Extract rows with levels of a dataframe-CodePudding

I've got a dataframe such as this:

df =  data.frame(col1=c(1,1,1,2,2,2,3,3,3), 
                 col2=as.factor(c('a','b','b','a','a','a','b','a','b')))

Then I extract all the categories (levels) related to each column:

levels_df = expand.grid(unique(df$col1), unique(df$col2))
colnames(levels_df)=c('col1','col2')

My objective now is to perform for the rows belonging to each pair of levels a function. How can I do that?

sapply(levels, FUN, dataset=df)

Any other strategy to perform the same task is accepted. The function operation could be whatever you like, for example a counting function (how many rows belong to each pair of levels), in which case the output would have this aspect:

In conclusion I want to susbset rows from a dataframe using each pair of levels, so I can manipulate those rows to perform a function ( such as nrows() )

CodePudding user response：

You can skip the levels part, and just use dplyr to group by col1 and col2, then count the rows. Finally, we use complete to add in any combinations that don't appear in our dataset:

library(tidyverse)

df %>%
  group_by(col1, col2) %>% # group df by col1 and col2
  summarise(n = n()) %>% # make a new column, n, which is the count
  complete(col1, col2, fill=list(n=0)) # Fill in missing pairs with 0

The output matches what you expected:

# A tibble: 6 x 3
# Groups:   col1 [3]
   col1 col2      n
  <dbl> <fct> <dbl>
1     1 a         1
2     1 b         2
3     2 a         3
4     2 b         0
5     3 a         1
6     3 b         2

CodePudding user response：

I‘m not sure if this specific count example will help you, but here‘s what you could do in the tidyverse:

library(tidyverse)
df %>%
  group_by(col1, col2) %>%
  count() %>%
  ungroup() %>%
  complete(col1, col2, fill = list(n = 0))

which gives:

# A tibble: 6 x 3
   col1 col2      n
  <dbl> <fct> <dbl>
1     1 a         1
2     1 b         2
3     2 a         3
4     2 b         0
5     3 a         1
6     3 b         2