From long to wide data with multiple columns

You can use data.table instead of reshape2, because its dcast() function accepts several variables, and is faster too:

require(data.table)
setDT(foo)
dcast(foo,group+num_users~times,value.var=c("action_rate","action_rate_c95"))

   group num_users action_rate_after action_rate_before action_rate_c95_after action_rate_c95_before
1:     a       100              0.15                0.1            0.06962893             0.05850000
2:     b       200              0.18                0.2            0.05297400             0.05515433
3:     c       300              0.35                0.3            0.05369881             0.05159215

Here's another alternative using tidyr:

library(tidyr)
foo %>%
  gather(key, value, -group, -times, -num_users) %>%
  unite(col, key, times) %>%
  spread(col, value)

Which gives:

#  group num_users action_rate_after action_rate_before action_rate_c95_after
#1     a       100              0.15                0.1            0.06962893
#2     b       200              0.18                0.2            0.05297400
#3     c       300              0.35                0.3            0.05369881
#  action_rate_c95_before
#1             0.05850000
#2             0.05515433
#3             0.05159215

Here is a base R option with reshape

reshape(foo, idvar=c("group", "num_users"), timevar="times", direction="wide")
#  group num_users action_rate.before action_rate_c95.before action_rate.after
#1     a       100                0.1             0.05850000              0.15
#3     b       200                0.2             0.05515433              0.18
#5     c       300                0.3             0.05159215              0.35
#  action_rate_c95.after
#1            0.06962893
#3            0.05297400
#5            0.05369881