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coding_data_with_match.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Coding your data with a dictionary and the `match()` function"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sometimes it may be appropriate to show an analysis you are doing with coded data. For example you may be analyzing\n",
"different institutions or companies with regard to some performance measure and you need to keep it anonymous.\n",
"In the below example we will perform coding for the car companies in the `mtcars` dataset."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**First we will extend the dataset to contain a column referring to the car company.**"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 6 × 12</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>mpg</th><th scope=col>cyl</th><th scope=col>disp</th><th scope=col>hp</th><th scope=col>drat</th><th scope=col>wt</th><th scope=col>qsec</th><th scope=col>vs</th><th scope=col>am</th><th scope=col>gear</th><th scope=col>carb</th><th scope=col>company</th></tr>\n",
"\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>Mazda RX4</th><td>21.0</td><td>6</td><td>160</td><td>110</td><td>3.90</td><td>2.620</td><td>16.46</td><td>0</td><td>1</td><td>4</td><td>4</td><td>Mazda </td></tr>\n",
"\t<tr><th scope=row>Mazda RX4 Wag</th><td>21.0</td><td>6</td><td>160</td><td>110</td><td>3.90</td><td>2.875</td><td>17.02</td><td>0</td><td>1</td><td>4</td><td>4</td><td>Mazda </td></tr>\n",
"\t<tr><th scope=row>Datsun 710</th><td>22.8</td><td>4</td><td>108</td><td> 93</td><td>3.85</td><td>2.320</td><td>18.61</td><td>1</td><td>1</td><td>4</td><td>1</td><td>Datsun </td></tr>\n",
"\t<tr><th scope=row>Hornet 4 Drive</th><td>21.4</td><td>6</td><td>258</td><td>110</td><td>3.08</td><td>3.215</td><td>19.44</td><td>1</td><td>0</td><td>3</td><td>1</td><td>Hornet </td></tr>\n",
"\t<tr><th scope=row>Hornet Sportabout</th><td>18.7</td><td>8</td><td>360</td><td>175</td><td>3.15</td><td>3.440</td><td>17.02</td><td>0</td><td>0</td><td>3</td><td>2</td><td>Hornet </td></tr>\n",
"\t<tr><th scope=row>Valiant</th><td>18.1</td><td>6</td><td>225</td><td>105</td><td>2.76</td><td>3.460</td><td>20.22</td><td>1</td><td>0</td><td>3</td><td>1</td><td>Valiant</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 6 × 12\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & mpg & cyl & disp & hp & drat & wt & qsec & vs & am & gear & carb & company\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <chr>\\\\\n",
"\\hline\n",
"\tMazda RX4 & 21.0 & 6 & 160 & 110 & 3.90 & 2.620 & 16.46 & 0 & 1 & 4 & 4 & Mazda \\\\\n",
"\tMazda RX4 Wag & 21.0 & 6 & 160 & 110 & 3.90 & 2.875 & 17.02 & 0 & 1 & 4 & 4 & Mazda \\\\\n",
"\tDatsun 710 & 22.8 & 4 & 108 & 93 & 3.85 & 2.320 & 18.61 & 1 & 1 & 4 & 1 & Datsun \\\\\n",
"\tHornet 4 Drive & 21.4 & 6 & 258 & 110 & 3.08 & 3.215 & 19.44 & 1 & 0 & 3 & 1 & Hornet \\\\\n",
"\tHornet Sportabout & 18.7 & 8 & 360 & 175 & 3.15 & 3.440 & 17.02 & 0 & 0 & 3 & 2 & Hornet \\\\\n",
"\tValiant & 18.1 & 6 & 225 & 105 & 2.76 & 3.460 & 20.22 & 1 & 0 & 3 & 1 & Valiant\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 6 × 12\n",
"\n",
