Question

I have a dataframe of 150,000 rows with 2,000 columns containing values, some being negatives.
I am replacing those negative values by 0, but it is extremely slow to do so (~60min or more).

df[df < 0] = 0

where df[,1441:1453] looks like (all columns/values numeric):

  V1441 V1442 V1443 V1444 V1445 V1446 V1447 V1448 V1449 V1450 V1451 V1452 V1453
1     3     1     0     4     4    -2     0     3    12     5    17    34    27
2     0     1     0     7     0     0     0     1     0     0     0     0     0
3     0     2     0     1     2     3     6     1     2     1    -6     3     1
4     1     2     3     6     1     2     1    -6     3     1    -4     1     0
5     1     2     1    -6     3     1    -4     1     0     0     1     0     0
6     1     0     0     1     0     0     0     0     0     0     1     2     2

Is there a way to speed up such process, eg the way I am doing it is utterly slow, and there is faster approach for this ?
Thanks.

Answer 1

Try transforming your df to a matrix.

df <- data.frame(a=rnorm(1000),b=rnorm(1000))
m <- as.matrix(df)
m[m<0] <- 0
df <- as.data.frame(m)