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rationale:
I sometimes work with square matricies that potentially could have a column (and row) of all na's
I find myself doing:
df.dropna(how='all',axis=0).dropna(how='all',axis=1)
so
df.dropna(how='all',axis=[0,1])
e.g.
_dropna = DataFrame.dropna def revised_dropna(self, axis = None, **kwargs): if isinstance(axis,(list,tuple)): return _dropna(_dropna(self,axis=axis[0],**kwargs),axis=axis[1],**kwargs) return _dropna(self,axis=axis,**kwargs) DataFrame.dropna = revised_dropna
The text was updated successfully, but these errors were encountered:
fa5f315
Great idea. Just pushed the enhancement / unit test
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rationale:
I sometimes work with square matricies that potentially could have a column (and row) of all na's
I find myself doing:
df.dropna(how='all',axis=0).dropna(how='all',axis=1)
so
df.dropna(how='all',axis=[0,1])
e.g.
The text was updated successfully, but these errors were encountered: