Borrowed this idea from pandas api. Current dropna methods will drop a
column or row if any data is missing. But it is also quite useful to
drop those columns or rows only if all of its elements are missing. This
is mostly used for pruning a table.
This method mimics pandas `drop_duplicates` when axis=rows.
For axis=cols this method will drop columns with 0-variance (only
1 unique value). NaNs (`_fill_value`) won't be counted as unique values.
So the following column (`-` would be the `_fill_value`) will be dropped:
foo
-
foo
foo
karajan1001
David de la Iglesia Castro
Saugat Pachhai