3. Working with text files.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with text files\n",
    "\n",
    "### Bogumił Kamiński\n",
    "\n",
    "In this notebook we will show how one can interact with CSV files when working with DataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m project at `~/JuliaAcademy-DataFrames`\n"
     ]
    }
   ],
   "source": [
    "] activate ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "using DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "using CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Arrow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we download the data set we will work with and save it as auto.txt file in a current working directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"auto.txt\""
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "download(\"https://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data-original\",\n",
    "         \"auto.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us check how the file looks inside using the `readlines` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406-element Vector{String}:\n",
       " \"18.0   8.   307.0      130.0   \" ⋯ 25 bytes ⋯ \" 1.\\t\\\"chevrolet chevelle malibu\\\"\"\n",
       " \"15.0   8.   350.0      165.0   \" ⋯ 17 bytes ⋯ \"5   70.  1.\\t\\\"buick skylark 320\\\"\"\n",
       " \"18.0   8.   318.0      150.0   \" ⋯ 18 bytes ⋯ \"   70.  1.\\t\\\"plymouth satellite\\\"\"\n",
       " \"16.0   8.   304.0      150.0      3433.      12.0   70.  1.\\t\\\"amc rebel sst\\\"\"\n",
       " \"17.0   8.   302.0      140.0      3449.      10.5   70.  1.\\t\\\"ford torino\\\"\"\n",
       " \"15.0   8.   429.0      198.0      4341.      10.0   70.  1.\\t\\\"ford galaxie 500\\\"\"\n",
       " \"14.0   8.   454.0      220.0      4354.       9.0   70.  1.\\t\\\"chevrolet impala\\\"\"\n",
       " \"14.0   8.   440.0      215.0   \" ⋯ 17 bytes ⋯ \"5   70.  1.\\t\\\"plymouth fury iii\\\"\"\n",
       " \"14.0   8.   455.0      225.0      4425.      10.0   70.  1.\\t\\\"pontiac catalina\\\"\"\n",
       " \"15.0   8.   390.0      190.0   \" ⋯ 18 bytes ⋯ \"   70.  1.\\t\\\"amc ambassador dpl\\\"\"\n",
       " \"NA     4.   133.0      115.0   \" ⋯ 20 bytes ⋯ \" 70.  2.\\t\\\"citroen ds-21 pallas\\\"\"\n",
       " \"NA     8.   350.0      165.0   \" ⋯ 32 bytes ⋯ \"evrolet chevelle concours (sw)\\\"\"\n",
       " \"NA     8.   351.0      153.0      4034.      11.0   70.  1.\\t\\\"ford torino (sw)\\\"\"\n",
       " ⋮\n",
       " \"25.0   6.   181.0      110.0   \" ⋯ 21 bytes ⋯ \"82.  1.\\t\\\"buick century limited\\\"\"\n",
       " \"38.0   6.   262.0      85.00   \" ⋯ 33 bytes ⋯ \"smobile cutlass ciera (diesel)\\\"\"\n",
       " \"26.0   4.   156.0      92.00   \" ⋯ 26 bytes ⋯ \"1.\\t\\\"chrysler lebaron medallion\\\"\"\n",
       " \"22.0   6.   232.0      112.0      2835       14.7   82.  1.\\t\\\"ford granada l\\\"\"\n",
       " \"32.0   4.   144.0      96.00      2665.      13.9   82.  3.\\t\\\"toyota celica gt\\\"\"\n",
       " \"36.0   4.   135.0      84.00   \" ⋯ 17 bytes ⋯ \"0   82.  1.\\t\\\"dodge charger 2.2\\\"\"\n",
       " \"27.0   4.   151.0      90.00      2950.      17.3   82.  1.\\t\\\"chevrolet camaro\\\"\"\n",
       " \"27.0   4.   140.0      86.00      2790.      15.6   82.  1.\\t\\\"ford mustang gl\\\"\"\n",
       " \"44.0   4.   97.00      52.00      2130.      24.6   82.  2.\\t\\\"vw pickup\\\"\"\n",
       " \"32.0   4.   135.0      84.00      2295.      11.6   82.  1.\\t\\\"dodge rampage\\\"\"\n",
       " \"28.0   4.   120.0      79.00      2625.      18.6   82.  1.\\t\\\"ford ranger\\\"\"\n",
       " \"31.0   4.   119.0      82.00      2720.      19.4   82.  1.\\t\\\"chevy s-10\\\"\""
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "readlines(\"auto.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this exercise we have chosen a typical file, which in practice means that things are not trivial.\n",
    "* first we note that it has no header with column names.\n",
    "* second, we see that the last column is tab separated, while earlier columns are separated with varying number of spaces\n",
    "* finally we see that missing values are encoded by \"NA\" in this file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will show several options how the file can be parsed to a `DataFrame`.\n",
    "The first one is to replace tabs with spaces in the source file, and then load it using `CSV.File` command."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by getting the contents of the file into a single string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"18.0   8.   307.0      130.0      3504.      12.0   70.  1.\\t\\\"chevrolet chevelle malibu\\\"\\n15.0   8.   350.0      165.0      3693.      11.5   70.  1.\\t\\\"buick skylark 320\\\"\\n18.0   8.   318.0      150.0      3436.      11.0   70.  1.\\t\\\"plymouth satellite\\\"\\n16.0   8.   304.0    \" ⋯ 31610 bytes ⋯ \"00      2130.      24.6   82.  2.\\t\\\"vw pickup\\\"\\n32.0   4.   135.0      84.00      2295.      11.6   82.  1.\\t\\\"dodge rampage\\\"\\n28.0   4.   120.0      79.00      2625.      18.6   82.  1.\\t\\\"ford ranger\\\"\\n31.0   4.   119.0      82.00      2720.      19.4   82.  1.\\t\\\"chevy s-10\\\"\\n\""
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_str = read(\"auto.txt\", String)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we replace all tabs in this string by spaces\n",
    "\n",
    "(note that in general it is not a safe operation as theoretically if you had columns that are strings they might have contained quoted tabs; fortunately in this case they do not have them so we are safe)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"18.0   8.   307.0      130.0      3504.      12.0   70.  1. \\\"chevrolet chevelle malibu\\\"\\n15.0   8.   350.0      165.0      3693.      11.5   70.  1. \\\"buick skylark 320\\\"\\n18.0   8.   318.0      150.0      3436.      11.0   70.  1. \\\"plymouth satellite\\\"\\n16.0   8.   304.0    \" ⋯ 31610 bytes ⋯ \"00      2130.      24.6   82.  2. \\\"vw pickup\\\"\\n32.0   4.   135.0      84.00      2295.      11.6   82.  1. \\\"dodge rampage\\\"\\n28.0   4.   120.0      79.00      2625.      18.6   82.  1. \\\"ford ranger\\\"\\n31.0   4.   119.0      82.00      2720.      19.4   82.  1. \\\"chevy s-10\\\"\\n\""
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str_no_tab = replace(raw_str, '\\t'=>' ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we create an `IOBuffer` backed by the string we have just created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IOBuffer(data=UInt8[...], readable=true, writable=false, seekable=true, append=false, size=32149, maxsize=Inf, ptr=1, mark=-1)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "io = IOBuffer(str_no_tab)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can think of variable `io` as an in-memory I/O stream. Therefore we can pass this stream to the `CSV.File` function to read it as-if it were a CSV file. Note that in the options we choose that:\n",
    "* the delimiter is space\n",
    "* we ignore repeated (consecutive) occurences of the delimiter (so we correctly handle our file which has columns padded by spaces)\n",
    "* we explicitly pass column names via `header` keyword argument\n",
    "* we specify that missing values are represented using `\"NA\"` string in our file\n",
    "\n",
    "Finally note that we pass the result of `CSV.File` operation to a `DataFrame` constructor using `|>`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×9 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">395</td><td style = \"font-style: italic; text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick century limited</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"font-style: italic; text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chrysler lebaron medallion</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford granada l</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"font-style: italic; text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td><td style = \"text-align: left;\">toyota celica gt</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge charger 2.2</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet camaro</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang gl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">vw pickup</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge rampage</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford ranger</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevy s-10</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t11 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t12 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t13 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t14 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t15 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t16 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t17 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t18 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t19 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t20 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t21 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t22 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t23 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t24 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t25 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t26 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t27 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t28 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t29 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t30 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×9 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      18.0        8.0         307.0       130.0   3504.0          12.0   ⋯\n",
       "   2 │      15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │      18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │      16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │      17.0        8.0         302.0       140.0   3449.0          10.5   ⋯\n",
       "   6 │      15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │      14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │      14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │      14.0        8.0         455.0       225.0   4425.0          10.0   ⋯\n",
       "  10 │      15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5\n",
       "  ⋮  │     ⋮          ⋮           ⋮            ⋮          ⋮          ⋮         ⋱\n",
       " 397 │      26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 398 │      22.0        6.0         232.0       112.0   2835.0          14.7   ⋯\n",
       " 399 │      32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 400 │      36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 401 │      27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 402 │      27.0        4.0         140.0        86.0   2790.0          15.6   ⋯\n",
       " 403 │      44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 404 │      32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 405 │      28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 406 │      31.0        4.0         119.0        82.0   2720.0          19.4   ⋯\n",
       "\u001b[36m                                                  3 columns and 385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = CSV.File(io,\n",
    "               delim=' ',\n",
    "               ignorerepeated=true,\n",
    "               header=[:mpg, :cylinders, :displacement, :horsepower,\n",
    "                       :weight, :acceleration, :year, :origin, :name],\n",
