CODEWITHSUNDEEP
rgroup-byaggregate
boring1
boring1

Reputation: 23

R Count Values of every Column in Dataframe

I can do it using group by with only one Column but I want the Count for every Column in the Dataframe. See example:

Dataframe with similar values in each Column: df =

      C1       C2       C3
 
1   Positiv  Negativ  Neutral
2   NA       Neutral  Positiv
3   Positiv  NA       Negativ
4   Negativ  Positiv  NA

I thought about something like this:

df %>% group_by(names(df)) %>% count()

desired Output: Count Values in each Column

                C1   C2  C3
 
1 Positive      2     1   1
2 Negative      1     1   1
3 Neutral       0     1   1
4 NA            1     1   1

Upvotes: 2

Views: 1177

Answers (2)

akrun
akrun

Reputation: 887951

We can use base R with table

sapply(df,  function(x) table(factor(x,
      levels = c('Negativ', 'Positiv', 'Neutral')), useNA = "always"))
#        C1 C2 C3
#Negativ  1  1  1
#Positiv  2  1  1
#Neutral  0  1  1
#<NA>     1  1  1

Or using a vectorized approach

table(unlist(df), c(col(df)), useNA = 'always')[, -4]
         
#          1 2 3
#  Negativ 1 1 1
#  Neutral 0 1 1
#  Positiv 2 1 1
#  <NA>    1 1 1

data

df <- structure(list(C1 = c("Positiv", NA, "Positiv", "Negativ"), C2 = c("Negativ", 
"Neutral", NA, "Positiv"), C3 = c("Neutral", "Positiv", "Negativ", 
NA)), class = "data.frame", row.names = c("1", "2", "3", "4"))

Upvotes: 1

Duck
Duck

Reputation: 39613

Try this with some tidyverse functions and reshaping your data to long and wide:

library(dplyr)
library(tidyr)
#Code
new <- df %>% pivot_longer(everything()) %>%
  group_by(across(everything())) %>%
  summarise(N=n()) %>%
  pivot_wider(names_from = name,values_from=N,values_fill=0)

Output:

# A tibble: 4 x 4
  value      C1    C2    C3
  <chr>   <int> <int> <int>
1 Negativ     1     1     1
2 Positiv     2     1     1
3 NA          1     1     1
4 Neutral     0     1     1

Some data used:

#Data
df <- structure(list(C1 = c("Positiv", NA, "Positiv", "Negativ"), C2 = c("Negativ", 
"Neutral", NA, "Positiv"), C3 = c("Neutral", "Positiv", "Negativ", 
NA)), class = "data.frame", row.names = c("1", "2", "3", "4"))

Upvotes: 2

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