Report frequency for multiple variables in a dataframe in R-CodePudding

I have a dataframe with data from a survey. I would like to produce a report in table format with the frequencies of each variable.

So working with the dataset mtcars, having this:

> count(mtcars, cyl)
  cyl  n
1   4 11
2   6  7
3   8 14
> count(mtcars, gear)
  gear  n
1    3 15
2    4 12
3    5  5

I would like to produce a table like this (or something similar):

variable	n
cyl
4	11
6	7
8	14
gear
3	15
4	12
5	5

Any idea as to how this may be achievable?

CodePudding user response：

We can write a nested pair of functions to map count to multiple variables and row-bind the results, using a little tidy evaluation:

library(tidyverse)

count_multi <- function(.data, ...) {
  count_var <- function(var, .data) {
    .data %>% 
      count(Value = as.character({{ var }})) %>%  # coerce to character to
      mutate(                                     # allow multiple var types
        Variable = as.character(ensym(var)),
        .before = everything()
      )
  }
  map_dfr(enquos(...), count_var, .data = .data)
}

mtcars %>% 
  count_multi(cyl, gear)

Output:

  Variable Value  n
1      cyl     4 11
2      cyl     6  7
3      cyl     8 14
4     gear     3 15
5     gear     4 12
6     gear     5  5

I believe you can use kableExtra::pack_rows() to create subheaders for each Variable in markdown.

CodePudding user response：

The below gets us the output in slightly different format. However, it does allow for subset (using column variable which OP's requirement does not.)

library(data.table)

df <- setDT(copy(mtcars))

# select columns as grouping by continuous variables is not appropriate
x <- c('cyl', 'gear')

y <- lapply(x, \(i) df[, .N, i])

names(y) <- x

y <- rbindlist(y, idcol=T, use.names=F)

names(y) <- c('variable', 'class', 'count')

   variable class count
1:      cyl     6     7
2:      cyl     4    11
3:      cyl     8    14
4:     gear     4    12
5:     gear     3    15
6:     gear     5     5