{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b96ce1ee",
   "metadata": {},
   "source": [
    "# Chapter 3: Summarizing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2b63c1dc-ef9e-460e-b91d-1c053171d64b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sidetable\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy.stats import norm\n",
    "\n",
    "\n",
    "import rpy2.robjects as ro\n",
    "from rpy2.robjects.packages import importr\n",
    "from rpy2.robjects import pandas2ri\n",
    "pandas2ri.activate()\n",
    "from rpy2.robjects.conversion import localconverter\n",
    "# import NHANES package\n",
    "base = importr('NHANES')\n",
    "\n",
    "with localconverter(ro.default_converter + pandas2ri.converter):\n",
    "  NHANES = ro.conversion.rpy2py(ro.r['NHANES'])\n",
    "\n",
    " \n",
    "NHANES = NHANES.drop_duplicates(subset='ID')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b982c75e-2986-4cf3-8b91-cf818a0c2be5",
   "metadata": {},
   "source": [
    "## Table 3.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eae1bc6e-96ca-4e34-8824-b8a67a8fc845",
   "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>PhysActive</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>2972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>2473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>1334</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PhysActive\n",
       "Yes        2972\n",
       "No         2473\n",
       "NaN        1334"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(NHANES.PhysActive.value_counts(dropna=False))\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1b9938e-ca6d-4599-a69b-debf5515afdc",
   "metadata": {},
   "source": [
    "## Table 3.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "beb448b8-c3e1-47be-9ab1-b6b4a094e806",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "</style>\n",
       "<table id=\"T_c8549\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th id=\"T_c8549_level0_col0\" class=\"col_heading level0 col0\" >PhysActive</th>\n",
       "      <th id=\"T_c8549_level0_col1\" class=\"col_heading level0 col1\" >AbsoluteFrequency</th>\n",
       "      <th id=\"T_c8549_level0_col2\" class=\"col_heading level0 col2\" >Percentage</th>\n",
       "      <th id=\"T_c8549_level0_col3\" class=\"col_heading level0 col3\" >RelativeFrequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td id=\"T_c8549_row0_col0\" class=\"data row0 col0\" >Yes</td>\n",
       "      <td id=\"T_c8549_row0_col1\" class=\"data row0 col1\" >2972</td>\n",
       "      <td id=\"T_c8549_row0_col2\" class=\"data row0 col2\" >54.582185</td>\n",
       "      <td id=\"T_c8549_row0_col3\" class=\"data row0 col3\" >0.545822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_c8549_row1_col0\" class=\"data row1 col0\" >No</td>\n",
       "      <td id=\"T_c8549_row1_col1\" class=\"data row1 col1\" >2473</td>\n",
       "      <td id=\"T_c8549_row1_col2\" class=\"data row1 col2\" >45.417815</td>\n",
       "      <td id=\"T_c8549_row1_col3\" class=\"data row1 col3\" >0.454178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9abefddd60>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_df = NHANES.stb.freq(['PhysActive']).drop(\n",
    "    ['cumulative_count', 'cumulative_percent'], axis=1)\n",
    "table_df['RelativeFrequency'] = table_df.percent / 100\n",
    "table_df = table_df.rename(columns={\n",
    "    'count': 'AbsoluteFrequency',\n",
    "    'percent': 'Percentage'})\n",
    "table_df.style.hide(axis=\"index\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9bb9c5c-f736-4ec7-9f5d-140189b29b19",
   "metadata": {},
   "source": [
    "## Table 3.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "26a69432-3104-4928-bf5e-8faf0af496ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "</style>\n",
       "<table id=\"T_55da3\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th id=\"T_55da3_level0_col0\" class=\"col_heading level0 col0\" >SleepHrsNight</th>\n",
