Suppose I have a Series with NaNs:
pd.Series([0, 1, None, 1])
I want to transform this to be equal to:
pd.Series([False, True, None, True])
You'd think x == 1 would suffice, but instead, this returns:
pd.Series([False, True, False, True])
where the null value has become False. This is because np.nan == 1 returns False, rather than None or np.nan as in R.
Is there a nice, vectorized way to get what I want?
Maybe map can do it:
import pandas as pd
x = pd.Series([0, 1, None, 1])
print x.map({1: True, 0: False})
0 False
1 True
2 NaN
3 True
dtype: object
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