Question

I think a reverse/negative dataframe.drop functionality would be a very useful tool.
Has anybody have a overcome to this?

Answer 1

Generally, I find myself using boolean indexing and the tilde operator when obtaining the inverse of a selection, rather than df.drop(), though the same concept applies to df.drop when boolean indexing is used to form the array of labels to drop. Hope that helps.

In [44]: df
Out[44]: 
          A         B
0  0.642010  0.116227
1  0.848426  0.710739
2  0.563803  0.416422

In [45]: cond = (df.A > .6) & (df.B > .3)

In [46]: df[cond]
Out[46]: 
          A         B
1  0.848426  0.710739

In [47]: df[~cond]
Out[47]: 
          A         B
0  0.642010  0.116227
2  0.563803  0.416422