BENCH: add DataFrame.reindex(columns=..) benchmark that selects existing columns
I noticed that the current `df.reindex(columns=idx)` benchmark uses an indexer with all-non-existing indices (it uses `range(4000, 7000)` as indexer, but there are only 1000 columns), so basically it is benchmarking to create empty (all-NaN) columns. Therefore added a case of reindexing with an indexer consisting of existing column labels.

For reindexing the rows, it's already using existing row labels.