"| <!--/--> | mpg &lt;dbl&gt; | cyl &lt;dbl&gt; | disp &lt;dbl&gt; | hp &lt;dbl&gt; | drat &lt;dbl&gt; | wt &lt;dbl&gt; | qsec &lt;dbl&gt; | vs &lt;dbl&gt; | am &lt;dbl&gt; | gear &lt;dbl&gt; | carb &lt;dbl&gt; | company &lt;chr&gt; |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| Mazda RX4 | 21.0 | 6 | 160 | 110 | 3.90 | 2.620 | 16.46 | 0 | 1 | 4 | 4 | Mazda |\n",
"| Mazda RX4 Wag | 21.0 | 6 | 160 | 110 | 3.90 | 2.875 | 17.02 | 0 | 1 | 4 | 4 | Mazda |\n",
"| Datsun 710 | 22.8 | 4 | 108 | 93 | 3.85 | 2.320 | 18.61 | 1 | 1 | 4 | 1 | Datsun |\n",
"| Hornet 4 Drive | 21.4 | 6 | 258 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 | Hornet |\n",
"| Hornet Sportabout | 18.7 | 8 | 360 | 175 | 3.15 | 3.440 | 17.02 | 0 | 0 | 3 | 2 | Hornet |\n",
"| Valiant | 18.1 | 6 | 225 | 105 | 2.76 | 3.460 | 20.22 | 1 | 0 | 3 | 1 | Valiant |\n",
"\n"
],
"text/plain": [
" mpg cyl disp hp drat wt qsec vs am gear carb company\n",
"Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda \n",
"Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 Mazda \n",
"Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 Datsun \n",
"Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 Hornet \n",
"Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 Hornet \n",
"Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 Valiant"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"library(stringr) # for string splitting\n",
"\n",
"# create new object\n",
"mtcars_new <- mtcars\n",
"# extract the car company by using only first chunk of model string\n",
"mtcars_new$company <- str_split(string = row.names(mtcars_new),\n",
" pattern = \"\\\\s+\",\n",
" simplify = TRUE)[, 1]\n",
"# show overview\n",
"head(mtcars_new)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Now we create a dictionary.**"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 6 × 2</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>company</th><th scope=col>company_id</th></tr>\n",
"\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>1</th><td>Mazda </td><td>561</td></tr>\n",
"\t<tr><th scope=row>2</th><td>Datsun </td><td>551</td></tr>\n",
"\t<tr><th scope=row>3</th><td>Hornet </td><td>159</td></tr>\n",
"\t<tr><th scope=row>4</th><td>Valiant</td><td>462</td></tr>\n",
"\t<tr><th scope=row>5</th><td>Duster </td><td>397</td></tr>\n",
"\t<tr><th scope=row>6</th><td>Merc </td><td>363</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 6 × 2\n",
"\\begin{tabular}{r|ll}\n",
" & company & company\\_id\\\\\n",
" & <fct> & <fct>\\\\\n",
"\\hline\n",
"\t1 & Mazda & 561\\\\\n",
"\t2 & Datsun & 551\\\\\n",
"\t3 & Hornet & 159\\\\\n",
"\t4 & Valiant & 462\\\\\n",
"\t5 & Duster & 397\\\\\n",
"\t6 & Merc & 363\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 6 × 2\n",
"\n",
"| <!--/--> | company &lt;fct&gt; | company_id &lt;fct&gt; |\n",
"|---|---|---|\n",
"| 1 | Mazda | 561 |\n",
"| 2 | Datsun | 551 |\n",
"| 3 | Hornet | 159 |\n",
"| 4 | Valiant | 462 |\n",
"| 5 | Duster | 397 |\n",
"| 6 | Merc | 363 |\n",
"\n"
],
"text/plain": [
" company company_id\n",
"1 Mazda 561 \n",
"2 Datsun 551 \n",
"3 Hornet 159 \n",
"4 Valiant 462 \n",
"5 Duster 397 \n",
"6 Merc 363 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# get unique companies as vector\n",
"company <- unique(mtcars_new$company)\n",
"# reproducibly sample some random three digit ids for each company\n",
"set.seed(1337)\n",
"company_id <- sample(x = 100:900, size = length(company), replace = FALSE)\n",
"# create dict\n",
"dictionary <- as.data.frame(cbind(company, company_id))\n",
"# show dict head\n",
"head(dictionary)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Now we add the new coded column to the data with the `match()` function.** \n",
"From the `match()` documentation: \"match returns a vector of the positions of matches of its first argument in its second.\" \n",
"In other words, and more specific to our current case: \"in which dictionary lines do company entries from our dataset match.\" \n",
"Matching the `company` column in `mtcars_new` with with the `company` column in the `dictionary` will thus return the correct `dictionary` indices of the ids for each company which can then be added as a new column to `mtcars_new`."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"mtcars_new$company_id <- dictionary$company_id[match(mtcars_new$company, dictionary$company)]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 32 × 13</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>mpg</th><th scope=col>cyl</th><th scope=col>disp</th><th scope=col>hp</th><th scope=col>drat</th><th scope=col>wt</th><th scope=col>qsec</th><th scope=col>vs</th><th scope=col>am</th><th scope=col>gear</th><th scope=col>carb</th><th scope=col>company</th><th scope=col>company_id</th></tr>\n",
"\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>Mazda RX4</th><td>21.0</td><td>6</td><td>160.0</td><td>110</td><td>3.90</td><td>2.620</td><td>16.46</td><td>0</td><td>1</td><td>4</td><td>4</td><td>Mazda </td><td>561</td></tr>\n",
"\t<tr><th scope=row>Mazda RX4 Wag</th><td>21.0</td><td>6</td><td>160.0</td><td>110</td><td>3.90</td><td>2.875</td><td>17.02</td><td>0</td><td>1</td><td>4</td><td>4</td><td>Mazda </td><td>561</td></tr>\n",
"\t<tr><th scope=row>Datsun 710</th><td>22.8</td><td>4</td><td>108.0</td><td> 93</td><td>3.85</td><td>2.320</td><td>18.61</td><td>1</td><td>1</td><td>4</td><td>1</td><td>Datsun </td><td>551</td></tr>\n",
"\t<tr><th scope=row>Hornet 4 Drive</th><td>21.4</td><td>6</td><td>258.0</td><td>110</td><td>3.08</td><td>3.215</td><td>19.44</td><td>1</td><td>0</td><td>3</td><td>1</td><td>Hornet </td><td>159</td></tr>\n",
"\t<tr><th scope=row>Hornet Sportabout</th><td>18.7</td><td>8</td><td>360.0</td><td>175</td><td>3.15</td><td>3.440</td><td>17.02</td><td>0</td><td>0</td><td>3</td><td>2</td><td>Hornet </td><td>159</td></tr>\n",
"\t<tr><th scope=row>Valiant</th><td>18.1</td><td>6</td><td>225.0</td><td>105</td><td>2.76</td><td>3.460</td><td>20.22</td><td>1</td><td>0</td><td>3</td><td>1</td><td>Valiant </td><td>462</td></tr>\n",
"\t<tr><th scope=row>Duster 360</th><td>14.3</td><td>8</td><td>360.0</td><td>245</td><td>3.21</td><td>3.570</td><td>15.84</td><td>0</td><td>0</td><td>3</td><td>4</td><td>Duster </td><td>397</td></tr>\n",