    "               missingstring=\"NA\") |>\n",
    "      DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us discuss an alternative way to read in the original file.\n",
    "This time we will first read the data in directly from the file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×2 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">metrics</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"String\" style = \"text-align: left;\">String</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">18.0   8.   307.0      130.0      3504.      12.0   70.  1.</td><td style = \"text-align: left;\">chevrolet chevelle malibu</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: left;\">15.0   8.   350.0      165.0      3693.      11.5   70.  1.</td><td style = \"text-align: left;\">buick skylark 320</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: left;\">18.0   8.   318.0      150.0      3436.      11.0   70.  1.</td><td style = \"text-align: left;\">plymouth satellite</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: left;\">16.0   8.   304.0      150.0      3433.      12.0   70.  1.</td><td style = \"text-align: left;\">amc rebel sst</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: left;\">17.0   8.   302.0      140.0      3449.      10.5   70.  1.</td><td style = \"text-align: left;\">ford torino</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: left;\">15.0   8.   429.0      198.0      4341.      10.0   70.  1.</td><td style = \"text-align: left;\">ford galaxie 500</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: left;\">14.0   8.   454.0      220.0      4354.       9.0   70.  1.</td><td style = \"text-align: left;\">chevrolet impala</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: left;\">14.0   8.   440.0      215.0      4312.       8.5   70.  1.</td><td style = \"text-align: left;\">plymouth fury iii</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: left;\">14.0   8.   455.0      225.0      4425.      10.0   70.  1.</td><td style = \"text-align: left;\">pontiac catalina</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: left;\">15.0   8.   390.0      190.0      3850.       8.5   70.  1.</td><td style = \"text-align: left;\">amc ambassador dpl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: left;\">NA     4.   133.0      115.0      3090.      17.5   70.  2.</td><td style = \"text-align: left;\">citroen ds-21 pallas</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"text-align: left;\">NA     8.   350.0      165.0      4142.      11.5   70.  1.</td><td style = \"text-align: left;\">chevrolet chevelle concours (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"text-align: left;\">NA     8.   351.0      153.0      4034.      11.0   70.  1.</td><td style = \"text-align: left;\">ford torino (sw)</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">395</td><td style = \"text-align: left;\">25.0   6.   181.0      110.0      2945.      16.4   82.  1.</td><td style = \"text-align: left;\">buick century limited</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"text-align: left;\">38.0   6.   262.0      85.00      3015.      17.0   82.  1.</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: left;\">26.0   4.   156.0      92.00      2585.      14.5   82.  1.</td><td style = \"text-align: left;\">chrysler lebaron medallion</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: left;\">22.0   6.   232.0      112.0      2835       14.7   82.  1.</td><td style = \"text-align: left;\">ford granada l</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"text-align: left;\">32.0   4.   144.0      96.00      2665.      13.9   82.  3.</td><td style = \"text-align: left;\">toyota celica gt</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: left;\">36.0   4.   135.0      84.00      2370.      13.0   82.  1.</td><td style = \"text-align: left;\">dodge charger 2.2</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: left;\">27.0   4.   151.0      90.00      2950.      17.3   82.  1.</td><td style = \"text-align: left;\">chevrolet camaro</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: left;\">27.0   4.   140.0      86.00      2790.      15.6   82.  1.</td><td style = \"text-align: left;\">ford mustang gl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: left;\">44.0   4.   97.00      52.00      2130.      24.6   82.  2.</td><td style = \"text-align: left;\">vw pickup</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: left;\">32.0   4.   135.0      84.00      2295.      11.6   82.  1.</td><td style = \"text-align: left;\">dodge rampage</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: left;\">28.0   4.   120.0      79.00      2625.      18.6   82.  1.</td><td style = \"text-align: left;\">ford ranger</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: left;\">31.0   4.   119.0      82.00      2720.      19.4   82.  1.</td><td style = \"text-align: left;\">chevy s-10</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cc}\n",
       "\t& metrics & name\\\\\n",
       "\t\\hline\n",
       "\t& String & String\\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0   8.   307.0      130.0      3504.      12.0   70.  1. & chevrolet chevelle malibu \\\\\n",
       "\t2 & 15.0   8.   350.0      165.0      3693.      11.5   70.  1. & buick skylark 320 \\\\\n",
       "\t3 & 18.0   8.   318.0      150.0      3436.      11.0   70.  1. & plymouth satellite \\\\\n",
       "\t4 & 16.0   8.   304.0      150.0      3433.      12.0   70.  1. & amc rebel sst \\\\\n",
       "\t5 & 17.0   8.   302.0      140.0      3449.      10.5   70.  1. & ford torino \\\\\n",
       "\t6 & 15.0   8.   429.0      198.0      4341.      10.0   70.  1. & ford galaxie 500 \\\\\n",
       "\t7 & 14.0   8.   454.0      220.0      4354.       9.0   70.  1. & chevrolet impala \\\\\n",
       "\t8 & 14.0   8.   440.0      215.0      4312.       8.5   70.  1. & plymouth fury iii \\\\\n",
       "\t9 & 14.0   8.   455.0      225.0      4425.      10.0   70.  1. & pontiac catalina \\\\\n",
       "\t10 & 15.0   8.   390.0      190.0      3850.       8.5   70.  1. & amc ambassador dpl \\\\\n",
       "\t11 & NA     4.   133.0      115.0      3090.      17.5   70.  2. & citroen ds-21 pallas \\\\\n",
       "\t12 & NA     8.   350.0      165.0      4142.      11.5   70.  1. & chevrolet chevelle concours (sw) \\\\\n",
       "\t13 & NA     8.   351.0      153.0      4034.      11.0   70.  1. & ford torino (sw) \\\\\n",
       "\t14 & NA     8.   383.0      175.0      4166.      10.5   70.  1. & plymouth satellite (sw) \\\\\n",
       "\t15 & NA     8.   360.0      175.0      3850.      11.0   70.  1. & amc rebel sst (sw) \\\\\n",
       "\t16 & 15.0   8.   383.0      170.0      3563.      10.0   70.  1. & dodge challenger se \\\\\n",
       "\t17 & 14.0   8.   340.0      160.0      3609.       8.0   70.  1. & plymouth 'cuda 340 \\\\\n",
       "\t18 & NA     8.   302.0      140.0      3353.       8.0   70.  1. & ford mustang boss 302 \\\\\n",
       "\t19 & 15.0   8.   400.0      150.0      3761.       9.5   70.  1. & chevrolet monte carlo \\\\\n",
       "\t20 & 14.0   8.   455.0      225.0      3086.      10.0   70.  1. & buick estate wagon (sw) \\\\\n",
       "\t21 & 24.0   4.   113.0      95.00      2372.      15.0   70.  3. & toyota corona mark ii \\\\\n",
       "\t22 & 22.0   6.   198.0      95.00      2833.      15.5   70.  1. & plymouth duster \\\\\n",
       "\t23 & 18.0   6.   199.0      97.00      2774.      15.5   70.  1. & amc hornet \\\\\n",
       "\t24 & 21.0   6.   200.0      85.00      2587.      16.0   70.  1. & ford maverick \\\\\n",
       "\t25 & 27.0   4.   97.00      88.00      2130.      14.5   70.  3. & datsun pl510 \\\\\n",
       "\t26 & 26.0   4.   97.00      46.00      1835.      20.5   70.  2. & volkswagen 1131 deluxe sedan \\\\\n",
       "\t27 & 25.0   4.   110.0      87.00      2672.      17.5   70.  2. & peugeot 504 \\\\\n",
       "\t28 & 24.0   4.   107.0      90.00      2430.      14.5   70.  2. & audi 100 ls \\\\\n",
       "\t29 & 25.0   4.   104.0      95.00      2375.      17.5   70.  2. & saab 99e \\\\\n",
       "\t30 & 26.0   4.   121.0      113.0      2234.      12.5   70.  2. & bmw 2002 \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×2 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m metrics                           \u001b[0m\u001b[1m name                              \u001b[0m\n",
       "     │\u001b[90m String                            \u001b[0m\u001b[90m String                            \u001b[0m\n",
       "─────┼──────────────────────────────────────────────────────────────────────\n",
       "   1 │ 18.0   8.   307.0      130.0    …  chevrolet chevelle malibu\n",
       "   2 │ 15.0   8.   350.0      165.0    …  buick skylark 320\n",
       "   3 │ 18.0   8.   318.0      150.0    …  plymouth satellite\n",
       "   4 │ 16.0   8.   304.0      150.0    …  amc rebel sst\n",
       "   5 │ 17.0   8.   302.0      140.0    …  ford torino\n",
       "   6 │ 15.0   8.   429.0      198.0    …  ford galaxie 500\n",
       "   7 │ 14.0   8.   454.0      220.0    …  chevrolet impala\n",
       "   8 │ 14.0   8.   440.0      215.0    …  plymouth fury iii\n",
       "   9 │ 14.0   8.   455.0      225.0    …  pontiac catalina\n",
       "  10 │ 15.0   8.   390.0      190.0    …  amc ambassador dpl\n",
       "  11 │ NA     4.   133.0      115.0    …  citroen ds-21 pallas\n",
       "  ⋮  │                 ⋮                                  ⋮\n",
       " 397 │ 26.0   4.   156.0      92.00    …  chrysler lebaron medallion\n",
       " 398 │ 22.0   6.   232.0      112.0    …  ford granada l\n",
       " 399 │ 32.0   4.   144.0      96.00    …  toyota celica gt\n",
       " 400 │ 36.0   4.   135.0      84.00    …  dodge charger 2.2\n",
       " 401 │ 27.0   4.   151.0      90.00    …  chevrolet camaro\n",
       " 402 │ 27.0   4.   140.0      86.00    …  ford mustang gl\n",
       " 403 │ 44.0   4.   97.00      52.00    …  vw pickup\n",
       " 404 │ 32.0   4.   135.0      84.00    …  dodge rampage\n",
       " 405 │ 28.0   4.   120.0      79.00    …  ford ranger\n",
       " 406 │ 31.0   4.   119.0      82.00    …  chevy s-10\n",
       "\u001b[36m                                                            385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw = CSV.File(\"auto.txt\", header=[:metrics, :name]) |> DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this time CSV.jl auto-detected that tab is the right delimiter to split the columns\n",
    "\n",
    "(it was the only delimiter that produced consistent number of columns)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will split `:metrics` column manually now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406-element Vector{Vector{SubString{String}}}:\n",
       " [\"18.0\", \"8.\", \"307.0\", \"130.0\", \"3504.\", \"12.0\", \"70.\", \"1.\"]\n",
       " [\"15.0\", \"8.\", \"350.0\", \"165.0\", \"3693.\", \"11.5\", \"70.\", \"1.\"]\n",
       " [\"18.0\", \"8.\", \"318.0\", \"150.0\", \"3436.\", \"11.0\", \"70.\", \"1.\"]\n",
       " [\"16.0\", \"8.\", \"304.0\", \"150.0\", \"3433.\", \"12.0\", \"70.\", \"1.\"]\n",
       " [\"17.0\", \"8.\", \"302.0\", \"140.0\", \"3449.\", \"10.5\", \"70.\", \"1.\"]\n",
       " [\"15.0\", \"8.\", \"429.0\", \"198.0\", \"4341.\", \"10.0\", \"70.\", \"1.\"]\n",
       " [\"14.0\", \"8.\", \"454.0\", \"220.0\", \"4354.\", \"9.0\", \"70.\", \"1.\"]\n",
       " [\"14.0\", \"8.\", \"440.0\", \"215.0\", \"4312.\", \"8.5\", \"70.\", \"1.\"]\n",
       " [\"14.0\", \"8.\", \"455.0\", \"225.0\", \"4425.\", \"10.0\", \"70.\", \"1.\"]\n",
       " [\"15.0\", \"8.\", \"390.0\", \"190.0\", \"3850.\", \"8.5\", \"70.\", \"1.\"]\n",
