ch1and2-exercises_with_solutions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 1 & 2: Practice Exercises with Solutions\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this exercise, you will gain insight into public health by generating simple graphical and numerical summaries of a dataset collected by the U.S. Centers for Disease Control and Prevention (CDC).\n",
    "\n",
    "The Behavioral Risk Factor Surveillance System (BRFSS) is an annual telephone survey of 350,000 people in the United States. As its name implies, the BRFSS is designed to identify risk factors in the adult population and report emerging health trends. For example, respondents are asked about their diet and weekly physical activity, their HIV/AIDS status, possible tobacco use, and even their level of healthcare coverage.\n",
    "\n",
    "Data source: https://www.cdc.gov/brfss/\n",
    "\n",
    "In this exercise, we will focus on a random sample of 20,000 people from the BRFSS survey conducted in 2000. While there are over 200 variables in this data set, we will work with a small subset.\n",
    "\n",
    "The data set is available as a CSV file named `cdc.csv` (Download from [here](https://raw.githubusercontent.com/imranture/practice_stats/main/datasets/cdc.csv))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 1:** Place the CSV file under the same directory where your Jupyter Notebook file is. Import Pandas as \"pd\" and NumPy as \"np\". Read the data into a Pandas data frame called `df`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = pd.read_csv('datasets/cdc.csv')  ## Update the directory before running this cell."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 2:** How many observations are there in this dataset?\n",
    "\n",
    "**Hint:** Use `shape()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 3:** Display the first 10 rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genhlth</th>\n",
       "      <th>exerany</th>\n",
       "      <th>hlthplan</th>\n",
       "      <th>smoke100</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>wtdesire</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>175</td>\n",
       "      <td>175</td>\n",
       "      <td>77</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>64</td>\n",
       "      <td>125</td>\n",
       "      <td>115</td>\n",
       "      <td>33</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>49</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>66</td>\n",
       "      <td>132</td>\n",
       "      <td>124</td>\n",
       "      <td>42</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>very good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>150</td>\n",
       "      <td>130</td>\n",
       "      <td>55</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>very good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>55</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>very good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71</td>\n",
       "      <td>194</td>\n",
       "      <td>185</td>\n",
       "      <td>31</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>very good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>170</td>\n",
       "      <td>160</td>\n",
       "      <td>45</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "      <td>150</td>\n",
       "      <td>130</td>\n",
       "      <td>27</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>180</td>\n",
       "      <td>170</td>\n",
       "      <td>44</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     genhlth  exerany  hlthplan  smoke100  height  weight  wtdesire  age  \\\n",
       "0       good        0         1         0      70     175       175   77   \n",
       "1       good        0         1         1      64     125       115   33   \n",
       "2       good        1         1         1      60     105       105   49   \n",
       "3       good        1         1         0      66     132       124   42   \n",
       "4  very good        0         1         0      61     150       130   55   \n",
       "5  very good        1         1         0      64     114       114   55   \n",
       "6  very good        1         1         0      71     194       185   31   \n",
       "7  very good        0         1         0      67     170       160   45   \n",
       "8       good        0         1         1      65     150       130   27   \n",
       "9       good        1         1         0      70     180       170   44   \n",
       "\n",
       "  gender  \n",
       "0      m  \n",
       "1      f  \n",
       "2      f  \n",
       "3      f  \n",
       "4      f  \n",
       "5      f  \n",
       "6      m  \n",
       "7      m  \n",
       "8      f  \n",
       "9      m  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 4:** How many variables are there in this dataset? For each variable, identify its data type (e.g., categorical, numerical).\n",
    "\n",
    "**Hint:** Try using Pandas' `dtypes()` method on your data frame. In the output of this method, `object` data type (\"dtype\") stands for a string type, which usually indicates a categorical variable. However, some numerical variables can actually be categorical in nature (think about `hlthplan`, for instance)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genhlth     object\n",
      "exerany      int64\n",
      "hlthplan     int64\n",
      "smoke100     int64\n",
      "height       int64\n",
      "weight       int64\n",
      "wtdesire     int64\n",
      "age          int64\n",
      "gender      object\n",
      "dtype: object\n",
      "\n",
      "Categorical variables: \n",
      "genhlth (ordinal), exerany, hlthplan, smoke100 and gender\n",
      "\n",
      "Numerical variables: \n",
