I previously posted about calculating medians using R. I used tapply to do it, but I’ve since found something that feels easier to use (at least to me).
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aggregated_output = aggregate(DV ~ IV1 * IV2, data=data_to_aggregate, FUN=median) aggregated_output
The above code saves an aggregated dataset to aggregated_output and gives you the median in a column. The median (or mean, or whatever function you want to apply) is specified by FUN=. The value to create a median for is specified by DV (dependent variable).
The aggregate function also gives additional columns for each IV (independent variable). You can have as many of these as you like. Here, I have two, and these are specified by IV1 * IV2.
Those of you who are familiar with relational databases will see immediately that this function is somewhat similar to GROUP BY (in MySQL). The bonus is that you don’t need to SELECT the IV columns that you want to be provided; those are done automatically. For example, take a look at this:
SELECT IV1, IV2, AVG(DV) FROM data_to_aggregate GROUP BY IV1, IV2
There is apparently more than one ways to skin a cat (even if it’s a cat that’s made of data).