CODEWITHSUNDEEP
r
user1308144
user1308144

Reputation: 475

replacing values in a data frame in R depending on column sums

I have a data frame that looks like this:

GooseIPA HeadHunter BlindPig MosaicPromise HopHunter
9 10 8 6 10
0 6 8 4 1
0 2 3 1 0

If the colSums <=10 I want to replace all values in that column with NA.

The output would look like this:

 GooseIPA HeadHunter BlindPig MosaicPromise HopHunter
NA 10 8 6 10
NA 6 8 4 1
NA 2 3 1 0

Upvotes: 0

Views: 172

Answers (2)

R18
R18

Reputation: 1560

If your data frame is called df, then you can use:

      df[,colSums(df)<=10]<-NA

Upvotes: 2

lmo
lmo

Reputation: 38520

Here is a method with sapply.

is.na(df) <- sapply(df, function(x) (sum(x) < 10))

The idea is that sapply loops through the variables and checks whether the sum of each is less than 10, if yes, TRUE is assigned to is.na.

df
  GooseIPA HeadHunter BlindPig MosaicPromise HopHunter
1       NA         10        8             6        10
2       NA          6        8             4         1
3       NA          2        3             1         0

The same method, but probably faster with colSums is

is.na(df) <- (colSums(df) < 10)

data

df <- 
dput(df)
structure(list(GooseIPA = c(9L, 0L, 0L), HeadHunter = c(10L, 
6L, 2L), BlindPig = c(8L, 8L, 3L), MosaicPromise = c(6L, 4L, 
1L), HopHunter = c(10L, 1L, 0L)), .Names = c("GooseIPA", "HeadHunter", 
"BlindPig", "MosaicPromise", "HopHunter"), class = "data.frame", row.names = c(NA, 
-3L))

Upvotes: 1

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