       " [\"NA\", \"4.\", \"133.0\", \"115.0\", \"3090.\", \"17.5\", \"70.\", \"2.\"]\n",
       " [\"NA\", \"8.\", \"350.0\", \"165.0\", \"4142.\", \"11.5\", \"70.\", \"1.\"]\n",
       " [\"NA\", \"8.\", \"351.0\", \"153.0\", \"4034.\", \"11.0\", \"70.\", \"1.\"]\n",
       " ⋮\n",
       " [\"25.0\", \"6.\", \"181.0\", \"110.0\", \"2945.\", \"16.4\", \"82.\", \"1.\"]\n",
       " [\"38.0\", \"6.\", \"262.0\", \"85.00\", \"3015.\", \"17.0\", \"82.\", \"1.\"]\n",
       " [\"26.0\", \"4.\", \"156.0\", \"92.00\", \"2585.\", \"14.5\", \"82.\", \"1.\"]\n",
       " [\"22.0\", \"6.\", \"232.0\", \"112.0\", \"2835\", \"14.7\", \"82.\", \"1.\"]\n",
       " [\"32.0\", \"4.\", \"144.0\", \"96.00\", \"2665.\", \"13.9\", \"82.\", \"3.\"]\n",
       " [\"36.0\", \"4.\", \"135.0\", \"84.00\", \"2370.\", \"13.0\", \"82.\", \"1.\"]\n",
       " [\"27.0\", \"4.\", \"151.0\", \"90.00\", \"2950.\", \"17.3\", \"82.\", \"1.\"]\n",
       " [\"27.0\", \"4.\", \"140.0\", \"86.00\", \"2790.\", \"15.6\", \"82.\", \"1.\"]\n",
       " [\"44.0\", \"4.\", \"97.00\", \"52.00\", \"2130.\", \"24.6\", \"82.\", \"2.\"]\n",
       " [\"32.0\", \"4.\", \"135.0\", \"84.00\", \"2295.\", \"11.6\", \"82.\", \"1.\"]\n",
       " [\"28.0\", \"4.\", \"120.0\", \"79.00\", \"2625.\", \"18.6\", \"82.\", \"1.\"]\n",
       " [\"31.0\", \"4.\", \"119.0\", \"82.00\", \"2720.\", \"19.4\", \"82.\", \"1.\"]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str_metrics = split.(df_raw.metrics)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let us create an empty `df1_2` data frame that we will populate with appropriate columns.\n",
    "The pattern we use here is typical when you e.g. perform repeated computations whose results you want to store in a `DataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>0×8 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin\\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64\\\\\n",
       "\t\\hline\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m0×8 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg     \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m ye\u001b[0m ⋯\n",
       "     │\u001b[90m Float64 \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┴──────────────────────────────────────────────────────────────────────────\n",
       "\u001b[36m                                                               2 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2 = DataFrame([col => Float64[] for\n",
    "                  col in [:mpg, :cylinders, :displacement, :horsepower, :weight, :acceleration, :year, :origin]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have a data frame that has 8 columns and 0 rows. It accepts floating point values. However in columns `:mpg` and `:horsepower` we have to allow the data frame to hold missing values. We do it using `allowmissing!` function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>0×8 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin\\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64\\\\\n",
       "\t\\hline\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m0×8 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg      \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m y\u001b[0m ⋯\n",
       "     │\u001b[90m Float64? \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m F\u001b[0m ⋯\n",
       "─────┴──────────────────────────────────────────────────────────────────────────\n",
       "\u001b[36m                                                               2 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allowmissing!(df1_2, [:mpg, :horsepower])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the element type of columns `:mpg` and `:horsepower` changed to `Float64?` which signals that that columns allows missing values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we are ready to populate our data frame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "for row in str_metrics\n",
    "    push!(df1_2, [v == \"NA\" ? missing : parse(Float64, v) for v in row])\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×8 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">307.0</td><td style = \"text-align: right;\">130.0</td><td style = \"text-align: right;\">3504.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">3693.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">318.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3436.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">16.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">304.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3433.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3449.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">429.0</td><td style = \"text-align: right;\">198.0</td><td style = \"text-align: right;\">4341.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">454.0</td><td style = \"text-align: right;\">220.0</td><td style = \"text-align: right;\">4354.0</td><td style = \"text-align: right;\">9.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">440.0</td><td style = \"text-align: right;\">215.0</td><td style = \"text-align: right;\">4312.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">455.0</td><td style = \"text-align: right;\">225.0</td><td style = \"text-align: right;\">4425.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">390.0</td><td style = \"text-align: right;\">190.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">133.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">3090.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">4142.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">351.0</td><td style = \"text-align: right;\">153.0</td><td style = \"text-align: right;\">4034.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">395</td><td style = \"font-style: italic; text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"font-style: italic; text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"font-style: italic; text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin\\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64\\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 \\\\\n",
       "\t11 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 \\\\\n",
       "\t12 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 \\\\\n",
       "\t13 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 \\\\\n",
       "\t14 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 \\\\\n",
       "\t15 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 \\\\\n",
       "\t16 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 \\\\\n",
       "\t17 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 \\\\\n",
       "\t18 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 \\\\\n",
       "\t19 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 \\\\\n",
       "\t20 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 \\\\\n",
       "\t21 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 \\\\\n",
       "\t22 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 \\\\\n",
       "\t23 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 \\\\\n",
       "\t24 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 \\\\\n",
       "\t25 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 \\\\\n",
       "\t26 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 \\\\\n",
       "\t27 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 \\\\\n",
       "\t28 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 \\\\\n",
       "\t29 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 \\\\\n",
       "\t30 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×8 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      18.0        8.0         307.0       130.0   3504.0          12.0   ⋯\n",
       "   2 │      15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │      18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │      16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │      17.0        8.0         302.0       140.0   3449.0          10.5   ⋯\n",
       "   6 │      15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │      14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │      14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │      14.0        8.0         455.0       225.0   4425.0          10.0   ⋯\n",
       "  10 │      15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5\n",
       "  ⋮  │     ⋮          ⋮           ⋮            ⋮          ⋮          ⋮         ⋱\n",
       " 397 │      26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 398 │      22.0        6.0         232.0       112.0   2835.0          14.7   ⋯\n",
       " 399 │      32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 400 │      36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 401 │      27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 402 │      27.0        4.0         140.0        86.0   2790.0          15.6   ⋯\n",
       " 403 │      44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 404 │      32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 405 │      28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 406 │      31.0        4.0         119.0        82.0   2720.0          19.4   ⋯\n",
       "\u001b[36m                                                  2 columns and 385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "finally, let us add a column `:name` from the `df_raw` data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406-element Vector{String}:\n",
       " \"chevrolet chevelle malibu\"\n",
       " \"buick skylark 320\"\n",
       " \"plymouth satellite\"\n",
       " \"amc rebel sst\"\n",
       " \"ford torino\"\n",
       " \"ford galaxie 500\"\n",
       " \"chevrolet impala\"\n",
       " \"plymouth fury iii\"\n",
       " \"pontiac catalina\"\n",
       " \"amc ambassador dpl\"\n",
       " \"citroen ds-21 pallas\"\n",
       " \"chevrolet chevelle concours (sw)\"\n",
       " \"ford torino (sw)\"\n",
       " ⋮\n",
       " \"buick century limited\"\n",
       " \"oldsmobile cutlass ciera (diesel)\"\n",
       " \"chrysler lebaron medallion\"\n",
       " \"ford granada l\"\n",
       " \"toyota celica gt\"\n",
       " \"dodge charger 2.2\"\n",
       " \"chevrolet camaro\"\n",
       " \"ford mustang gl\"\n",
       " \"vw pickup\"\n",
       " \"dodge rampage\"\n",
       " \"ford ranger\"\n",
       " \"chevy s-10\""
