Home/ Questions/Q 9133365
In Process

The Archive Base Latest Questions

Editorial Team
  • 0
Asked: 2026-06-17T08:28:34+00:00

I have a data frame with something like the following structure: Trial Index Condition1

  • 0

I have a data frame with something like the following structure:

Trial Index    Condition1    Condition2    Measures
1              A             Y             ...
2              A             Y             ...        
3              B             Y             ...
4              B             Y             ...
5              A             Z             ...
6              A             Z             ...        
7              B             Z             ...
8              B             Z             ...

I would like to compute a number of summary measures on each combination of Condition1 and Condition2, and for the margins. I can use multiple calls to ddply to do this, but I was wondering if there is some simple way to get a single data structure out of it, something like:

Condition1    Condition2    Mean    Median    ....
A             Y             ...     ...       ....
A             Z             ...     ...       ....
A             -             ...     ...       ....             
B             Y             ...     ...       ....
B             Z             ...     ...       ....
B             -             ...     ...       ....
-             Y             ...     ...       ....
-             Z             ...     ...       ....
Share

Leave an answer

You must login to add an answer.

Need An Account,

1 Answer

  1. Editorial Team

    @DWin is right, tables package might be the right clue here. Without taking care of formating here’s an example: 

    library(tables)
d1 <- data.frame(id = 1:10, c1 = sample(c("a","b"), 10, replace = TRUE), 
        c2 = sample(c("c", "d"), 10, replace = TRUE), measures = rnorm(1:10))
t1 <- tabular((c1 + c2 + c1*c2 +1) ~ (measures)*(mean + median), data = d1)

             measures        
             mean     median 
      c1 a   -0.33306 -0.1801
         b   -0.54121 -0.6381
      c2 c   -0.04862  0.1647
         d   -0.69615 -0.8129
 c1 a c2 c   -0.26195 -0.2619
         d   -0.38047 -0.1801
    b    c    0.16472  0.1647
         d   -1.01182 -1.1863
         All -0.43713 -0.4678

    It takes a while to get into the syntax though; on the plus side it provides functionality to export the tables to LaTeX. If you don’t want/need all the labeling in that tabular object you can extract the values via as.matrix(t1, format = as.numeric).

    NOTE: c1 and c2 on the left hand side of the formula have to be factor for this to work

    • 0