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R tip: use slices.

R has a very powerful array slicing ability that allows for some very slick data processing.

Suppose we have a data.framed“, and for every row where d$n_observations < 5 we wish to “NA-out” some other columns (mark them as not yet reliably available). Using slicing techniques this can be done quite quickly as follows. library("wrapr") d[d$n_observations < 5,
qc(mean_cost, mean_revenue, mean_duration)] <- NA


(For “qc()” please see R Tip: Use qc() For Fast Legible Quoting.)

The above notation is very convenient, compact, and powerful. We are adding this as operator to our rquery query generator as assign_slice() (and a related method for directly dealing with NA/NULL).