      "height, weight, wtdesire and age\n"
     ]
    }
   ],
   "source": [
    "print(df.dtypes)\n",
    "\n",
    "print('''\n",
    "Categorical variables: \n",
    "genhlth (ordinal), exerany, hlthplan, smoke100 and gender''')\n",
    "\n",
    "print('''\n",
    "Numerical variables: \n",
    "height, weight, wtdesire and age''')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 5:**  State how many levels each categorical variable has. Print all the levels for each categorical variable.\n",
    "\n",
    "**Hint:** Use Pandas' `unique()` and `nunique()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column: genhlth\n",
      "['good' 'very good' 'excellent' 'fair' 'poor']\n",
      "There are 5 levels in genhlth categorical variable.\n",
      "\n",
      "column: exerany\n",
      "[0 1]\n",
      "There are 2 levels in exerany categorical variable.\n",
      "\n",
      "column: hlthplan\n",
      "[1 0]\n",
      "There are 2 levels in hlthplan categorical variable.\n",
      "\n",
      "column: smoke100\n",
      "[0 1]\n",
      "There are 2 levels in smoke100 categorical variable.\n",
      "\n",
      "column: gender\n",
      "['m' 'f']\n",
      "There are 2 levels in gender categorical variable.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "categorical_variables = ['genhlth', 'exerany', 'hlthplan', 'smoke100', 'gender']\n",
    "\n",
    "for col in categorical_variables:\n",
    "    print(f'column: {col}')\n",
    "    print(f'{df[col].unique()}')\n",
    "    print(f'There are {df[col].nunique()} levels in {col} categorical variable.\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 6:** Find the mean, sample standard deviation, and median of `weight`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:  169.68\n",
      "std:  40.08\n",
      "median:  165.0\n"
     ]
    }
   ],
   "source": [
    "print('mean: ', df['weight'].mean().round(2))\n",
    "print('std: ', df['weight'].std(ddof = 1).round(2))\n",
    "print('median: ', df['weight'].median())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 7:** Find the mean, sample standard deviation, and median of `weight` for respondents who exercised in the past month. Is there any significant difference in the results when compared to the results of Exercise 6?\n",
    "\n",
    "**Hint:** `exerany` is the variable that is 1 if the respondent exercised in the past month and 0 otherwise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:  169.04\n",
      "std:  38.83\n",
      "median:  165.0\n"
     ]
    }
   ],
   "source": [
    "print('mean: ', df[df['exerany'] == 1]['weight'].mean().round(2))\n",
    "print('std: ', df[df['exerany'] == 1]['weight'].std(ddof = 1).round(2))\n",
    "print('median: ', df[df['exerany'] == 1]['weight'].median())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compared with the previous results, there seems to be no significant difference."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 8:** Compute the 5-number summary for `wtdesire`, respondent's desired weight in pound, in ascending order (that is, min, Q1, Q2 (median), Q3, and max). Also compute the interquartile range (IQR) for this variable (which is Q3-Q1). In addition, compute max upper whisker reach and max lower whisker reach. Based on these values, how many outliers are there for `wtdesire`? Finally, using Matplotlib, create a boxplot for this variable.\n",
    "\n",
    "**Hint:** For quantiles, you can use NumPy' `quantile()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min: 68\n",
      "q1: 130.0\n",
      "q2 (median): 150.0\n",
      "q3: 175.0\n",
      "max: 680\n",
      "IQR: 45.0\n"
     ]
    }
   ],
   "source": [
    "min_val = df['wtdesire'].min()\n",
    "q1_val  = df['wtdesire'].quantile(0.25)\n",
    "q2_val  = df['wtdesire'].quantile(0.50)  # this is also the median\n",
    "q3_val  = df['wtdesire'].quantile(0.75)\n",
    "max_val = df['wtdesire'].max()\n",
    "iqr     = q3_val - q1_val\n",
    "\n",
    "print('min:', min_val)\n",
    "print('q1:', q1_val)\n",
    "print('q2 (median):', q2_val)\n",
    "print('q3:', q3_val)\n",
    "print('max:', max_val)\n",
    "print('IQR:', iqr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max_whisker: 242.5\n",
      "min_whisker: 62.5\n"
     ]
    }
   ],
   "source": [
    "max_whisker = q3_val + 1.5*iqr\n",
    "min_whisker = q1_val - 1.5*iqr\n",
    "print('max_whisker:', max_whisker)\n",
    "print('min_whisker:', min_whisker)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16873    680\n",
      "10033    601\n",
      "13606    350\n",
      "1615     325\n",
      "9110     325\n",
      "Name: wtdesire, dtype: int64\n",
      "Number of \"wtdesire\" outliers: 175\n"
     ]
    }
   ],
   "source": [
    "wtdesire_outliers = df[(df['wtdesire'] < min_whisker) | \n",
    "                        (df['wtdesire'] > max_whisker)]['wtdesire']\n",
    "\n",
    "# print the highest 5 wtdesire outlier values\n",
    "print(wtdesire_outliers.sort_values(ascending = False).head())\n",
    "\n",
    "print('Number of \"wtdesire\" outliers:', wtdesire_outliers.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 452,
       "width": 831
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline \n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.style.use(\"ggplot\")\n",
    "plt.rcParams['figure.figsize'] = (10, 5)\n",
    "\n",
    "plt.boxplot(x = df['wtdesire'])\n",
    "plt.title(\"Boxplot of wtdesire\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 9:** Let's consider a new variable: the difference between desired weight (`wtdesire`) and current weight (`weight`). Create this new variable by subtracting the two columns in the `df` data frame and assigning them to a new variable called `wdiff`. Display the first 5 rows of `df`. How many columns are there?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genhlth</th>\n",