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2.name = df_raw.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×9 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">307.0</td><td style = \"text-align: right;\">130.0</td><td style = \"text-align: right;\">3504.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle malibu</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">3693.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick skylark 320</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">318.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3436.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth satellite</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">16.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">304.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3433.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc rebel sst</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3449.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">429.0</td><td style = \"text-align: right;\">198.0</td><td style = \"text-align: right;\">4341.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford galaxie 500</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">454.0</td><td style = \"text-align: right;\">220.0</td><td style = \"text-align: right;\">4354.0</td><td style = \"text-align: right;\">9.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet impala</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">440.0</td><td style = \"text-align: right;\">215.0</td><td style = \"text-align: right;\">4312.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth fury iii</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">455.0</td><td style = \"text-align: right;\">225.0</td><td style = \"text-align: right;\">4425.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">pontiac catalina</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">390.0</td><td style = \"text-align: right;\">190.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc ambassador dpl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">133.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">3090.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">citroen ds-21 pallas</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">4142.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle concours (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">351.0</td><td style = \"text-align: right;\">153.0</td><td style = \"text-align: right;\">4034.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino (sw)</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">395</td><td style = \"font-style: italic; text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick century limited</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"font-style: italic; text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chrysler lebaron medallion</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford granada l</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"font-style: italic; text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td><td style = \"text-align: left;\">toyota celica gt</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge charger 2.2</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet camaro</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang gl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">vw pickup</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge rampage</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford ranger</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevy s-10</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t11 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t12 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t13 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t14 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t15 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t16 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t17 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t18 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t19 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t20 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t21 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t22 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t23 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t24 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t25 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t26 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t27 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t28 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t29 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t30 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×9 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      18.0        8.0         307.0       130.0   3504.0          12.0   ⋯\n",
       "   2 │      15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │      18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │      16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │      17.0        8.0         302.0       140.0   3449.0          10.5   ⋯\n",
       "   6 │      15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │      14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │      14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │      14.0        8.0         455.0       225.0   4425.0          10.0   ⋯\n",
       "  10 │      15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5\n",
       "  ⋮  │     ⋮          ⋮           ⋮            ⋮          ⋮          ⋮         ⋱\n",
       " 397 │      26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 398 │      22.0        6.0         232.0       112.0   2835.0          14.7   ⋯\n",
       " 399 │      32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 400 │      36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 401 │      27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 402 │      27.0        4.0         140.0        86.0   2790.0          15.6   ⋯\n",
       " 403 │      44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 404 │      32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 405 │      28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 406 │      31.0        4.0         119.0        82.0   2720.0          19.4   ⋯\n",
       "\u001b[36m                                                  3 columns and 385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we move forward we should stress one very important thing that is related to `df1_2.name = df_raw.name` assignment. After this operation columns `:name` in both `df1_2` and `df_raw` are the same objects.\n",
    "We can easily check it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2.name === df_raw.name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Such behavior is allowed for performance reasons. In this case we accepted it as we want to discard `df_raw` data frame and not use it in later analysis.\n",
    "However, in general it would be safer to create a copy of `:name` column when assigning it ti `df1_2` data frame.\n",
    "\n",
    "It can be achieved like this:\n",
    "```\n",
    "df1_2[:, :name] = df_raw.name\n",
    "```\n",
    "or like this\n",
    "```\n",
    "df1_2.name = df_raw[:, :name]\n",
    "```\n",
    "We could also write:\n",
    "```\n",
    "df1_2[:, :name] = df_raw[:, :name]\n",
    "```\n",
    "but this time there would be one unnecessary copy made (one when reading the data from `df_raw` the other when writing data to `df1_2`)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can check that `df1` and `df1_2` data frames are equal using `isequal` funtion, so that we ended up with identical data frames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isequal(df1_2, df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that as the data frames contain missing values comparing them with `missing` would produce `missing`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "missing"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_2 == df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us investigate yet another way to create our data frame, this time in one-shot (this line is more difficult to understand, but it shows you the power that DataFrames.jl gives you when working with data, in part 4 of the tutorial we will give some more examples of supported transformations):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×9 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">307.0</td><td style = \"text-align: right;\">130.0</td><td style = \"text-align: right;\">3504.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle malibu</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">3693.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick skylark 320</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">318.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3436.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth satellite</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">16.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">304.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3433.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc rebel sst</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3449.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">429.0</td><td style = \"text-align: right;\">198.0</td><td style = \"text-align: right;\">4341.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford galaxie 500</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">454.0</td><td style = \"text-align: right;\">220.0</td><td style = \"text-align: right;\">4354.0</td><td style = \"text-align: right;\">9.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet impala</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">440.0</td><td style = \"text-align: right;\">215.0</td><td style = \"text-align: right;\">4312.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth fury iii</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">455.0</td><td style = \"text-align: right;\">225.0</td><td style = \"text-align: right;\">4425.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">pontiac catalina</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">390.0</td><td style = \"text-align: right;\">190.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc ambassador dpl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">133.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">3090.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">citroen ds-21 pallas</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">4142.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle concours (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">351.0</td><td style = \"text-align: right;\">153.0</td><td style = \"text-align: right;\">4034.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino (sw)</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">395</td><td style = \"font-style: italic; text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick century limited</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"font-style: italic; text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chrysler lebaron medallion</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford granada l</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"font-style: italic; text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td><td style = \"text-align: left;\">toyota celica gt</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge charger 2.2</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet camaro</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang gl</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">vw pickup</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge rampage</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford ranger</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevy s-10</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t11 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t12 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t13 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t14 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t15 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t16 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t17 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t18 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t19 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t20 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t21 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t22 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t23 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t24 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t25 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t26 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t27 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t28 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t29 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t30 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×9 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      18.0        8.0         307.0       130.0   3504.0          12.0   ⋯\n",
