Summing columns in a data frame and adding those values to a new data frame in R [duplicate] - r

Question

This question already has answers here:
How to sum data.frame column values?
(5 answers)
Closed 2 years ago.
I am trying to sum the columns of a data frame and add these sums to a new output data frame. When I run the following script, I get an error stating that the replacement has two rows and the data has 3.
a <-data.frame(replicate(3,sample(1:100,10,rep=TRUE)))
colnames(a) <- c("name1", "name2","name3")
for (i in 1:ncol(a)) {
b <-as.data.frame(names(a))
c <- sum(a[i])
b$d[i] <- c[i]
}
I am looking for the output as a data frame such as:
name1 sum1
name2 sum2
name3 sum3

Answer 1

Your solution was already pretty close. I made some slight modifications for you and it works:
a <-data.frame(replicate(3,sample(1:100,10,rep=TRUE)))
colnames(a) <- c("name1", "name2","name3")
b <-as.data.frame(names(a))
for (i in 1:ncol(a)) {
b$sum[i] <- sum(a[i])
}
Output:
names(a) sum
1 name1 470
2 name2 616
3 name3 495

Answer 2

I would suggest a dplyr approach:
library(dplyr)
#Data
a <-data.frame(replicate(3,sample(1:100,10,rep=TRUE)))
colnames(a) <- c("name1", "name2","name3")
#Code
a %>%
mutate(across(c(name1:name3),.fns = list(sum = ~ sum(.,na.rm=T)) ))
Output:
name1 name2 name3 name1_sum name2_sum name3_sum
1 98 31 79 599 489 506
2 8 71 4 599 489 506
3 59 23 48 599 489 506
4 65 76 64 599 489 506
5 47 53 57 599 489 506
6 80 84 55 599 489 506
7 40 19 28 599 489 506
8 39 2 47 599 489 506
9 65 36 40 599 489 506
10 98 94 84 599 489 506
If only one dataframe is desired you can use this:
a %>%
summarise(across(c(name1:name3),.fns = list(sum = ~ sum(.,na.rm=T)) ))
Output:
name1_sum name2_sum name3_sum
1 599 489 506
Initial code should be used when you want to add those variables to same dataframe.
And if you want a variable for the names and another for results you can use previous code with pivot_longer() from tidyverse to produce this:
library(tidyverse)
#Code
a %>%
summarise(across(c(name1:name3),.fns = list(sum = ~ sum(.,na.rm=T)) )) %>%
pivot_longer(cols = everything())
Output:
# A tibble: 3 x 2
name value
<chr> <int>
1 name1_sum 599
2 name2_sum 489
3 name3_sum 506

Answer 3

It can be vectorized with colSums in base R
as.data.frame.list(colSums(a))
Or for a two column summary
stack(colSums(a))
If we need to create new columns in 'a'
a[paste0(names(a), "_sum")] <- colSums(a)