[R] Computing stats on common parts of multiple dataframes

[Murali Menon]

Folks,

I have three dataframes storing some information about
two currency pairs, as follows:

R> a

EUR-USD	NOK-SEK
1.23	1.33
1.22	1.43
1.26	1.42
1.24	1.50
1.21	1.36
1.26	1.60
1.29	1.44
1.25	1.36
1.27	1.39
1.23	1.48
1.22	1.26
1.24	1.29
1.27	1.57
1.21	1.55
1.23	1.35
1.25	1.41
1.25	1.30
1.23	1.11
1.28	1.37
1.27	1.23



R> b
EUR-USD	NOK-SEK
1.23	1.22
1.21	1.36
1.28	1.61
1.23	1.34
1.21	1.22



R> d

EUR-USD	NOK-SEK
1.27	1.39
1.23	1.48
1.22	1.26
1.24	1.29
1.27	1.57
1.21	1.55
1.23	1.35
1.25	1.41
1.25	1.33
1.23	1.11
1.28	1.37
1.27	1.23

The twist is that these entries correspond to dates where the
*last* rows in each frame are today's entries, and so on
backwards in time.

I would like to create a matrix of medians (a median for each row
and for each currency pair), but only for those rows where all
dataframes have entries.

My answer in this case should look like:

EUR-USD	NOK-SEK

1.25	1.41
1.25	1.33
1.23	1.11
1.28	1.37
1.27	1.23

where the last EUR-USD entry = median(1.27, 1.21, 1.27), etc.

Notice that the output is of the same dimensions as the smallest dataframe
(in this case 'b').

I can do it in a clumsy fashion by first obtaining the number
of rows in the smallest matrix, chopping off the top rows
of the other matrices to reduce them this size, then doing a
for-loop across each currency pair, row-wise, to create a
3-vector which I then apply median() on.

Surely there's a better way to do this?

Please advise.

Thanks,

Murali Menon

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