CODEWITHSUNDEEP
rdplyr
Lowpar
Lowpar

Reputation: 907

Merge across two columns with dplyr

I am looking to merge across two columns which contain different data. That is where it is empty in one column it is not empty in another, essentially data collected from two different conditions in a study, in order to run analysis I need to combine this data and run t-tests. I was wondering how to combine numerical columns with dplyr -

check <- check %>% 
  mutate(cat = rowSums(.[1:2]))


> dput(head(check))
structure(list(t7_1_ExpA_Intro1 = c(NA_integer_, NA_integer_, 
NA_integer_, NA_integer_, NA_integer_, NA_integer_), t7_1_ExpB_Intro1 = c(NA, 
NA, NA, 3L, NA, NA), t7_1_ExpA_DV = c(NA_integer_, NA_integer_, 
NA_integer_, NA_integer_, NA_integer_, NA_integer_), t7_1_ExpB_DV = c(NA, 
NA, NA, 3L, NA, NA), cat = c(NA_integer_, NA_integer_, NA_integer_, 
NA_integer_, NA_integer_, NA_integer_)), .Names = c("t7_1_ExpA_Intro1", 
"t7_1_ExpB_Intro1", "t7_1_ExpA_DV", "t7_1_ExpB_DV", "cat"), row.names = c(NA, 
-6L), class = c("tbl_df", "tbl", "data.frame"))

Upvotes: 0

Views: 3990

Answers (1)

akuiper
akuiper

Reputation: 215117

You can use dplyr::coalesce function which selects values from columns that first appear as non NA; say if you want to combine the first two columns:

check %>% mutate(cat = coalesce(t7_1_ExpA_Intro1, t7_1_ExpB_Intro1))
# or check %>% mutate(cat = do.call(coalesce, .[1:n])) if you have more columns to coalesce

# A tibble: 6 x 5
#  t7_1_ExpA_Intro1 t7_1_ExpB_Intro1 t7_1_ExpA_DV t7_1_ExpB_DV   cat
#             <int>            <int>        <int>        <int> <int>
#1               NA               NA           NA           NA    NA
#2               NA               NA           NA           NA    NA
#3               NA               NA           NA           NA    NA
#4               NA                3           NA            3     3
#5               NA               NA           NA           NA    NA
#6               NA               NA           NA           NA    NA

Upvotes: 5

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