"\t<tr><th scope=row>Merc 240D</th><td>24.4</td><td>4</td><td>146.7</td><td> 62</td><td>3.69</td><td>3.190</td><td>20.00</td><td>1</td><td>0</td><td>4</td><td>2</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 230</th><td>22.8</td><td>4</td><td>140.8</td><td> 95</td><td>3.92</td><td>3.150</td><td>22.90</td><td>1</td><td>0</td><td>4</td><td>2</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 280</th><td>19.2</td><td>6</td><td>167.6</td><td>123</td><td>3.92</td><td>3.440</td><td>18.30</td><td>1</td><td>0</td><td>4</td><td>4</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 280C</th><td>17.8</td><td>6</td><td>167.6</td><td>123</td><td>3.92</td><td>3.440</td><td>18.90</td><td>1</td><td>0</td><td>4</td><td>4</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 450SE</th><td>16.4</td><td>8</td><td>275.8</td><td>180</td><td>3.07</td><td>4.070</td><td>17.40</td><td>0</td><td>0</td><td>3</td><td>3</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 450SL</th><td>17.3</td><td>8</td><td>275.8</td><td>180</td><td>3.07</td><td>3.730</td><td>17.60</td><td>0</td><td>0</td><td>3</td><td>3</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Merc 450SLC</th><td>15.2</td><td>8</td><td>275.8</td><td>180</td><td>3.07</td><td>3.780</td><td>18.00</td><td>0</td><td>0</td><td>3</td><td>3</td><td>Merc </td><td>363</td></tr>\n",
"\t<tr><th scope=row>Cadillac Fleetwood</th><td>10.4</td><td>8</td><td>472.0</td><td>205</td><td>2.93</td><td>5.250</td><td>17.98</td><td>0</td><td>0</td><td>3</td><td>4</td><td>Cadillac</td><td>853</td></tr>\n",
"\t<tr><th scope=row>Lincoln Continental</th><td>10.4</td><td>8</td><td>460.0</td><td>215</td><td>3.00</td><td>5.424</td><td>17.82</td><td>0</td><td>0</td><td>3</td><td>4</td><td>Lincoln </td><td>323</td></tr>\n",
"\t<tr><th scope=row>Chrysler Imperial</th><td>14.7</td><td>8</td><td>440.0</td><td>230</td><td>3.23</td><td>5.345</td><td>17.42</td><td>0</td><td>0</td><td>3</td><td>4</td><td>Chrysler</td><td>294</td></tr>\n",
"\t<tr><th scope=row>Fiat 128</th><td>32.4</td><td>4</td><td> 78.7</td><td> 66</td><td>4.08</td><td>2.200</td><td>19.47</td><td>1</td><td>1</td><td>4</td><td>1</td><td>Fiat </td><td>215</td></tr>\n",
"\t<tr><th scope=row>Honda Civic</th><td>30.4</td><td>4</td><td> 75.7</td><td> 52</td><td>4.93</td><td>1.615</td><td>18.52</td><td>1</td><td>1</td><td>4</td><td>2</td><td>Honda </td><td>874</td></tr>\n",
"\t<tr><th scope=row>Toyota Corolla</th><td>33.9</td><td>4</td><td> 71.1</td><td> 65</td><td>4.22</td><td>1.835</td><td>19.90</td><td>1</td><td>1</td><td>4</td><td>1</td><td>Toyota </td><td>885</td></tr>\n",
"\t<tr><th scope=row>Toyota Corona</th><td>21.5</td><td>4</td><td>120.1</td><td> 97</td><td>3.70</td><td>2.465</td><td>20.01</td><td>1</td><td>0</td><td>3</td><td>1</td><td>Toyota </td><td>885</td></tr>\n",
"\t<tr><th scope=row>Dodge Challenger</th><td>15.5</td><td>8</td><td>318.0</td><td>150</td><td>2.76</td><td>3.520</td><td>16.87</td><td>0</td><td>0</td><td>3</td><td>2</td><td>Dodge </td><td>752</td></tr>\n",
"\t<tr><th scope=row>AMC Javelin</th><td>15.2</td><td>8</td><td>304.0</td><td>150</td><td>3.15</td><td>3.435</td><td>17.30</td><td>0</td><td>0</td><td>3</td><td>2</td><td>AMC </td><td>252</td></tr>\n",
"\t<tr><th scope=row>Camaro Z28</th><td>13.3</td><td>8</td><td>350.0</td><td>245</td><td>3.73</td><td>3.840</td><td>15.41</td><td>0</td><td>0</td><td>3</td><td>4</td><td>Camaro </td><td>872</td></tr>\n",
"\t<tr><th scope=row>Pontiac Firebird</th><td>19.2</td><td>8</td><td>400.0</td><td>175</td><td>3.08</td><td>3.845</td><td>17.05</td><td>0</td><td>0</td><td>3</td><td>2</td><td>Pontiac </td><td>119</td></tr>\n",
"\t<tr><th scope=row>Fiat X1-9</th><td>27.3</td><td>4</td><td> 79.0</td><td> 66</td><td>4.08</td><td>1.935</td><td>18.90</td><td>1</td><td>1</td><td>4</td><td>1</td><td>Fiat </td><td>215</td></tr>\n",
"\t<tr><th scope=row>Porsche 914-2</th><td>26.0</td><td>4</td><td>120.3</td><td> 91</td><td>4.43</td><td>2.140</td><td>16.70</td><td>0</td><td>1</td><td>5</td><td>2</td><td>Porsche </td><td>863</td></tr>\n",
"\t<tr><th scope=row>Lotus Europa</th><td>30.4</td><td>4</td><td> 95.1</td><td>113</td><td>3.77</td><td>1.513</td><td>16.90</td><td>1</td><td>1</td><td>5</td><td>2</td><td>Lotus </td><td>824</td></tr>\n",
"\t<tr><th scope=row>Ford Pantera L</th><td>15.8</td><td>8</td><td>351.0</td><td>264</td><td>4.22</td><td>3.170</td><td>14.50</td><td>0</td><td>1</td><td>5</td><td>4</td><td>Ford </td><td>365</td></tr>\n",
"\t<tr><th scope=row>Ferrari Dino</th><td>19.7</td><td>6</td><td>145.0</td><td>175</td><td>3.62</td><td>2.770</td><td>15.50</td><td>0</td><td>1</td><td>5</td><td>6</td><td>Ferrari </td><td>292</td></tr>\n",
"\t<tr><th scope=row>Maserati Bora</th><td>15.0</td><td>8</td><td>301.0</td><td>335</td><td>3.54</td><td>3.570</td><td>14.60</td><td>0</td><td>1</td><td>5</td><td>8</td><td>Maserati</td><td>763</td></tr>\n",
"\t<tr><th scope=row>Volvo 142E</th><td>21.4</td><td>4</td><td>121.0</td><td>109</td><td>4.11</td><td>2.780</td><td>18.60</td><td>1</td><td>1</td><td>4</td><td>2</td><td>Volvo </td><td>664</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 32 × 13\n",
"\\begin{tabular}{r|lllllllllllll}\n",
" & mpg & cyl & disp & hp & drat & wt & qsec & vs & am & gear & carb & company & company\\_id\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <fct>\\\\\n",
"\\hline\n",
"\tMazda RX4 & 21.0 & 6 & 160.0 & 110 & 3.90 & 2.620 & 16.46 & 0 & 1 & 4 & 4 & Mazda & 561\\\\\n",
"\tMazda RX4 Wag & 21.0 & 6 & 160.0 & 110 & 3.90 & 2.875 & 17.02 & 0 & 1 & 4 & 4 & Mazda & 561\\\\\n",
"\tDatsun 710 & 22.8 & 4 & 108.0 & 93 & 3.85 & 2.320 & 18.61 & 1 & 1 & 4 & 1 & Datsun & 551\\\\\n",
"\tHornet 4 Drive & 21.4 & 6 & 258.0 & 110 & 3.08 & 3.215 & 19.44 & 1 & 0 & 3 & 1 & Hornet & 159\\\\\n",
"\tHornet Sportabout & 18.7 & 8 & 360.0 & 175 & 3.15 & 3.440 & 17.02 & 0 & 0 & 3 & 2 & Hornet & 159\\\\\n",
"\tValiant & 18.1 & 6 & 225.0 & 105 & 2.76 & 3.460 & 20.22 & 1 & 0 & 3 & 1 & Valiant & 462\\\\\n",
"\tDuster 360 & 14.3 & 8 & 360.0 & 245 & 3.21 & 3.570 & 15.84 & 0 & 0 & 3 & 4 & Duster & 397\\\\\n",
"\tMerc 240D & 24.4 & 4 & 146.7 & 62 & 3.69 & 3.190 & 20.00 & 1 & 0 & 4 & 2 & Merc & 363\\\\\n",
"\tMerc 230 & 22.8 & 4 & 140.8 & 95 & 3.92 & 3.150 & 22.90 & 1 & 0 & 4 & 2 & Merc & 363\\\\\n",
"\tMerc 280 & 19.2 & 6 & 167.6 & 123 & 3.92 & 3.440 & 18.30 & 1 & 0 & 4 & 4 & Merc & 363\\\\\n",
"\tMerc 280C & 17.8 & 6 & 167.6 & 123 & 3.92 & 3.440 & 18.90 & 1 & 0 & 4 & 4 & Merc & 363\\\\\n",
"\tMerc 450SE & 16.4 & 8 & 275.8 & 180 & 3.07 & 4.070 & 17.40 & 0 & 0 & 3 & 3 & Merc & 363\\\\\n",
"\tMerc 450SL & 17.3 & 8 & 275.8 & 180 & 3.07 & 3.730 & 17.60 & 0 & 0 & 3 & 3 & Merc & 363\\\\\n",
"\tMerc 450SLC & 15.2 & 8 & 275.8 & 180 & 3.07 & 3.780 & 18.00 & 0 & 0 & 3 & 3 & Merc & 363\\\\\n",
"\tCadillac Fleetwood & 10.4 & 8 & 472.0 & 205 & 2.93 & 5.250 & 17.98 & 0 & 0 & 3 & 4 & Cadillac & 853\\\\\n",
"\tLincoln Continental & 10.4 & 8 & 460.0 & 215 & 3.00 & 5.424 & 17.82 & 0 & 0 & 3 & 4 & Lincoln & 323\\\\\n",
"\tChrysler Imperial & 14.7 & 8 & 440.0 & 230 & 3.23 & 5.345 & 17.42 & 0 & 0 & 3 & 4 & Chrysler & 294\\\\\n",
