将总计行求和列添加到R中的数据框中

Question

I have a dataframe made up to multiple volume columns only and I want to create a total column called test which sits in the dataframe. The below code will work if I just set test <- ... but if I add summary_transposed_no_time$ to the left, the code doesn't seem to add it to the dataframe.

I would also like to know how I could evolve this piece of code so that I could create test to be all columns minus column 1, and then later in the process create another test column (maybe called test2) which would be a summation of all columns minus column 2 - I can hard code the column positions but not the column names (as they can change in naming convention each time the code is run) so I haven't included them here

w <- ncol(summary_transposed_no_time)
summary_transposed_no_time$test <- apply(summary_transposed_no_time[,c(1:w)], 1, sum)

Example of summary_transposed_no_time:

postal_dist_a | postal_dist_b | postal_dist_c
------------- | ------------- | -------------
20            | 25            | 15
25            | 40            | 23
31            | 32            | 19
24            | 39            | 17
37            | 19            | 26

Desired result columns within summary_transposed_no_time:

postal_dist_a | postal_dist_b | postal_dist_c | test
------------- | ------------- | ------------- | -------------
20            | 25            | 15            | 60
25            | 40            | 23            | 88
31            | 32            | 19            | 82
24            | 39            | 17            | 80
37            | 19            | 26            | 82

Answer 1

You should provide a reprocucible example. But if your question is really just about how to do rowsums, I would rather use the built in function rowSums. Your code would be :

set.seed(1)
# I recreate a table more or less like yours
summary_transposed_no_time=data.frame(matrix(rnorm(1000),ncol=5))
n=ncol(summary_transposed_no_time)

# Test that contains the rowsum
summary_transposed_no_time$test=rowSums(summary_transposed_no_time)

# test1 rowsum minus column 1
summary_transposed_no_time$testm1=rowSums(summary_transposed_no_time[,2:n])
# test2 rowsum minus column 2
summary_transposed_no_time$testm2=rowSums(summary_transposed_no_time[,c(1,3:n)])
#test_i minus column i
i=3
summary_transposed_no_time$testmi=rowSums(summary_transposed_no_time[,c(1:n)][,-i])

#check on first line :
sum(summary_transposed_no_time[1,1:n])==summary_transposed_no_time$test[1]
sum(summary_transposed_no_time[1,2:n])==summary_transposed_no_time$testm1[1]
sum(summary_transposed_no_time[1,c(1,3:n)])==summary_transposed_no_time$testm2[1]
sum(summary_transposed_no_time[1,c(1:2,4:n)])==summary_transposed_no_time$testmi[1]

Answer 2

I've found how to create a "total_" for every column within the df. total_1 is the sum of all columns minus column 1, total_2 the sum of all columns minus column 2 etc etc

n=ncol(summary_transposed_no_time)

for (h in 1:ncol(summary_transposed_no_time)) {

  summary_transposed_no_time[,paste0("total_",h)] <- rowSums(summary_transposed_no_time[,c(1:n)][,-h])
  m = ncol(summary_transposed_no_time)
  print(paste("added in a total columns for region", h, "so the column count is now : ",m))

} # end for (h in 1:nrow(filtered_data_contents)){