CODEWITHSUNDEEP
r
T-T
T-T

Reputation: 713

Count number of rows for each column in a data frame/table

This is a simple question, but I'm not sure what I did wrong. 

df1 <- data.frame(
  A = c(NA, 0.57, 0.60, 0.51), 
  B = c(NA, 0, 0.09,0.19), 
  C = c(0., 0.05, 0.07, 0.05), 
  D = c(0.23, 0.26, 0.23, 0.26)
)
View(df1)
#   A       B       C       D  
# 1 NA      NA      0.00    0.23
# 2 0.57    0.00    0.05    0.26
# 3 0.60    0.09    0.07    0.23
# 4 0.51    0.19    0.05    0.26

I need to get the sum of each column and divide by the number of rows in each column that are neither NA nor 0.00 The result should be:

#    A       B       C       D
# 1  0.56    0.14    0.06    0.25

I tried df2 <- apply(df1, 2, function(x) colSums(df1, na.rm = T) /length(which(x !=0))) but it returns a 4x4 matrix. I suspect the problem is with length(which(x !=0)). Please advice.

Upvotes: 0

Views: 1559

Answers (2)

Sandipan Dey
Sandipan Dey

Reputation: 23101

With dplyr:

df1 %>%
  replace(is.na(.), 0) %>%
  summarise_each(funs(round(sum(.)/sum(.!=0),2))) 

#      A    B    C    D
#  1 0.56 0.14 0.06 0.24

Upvotes: 0

akrun
akrun

Reputation: 886938

We can do

round(colSums(df1, na.rm = TRUE)/colSums(df1!=0, na.rm=TRUE), 2)
#   A    B    C    D 
# 0.56 0.14 0.06 0.24

Upvotes: 1

Related Questions