25000.0\n",
       "12           0.0\n",
       "13           0.0\n",
       "14       50000.0\n",
       "15      200000.0\n",
       "16      200000.0\n",
       "17       75000.0\n",
       "18       25000.0\n",
       "19       75000.0\n",
       "20       75000.0\n",
       "21           0.0\n",
       "23           0.0\n",
       "24       50000.0\n",
       "25      200000.0\n",
       "26       50000.0\n",
       "27      100000.0\n",
       "28           NaN\n",
       "29       75000.0\n",
       "30       25000.0\n",
       "32           NaN\n",
       "          ...   \n",
       "1024    100000.0\n",
       "1025     75000.0\n",
       "1026    175000.0\n",
       "1027     75000.0\n",
       "1029     50000.0\n",
       "1030     10000.0\n",
       "1031     75000.0\n",
       "1033     75000.0\n",
       "1034         NaN\n",
       "1035     25000.0\n",
       "1037     10000.0\n",
       "1038    100000.0\n",
       "1039     75000.0\n",
       "1040     50000.0\n",
       "1041     25000.0\n",
       "1042    125000.0\n",
       "1043     75000.0\n",
       "1044     25000.0\n",
       "1045     75000.0\n",
       "1046     10000.0\n",
       "1047     25000.0\n",
       "1048     75000.0\n",
       "1049         NaN\n",
       "1050    125000.0\n",
       "1051    125000.0\n",
       "1053    100000.0\n",
       "1054     50000.0\n",
       "1055    100000.0\n",
       "1056         NaN\n",
       "1057         NaN\n",
       "Name: int_income, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_income\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25000.0     166\n",
       "75000.0     127\n",
       "50000.0     127\n",
       "100000.0    109\n",
       "200000.0     76\n",
       "10000.0      60\n",
       "0.0          52\n",
       "125000.0     48\n",
       "150000.0     38\n",
       "175000.0     26\n",
       "Name: int_income, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_income\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "$25,000 to $49,999      166\n",
       "$75,000 to $99,999      127\n",
       "$50,000 to $74,999      127\n",
       "Prefer not to answer    118\n",
       "$100,000 to $124,999    109\n",
       "$200,000 and up          76\n",
       "$10,000 to $24,999       60\n",
       "$0 to $9,999             52\n",
       "$125,000 to $149,999     48\n",
       "$150,000 to $174,999     38\n",
       "$175,000 to $199,999     26\n",
       "Name: How much total combined money did all members of your HOUSEHOLD earn last year?, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"How much total combined money did all members of your HOUSEHOLD earn last year?\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examine Statistics of 'int_income' Column of Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       829.000000\n",
       "mean      75965.018094\n",
       "std       59068.636748\n",
       "min           0.000000\n",
       "25%       25000.000000\n",
       "50%       75000.000000\n",
       "75%      100000.000000\n",
       "max      200000.000000\n",
       "Name: int_income, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"int_income\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Findings\n",
    "As with the age of the respondents, we chose the lower bound of each income bracket and therefore do not have a reliable measure of the true statistics governing the respondents' income.  However, from that lower bound, it appears the average income of respondents is quite high at near $76,000.  The high standard deviation, though, signifies huge fluctuations in the respondents' income about this mean and, thus, a large range of incomes between the minimum and maximum values.   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter Out 'int_income' < 150000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "int_income_lt_150000 = data[data[\"int_income\"] < 150000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Responses to 'How far will you travel for Thanksgiving?' and Display Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Thanksgiving is happening at my home--I won't travel at all                         281\n",
       "Thanksgiving is local--it will take place in the town I live in                     203\n",
       "Thanksgiving is out of town but not too far--it's a drive of a few hours or less    150\n",
       "Thanksgiving is out of town and far away--I have to drive several hours or fly       55\n",
       "Name: How far will you travel for Thanksgiving?, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "int_income_lt_150000[\"How far will you travel for Thanksgiving?\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter Out 'int_income' > 150000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "int_income_gt_150000 = data[data[\"int_income\"] > 150000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Responses to 'How far will you travel for Thanksgiving?' and Display Corresponding Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Thanksgiving is happening at my home--I won't travel at all                         49\n",
       "Thanksgiving is local--it will take place in the town I live in                     25\n",
       "Thanksgiving is out of town but not too far--it's a drive of a few hours or less    16\n",
       "Thanksgiving is out of town and far away--I have to drive several hours or fly      12\n",
       "Name: How far will you travel for Thanksgiving?, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "int_income_gt_150000[\"How far will you travel for Thanksgiving?\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Findings\n",
    "It appears there is a greater fraction of high-income people (~48%) that has Thanksgiving at home than the corresponding fraction of low-income people (~41%).  Younger people, typically students and those just starting out in the workforce, earn less income and thereby travel for Thanksgiving out of a necessity to save.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate and Display Pivot Table Showing Average Age of Respondents for Responses to 'Have you ever tried to meet up with hometown friends on Thanksgiving night?' and 'Have you ever attended a \"Friendsgiving?' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Have you ever attended a \"Friendsgiving?\"</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Have you ever tried to meet up with hometown friends on Thanksgiving night?</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>42.283702</td>\n",
       "      <td>37.010526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>41.475410</td>\n",
       "      <td>33.976744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Have you ever attended a \"Friendsgiving?\"                  No        Yes\n",
       "Have you ever tried to meet up with hometown fr...                      \n",
       "No                                                  42.283702  37.010526\n",
       "Yes                                                 41.475410  33.976744"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(\n",
    "    index=\"Have you ever tried to meet up with hometown friends on Thanksgiving night?\",\n",
    "    columns='Have you ever attended a \"Friendsgiving?\"',\n",
    "    values=\"int_age\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate and Display Pivot Table Showing Average Income of Respondents for Responses to 'Have you ever tried to meet up with hometown friends on Thanksgiving night?' and 'Have you ever attended a \"Friendsgiving?' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Have you ever attended a \"Friendsgiving?\"</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Have you ever tried to meet up with hometown friends on Thanksgiving night?</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>78914.549654</td>\n",
       "      <td>72894.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>78750.000000</td>\n",
       "      <td>66019.736842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Have you ever attended a \"Friendsgiving?\"                     No           Yes\n",
       "Have you ever tried to meet up with hometown fr...                            \n",
       "No                                                  78914.549654  72894.736842\n",
       "Yes                                                 78750.000000  66019.736842"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.pivot_table(\n",
    "    index=\"Have you ever tried to meet up with hometown friends on Thanksgiving night?\",\n",
    "    columns='Have you ever attended a \"Friendsgiving?\"',\n",
    "    values=\"int_income\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Findings\n",
    "Younger people, on average, attend 'Friendsgiving' as well as meet up with hometown friends on Thanksgiving night.  Confirmation of this young age, as established in a previous link between younger age and lower income, is provided by the corresponding average income from the 2nd pivot table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Value_Counts Function to Dessert Columns of Data and Assign Result to Dessert_Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dessert_cols = [col for col in data.columns if 'dessert' in col]\n",
    "\n",
    "dessert_counts = data[dessert_cols].apply(pd.Series.value_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Max Function to Dessert_Counts and Display Result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Apple cobbler               110.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Blondies                     16.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Brownies                    128.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Carrot cake                  72.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Cheesecake                  191.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Cookies                     204.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Fudge                        43.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Ice cream                   266.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Peach cobbler               103.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - None                        295.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Other (please specify)      134.0\n",
       "Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply.   - Other (please specify).1     13.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dessert_counts.apply(pd.Series.max)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Findings\n",
    "The most common dessert people eat at Thanksgiving is ice cream.  "
   ]
  }
 ],
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