I have a dataframe like this :
cols = [ 'a','b']
df = pd.DataFrame(data=[[NaN, -1, NaN, 34],[-32, 1, -4, NaN],[4,5,41,14],[3, NaN, 1, NaN]], columns=['a', 'b', 'c', 'd'])
I want to retrieve all rows, when the columns 'a' and 'b' are non-negative but if any of them or all are missing, I want to keep them.
The result should be
a b c d
2 4 5 41 14
3 3 NaN 1 NaN
I've tried this but it doesn't give the expected result.
df[(df[cols]>0).all(axis=1) | df[cols].isnull().any(axis=1)]
IIUC, you actually want
>>> df[((df[cols] > 0) | df[cols].isnull()).all(axis=1)]
a b c d
2 4 5 41 14
3 3 NaN 1 NaN
Right now you're getting "if they're all positive" or "any are null". You want "if they're all (positive or null)". (Replace > 0
with >=0
for nonnegativity.)
And since NaN isn't positive, we could simplify by flipping the condition, and use something like
>>> df[~(df[cols] <= 0).any(axis=1)]
a b c d
2 4 5 41 14
3 3 NaN 1 NaN
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