How to summarize a data frame into a new one that tells means of separate levels? [duplicate]

Answer 1

You have several options:

base R:

aggregate(. ~ id + act, k, mean)

or

aggregate(cbind(var1, var2) ~ id + act, k, mean)

The first option aggregates all the column by id and act, the second option only the column you specify. In this case both give the same result, but it is good to know for when you have more columns and only want to aggregate some of them.

dplyr:

library(dplyr)
k %>%
  group_by(id, act) %>% 
  summarise_each(funs(mean))

If you want to specify the columns for which to calculate the mean, you can use summarise instead of summarise_each:

k %>%
  group_by(id, act) %>% 
  summarise(var1mean = mean(var1), var2mean = mean(var2))

data.table:

library(data.table)
setDT(k)[, lapply(.SD, mean), by = .(id, act)]

If you want to specify the columns for which to calculate the mean, you can add .SDcols like:

setDT(k)[, lapply(.SD, mean), by = .(id, act), .SDcols=c("var1", "var2")]