How to make a table function on a dataframe based on a series of subsets?

I have these many datasets : df as the main data frame (but let’s imagine all of them as very big datasets)

df = data.frame(x = seq(1,20,2),
y = c('a','a','b','c','a','a','b','c','a','a'),
z = c('d','e','e','d','f','e','e','d','e','f') )

g = data.frame(xx = c(2,3,4,5,7,8,9) )

h = data.frame(xx = c(3,5,7,8,9) )

i = data.frame(xx = c(2,3,6,8) )

j = data.frame(xx = c(1,3,6) )

And I wish to make a group of tables of frequency to the y column of df using the xx of each other dataframe each time (xx is used to subset df).

And then making a group of tables of frequency to the Z column of df using the xx of each other dataframe each time (xx is used to subset df).

>Solution :

We could place the datasets in a list (dplyr::lst– returns a named list), loop over the list with map, subset the main dataset based on the ‘x’ column or do a inner_join and get the frequency count

library(dplyr)
library(purrr)
map(lst(g, h, i,j), 
   ~ inner_join(df, .x, by = c("x" = "xx")) %>%      
       count(y, name = 'Count'))

-output

$g
  y Count
1 a     2
2 b     1
3 c     1

$h
  y Count
1 a     2
2 b     1
3 c     1

$i
  y Count
1 a     1

$j
  y Count
1 a     2

Or in base R

lapply(list(g = g, h = h, i = i, j = j),
  \(dat) subset(df, x %in% dat$xx, select = y ) |>
      table())