"\tFiat 128 & 32.4 & 4 & 78.7 & 66 & 4.08 & 2.200 & 19.47 & 1 & 1 & 4 & 1 & Fiat & 215\\\\\n",
"\tHonda Civic & 30.4 & 4 & 75.7 & 52 & 4.93 & 1.615 & 18.52 & 1 & 1 & 4 & 2 & Honda & 874\\\\\n",
"\tToyota Corolla & 33.9 & 4 & 71.1 & 65 & 4.22 & 1.835 & 19.90 & 1 & 1 & 4 & 1 & Toyota & 885\\\\\n",
"\tToyota Corona & 21.5 & 4 & 120.1 & 97 & 3.70 & 2.465 & 20.01 & 1 & 0 & 3 & 1 & Toyota & 885\\\\\n",
"\tDodge Challenger & 15.5 & 8 & 318.0 & 150 & 2.76 & 3.520 & 16.87 & 0 & 0 & 3 & 2 & Dodge & 752\\\\\n",
"\tAMC Javelin & 15.2 & 8 & 304.0 & 150 & 3.15 & 3.435 & 17.30 & 0 & 0 & 3 & 2 & AMC & 252\\\\\n",
"\tCamaro Z28 & 13.3 & 8 & 350.0 & 245 & 3.73 & 3.840 & 15.41 & 0 & 0 & 3 & 4 & Camaro & 872\\\\\n",
"\tPontiac Firebird & 19.2 & 8 & 400.0 & 175 & 3.08 & 3.845 & 17.05 & 0 & 0 & 3 & 2 & Pontiac & 119\\\\\n",
"\tFiat X1-9 & 27.3 & 4 & 79.0 & 66 & 4.08 & 1.935 & 18.90 & 1 & 1 & 4 & 1 & Fiat & 215\\\\\n",
"\tPorsche 914-2 & 26.0 & 4 & 120.3 & 91 & 4.43 & 2.140 & 16.70 & 0 & 1 & 5 & 2 & Porsche & 863\\\\\n",
"\tLotus Europa & 30.4 & 4 & 95.1 & 113 & 3.77 & 1.513 & 16.90 & 1 & 1 & 5 & 2 & Lotus & 824\\\\\n",
"\tFord Pantera L & 15.8 & 8 & 351.0 & 264 & 4.22 & 3.170 & 14.50 & 0 & 1 & 5 & 4 & Ford & 365\\\\\n",
"\tFerrari Dino & 19.7 & 6 & 145.0 & 175 & 3.62 & 2.770 & 15.50 & 0 & 1 & 5 & 6 & Ferrari & 292\\\\\n",
"\tMaserati Bora & 15.0 & 8 & 301.0 & 335 & 3.54 & 3.570 & 14.60 & 0 & 1 & 5 & 8 & Maserati & 763\\\\\n",
"\tVolvo 142E & 21.4 & 4 & 121.0 & 109 & 4.11 & 2.780 & 18.60 & 1 & 1 & 4 & 2 & Volvo & 664\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 32 × 13\n",
"\n",
"| <!--/--> | mpg &lt;dbl&gt; | cyl &lt;dbl&gt; | disp &lt;dbl&gt; | hp &lt;dbl&gt; | drat &lt;dbl&gt; | wt &lt;dbl&gt; | qsec &lt;dbl&gt; | vs &lt;dbl&gt; | am &lt;dbl&gt; | gear &lt;dbl&gt; | carb &lt;dbl&gt; | company &lt;chr&gt; | company_id &lt;fct&gt; |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| Mazda RX4 | 21.0 | 6 | 160.0 | 110 | 3.90 | 2.620 | 16.46 | 0 | 1 | 4 | 4 | Mazda | 561 |\n",
"| Mazda RX4 Wag | 21.0 | 6 | 160.0 | 110 | 3.90 | 2.875 | 17.02 | 0 | 1 | 4 | 4 | Mazda | 561 |\n",
"| Datsun 710 | 22.8 | 4 | 108.0 | 93 | 3.85 | 2.320 | 18.61 | 1 | 1 | 4 | 1 | Datsun | 551 |\n",
"| Hornet 4 Drive | 21.4 | 6 | 258.0 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 | Hornet | 159 |\n",
"| Hornet Sportabout | 18.7 | 8 | 360.0 | 175 | 3.15 | 3.440 | 17.02 | 0 | 0 | 3 | 2 | Hornet | 159 |\n",
"| Valiant | 18.1 | 6 | 225.0 | 105 | 2.76 | 3.460 | 20.22 | 1 | 0 | 3 | 1 | Valiant | 462 |\n",
"| Duster 360 | 14.3 | 8 | 360.0 | 245 | 3.21 | 3.570 | 15.84 | 0 | 0 | 3 | 4 | Duster | 397 |\n",
"| Merc 240D | 24.4 | 4 | 146.7 | 62 | 3.69 | 3.190 | 20.00 | 1 | 0 | 4 | 2 | Merc | 363 |\n",
"| Merc 230 | 22.8 | 4 | 140.8 | 95 | 3.92 | 3.150 | 22.90 | 1 | 0 | 4 | 2 | Merc | 363 |\n",
"| Merc 280 | 19.2 | 6 | 167.6 | 123 | 3.92 | 3.440 | 18.30 | 1 | 0 | 4 | 4 | Merc | 363 |\n",
"| Merc 280C | 17.8 | 6 | 167.6 | 123 | 3.92 | 3.440 | 18.90 | 1 | 0 | 4 | 4 | Merc | 363 |\n",
"| Merc 450SE | 16.4 | 8 | 275.8 | 180 | 3.07 | 4.070 | 17.40 | 0 | 0 | 3 | 3 | Merc | 363 |\n",
"| Merc 450SL | 17.3 | 8 | 275.8 | 180 | 3.07 | 3.730 | 17.60 | 0 | 0 | 3 | 3 | Merc | 363 |\n",
"| Merc 450SLC | 15.2 | 8 | 275.8 | 180 | 3.07 | 3.780 | 18.00 | 0 | 0 | 3 | 3 | Merc | 363 |\n",
