Using index to reference column in summarise() in dplyr - R - r

Question

I would like to reference a column inside the summarise() in dplyr with its index rather than with its name. For example:
> a
id visit timepoint bedroom den
1 0 0 62 NA
2 1 0 53 6.00
3 2 0 56 2.75
4 0 1 55 NA
5 1 2 61 NA
6 2 0 54 NA
7 0 1 58 2.75
8 1 2 59 NA
9 2 2 60 NA
10 0 1 57 NA
# E.g.
a %>% group_by(visit) %>% summarise(avg.bedroom = mean(bedroom, na.rm =T)
# Returns
visit avg.dedroom
<dbl> <dbl>
1 0 4.375
2 1 2.750
3 2 NaN
How could I use the index of column "bedroom" rather its name in the summarise clause? I tried:
a %>% group_by(visit) %>% summarise("4" = mean(.[[4]], na.rm = T))
but this returned false results:
visit `4`
<dbl> <dbl>
1 0 3.833333
2 1 3.833333
3 2 3.833333
Is my objective achievable and if yes how? Thank you.

Answer 1

Perhaps not exactly what you're looking for, but one option would be to use purrr rather than dplyr. Something like
# Read in data
d <- read.table(textConnection(" id visit timepoint bedroom den
1 12 0 62 NA
2 14 0 53 6.00
3 14 0 56 2.75
4 14 1 55 NA
5 14 2 61 NA
6 15 0 54 NA
7 15 1 58 2.75
8 16 2 59 NA
9 16 2 60 NA
10 17 1 57 NA "),
header = TRUE)
library(purrr)
d %>%
split(.$timepoint) %>%
map_dbl(function(x) mean(x[ ,5], na.rm = TRUE))
# 0 1 2
# 4.375 2.750 NaN
Or, with base
aggregate(d[ ,5] ~ timepoint, data = d, mean)
# timepoint d[, 5]
# 1 0 4.375
# 2 1 2.750

Answer 2

The answer I found is the summarize_at() function of dplyr. Here is how I used summarize_at() to create summary statistics on subsets of my dataframe where the columns were not known in advance (object is my original dataframe which is in a long form and has a column -- room -- that contains the names of the rooms, as well as two other columns, "visit" and "value"):
# Convert object to a wide form
object$row <- 1 : nrow(object)
y <- spread(object, room, value)
# Remove the row column from y
y <- y %>% select(-row)
# Initialize stat1, the dataframe with the summary
# statistics
stat1 <- data.frame(visit = c(0, 1, 2))
# Find the number of columns that stat1 will eventually
# have
y <- y %>% filter(id == id) %>%
select_if(function(col) mean(is.na(col)) != 1)
n <- ncol(y)
# Append columns with summary statistics to stat1
for (i in 3 : n) {
t <- y %>% group_by(visit) %>%
summarise_at(c(i), mean, na.rm = T)
t[, 2] <- round(t[, 2], 2)
stat1 <- cbind(stat1, t[, 2])
}
# Pass the dataframe stat1 to the list "results"
results$stat1 <- stat1