I can calculate the rank of the values (val) in my dataframe df within the group name1 with the code:
res <- df %>% arrange(val) %>% group_by(name1
We can use group_by_
library(dplyr)
df %>%
arrange(val) %>%
group_by_(.dots=crit1) %>%
mutate(RANK=row_number())
#Source: local data frame [10 x 4]
#Groups: name1, name2 [7]
# val name1 name2 RANK
# <dbl> <chr> <chr> <int>
#1 -0.848370044 b c 1
#2 -0.583627199 a a 1
#3 -0.545880758 a a 2
#4 -0.466495124 b b 1
#5 0.002311942 a c 1
#6 0.266021979 c a 1
#7 0.419623149 c b 1
#8 0.444585270 a c 2
#9 0.536585304 b a 1
1#0 0.847460017 a c 3
group_by_
is deprecated in the recent versions (now using dplyr
version - 0.8.1
), so we can use group_by_at
which takes a vector of strings as input variables
df %>%
arrange(val) %>%
group_by_at(crit1) %>%
mutate(RANK=row_number())
Or another option is to convert to symbols (syms
from rlang
) and evaluate (!!!
)
df %>%
arrange(val) %>%
group_by(!!! rlang::syms(crit1)) %>%
mutate(RANK = row_number())
set.seed(24)
df <- data.frame(val = rnorm(10), name1= sample(letters[1:3], 10, replace=TRUE),
name2 = sample(letters[1:3], 10, replace=TRUE),
stringsAsFactors=FALSE)
crit1 <- c("name1", "name2")