       "   2 │      15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │      18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │      16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │      17.0        8.0         302.0       140.0   3449.0          10.5   ⋯\n",
       "   6 │      15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │      14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │      14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │      14.0        8.0         455.0       225.0   4425.0          10.0   ⋯\n",
       "  10 │      15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5\n",
       "  ⋮  │     ⋮          ⋮           ⋮            ⋮          ⋮          ⋮         ⋱\n",
       " 397 │      26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 398 │      22.0        6.0         232.0       112.0   2835.0          14.7   ⋯\n",
       " 399 │      32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 400 │      36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 401 │      27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 402 │      27.0        4.0         140.0        86.0   2790.0          15.6   ⋯\n",
       " 403 │      44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 404 │      32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 405 │      28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 406 │      31.0        4.0         119.0        82.0   2720.0          19.4   ⋯\n",
       "\u001b[36m                                                  3 columns and 385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_3 = select(df_raw,\n",
    "               :metrics =>\n",
    "               ByRow(x -> something.(tryparse.(Float64, split(x)), missing)) =>\n",
    "               [:mpg, :cylinders, :displacement, :horsepower, :weight, :acceleration, :year, :origin],\n",
    "               :name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us understand what is going on in the above expression.\n",
    "\n",
    "The general rule os specifying transformations in `select` (also `transform` and `combine`) is:\n",
    "\n",
    "`source_columns => transformation => destination_columns`\n",
    "\n",
    "In this case we take `:metrics` column from the source data frame. We process it element by element,\n",
    "which is signaled by `ByRow` (you can think of this as broadcasting).\n",
    "Now each element is first `split` and then we try parsing it as `Float64`.\n",
    "If we fail `tryparse` returns `nothing`, which we convert to `missing` using the `something` function.\n",
    "As a result we obtain a vector of `Float64` or `Missing` values.\n",
    "Since the last element of our transformation is a vector of culumn names this vector is expanded into\n",
    "that many columns.\n",
    "\n",
    "Finally we add the `:name` column from the source data frame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As above we check that the result is the same as `df1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isequal(df1_3, df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can easily count the number of missing values in the `df1` data frame using the `eachcol` function that returns the iterator over columns of the data frame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(count(ismissing, col) for col in eachcol(df1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we could alternatively transform our data frame to a `Matrix` and use `count` on it (it would be slower though as unnecessary copies of data would be performed):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count(ismissing, Matrix(df1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or if you like iterators:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count(ismissing, Iterators.flatten(eachcol(df1)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively could use the `mapcols` function to get the number of missings per column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>1×9 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">8</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">6</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Int64 & Int64 & Int64 & Int64 & Int64 & Int64 & Int64 & Int64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 8 & 0 & 0 & 6 & 0 & 0 & 0 & 0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m1×9 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg   \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m year \u001b[0m ⋯\n",
       "     │\u001b[90m Int64 \u001b[0m\u001b[90m Int64     \u001b[0m\u001b[90m Int64        \u001b[0m\u001b[90m Int64      \u001b[0m\u001b[90m Int64  \u001b[0m\u001b[90m Int64        \u001b[0m\u001b[90m Int64\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │     8          0             0           6       0             0      0 ⋯\n",
       "\u001b[36m                                                               2 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapcols(x -> count(ismissing, x), df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "also it is easy to find the rows containing missing values using the `filter` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>14×9 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">133.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">3090.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">citroen ds-21 pallas</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">4142.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle concours (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">351.0</td><td style = \"text-align: right;\">153.0</td><td style = \"text-align: right;\">4034.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">383.0</td><td style = \"text-align: right;\">175.0</td><td style = \"text-align: right;\">4166.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth satellite (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">360.0</td><td style = \"text-align: right;\">175.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc rebel sst (sw)</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3353.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang boss 302</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">98.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">2046.0</td><td style = \"text-align: right;\">19.0</td><td style = \"text-align: right;\">71.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford pinto</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">48.0</td><td style = \"text-align: right;\">1978.0</td><td style = \"text-align: right;\">20.0</td><td style = \"text-align: right;\">71.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">volkswagen super beetle 117</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">21.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">200.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">2875.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">74.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford maverick</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">40.9</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">85.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">1835.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">80.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">renault lecar deluxe</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: right;\">23.6</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">2905.0</td><td style = \"text-align: right;\">14.3</td><td style = \"text-align: right;\">80.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang cobra</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"text-align: right;\">34.5</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">100.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">2320.0</td><td style = \"text-align: right;\">15.8</td><td style = \"text-align: right;\">81.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">renault 18i</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2800.0</td><td style = \"text-align: right;\">15.4</td><td style = \"text-align: right;\">81.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 900s</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">14</td><td style = \"text-align: right;\">23.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">3035.0</td><td style = \"text-align: right;\">20.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc concord dl</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t2 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 25.0 & 4.0 & 98.0 & \\emph{missing} & 2046.0 & 19.0 & 71.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & \\emph{missing} & 4.0 & 97.0 & 48.0 & 1978.0 & 20.0 & 71.0 & 2.0 & $\\dots$ \\\\\n",
       "\t9 & 21.0 & 6.0 & 200.0 & \\emph{missing} & 2875.0 & 17.0 & 74.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 40.9 & 4.0 & 85.0 & \\emph{missing} & 1835.0 & 17.3 & 80.0 & 2.0 & $\\dots$ \\\\\n",
       "\t11 & 23.6 & 4.0 & 140.0 & \\emph{missing} & 2905.0 & 14.3 & 80.0 & 1.0 & $\\dots$ \\\\\n",
       "\t12 & 34.5 & 4.0 & 100.0 & \\emph{missing} & 2320.0 & 15.8 & 81.0 & 2.0 & $\\dots$ \\\\\n",
       "\t13 & \\emph{missing} & 4.0 & 121.0 & 110.0 & 2800.0 & 15.4 & 81.0 & 2.0 & $\\dots$ \\\\\n",
       "\t14 & 23.0 & 4.0 & 151.0 & \\emph{missing} & 3035.0 & 20.5 & 82.0 & 1.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m14×9 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5   ⋯\n",
       "   2 │\u001b[90m missing   \u001b[0m       8.0         350.0       165.0   4142.0          11.5\n",
       "   3 │\u001b[90m missing   \u001b[0m       8.0         351.0       153.0   4034.0          11.0\n",
       "   4 │\u001b[90m missing   \u001b[0m       8.0         383.0       175.0   4166.0          10.5\n",
       "   5 │\u001b[90m missing   \u001b[0m       8.0         360.0       175.0   3850.0          11.0   ⋯\n",
       "   6 │\u001b[90m missing   \u001b[0m       8.0         302.0       140.0   3353.0           8.0\n",
       "   7 │      25.0        4.0          98.0 \u001b[90m  missing   \u001b[0m  2046.0          19.0\n",
       "   8 │\u001b[90m missing   \u001b[0m       4.0          97.0        48.0   1978.0          20.0\n",
       "   9 │      21.0        6.0         200.0 \u001b[90m  missing   \u001b[0m  2875.0          17.0   ⋯\n",
       "  10 │      40.9        4.0          85.0 \u001b[90m  missing   \u001b[0m  1835.0          17.3\n",
       "  11 │      23.6        4.0         140.0 \u001b[90m  missing   \u001b[0m  2905.0          14.3\n",
       "  12 │      34.5        4.0         100.0 \u001b[90m  missing   \u001b[0m  2320.0          15.8\n",
       "  13 │\u001b[90m missing   \u001b[0m       4.0         121.0       110.0   2800.0          15.4   ⋯\n",
       "  14 │      23.0        4.0         151.0 \u001b[90m  missing   \u001b[0m  3035.0          20.5\n",
       "\u001b[36m                                                               3 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter(row -> any(ismissing, row), df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assume we are interested in the brand of each car. We can extract it from `:name` column using broadcasting like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406-element Vector{SubString{String}}:\n",
       " \"chevrolet\"\n",
       " \"buick\"\n",
       " \"plymouth\"\n",
       " \"amc\"\n",
       " \"ford\"\n",
       " \"ford\"\n",
       " \"chevrolet\"\n",
       " \"plymouth\"\n",
       " \"pontiac\"\n",
       " \"amc\"\n",
       " \"citroen\"\n",
       " \"chevrolet\"\n",
       " \"ford\"\n",
       " ⋮\n",
       " \"buick\"\n",
       " \"oldsmobile\"\n",
       " \"chrysler\"\n",
       " \"ford\"\n",
       " \"toyota\"\n",
       " \"dodge\"\n",
       " \"chevrolet\"\n",
       " \"ford\"\n",
       " \"vw\"\n",
       " \"dodge\"\n",
       " \"ford\"\n",
       " \"chevy\""
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.brand = first.(split.(df1.name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>406×10 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">381 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th><th style = \"text-align: left;\">brand</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Union{Missing, Float64}\" style = \"text-align: left;\">Float64?</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"SubString{String}\" style = \"text-align: left;\">SubStrin…</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">307.0</td><td style = \"text-align: right;\">130.0</td><td style = \"text-align: right;\">3504.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle malibu</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">3693.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick skylark 320</td><td style = \"text-align: left;\">buick</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">318.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3436.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth satellite</td><td style = \"text-align: left;\">plymouth</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">16.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">304.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3433.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc rebel sst</td><td style = \"text-align: left;\">amc</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3449.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">429.0</td><td style = \"text-align: right;\">198.0</td><td style = \"text-align: right;\">4341.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford galaxie 500</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">454.0</td><td style = \"text-align: right;\">220.0</td><td style = \"text-align: right;\">4354.0</td><td style = \"text-align: right;\">9.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet impala</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">440.0</td><td style = \"text-align: right;\">215.0</td><td style = \"text-align: right;\">4312.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth fury iii</td><td style = \"text-align: left;\">plymouth</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">455.0</td><td style = \"text-align: right;\">225.0</td><td style = \"text-align: right;\">4425.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">pontiac catalina</td><td style = \"text-align: left;\">pontiac</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">390.0</td><td style = \"text-align: right;\">190.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc ambassador dpl</td><td style = \"text-align: left;\">amc</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">133.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">3090.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">citroen ds-21 pallas</td><td style = \"text-align: left;\">citroen</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">4142.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle concours (sw)</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"font-style: italic; text-align: right;\">missing</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">351.0</td><td style = \"text-align: right;\">153.0</td><td style = \"text-align: right;\">4034.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino (sw)</td><td style = \"text-align: left;\">ford</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">395</td><td style = \"font-style: italic; text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick century limited</td><td style = \"text-align: left;\">buick</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">396</td><td style = \"font-style: italic; text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td><td style = \"text-align: left;\">oldsmobile</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">397</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chrysler lebaron medallion</td><td style = \"text-align: left;\">chrysler</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">398</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford granada l</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">399</td><td style = \"font-style: italic; text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td><td style = \"text-align: left;\">toyota celica gt</td><td style = \"text-align: left;\">toyota</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">400</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge charger 2.2</td><td style = \"text-align: left;\">dodge</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">401</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet camaro</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">402</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang gl</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">403</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">vw pickup</td><td style = \"text-align: left;\">vw</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">404</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge rampage</td><td style = \"text-align: left;\">dodge</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">405</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford ranger</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">406</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevy s-10</td><td style = \"text-align: left;\">chevy</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64? & Float64 & Float64 & Float64? & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t11 & \\emph{missing} & 4.0 & 133.0 & 115.0 & 3090.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t12 & \\emph{missing} & 8.0 & 350.0 & 165.0 & 4142.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t13 & \\emph{missing} & 8.0 & 351.0 & 153.0 & 4034.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t14 & \\emph{missing} & 8.0 & 383.0 & 175.0 & 4166.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t15 & \\emph{missing} & 8.0 & 360.0 & 175.0 & 3850.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t16 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t17 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t18 & \\emph{missing} & 8.0 & 302.0 & 140.0 & 3353.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t19 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t20 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t21 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t22 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t23 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t24 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t25 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t26 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t27 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t28 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t29 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t30 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m406×10 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg       \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "     │\u001b[90m Float64?  \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64?   \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      18.0        8.0         307.0       130.0   3504.0          12.0   ⋯\n",
       "   2 │      15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │      18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │      16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │      17.0        8.0         302.0       140.0   3449.0          10.5   ⋯\n",
       "   6 │      15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │      14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │      14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │      14.0        8.0         455.0       225.0   4425.0          10.0   ⋯\n",
       "  10 │      15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │\u001b[90m missing   \u001b[0m       4.0         133.0       115.0   3090.0          17.5\n",
       "  ⋮  │     ⋮          ⋮           ⋮            ⋮          ⋮          ⋮         ⋱\n",
       " 397 │      26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 398 │      22.0        6.0         232.0       112.0   2835.0          14.7   ⋯\n",
       " 399 │      32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 400 │      36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 401 │      27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 402 │      27.0        4.0         140.0        86.0   2790.0          15.6   ⋯\n",
       " 403 │      44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 404 │      32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 405 │      28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 406 │      31.0        4.0         119.0        82.0   2720.0          19.4   ⋯\n",
       "\u001b[36m                                                  4 columns and 385 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Earlier we have shown how one can manually find rows that have missing values. A common operation is the reverse - i.e. selecting only rows that do not contain missing values. This can be achieved like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>392×10 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">367 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th><th style = \"text-align: left;\">brand</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"SubString{String}\" style = \"text-align: left;\">SubStrin…</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">307.0</td><td style = \"text-align: right;\">130.0</td><td style = \"text-align: right;\">3504.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet chevelle malibu</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">350.0</td><td style = \"text-align: right;\">165.0</td><td style = \"text-align: right;\">3693.0</td><td style = \"text-align: right;\">11.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick skylark 320</td><td style = \"text-align: left;\">buick</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">18.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">318.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3436.0</td><td style = \"text-align: right;\">11.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth satellite</td><td style = \"text-align: left;\">plymouth</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">16.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">304.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3433.0</td><td style = \"text-align: right;\">12.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc rebel sst</td><td style = \"text-align: left;\">amc</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">302.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">3449.0</td><td style = \"text-align: right;\">10.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford torino</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">429.0</td><td style = \"text-align: right;\">198.0</td><td style = \"text-align: right;\">4341.