dataframe - Convert multiple columns from factor to numeric but obtaining NAs in R

Question

Assuming the following dataframe df:

df <- structure(list(`week1` = structure(c(number = 4L, 
area1 = 1L, area2 = 2L, price1 = 3L, 
price2 = 5L), .Label = c("154.93", "304.69", "3554.50", 
"49", "7587.22"), class = "factor"), `week2` = structure(c(number = 3L, 
area1 = 1L, area2 = 4L, price1 = 2L, 
price2 = 5L), .Label = c("28.12", "2882.91", "30", 
"44.24", "4534.47"), class = "factor")), class = "data.frame", row.names = c("number", 
"area1", "area2", "price1", 
"price2"))

I'm try to convert its week1 and week2 columns from factor to numeric with:

cols = c(1, 2)
df[, cols] <- as.numeric(as.character(df[, cols]))
# df[cols] <- lapply(df[cols], as.numeric) # gives incorrect results

Out:

But it returns NAs or incorrect results for those columns. However, the following code gives right answer:

cols = c(1, 2)   
df[, cols] = apply(df[, cols], 2, function(x) as.numeric(as.character(x)))
df 

Out:

Why did I get NAs with the first solution which works for this case? Thanks.

question from:https://stackoverflow.com/questions/65840013/convert-multiple-columns-from-factor-to-numeric-but-obtaining-nas-in-r

Answer 1

as.character/as.numeric expects a vector as input. With df[, cols] you are passing a dataframe to it (check class(df[, cols])).

If you are talking about the accepted answer in the link it says to change the code in for loop and doesn't suggest to pass entire dataframe. To change class of multiple columns you can use for loop, apply or lapply.

df[cols] <- lapply(df[cols], function(x) as.numeric(as.character(x)))