How to remove rows where all columns are zero using dplyr pipe

Question

I have the following data frame:

dat <- structure(list(`A-XXX` = c(1.51653275922944, 0.077037240321129, 
0), `fBM-         


        

Answer 1

We could use reduce from purrr to get the sum of rows and filter the dataset based on the logical vector

library(tidyverse)
dat %>%
    reduce(`+`) %>%
    {. != 0} %>% 
   filter(dat, .)
#       A-XXX  fBM-XXX    P-XXX  vBM-XXX
#1 1.51653276 2.228752 1.733567 3.003979
#2 0.07703724 0.000000 0.000000 0.000000

NOTE: Within the %>%, the row.names gets stripped off. It may be better to create a new column or assign row.names later

---

If we need the row names as well, then create a row names column early and then use that to change the row names at the end

dat %>%
  rownames_to_column('rn') %>%
  filter(rowSums(.[-1]) != 0) %>% 
  `row.names<-`(., .[['rn']]) %>% select(-rn)
#                   A-XXX  fBM-XXX    P-XXX  vBM-XXX
#BATF::JUN_AHR  1.51653276 2.228752 1.733567 3.003979
#BATF::JUN_CCR9 0.07703724 0.000000 0.000000 0.000000