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford galaxie 500</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">454.0</td><td style = \"text-align: right;\">220.0</td><td style = \"text-align: right;\">4354.0</td><td style = \"text-align: right;\">9.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet impala</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">440.0</td><td style = \"text-align: right;\">215.0</td><td style = \"text-align: right;\">4312.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth fury iii</td><td style = \"text-align: left;\">plymouth</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">455.0</td><td style = \"text-align: right;\">225.0</td><td style = \"text-align: right;\">4425.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">pontiac catalina</td><td style = \"text-align: left;\">pontiac</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">390.0</td><td style = \"text-align: right;\">190.0</td><td style = \"text-align: right;\">3850.0</td><td style = \"text-align: right;\">8.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">amc ambassador dpl</td><td style = \"text-align: left;\">amc</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">383.0</td><td style = \"text-align: right;\">170.0</td><td style = \"text-align: right;\">3563.0</td><td style = \"text-align: right;\">10.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge challenger se</td><td style = \"text-align: left;\">dodge</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">340.0</td><td style = \"text-align: right;\">160.0</td><td style = \"text-align: right;\">3609.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">plymouth &apos;cuda 340</td><td style = \"text-align: left;\">plymouth</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"text-align: right;\">15.0</td><td style = \"text-align: right;\">8.0</td><td style = \"text-align: right;\">400.0</td><td style = \"text-align: right;\">150.0</td><td style = \"text-align: right;\">3761.0</td><td style = \"text-align: right;\">9.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet monte carlo</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">381</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">181.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2945.0</td><td style = \"text-align: right;\">16.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">buick century limited</td><td style = \"text-align: left;\">buick</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">382</td><td style = \"text-align: right;\">38.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">262.0</td><td style = \"text-align: right;\">85.0</td><td style = \"text-align: right;\">3015.0</td><td style = \"text-align: right;\">17.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">oldsmobile cutlass ciera (diesel)</td><td style = \"text-align: left;\">oldsmobile</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">383</td><td style = \"text-align: right;\">26.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">156.0</td><td style = \"text-align: right;\">92.0</td><td style = \"text-align: right;\">2585.0</td><td style = \"text-align: right;\">14.5</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chrysler lebaron medallion</td><td style = \"text-align: left;\">chrysler</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">384</td><td style = \"text-align: right;\">22.0</td><td style = \"text-align: right;\">6.0</td><td style = \"text-align: right;\">232.0</td><td style = \"text-align: right;\">112.0</td><td style = \"text-align: right;\">2835.0</td><td style = \"text-align: right;\">14.7</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford granada l</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">385</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">144.0</td><td style = \"text-align: right;\">96.0</td><td style = \"text-align: right;\">2665.0</td><td style = \"text-align: right;\">13.9</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">3.0</td><td style = \"text-align: left;\">toyota celica gt</td><td style = \"text-align: left;\">toyota</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">386</td><td style = \"text-align: right;\">36.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2370.0</td><td style = \"text-align: right;\">13.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge charger 2.2</td><td style = \"text-align: left;\">dodge</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">387</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">151.0</td><td style = \"text-align: right;\">90.0</td><td style = \"text-align: right;\">2950.0</td><td style = \"text-align: right;\">17.3</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevrolet camaro</td><td style = \"text-align: left;\">chevrolet</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">388</td><td style = \"text-align: right;\">27.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">140.0</td><td style = \"text-align: right;\">86.0</td><td style = \"text-align: right;\">2790.0</td><td style = \"text-align: right;\">15.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford mustang gl</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">389</td><td style = \"text-align: right;\">44.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">97.0</td><td style = \"text-align: right;\">52.0</td><td style = \"text-align: right;\">2130.0</td><td style = \"text-align: right;\">24.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">vw pickup</td><td style = \"text-align: left;\">vw</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">390</td><td style = \"text-align: right;\">32.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">135.0</td><td style = \"text-align: right;\">84.0</td><td style = \"text-align: right;\">2295.0</td><td style = \"text-align: right;\">11.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">dodge rampage</td><td style = \"text-align: left;\">dodge</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">391</td><td style = \"text-align: right;\">28.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">120.0</td><td style = \"text-align: right;\">79.0</td><td style = \"text-align: right;\">2625.0</td><td style = \"text-align: right;\">18.6</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">ford ranger</td><td style = \"text-align: left;\">ford</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">392</td><td style = \"text-align: right;\">31.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">119.0</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">2720.0</td><td style = \"text-align: right;\">19.4</td><td style = \"text-align: right;\">82.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: left;\">chevy s-10</td><td style = \"text-align: left;\">chevy</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 18.0 & 8.0 & 307.0 & 130.0 & 3504.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t2 & 15.0 & 8.0 & 350.0 & 165.0 & 3693.0 & 11.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t3 & 18.0 & 8.0 & 318.0 & 150.0 & 3436.0 & 11.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t4 & 16.0 & 8.0 & 304.0 & 150.0 & 3433.0 & 12.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t5 & 17.0 & 8.0 & 302.0 & 140.0 & 3449.0 & 10.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t6 & 15.0 & 8.0 & 429.0 & 198.0 & 4341.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t7 & 14.0 & 8.0 & 454.0 & 220.0 & 4354.0 & 9.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t8 & 14.0 & 8.0 & 440.0 & 215.0 & 4312.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t9 & 14.0 & 8.0 & 455.0 & 225.0 & 4425.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t10 & 15.0 & 8.0 & 390.0 & 190.0 & 3850.0 & 8.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t11 & 15.0 & 8.0 & 383.0 & 170.0 & 3563.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t12 & 14.0 & 8.0 & 340.0 & 160.0 & 3609.0 & 8.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t13 & 15.0 & 8.0 & 400.0 & 150.0 & 3761.0 & 9.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t14 & 14.0 & 8.0 & 455.0 & 225.0 & 3086.0 & 10.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t15 & 24.0 & 4.0 & 113.0 & 95.0 & 2372.0 & 15.0 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t16 & 22.0 & 6.0 & 198.0 & 95.0 & 2833.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t17 & 18.0 & 6.0 & 199.0 & 97.0 & 2774.0 & 15.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t18 & 21.0 & 6.0 & 200.0 & 85.0 & 2587.0 & 16.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t19 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 70.0 & 3.0 & $\\dots$ \\\\\n",
       "\t20 & 26.0 & 4.0 & 97.0 & 46.0 & 1835.0 & 20.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t21 & 25.0 & 4.0 & 110.0 & 87.0 & 2672.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t22 & 24.0 & 4.0 & 107.0 & 90.0 & 2430.0 & 14.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t23 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t24 & 26.0 & 4.0 & 121.0 & 113.0 & 2234.0 & 12.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t25 & 21.0 & 6.0 & 199.0 & 90.0 & 2648.0 & 15.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t26 & 10.0 & 8.0 & 360.0 & 215.0 & 4615.0 & 14.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t27 & 10.0 & 8.0 & 307.0 & 200.0 & 4376.0 & 15.0 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t28 & 11.0 & 8.0 & 318.0 & 210.0 & 4382.0 & 13.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t29 & 9.0 & 8.0 & 304.0 & 193.0 & 4732.0 & 18.5 & 70.0 & 1.0 & $\\dots$ \\\\\n",
       "\t30 & 27.0 & 4.0 & 97.0 & 88.0 & 2130.0 & 14.5 & 71.0 & 3.0 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m392×10 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg     \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m ye\u001b[0m ⋯\n",
       "     │\u001b[90m Float64 \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │    18.0        8.0         307.0       130.0   3504.0          12.0     ⋯\n",
       "   2 │    15.0        8.0         350.0       165.0   3693.0          11.5\n",
       "   3 │    18.0        8.0         318.0       150.0   3436.0          11.0\n",
       "   4 │    16.0        8.0         304.0       150.0   3433.0          12.0\n",
       "   5 │    17.0        8.0         302.0       140.0   3449.0          10.5     ⋯\n",
       "   6 │    15.0        8.0         429.0       198.0   4341.0          10.0\n",
       "   7 │    14.0        8.0         454.0       220.0   4354.0           9.0\n",
       "   8 │    14.0        8.0         440.0       215.0   4312.0           8.5\n",
       "   9 │    14.0        8.0         455.0       225.0   4425.0          10.0     ⋯\n",
       "  10 │    15.0        8.0         390.0       190.0   3850.0           8.5\n",
       "  11 │    15.0        8.0         383.0       170.0   3563.0          10.0\n",
       "  ⋮  │    ⋮         ⋮           ⋮            ⋮          ⋮          ⋮           ⋱\n",
       " 383 │    26.0        4.0         156.0        92.0   2585.0          14.5\n",
       " 384 │    22.0        6.0         232.0       112.0   2835.0          14.7     ⋯\n",
       " 385 │    32.0        4.0         144.0        96.0   2665.0          13.9\n",
       " 386 │    36.0        4.0         135.0        84.0   2370.0          13.0\n",
       " 387 │    27.0        4.0         151.0        90.0   2950.0          17.3\n",
       " 388 │    27.0        4.0         140.0        86.0   2790.0          15.6     ⋯\n",
       " 389 │    44.0        4.0          97.0        52.0   2130.0          24.6\n",
       " 390 │    32.0        4.0         135.0        84.0   2295.0          11.6\n",
       " 391 │    28.0        4.0         120.0        79.0   2625.0          18.6\n",
