I would like to select a row with maximum value in each group with dplyr.
Firstly I generate some random data to show my question
set.seed(1)
df <- expand.grid(list(A = 1:5, B = 1:5, C = 1:5))
df$value <- runif(nrow(df))
In plyr, I could use a custom function to select this row.
library(plyr)
ddply(df, .(A, B), function(x) x[which.max(x$value),])
In dplyr, I am using this code to get the maximum value, but not the rows with maximum value (Column C in this case).
library(dplyr)
df %>% group_by(A, B) %>%
summarise(max = max(value))
How could I achieve this? Thanks for any suggestion.
sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_0.2 plyr_1.8.1
loaded via a namespace (and not attached):
[1] assertthat_0.1.0.99 parallel_3.1.0 Rcpp_0.11.1
[4] tools_3.1.0
Try this:
result <- df %>%
group_by(A, B) %>%
filter(value == max(value)) %>%
arrange(A,B,C)
Seems to work:
identical(
as.data.frame(result),
ddply(df, .(A, B), function(x) x[which.max(x$value),])
)
#[1] TRUE
As pointed out in the comments, slice
may be preferred here as per @RoyalITS' answer below if you strictly only want 1 row per group. This answer will return multiple rows if there are multiple with an identical maximum value.