Question

I want to (as ever) use code that performs better but functions equivalently to the following:

write.table(results.df[seq(1, ncol(results.df),2)],file="/path/file.txt", row.names=TRUE, sep="\t") 
write.table(results.df[seq(2, ncol(results.df),2)],file="/path/file2.txt",row.names=TRUE, sep="\t")

results.df is a dataframe that looks something thus:

row.names 171401    171401 111201     111201
    1      1     0.8320923  10     0.8320923
    2      2     0.8510621  11     0.8510621
    3      3     0.1009001  12     0.1009001
    4      4     0.9796110  13     0.9796110
    5      5     0.4178686  14     0.4178686
    6      6     0.6570377  15     0.6570377
    7      7     0.3689075  16     0.3689075

There is no consistent patterning in the column headers except that each one is repeated twice consecutively.

I want to create (1) one file with only odd-numbered columns of results.df and (2) another file with only even-numbered columns of results.df. I have one solution above, but was wondering whether there is a better-performing means of achieving the same thing.

IDEA UPDATE: I was thinking there may be some way of excising – deleting it from memory – each processed column rather than just copying it. This way the size of the dataframe progressively decreases and may result in a performance increase???

Answer 1

The code is only slightly shorter but…

# Instead of 
results.df[seq(1, ncol(results.df), 2]
results.df[seq(2, ncol(results.df), 2]
#you could use 
results.df[c(T,F)]
results.df[c(F,T)]