Pandas where

In [20]: df
Out[20]:
   A  B  C
0  1  2  1
1  2  3  0
2  3  4  0
3  4  5  1

# Note that df.C is a mask
# Note that this is np.where, not df.where. That is different.
In [21]: df['D'] = np.where(df.C, df.A, df.B)

In [22]: df
Out[22]:
   A  B  C  D
0  1  2  1  1
1  2  3  0  3
2  3  4  0  4
3  4  5  1  4

Source: stackoverflow.com

Similar codes

83 votes129 views6 answers
Activate venv windows
Python
2 votes116 views1 answer
Pandas transform
Python
2 votes123 views2 answers
Format binary string python
Python
2 votes122 views1 answer
Numpy function for calculation inverse of a matrix
Python
0 vote111 views1 answer
Python 123 + 0.00
Python
0 vote105 views1 answer
Change set item python
Python
0 vote121 views1 answer
Comment a lot of lines python vscode
Python
0 vote117 views1 answer
Noninspection access to protected member
Python
0 vote121 views1 answer
What is onetomany and manytoone
Python
1 vote111 views1 answer
Run streamlit from python
Python