Order columns in a tibble by column type

[AJF]

Hi all,

Does anyone know if there is a way to order columns in a data.frame or tibble by column type?

For example, if the standard gapminder data set looks like this:

suppressPackageStartupMessages(library(dplyr))
library(gapminder)

glimpse(gapminder)
#> Observations: 1,704
#> Variables: 6
#> $ country   <fct> Afghanistan, Afghanistan, Afghanistan, Afghanistan, Af…
#> $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
#> $ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, …
#> $ lifeExp   <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854…
#> $ pop       <int> 8425333, 9240934, 10267083, 11537966, 13079460, 148803…
#> $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.…

If we want to move the columns year and lifeExp to the front, we could utilize the select and everything() function as follows:

gapminder %>% select(year, lifeExp, everything()) %>% glimpse()
#> Observations: 1,704
#> Variables: 6
#> $ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, …
#> $ lifeExp   <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854…
#> $ country   <fct> Afghanistan, Afghanistan, Afghanistan, Afghanistan, Af…
#> $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
#> $ pop       <int> 8425333, 9240934, 10267083, 11537966, 13079460, 148803…
#> $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.…

If we want to only keep the columns of type integer, we could use the select_if() and is.integer functions as follows:

gapminder %>% select_if(is.integer) %>% glimpse()
#> Observations: 1,704
#> Variables: 2
#> $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997,…
#> $ pop  <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 1…

What if we wanted to combine the two? For example if we wanted to programmatically move the integer columns to the front, but keep the rest.

Thanks!

^{Created on 2019-08-08 by the reprex package (v0.3.0)}