I have not found this exact issue yet on here. I have many columns and for all the ones that match ANY of a list of strings, I want to convert from factor -> character -> numeric.
Below shows an example where columns containing one of the strings are converted, and the two things I've tried for the case of multiple strings that failed
#Making fake data where every column is a factor. At the end I'd like to convert all factors that contain either "alcium" or "zinc" in the column name.
library(reshape2)
fake <-data.frame(id=c(1,1,1,2,2,2,3,3,3,1,1,1,2,2,2,3,3,3),
time=c(rep("Time1",9), rep("Time2",9)),
test=c("calcium","magnesium","zinc","calcium","magnesium","zinc","calcium","magnesium","zinc","calcium","magnesium","zinc","calcium","magnesium","zinc","calcium","magnesium","zinc"),
score=floor(runif(18, min=1, max=5)))
fake <- dcast(fake, id ~ time + test)
fake <- fake %>% mutate_if(is.numeric,as.factor)
#This works, but only for columns containing one of the strings
fake <- fake %>% mutate_at(vars(contains('alcium')), function(x) as.numeric(as.character(x)))
#Now trying to convert all columns containing either "alcium" or "zinc"
fake <- fake %>% mutate_at(vars(contains('alcium'| 'zinc')), function(x) as.numeric(as.character(x)))
#gives an error
#2nd attempt:
strings <- c("alcium", "zinc")
fake <- fake %>% mutate_at(vars(contains(strings)), function(x) as.numeric(as.character(x)))
#gives an error
Using the select helper matches()
instead of contains()
allows the passing of the strings collapsed into a regex friendly format.
library(dplyr)
strings <- c("alcium", "zinc")
fake %>%
as_tibble %>%
mutate_at(vars(matches(paste0(strings, collapse = "|"))), as.numeric)
# A tibble: 3 x 8
id Time1_calcium `Time1_ma gnesium` Time1_magnesium Time1_zinc Time2_calcium Time2_magnesium Time2_zinc
<fct> <dbl> <fct> <fct> <dbl> <dbl> <fct> <dbl>
1 1 2 NA 4 1 3 4 1
2 2 2 NA 3 2 1 1 3
3 3 1 3 NA 1 2 3 2
I have updated your code a bit.
If you don't have too many you could do them separately. Otherwise, I couldn't get multiple strings to work.
sofaWa <- fake %>% mutate_at(vars(contains('alcium')), list(as.numeric)) %>%
mutate_at(vars(contains('zinc')), list(as.numeric))
Produces this
# A tibble: 3 x 7
id Time1_calcium Time1_magnesium Time1_zinc Time2_calcium Time2_magnesium Time2_zinc
<fct> <dbl> <fct> <dbl> <dbl> <fct> <dbl>
1 1 3 2 1 1 2 1
2 2 2 1 2 1 1 2
3 3 1 4 2 2 3 1
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