CODEWITHSUNDEEP
pythonpandas
ytu
ytu

Reputation: 1850

Bitwise not True (including NaN) in pandas DataFrame

I have a data frame which looks like:

import pandas as pd
import numpy as np

df = pd.DataFrame({"id": range(5), "is_bar": [np.nan, np.nan, False, True, False], "is_foo": [True, False, True, True, False]})

Now I want rows of df where are foo, but not bar or bar is missing. In other words, this is the desired result:

   id is_bar  is_foo
0   0    NaN    True
2   2  False    True

I expected df.loc[df["is_foo"] & ~df["is_bar"]] to work, but obviously the np.nans are causing TypeError.

How can it be achieved?

Upvotes: 1

Views: 287

Answers (1)

jezrael
jezrael

Reputation: 863146

I think need fillna:

df = df.loc[df["is_foo"] & ~df["is_bar"].fillna(False)]
print (df)
   id is_bar  is_foo
0   0    NaN    True
2   2  False    True

Upvotes: 1

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