       "      <th id=\"T_55da3_level0_col1\" class=\"col_heading level0 col1\" >AbsoluteFrequency</th>\n",
       "      <th id=\"T_55da3_level0_col2\" class=\"col_heading level0 col2\" >Percentage</th>\n",
       "      <th id=\"T_55da3_level0_col3\" class=\"col_heading level0 col3\" >RelativeFrequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row0_col0\" class=\"data row0 col0\" >2</td>\n",
       "      <td id=\"T_55da3_row0_col1\" class=\"data row0 col1\" >9</td>\n",
       "      <td id=\"T_55da3_row0_col2\" class=\"data row0 col2\" >0.178749</td>\n",
       "      <td id=\"T_55da3_row0_col3\" class=\"data row0 col3\" >0.001787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row1_col0\" class=\"data row1 col0\" >3</td>\n",
       "      <td id=\"T_55da3_row1_col1\" class=\"data row1 col1\" >49</td>\n",
       "      <td id=\"T_55da3_row1_col2\" class=\"data row1 col2\" >0.973188</td>\n",
       "      <td id=\"T_55da3_row1_col3\" class=\"data row1 col3\" >0.009732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row2_col0\" class=\"data row2 col0\" >4</td>\n",
       "      <td id=\"T_55da3_row2_col1\" class=\"data row2 col1\" >200</td>\n",
       "      <td id=\"T_55da3_row2_col2\" class=\"data row2 col2\" >3.972195</td>\n",
       "      <td id=\"T_55da3_row2_col3\" class=\"data row2 col3\" >0.039722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row3_col0\" class=\"data row3 col0\" >5</td>\n",
       "      <td id=\"T_55da3_row3_col1\" class=\"data row3 col1\" >406</td>\n",
       "      <td id=\"T_55da3_row3_col2\" class=\"data row3 col2\" >8.063555</td>\n",
       "      <td id=\"T_55da3_row3_col3\" class=\"data row3 col3\" >0.080636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row4_col0\" class=\"data row4 col0\" >6</td>\n",
       "      <td id=\"T_55da3_row4_col1\" class=\"data row4 col1\" >1172</td>\n",
       "      <td id=\"T_55da3_row4_col2\" class=\"data row4 col2\" >23.277061</td>\n",
       "      <td id=\"T_55da3_row4_col3\" class=\"data row4 col3\" >0.232771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row5_col0\" class=\"data row5 col0\" >7</td>\n",
       "      <td id=\"T_55da3_row5_col1\" class=\"data row5 col1\" >1394</td>\n",
       "      <td id=\"T_55da3_row5_col2\" class=\"data row5 col2\" >27.686197</td>\n",
       "      <td id=\"T_55da3_row5_col3\" class=\"data row5 col3\" >0.276862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row6_col0\" class=\"data row6 col0\" >8</td>\n",
       "      <td id=\"T_55da3_row6_col1\" class=\"data row6 col1\" >1405</td>\n",
       "      <td id=\"T_55da3_row6_col2\" class=\"data row6 col2\" >27.904667</td>\n",
       "      <td id=\"T_55da3_row6_col3\" class=\"data row6 col3\" >0.279047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row7_col0\" class=\"data row7 col0\" >9</td>\n",
       "      <td id=\"T_55da3_row7_col1\" class=\"data row7 col1\" >271</td>\n",
       "      <td id=\"T_55da3_row7_col2\" class=\"data row7 col2\" >5.382324</td>\n",
       "      <td id=\"T_55da3_row7_col3\" class=\"data row7 col3\" >0.053823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row8_col0\" class=\"data row8 col0\" >10</td>\n",
       "      <td id=\"T_55da3_row8_col1\" class=\"data row8 col1\" >97</td>\n",
       "      <td id=\"T_55da3_row8_col2\" class=\"data row8 col2\" >1.926514</td>\n",
       "      <td id=\"T_55da3_row8_col3\" class=\"data row8 col3\" >0.019265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row9_col0\" class=\"data row9 col0\" >11</td>\n",
       "      <td id=\"T_55da3_row9_col1\" class=\"data row9 col1\" >15</td>\n",
       "      <td id=\"T_55da3_row9_col2\" class=\"data row9 col2\" >0.297915</td>\n",
       "      <td id=\"T_55da3_row9_col3\" class=\"data row9 col3\" >0.002979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_55da3_row10_col0\" class=\"data row10 col0\" >12</td>\n",
       "      <td id=\"T_55da3_row10_col1\" class=\"data row10 col1\" >17</td>\n",
       "      <td id=\"T_55da3_row10_col2\" class=\"data row10 col2\" >0.337637</td>\n",
