2.3 Design for Humans and the Tidyverse

The tidyverse offers packages that are easily readable and understood by humans. It enables them to more easily achieve their programming goals.

Consider the mtcars dataset, which comprises fuel consumption and 10 aspects of autombile design and performance from 1973-1974. Previewing the first six rows of the data, we see:

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

If we wanted to arrange these in ascending order based on the mpg and gear variables, how could we do this?

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The function arrange(), in the dplyr package of the tidyverse, takes a data frame and column names as such:

arrange(.data = mtcars, gear, mpg)

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arrange(), and other tidyverse functions, use names that are descriptive and explicit. For general methods, there is a focus on verbs, as seen with the functions pivot_longer() and pivot_wider() in the tidyr package.