Row-wise and column-wise operations in dplyr and tidyverse

Column- and row-wise operations

With the development of dplyr or its umbrella package tidyverse, it becomes quite straightforward to perform operations over columns or rows in R. These column- or row-wise methods can also be directly integrated with other dplyr verbs like select, mutate, filter and summarise, making them more comparable with other functions in apply or map families. In this blog, I will briefly cover some useful manipulations over rows or columns.

1. Column-wise operation

Example 1: select those string columns with less than 5 levels in the dataset of starwars.

# solution 1: anonymous function (recommended)
starwars %>% 
  select_if(~ is.character(.x) & length(unique(.x)) <= 5)

Final output via select_if function

We can use a convenient function select_if to identify certain columns by multiple criteria. This is essentially equivalent to the following expanded format.

# solution 2: expanded form of function
starwars %>%
  select_if(function(x) is.character(x) & length(unique(x)) <= 5)

It is worth noting that we are using tilde (~) to define an anonymous function, and thus we should use dot x (.x) to…