       "      <td id=\"T_55da3_row10_col3\" class=\"data row10 col3\" >0.003376</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9abefddcd0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NHANES_sleep = NHANES.query('SleepHrsNight > 0')\n",
    "table_df = NHANES_sleep.stb.freq(\n",
    "    ['SleepHrsNight'])\n",
    "table_df['RelativeFrequency'] = table_df.percent / 100\n",
    "table_df = table_df.rename(columns={\n",
    "    'count': 'AbsoluteFrequency',\n",
    "    'percent': 'Percentage'}).sort_values(by='SleepHrsNight').drop(\n",
    "    ['cumulative_count', 'cumulative_percent'], axis=1)\n",
    "\n",
    "table_df.style.hide(axis=\"index\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0146d77a-e3a2-474b-9d99-3a216d3efcf6",
   "metadata": {
    "Rmd_chunk_options": "sleepTable, echo=FALSE",
    "jupyter": {
     "output_hidden": false
    },
    "kernel": "R",
    "tags": [
     "report_output"
    ]
   },
   "source": [
    "## Figure 3.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "42b6b996-8d9d-4b86-9009-d0bc99a94e33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='SleepHrsNight', ylabel='Density'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12,8))\n",
    "\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight, ax=ax[0], discrete=True)\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight, ax=ax[1], stat='density', discrete=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68269149-b4d5-4c8c-9719-a1832e20a928",
   "metadata": {},
   "source": [
    "## Figure 3.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c85c7afe-6c62-444d-a694-896332afb88d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='SleepHrsNight', ylabel='Density'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12,8))\n",
    "\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight, ax=ax[0],\n",
    "             element=\"step\", fill=False, cumulative=True, )\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight,  ax=ax[0], discrete=True)\n",
    "\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight, ax=ax[1], stat='density',\n",
    "             element=\"step\", fill=False, cumulative=True, )\n",
    "sns.histplot(NHANES_sleep.SleepHrsNight, ax=ax[1], stat='density', discrete=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28cff840",
   "metadata": {},
   "source": [
    "## Figure 3.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f7834618-f08e-4351-b9b8-98b746f28cb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='Height', ylabel='Count'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12,8))\n",
    "\n",
    "sns.histplot(NHANES.Age, binwidth=1, ax=ax[0])\n",
    "\n",
    "sns.histplot(NHANES.Height, binwidth=1, ax=ax[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e97ae2fc-84af-4290-b2e0-98d806933b2b",
   "metadata": {},
   "source": [
    "## Figure 3.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6579c71f-636f-4f11-97f0-2c9b20bcf07c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'B. Adults only (bin width=.1)')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 2, figsize=(12,8))\n",
    "\n",
    "NHANES['isChild'] = NHANES.Age < 18\n",
    "NHANES_adult = NHANES.dropna(subset=['Age', 'Height']).query('Age > 17')\n",
    "\n",
    "sns.histplot(NHANES, x='Height', hue='isChild', binwidth=1, ax=ax[0][0])\n",
    "ax[0][0].set_title('A. All individuals')\n",
    "\n",
    "sns.histplot(NHANES_adult, x='Height',  binwidth=1, ax=ax[0][1])\n",
    "ax[0][0].set_title('B. Adults only')\n",
    "\n",
    "sns.histplot(NHANES_adult, x='Height',  binwidth=.1, ax=ax[1][0])\n",
    "ax[1][0].set_title('B. Adults only (bin width=.1)')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "007068a4",
   "metadata": {},
   "source": [
    "## Table 3.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fc59496c-7633-44a5-b040-ca8ae408c024",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "96     169.6\n",
       "97     169.8\n",