       "      <th>exerany</th>\n",
       "      <th>hlthplan</th>\n",
       "      <th>smoke100</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>wtdesire</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>wdiff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>175</td>\n",
       "      <td>175</td>\n",
       "      <td>77</td>\n",
       "      <td>m</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>64</td>\n",
       "      <td>125</td>\n",
       "      <td>115</td>\n",
       "      <td>33</td>\n",
       "      <td>f</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>49</td>\n",
       "      <td>f</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>good</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>66</td>\n",
       "      <td>132</td>\n",
       "      <td>124</td>\n",
       "      <td>42</td>\n",
       "      <td>f</td>\n",
       "      <td>-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>very good</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>150</td>\n",
       "      <td>130</td>\n",
       "      <td>55</td>\n",
       "      <td>f</td>\n",
       "      <td>-20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     genhlth  exerany  hlthplan  smoke100  height  weight  wtdesire  age  \\\n",
       "0       good        0         1         0      70     175       175   77   \n",
       "1       good        0         1         1      64     125       115   33   \n",
       "2       good        1         1         1      60     105       105   49   \n",
       "3       good        1         1         0      66     132       124   42   \n",
       "4  very good        0         1         0      61     150       130   55   \n",
       "\n",
       "  gender  wdiff  \n",
       "0      m      0  \n",
       "1      f    -10  \n",
       "2      f      0  \n",
       "3      f     -8  \n",
       "4      f    -20  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['wdiff'] = df['wtdesire'] - df['weight']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 10:** What percent of respondents' `wdiff` is zero? Comment on the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Only 28.08% of the respondents are happy with their current weight.\n"
     ]
    }
   ],
   "source": [
    "wdiff_zero = df['wdiff'][df['wdiff'] == 0].shape[0] / df.shape[0] * 100\n",
    "\n",
    "print(f'Only {wdiff_zero}% of the respondents are happy with their current weight.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 11:** What percent of respondents think they are overweight, that is, their `wdiff` value is less than 0? What percent of respondents think they are underweight?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Only 8.1% of the respondents think they are underweight.\n",
      "About 63.82% of the respondents think they are overweight.\n"
     ]
    }
   ],
   "source": [
    "underweight = df['wdiff'][df['wdiff'] > 0].shape[0] / df.shape[0] * 100\n",
    "overweight = df['wdiff'][df['wdiff'] < 0].shape[0] / df.shape[0] * 100\n",
    "\n",
    "print(f'Only {underweight}% of the respondents think they are underweight.')\n",
    "print(f'About {overweight}% of the respondents think they are overweight.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 12:** Create a side-by-side boxplot to determine if men tend to view their weight differently than women.\n",
    "\n",
    "**Hint**: For this, you will need to use the *seaborn* module."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 450,
       "width": 864
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.boxplot(x = df['gender'], y = df['wdiff'])\n",
    "plt.show(); "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There seems to be no significant difference between actual weight and desired weight distribution for men vs. women."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 13:**  Generate a histogram of `age` with the bin size of 7. Comment on the skewness and modality of this histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 452,
       "width": 862
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['age'].plot(kind = 'hist', color = 'salmon', edgecolor = 'black', \n",
    "                linewidth = 1.2, title = 'Histogram of age', bins = 7)\n",
    "plt.show(); "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This histogram suggests a unimodal, right-skewed distribution for age."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 14:** Make a scatterplot of weight versus desired weight. Set the fill color as blue and alpha level as 0.3. Describe the relationship between these two variables.\n",
    "\n",
    "**Bonus**: Also fit a red line with a slope of 1 and an intercept value of 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 474,
       "width": 853
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_line(axis, slope, intercept, **kargs):\n",
    "    xmin, xmax = axis.get_xlim()\n",
    "    plt.plot([xmin, xmax], [xmin*slope + intercept, xmax*slope + intercept], **kargs)\n",
    "    \n",
    "x = df['weight']\n",
    "y = df['wtdesire']\n",
    "plt.scatter(x, y,  c = 'blue', alpha = 0.3)\n",
    "plot_line(axis = plt.gca(), slope = 1, intercept = 0, color = \"red\")\n",
    "plt.xlabel('Actual Weight')\n",
    "plt.ylabel('Desired Weight')\n",
    "plt.title('Actual vs. Desired Weight')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the weight increases, the desired weight also increases,\n",
    "but not as much the weight itself. There are more respondents\n",
    "who think they are overweight compared to underweight\n",
    "(more points under the line compared to over the line)."
   ]
  }
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