CODEWITHSUNDEEP
rdplyrpurrr
Chris
Chris

Reputation: 820

Where can I find information about the limitations of dplyr::rowwise?

Instead of explicitly stating the column names in a mutate call, I want to do so dynamically from a list of names generated elsewhere. I tried something along these lines:

df <- data.frame(x=1:10, y=21:30) 
l <- c('x', 'y')
get_from_df <- function(x) { get(pos=df,x) }
df %>% rowwise %>% mutate(presum=do.call(sum, map(l, get_from_df)))

It gives the sum for the whole data.frame, 310, not the row sums. output is:

df %>% rowwise %>% mutate(presum=do.call(sum, map(l, get_from_df)))
# A tibble: 10 x 3
# Rowwise: 
       x     y presum
   <int> <int>  <int>
 1     1    21    310
 2     2    22    310
 3     3    23    310
 4     4    24    310
 5     5    25    310
 6     6    26    310
 7     7    27    310
 8     8    28    310
 9     9    29    310
10    10    30    310

I ended up back without rowwise using rowSum instead.

df %>%  mutate(presum=rowSums(do.call(cbind, map(l,f)) ))

It works, but I'd like to understand better what rowwise is doing under the covers and what limitations I ran into. Is there anywhere that describes this before I make time to read some code?

Upvotes: 1

Views: 53

Answers (1)

jpdugo17
jpdugo17

Reputation: 7116

Perhaps this is what you looking for?

Note the use of c_across and all_of from tidy selection.

library(tidyverse)

df <- data.frame(x=1:10, y=21:30) 
l <- c('x', 'y')
get_from_df <- function(x) { get(pos=df,x) }
#df %>% rowwise %>% mutate(presum=do.call(sum, map(l, get_from_df)))

df %>% 
  rowwise() %>% 
  mutate(presum = sum(c_across(all_of(l))))
#> # A tibble: 10 × 3
#> # Rowwise: 
#>        x     y presum
#>    <int> <int>  <int>
#>  1     1    21     22
#>  2     2    22     24
#>  3     3    23     26
#>  4     4    24     28
#>  5     5    25     30
#>  6     6    26     32
#>  7     7    27     34
#>  8     8    28     36
#>  9     9    29     38
#> 10    10    30     40

Created on 2021-11-24 by the reprex package (v2.0.1)

Upvotes: 1

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