       "101    167.5\n",
       "102    155.2\n",
       "104    173.8\n",
       "107    174.5\n",
       "Name: Height, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NHANES_adult['Height'][44:50]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ab33695-d56c-46fb-a26a-58d3a2c4ee98",
   "metadata": {},
   "source": [
    "## Figure 3.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b19a1613-d650-4d6f-9bfd-50c9b1b23eca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first update the summary to include the mean and standard deviation of each\n",
    "# dataset\n",
    "# NOTE: some NA values get turned into large negative numbers in the conversion from R, so remove those\n",
    "\n",
    "pulsedata = NHANES_adult.dropna(subset=['Pulse']).query('Pulse > 0')[['Pulse']]\n",
    "heightdata = NHANES_adult.dropna(subset=['Height']).query('Height > 0')[['Height']]\n",
    "\n",
    "pulse_summary = pulsedata.describe()\n",
    "pulse_summary.loc['binwidth'] = np.diff(np.histogram_bin_edges(pulsedata.Pulse, 'fd'))[0]\n",
    "\n",
    "height_summary = heightdata.describe()\n",
    "height_summary.loc['binwidth'] = np.diff(np.histogram_bin_edges(heightdata.Height, 'fd'))[0]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4f46878f-0cfb-4b13-aa13-f6d83394bba2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9a821aa0a0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "heightDist = pd.DataFrame({'x': np.arange(height_summary.loc['min'][0], height_summary.loc['max'][0], .1)})\n",
    "heightDist['norm'] = norm.pdf(\n",
    "    heightDist.x, height_summary.loc['mean'][0], height_summary.loc['std'])\n",
    "\n",
    "pulseDist = pd.DataFrame({'x': np.arange(pulse_summary.loc['min'][0], pulse_summary.loc['max'][0], .1)})\n",
    "pulseDist['norm'] = norm.pdf(\n",
    "    pulseDist.x, pulse_summary.loc['mean'][0], pulse_summary.loc['std'])\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(12,8))\n",
    "\n",
    "sns.histplot(heightdata.Height, stat='density', binwidth=height_summary.loc['binwidth'][0], color='gray', ax=ax[0])\n",
    "ax[0].plot(heightDist.x, heightDist.norm, lw=2, color='b')\n",
    "\n",
    "sns.histplot(pulsedata.Pulse, stat='density', binwidth=pulse_summary.loc['binwidth'][0], color='gray', ax=ax[1])\n",
    "ax[1].plot(pulseDist.x, pulseDist.norm, lw=2, color='b')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bf2957d-5fe8-4594-9d9b-1c5806ded771",
   "metadata": {},
   "source": [
    "## Figure 3.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9093c121-86c2-48a9-a998-950fa2915438",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9a81f91ca0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waittimes = pd.read_csv('https://raw.githubusercontent.com/statsthinking21/statsthinking21-figures-data/main/04/sfo_wait_times_2017.csv')\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(12,8))\n",
    "sns.histplot(waittimes.waittime, binwidth=1, ax=ax[0])\n",
    "\n",
    "fbdata = pd.read_csv('https://raw.githubusercontent.com/statsthinking21/statsthinking21-figures-data/main/04/facebook_combined.txt', names=['V1', 'V2'], delimiter=' ')\n",
    "friends_table = fbdata.groupby('V1').count()\n",
    "sns.histplot(friends_table.V2, binwidth=2, ax=ax[1])\n",
    "plt.plot([friends_table.max()['V2']], [5], marker='.', markersize=14, color='k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8278b781-c089-498c-bad9-5a3448dbfeb3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "Rmd_chunk_options": {
   "output": {
    "bookdown::gitbook": {
     "includes": {
      "in_header": "google_analytics.html"
     },
     "lib_dir": "book_assets"
    },
    "html_document": "default",
    "pdf_document": "default"
   }
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
  },
  "sos": {
   "kernels": [
    [
     "SoS",
     "sos",
     "",
     ""
    ],
    [
     "R",
     "ir",
     "",
     ""
    ],
    [
     "Markdown",
     "markdown",
     "",
     ""
    ]
   ]
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}