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I want to calculate mean of each of several columns in a data.table, grouped by another column. My question is similar to two other questions on SO ( one and two ) but I couldn't apply those on my problem. Here is an example: library(data.table) dtb <- fread(input = "condition,var1,var2,var3 one,100,1000,10000 one,101,1001,10001 one,102,1002,10002 two,103,1003,10003 two,104,1004,10004 two,105,1005,10005 three,106,1006,10006 three,107,1007,10007 three,108,1008,10008 four,109,1009,10009 four,110,1010,10010") dtb # condition var1 var2 var3 # 1: one 100 1000 10000 # 2: one 101 1001 10001 # 3: one 102 1002 10002 # 4: two 103 1003 10003 # 5: two 104 1004 10004 # 6: two 105 1005 10005 # 7: three 106 1006 10006 # 8: three 107 1007 10007 # 9: three 108 1008 10008 # 10: four 109 1009 10009 # 11: four 110 1010 10010 The calculation of each single mean is easy; e.g. for "var1": dtb[ , mean(var1), by = condition] . But I this quickly becomes cumbersome if there are many variables and you need to write all of them. Thus, dtb[, list(mean(var1), mean(var2), mean(var3)), by = condition] is undesirable. I need the column names to be dynamic and I wish to end up with something like this: condition var1 var2 var3 1: one 101.0 1001.0 10001.0 2: two 104.0 1004.0 10004.0 3: three 107.0 1007.0 10007.0 4: four 109.5 1009.5 10009.5

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