       " 392 │    31.0        4.0         119.0        82.0   2720.0          19.4     ⋯\n",
       "\u001b[36m                                                  4 columns and 371 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = dropmissing(df1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let us find all rows that correspond to `\"saab\"` brand. You can do it in two ways, either indexing or using `filter` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>4×10 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th><th style = \"text-align: left;\">brand</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"SubString{String}\" style = \"text-align: left;\">SubStrin…</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">104.0</td><td style = \"text-align: right;\">95.0</td><td style = \"text-align: right;\">2375.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99e</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">24.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2660.0</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">73.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2671.0</td><td style = \"text-align: right;\">13.5</td><td style = \"text-align: right;\">75.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">21.6</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2795.0</td><td style = \"text-align: right;\">15.7</td><td style = \"text-align: right;\">78.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99gle</td><td style = \"text-align: left;\">saab</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t2 & 24.0 & 4.0 & 121.0 & 110.0 & 2660.0 & 14.0 & 73.0 & 2.0 & $\\dots$ \\\\\n",
       "\t3 & 25.0 & 4.0 & 121.0 & 115.0 & 2671.0 & 13.5 & 75.0 & 2.0 & $\\dots$ \\\\\n",
       "\t4 & 21.6 & 4.0 & 121.0 & 115.0 & 2795.0 & 15.7 & 78.0 & 2.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m4×10 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg     \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m ye\u001b[0m ⋯\n",
       "     │\u001b[90m Float64 \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │    25.0        4.0         104.0        95.0   2375.0          17.5     ⋯\n",
       "   2 │    24.0        4.0         121.0       110.0   2660.0          14.0\n",
       "   3 │    25.0        4.0         121.0       115.0   2671.0          13.5\n",
       "   4 │    21.6        4.0         121.0       115.0   2795.0          15.7\n",
       "\u001b[36m                                                               4 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[df2.brand .== \"saab\", :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>4×10 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th><th style = \"text-align: left;\">brand</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"SubString{String}\" style = \"text-align: left;\">SubStrin…</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">104.0</td><td style = \"text-align: right;\">95.0</td><td style = \"text-align: right;\">2375.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99e</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">24.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2660.0</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">73.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2671.0</td><td style = \"text-align: right;\">13.5</td><td style = \"text-align: right;\">75.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">21.6</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2795.0</td><td style = \"text-align: right;\">15.7</td><td style = \"text-align: right;\">78.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99gle</td><td style = \"text-align: left;\">saab</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t2 & 24.0 & 4.0 & 121.0 & 110.0 & 2660.0 & 14.0 & 73.0 & 2.0 & $\\dots$ \\\\\n",
       "\t3 & 25.0 & 4.0 & 121.0 & 115.0 & 2671.0 & 13.5 & 75.0 & 2.0 & $\\dots$ \\\\\n",
       "\t4 & 21.6 & 4.0 & 121.0 & 115.0 & 2795.0 & 15.7 & 78.0 & 2.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m4×10 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg     \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m ye\u001b[0m ⋯\n",
       "     │\u001b[90m Float64 \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │    25.0        4.0         104.0        95.0   2375.0          17.5     ⋯\n",
       "   2 │    24.0        4.0         121.0       110.0   2660.0          14.0\n",
       "   3 │    25.0        4.0         121.0       115.0   2671.0          13.5\n",
       "   4 │    21.6        4.0         121.0       115.0   2795.0          15.7\n",
       "\u001b[36m                                                               4 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter(:brand => ==(\"saab\"), df2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the `:brand => ==(\"saab\")` syntax means that we take elements of `:brand` column and pass it to `==(\"saab\")` function.\n",
    "\n",
    "Now `==(\"saab\")` is just a shorthand for `x -> x == \"saab\"`.\n",
    "\n",
    "Alternatively we could do the filtering operation in the following way (this is a bit slower but you might find it more readable):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>4×10 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">mpg</th><th style = \"text-align: left;\">cylinders</th><th style = \"text-align: left;\">displacement</th><th style = \"text-align: left;\">horsepower</th><th style = \"text-align: left;\">weight</th><th style = \"text-align: left;\">acceleration</th><th style = \"text-align: left;\">year</th><th style = \"text-align: left;\">origin</th><th style = \"text-align: left;\">name</th><th style = \"text-align: left;\">brand</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"String\" style = \"text-align: left;\">String</th><th title = \"SubString{String}\" style = \"text-align: left;\">SubStrin…</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">104.0</td><td style = \"text-align: right;\">95.0</td><td style = \"text-align: right;\">2375.0</td><td style = \"text-align: right;\">17.5</td><td style = \"text-align: right;\">70.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99e</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">24.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">110.0</td><td style = \"text-align: right;\">2660.0</td><td style = \"text-align: right;\">14.0</td><td style = \"text-align: right;\">73.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">25.0</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2671.0</td><td style = \"text-align: right;\">13.5</td><td style = \"text-align: right;\">75.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99le</td><td style = \"text-align: left;\">saab</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">21.6</td><td style = \"text-align: right;\">4.0</td><td style = \"text-align: right;\">121.0</td><td style = \"text-align: right;\">115.0</td><td style = \"text-align: right;\">2795.0</td><td style = \"text-align: right;\">15.7</td><td style = \"text-align: right;\">78.0</td><td style = \"text-align: right;\">2.0</td><td style = \"text-align: left;\">saab 99gle</td><td style = \"text-align: left;\">saab</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccccc}\n",
       "\t& mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 25.0 & 4.0 & 104.0 & 95.0 & 2375.0 & 17.5 & 70.0 & 2.0 & $\\dots$ \\\\\n",
       "\t2 & 24.0 & 4.0 & 121.0 & 110.0 & 2660.0 & 14.0 & 73.0 & 2.0 & $\\dots$ \\\\\n",
       "\t3 & 25.0 & 4.0 & 121.0 & 115.0 & 2671.0 & 13.5 & 75.0 & 2.0 & $\\dots$ \\\\\n",
       "\t4 & 21.6 & 4.0 & 121.0 & 115.0 & 2795.0 & 15.7 & 78.0 & 2.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m4×10 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m mpg     \u001b[0m\u001b[1m cylinders \u001b[0m\u001b[1m displacement \u001b[0m\u001b[1m horsepower \u001b[0m\u001b[1m weight  \u001b[0m\u001b[1m acceleration \u001b[0m\u001b[1m ye\u001b[0m ⋯\n",
       "     │\u001b[90m Float64 \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │    25.0        4.0         104.0        95.0   2375.0          17.5     ⋯\n",
       "   2 │    24.0        4.0         121.0       110.0   2660.0          14.0\n",
       "   3 │    25.0        4.0         121.0       115.0   2671.0          13.5\n",
       "   4 │    21.6        4.0         121.0       115.0   2795.0          15.7\n",
       "\u001b[36m                                                               4 columns omitted\u001b[0m"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter(row -> row.brand == \"saab\", df2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To finish this part of the tutorial let us save the `df2` file to auto2.csv and auto2.arrow files. We will use them later in the next parts of the course."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"auto2.csv\""
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CSV.write(\"auto2.csv\", df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"auto2.arrow\""
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Arrow.write(\"auto2.arrow\", df2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us just quickly inspect what we have written to disk in auto2.csv (auto2.arrow file is binary) before we finish:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "393-element Vector{String}:\n",
       " \"mpg,cylinders,displacement,hors\" ⋯ 18 bytes ⋯ \"leration,year,origin,name,brand\"\n",
       " \"18.0,8.0,307.0,130.0,3504.0,12.0,70.0,1.0,chevrolet chevelle malibu,chevrolet\"\n",
       " \"15.0,8.0,350.0,165.0,3693.0,11.5,70.0,1.0,buick skylark 320,buick\"\n",
       " \"18.0,8.0,318.0,150.0,3436.0,11.0,70.0,1.0,plymouth satellite,plymouth\"\n",
       " \"16.0,8.0,304.0,150.0,3433.0,12.0,70.0,1.0,amc rebel sst,amc\"\n",
       " \"17.0,8.0,302.0,140.0,3449.0,10.5,70.0,1.0,ford torino,ford\"\n",
       " \"15.0,8.0,429.0,198.0,4341.0,10.0,70.0,1.0,ford galaxie 500,ford\"\n",
       " \"14.0,8.0,454.0,220.0,4354.0,9.0,70.0,1.0,chevrolet impala,chevrolet\"\n",
       " \"14.0,8.0,440.0,215.0,4312.0,8.5,70.0,1.0,plymouth fury iii,plymouth\"\n",
       " \"14.0,8.0,455.0,225.0,4425.0,10.0,70.0,1.0,pontiac catalina,pontiac\"\n",
       " \"15.0,8.0,390.0,190.0,3850.0,8.5,70.0,1.0,amc ambassador dpl,amc\"\n",
       " \"15.0,8.0,383.0,170.0,3563.0,10.0,70.0,1.0,dodge challenger se,dodge\"\n",
       " \"14.0,8.0,340.0,160.0,3609.0,8.0,70.0,1.0,plymouth 'cuda 340,plymouth\"\n",
       " ⋮\n",
       " \"25.0,6.0,181.0,110.0,2945.0,16.4,82.0,1.0,buick century limited,buick\"\n",
       " \"38.0,6.0,262.0,85.0,3015.0,17.0\" ⋯ 23 bytes ⋯ \"tlass ciera (diesel),oldsmobile\"\n",
       " \"26.0,4.0,156.0,92.0,2585.0,14.5,82.0,1.0,chrysler lebaron medallion,chrysler\"\n",
       " \"22.0,6.0,232.0,112.0,2835.0,14.7,82.0,1.0,ford granada l,ford\"\n",
       " \"32.0,4.0,144.0,96.0,2665.0,13.9,82.0,3.0,toyota celica gt,toyota\"\n",
       " \"36.0,4.0,135.0,84.0,2370.0,13.0,82.0,1.0,dodge charger 2.2,dodge\"\n",
       " \"27.0,4.0,151.0,90.0,2950.0,17.3,82.0,1.0,chevrolet camaro,chevrolet\"\n",
       " \"27.0,4.0,140.0,86.0,2790.0,15.6,82.0,1.0,ford mustang gl,ford\"\n",
       " \"44.0,4.0,97.0,52.0,2130.0,24.6,82.0,2.0,vw pickup,vw\"\n",
       " \"32.0,4.0,135.0,84.0,2295.0,11.6,82.0,1.0,dodge rampage,dodge\"\n",
       " \"28.0,4.0,120.0,79.0,2625.0,18.6,82.0,1.0,ford ranger,ford\"\n",
       " \"31.0,4.0,119.0,82.0,2720.0,19.4,82.0,1.0,chevy s-10,chevy\""
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "readlines(\"auto2.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that CSV.jl by default used a comma to separate the fields in our file and written a header in the first row of the file."
   ]
  }
 ],
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