I have a dataframe datwe
with 37 columns. I am interested in converting the integer values(1,2,99) in columns 23 to 35 to character values('Yes','No','NA').
datwe$COL23 <- sqldf("SELECT CASE COL23 WHEN 1 THEN 'Yes'
WHEN 2 THEN 'No'
WHEN 99 THEN 'NA'
ELSE 'Name ittt'
END as newCol
FROM datwe")$newCol
I have been using the above sqldf
statements to convert each column separately. I was wondering if there is any other smart way to do this, perhaps apply functions ?
If you require any reproducible data for building dataframe datwe
, I will add it here. Thanks.
Edit:
Example datwe
set.seed(12)
data.frame(replicate(37,sample(c(1,2,99),10,rep=TRUE)))
Not sure why you used sqldf
, see this example:
#dummy data
set.seed(12)
datwe <- data.frame(replicate(37,sample(c(1,2,99),10,rep=TRUE)))
#convert to Yes/No
res <- as.data.frame(
sapply(datwe[,23:37], function(i)
ifelse(i==1, "Yes",
ifelse(i==2, "No",
ifelse(i==99,NA,"Name itttt")))))
#update dataframe
datwe <- cbind(datwe[, 1:22],res)
#output, just showing first 2 columns
datwe[,23:24]
# X23 X24
# 1 No Yes
# 2 Yes Yes
# 3 Yes No
# 4 No No
# 5 Yes No
# 6 Yes Yes
# 7 <NA> No
# 8 No No
# 9 Yes <NA>
#10 No <NA>
EDIT:
Using sqldf
within a for loop with an external variable:
library(sqldf)
#dummy data
set.seed(12)
datwe <- data.frame(replicate(37,sample(c(1,2,99),10,rep=TRUE)))
#sqldf within a loop
for(myCol in paste0("X",23:37))
datwe[,myCol] <-
fn$sqldf("SELECT CASE $myCol
WHEN 1 THEN 'Yes'
WHEN 2 THEN 'No'
WHEN 99 THEN 'NA'
ELSE 'Name ittt'
END as newCol
FROM datwe")$newCol
#check output, showing only 2 columns
datwe[,23:24]
# X23 X24
# 1 No Yes
# 2 Yes Yes
# 3 Yes No
# 4 No No
# 5 Yes No
# 6 Yes Yes
# 7 NA No
# 8 No No
# 9 Yes NA
# 10 No NA
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