When reviewing some code, I noticed there seems to be an issue with using rowwise() with mutate() to create a new dataframe column.
# Create a dataframe with some values that are in 2 rows
df <- as.data.frame(matrix(c(2,3,4,5,20,6,1,7,2,3), nrow = 2, byrow = TRUE))
# Use Apply to generate the median of each row: This gives correct values
df$apply.median <- apply(x, 1, median)
# Use rowwise with mutate to get medians: This gives incorrect values
df %<>% rowwise() %>%
dplyr::mutate(dplyr.median=median(V1:V5))
df
Source: local data frame [2 x 7]
Groups: <by row>
# A tibble: 2 x 7
V1 V2 V3 V4 V5 apply.median dplyr.median
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 2 3 4 5 20 4 11
2 6 1 7 2 3 3 4.5I've seen this issue not just with looking at medians, but also other basic functions. For example if I try to look at the length of V1:V5 in the same manner, this is the output:
# Look for the length of the vector that is being used for the median
df %<>% rowwise() %>%
dplyr::mutate(length = length(V1:V5))
> df
Source: local data frame [2 x 8]
Groups: <by row>
# A tibble: 2 x 8
V1 V2 V3 V4 V5 apply.median dplyr.median length
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
1 2 3 4 5 20 4 11 19
2 6 1 7 2 3 3 4.5 4
When reviewing some code, I noticed there seems to be an issue with using
rowwise()withmutate()to create a new dataframe column.I've seen this issue not just with looking at medians, but also other basic functions. For example if I try to look at the length of V1:V5 in the same manner, this is the output: