我如何使用 dplyr 跨所有列计算 function，但所有其他列没有 NA 和没有 0？

Question

i have a data frame that looks like this:

A	B	C	D
1	0	2.1	6.2
2	3.2	3.2	0
3	4.4	NA	8.3
4	NA	0	0
5	NA	NA	8.8
6	NA	NA	0
7	30	0	9.1
8	30	6.6	0

I want to calculate the pariwise sum of A with all the columns (including itself) but only those who match the A but are NOT NA and NOT 0.

The ideal output must be:

A	B	C	D
72	12.6	22.9	68.4

library(tidyverse)
A = seq(1:8)
B = c(0,3.2,4.4,NA,NA,NA,NA,NA)
C = c(2.1,3.2,NA,0,NA,NA,0,6.6)
D = c(6.2,0,8.3,0,8.8,0,9.1,0)
table = tibble(A,B,C,D);table

My effort is:

table%>%
  dplyr::filter(!is.na(A))%>%
  dplyr::summarise(across(everything(), ~ sum(.x,A),na.rm=TRUE))

How i can do this in R using dplyr? Any help?

Answer 1

1. base

sapply(table, \(x) sum((x + table$A)[!is.na(x) & x != 0]))

2. dplyr

table %>%
  summarise(across(everything(), ~ sum((.x + A)[!is.na(.x) & .x != 0])))

# # A tibble: 1 × 4
#       A     B     C     D
#   <int> <dbl> <dbl> <dbl>
# 1    72  12.6  22.9  48.4