CODEWITHSUNDEEP
rdplyr
MeetMrMet
MeetMrMet

Reputation: 1359

dplyr conditional mutate on itself

I have a data frame with a character variable consisting of mostly numeric values, with occasional known character strings as well as some NA values. I want to conditionally reformat the numeric values to have one decimal place, but leave the character and NA values alone.

This code works on a toy data frame and produces the desired output:

df <- data.frame(a = c("1", "2", "3", "none", NA),
                 stringsAsFactors = FALSE)

test <- df %>%
  mutate(a = ifelse(is.na(a) | a == "none",
                    a,
                    format(round(as.numeric(a), 1), nsmall = 1)))

test
#    a
# 1  1.0
# 2  2.0
# 3  3.0
# 4 none
# 5 <NA>

But throws a warning message

Warning message:
In format(round(as.numeric(c("1", "2", "3", "none", NA)), 1), nsmall = 1) :
  NAs introduced by coercion

which I believe is the case b/c format(round(as.numeric(a), 1), nsmall = 1))) is still acting on the entire vector, even though the values from that are only used in the mutate statement where the ifelse condition is false.

I can wrap the whole thing in suppressWarnings(), but is there some other way to have this generate the desired output without warnings within the dplyr framework? I'm sure there's a data.table way to do it but this is part of a package that doesn't need data.table for anything else and it seems silly to make it necessary for such a small piece...

Upvotes: 3

Views: 502

Answers (1)

akuiper
akuiper

Reputation: 214927

Use replace and you can convert just the numeric type data in column a:

test <- df %>%
    mutate(a = replace(a, !is.na(a) & a != "none",
                       format(round(as.numeric(a[!is.na(a) & a != "none"]), 1), nsmall = 1)))

test
#     a
#1  1.0
#2  2.0
#3  3.0
#4 none
#5 <NA>

Upvotes: 7

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