"| Cadillac Fleetwood | 10.4 | 8 | 472.0 | 205 | 2.93 | 5.250 | 17.98 | 0 | 0 | 3 | 4 | Cadillac | 853 |\n",
"| Lincoln Continental | 10.4 | 8 | 460.0 | 215 | 3.00 | 5.424 | 17.82 | 0 | 0 | 3 | 4 | Lincoln | 323 |\n",
"| Chrysler Imperial | 14.7 | 8 | 440.0 | 230 | 3.23 | 5.345 | 17.42 | 0 | 0 | 3 | 4 | Chrysler | 294 |\n",
"| Fiat 128 | 32.4 | 4 | 78.7 | 66 | 4.08 | 2.200 | 19.47 | 1 | 1 | 4 | 1 | Fiat | 215 |\n",
"| Honda Civic | 30.4 | 4 | 75.7 | 52 | 4.93 | 1.615 | 18.52 | 1 | 1 | 4 | 2 | Honda | 874 |\n",
"| Toyota Corolla | 33.9 | 4 | 71.1 | 65 | 4.22 | 1.835 | 19.90 | 1 | 1 | 4 | 1 | Toyota | 885 |\n",
"| Toyota Corona | 21.5 | 4 | 120.1 | 97 | 3.70 | 2.465 | 20.01 | 1 | 0 | 3 | 1 | Toyota | 885 |\n",
"| Dodge Challenger | 15.5 | 8 | 318.0 | 150 | 2.76 | 3.520 | 16.87 | 0 | 0 | 3 | 2 | Dodge | 752 |\n",
"| AMC Javelin | 15.2 | 8 | 304.0 | 150 | 3.15 | 3.435 | 17.30 | 0 | 0 | 3 | 2 | AMC | 252 |\n",
"| Camaro Z28 | 13.3 | 8 | 350.0 | 245 | 3.73 | 3.840 | 15.41 | 0 | 0 | 3 | 4 | Camaro | 872 |\n",
"| Pontiac Firebird | 19.2 | 8 | 400.0 | 175 | 3.08 | 3.845 | 17.05 | 0 | 0 | 3 | 2 | Pontiac | 119 |\n",
"| Fiat X1-9 | 27.3 | 4 | 79.0 | 66 | 4.08 | 1.935 | 18.90 | 1 | 1 | 4 | 1 | Fiat | 215 |\n",
"| Porsche 914-2 | 26.0 | 4 | 120.3 | 91 | 4.43 | 2.140 | 16.70 | 0 | 1 | 5 | 2 | Porsche | 863 |\n",
"| Lotus Europa | 30.4 | 4 | 95.1 | 113 | 3.77 | 1.513 | 16.90 | 1 | 1 | 5 | 2 | Lotus | 824 |\n",
"| Ford Pantera L | 15.8 | 8 | 351.0 | 264 | 4.22 | 3.170 | 14.50 | 0 | 1 | 5 | 4 | Ford | 365 |\n",
"| Ferrari Dino | 19.7 | 6 | 145.0 | 175 | 3.62 | 2.770 | 15.50 | 0 | 1 | 5 | 6 | Ferrari | 292 |\n",
"| Maserati Bora | 15.0 | 8 | 301.0 | 335 | 3.54 | 3.570 | 14.60 | 0 | 1 | 5 | 8 | Maserati | 763 |\n",
"| Volvo 142E | 21.4 | 4 | 121.0 | 109 | 4.11 | 2.780 | 18.60 | 1 | 1 | 4 | 2 | Volvo | 664 |\n",
"\n"
],
"text/plain": [
" mpg cyl disp hp drat wt qsec vs am gear carb\n",
"Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 \n",
"Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 \n",
"Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 \n",
"Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 \n",
"Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 \n",
"Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 \n",
"Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 \n",
"Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 \n",
"Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 \n",
"Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 \n",
"Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 \n",
"Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 \n",
"Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 \n",
"Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 \n",
"Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 \n",
"Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 \n",
"Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 \n",
"Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 \n",
"Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 \n",
"Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 \n",
"Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 \n",
"Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 \n",
"AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 \n",
"Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 \n",
"Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 \n",
"Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 \n",
"Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 \n",
"Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 \n",
"Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 \n",
"Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 \n",
"Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 \n",
"Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 \n",
" company company_id\n",
"Mazda RX4 Mazda 561 \n",
"Mazda RX4 Wag Mazda 561 \n",
"Datsun 710 Datsun 551 \n",
"Hornet 4 Drive Hornet 159 \n",
"Hornet Sportabout Hornet 159 \n",
"Valiant Valiant 462 \n",
"Duster 360 Duster 397 \n",
"Merc 240D Merc 363 \n",
"Merc 230 Merc 363 \n",
"Merc 280 Merc 363 \n",
"Merc 280C Merc 363 \n",
"Merc 450SE Merc 363 \n",
"Merc 450SL Merc 363 \n",
"Merc 450SLC Merc 363 \n",
"Cadillac Fleetwood Cadillac 853 \n",
"Lincoln Continental Lincoln 323 \n",
"Chrysler Imperial Chrysler 294 \n",
"Fiat 128 Fiat 215 \n",
"Honda Civic Honda 874 \n",
"Toyota Corolla Toyota 885 \n",
"Toyota Corona Toyota 885 \n",
"Dodge Challenger Dodge 752 \n",
"AMC Javelin AMC 252 \n",
"Camaro Z28 Camaro 872 \n",
"Pontiac Firebird Pontiac 119 \n",
"Fiat X1-9 Fiat 215 \n",
"Porsche 914-2 Porsche 863 \n",
"Lotus Europa Lotus 824 \n",
"Ford Pantera L Ford 365 \n",
"Ferrari Dino Ferrari 292 \n",
"Maserati Bora Maserati 763 \n",
"Volvo 142E Volvo 664 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mtcars_new"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"TRUE"
],
"text/latex": [
"TRUE"
],
"text/markdown": [
"TRUE"
],
"text/plain": [
"[1] TRUE"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"TRUE"
],
"text/latex": [
"TRUE"
],
"text/markdown": [
"TRUE"
],
"text/plain": [
"[1] TRUE"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"TRUE"
],
"text/latex": [
"TRUE"
],
"text/markdown": [
"TRUE"
],
"text/plain": [
"[1] TRUE"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"TRUE"
],
"text/latex": [
"TRUE"
],
"text/markdown": [
"TRUE"
],
"text/plain": [
"[1] TRUE"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"TRUE"
],
"text/latex": [
"TRUE"
],
"text/markdown": [
"TRUE"
],
"text/plain": [
"[1] TRUE"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# some sanity checks (should all return TRUE)\n",
"# 22x22 matrix in which only once cell per row and column should not be 0\n",
"all.equal(dim(table(mtcars_new$company, mtcars_new$company_id)), c(22, 22))\n",
"# we can sum up the TRUEs\n",
"# i.e. 21 values per row and column should be 0\n",
"all(as.vector(rowSums(table(mtcars_new$company, mtcars_new$company_id) == 0)) == 21)\n",
"all(as.vector(colSums(table(mtcars_new$company, mtcars_new$company_id) == 0)) == 21)\n",
"# or 1 value per row and column should not be 0\n",
"all(as.vector(rowSums(table(mtcars_new$company, mtcars_new$company_id) != 0)) == 1)\n",
"all(as.vector(colSums(table(mtcars_new$company, mtcars_new$company_id) != 0)) == 1)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "conda-env-r-r"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.5.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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