How to use boolean logic in new column assignment?

Question

I have a dataframe with two boolean columns.

I am trying to assign a new column using the following logic:

df['C'] = df['A']==True and df['B']==False

The error says the truth of a Series is ambiguous. I can see the problem but I don't know how to tell it that I want it perform the operation row-wise.

Possible duplicate: https://stackoverflow.com/questions/36921951/truth-value-of-a-series-is-ambiguous-use-a-empty-a-bool-a-item-a-any-o — Alexander, Feb 02 '18 at 06:06

score 0 · Answer 1 · answered Feb 02 '18 at 05:51

0

df['C']=((df['A']==True) & (df['B']==False))*1

answered Feb 02 '18 at 05:51

Yury Wallet

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jezrael · Accepted Answer · 2018-02-02T06:03:14.623

Use:

df['C'] = (df['A']==True) & (df['B']==False)

Or better as pointed @Yakym Pirozhenko in comment is invert B column by ~:

df['C'] = df['A'] & ~df['B']

Sample:

df = pd.DataFrame({'A':[True, False, True, True],
                   'B':[True, False, False, True]})

print (df)
       A      B
0   True   True
1  False  False
2   True  False
3   True   True

df['C'] = df['A'] & ~df['B']
print (df)
       A      B      C
0   True   True  False
1  False  False  False
2   True  False   True
3   True   True  False

How to use boolean logic in new column assignment?

2 Answers2