CODEWITHSUNDEEP
rdplyr
Ernesto Riveros Barrientos
Ernesto Riveros Barrientos

Reputation: 117

How to count one column and adding up several columns at the same time using summarise in dplyr R

I have this dataframe (there are 20 more columns like class but just for the example I show a short version):

 niv  ID  class1 class2 class3
  A   x    10      5      7
  A   y    15      3      1
  A   z    11      2      4
  B   u    17      7      3
  B   w    18      7      9

So I wanted to group_by(niv) and to summarise the ID column just counting it and class1, class2 and class3 columns to add up in just one command. I tried summarise_each but I can't sort out how to use it. Also the objetive would be to learn how to mix different funs in the summarise function when you have a dataframe with a lot of columns.

The summarise dataframe I need is this one:

 niv  n_ID  sum_class1 sum_class2 sum_class3
  A    3        36         10         12
  B    2        35         14         12

Thanks in advance.

Upvotes: 1

Views: 66

Answers (2)

akrun
akrun

Reputation: 886938

We can use summarise with across

library(dplyr)
df %>%
   mutate(n_ID = 1) %>%
   group_by(niv) %>%
   summarise(across(starts_with('class'), sum))

With across, we can have multiple functions

iris %>%      
   summarise(across(where(is.factor), nlevels), 
            across(where(is.numeric), mean))
#  Species Sepal.Length Sepal.Width Petal.Length Petal.Width
#1       3     5.843333    3.057333        3.758    1.199333

data

df <- structure(list(niv = c("A", "A", "A", "B", "B"), ID = c("x", 
"y", "z", "u", "w"), class1 = c(10L, 15L, 11L, 17L, 18L), class2 = c(5L, 
3L, 2L, 7L, 7L), class3 = c(7L, 1L, 4L, 3L, 9L)), 
class = "data.frame", row.names = c(NA, -5L))

Upvotes: 1

Ronak Shah
Ronak Shah

Reputation: 388807

You can create n_ID column with all 1's and sum them with all 'class' columns. 

library(dplyr)

df %>%
 mutate(n_ID = 1) %>%
 group_by(niv) %>%
 summarise_at(vars(n_ID, starts_with('class')), sum)

# A tibble: 2 x 5
#  niv    n_ID class1 class2 class3
#  <chr> <dbl>  <int>  <int>  <int>
#1 A         3     36     10     12
#2 B         2     35     14     12

data

df <- structure(list(niv = c("A", "A", "A", "B", "B"), ID = c("x", 
"y", "z", "u", "w"), class1 = c(10L, 15L, 11L, 17L, 18L), class2 = c(5L, 
3L, 2L, 7L, 7L), class3 = c(7L, 1L, 4L, 3L, 9L)), 
class = "data.frame", row.names = c(NA, -5L))

Upvotes: 0

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