pandas: add new column with value from either of two other colum

pandas: add new column with value from either of two other columns

pd.DataFrame({'A':[None,2,None,None,3,4],'B':[1,2,3,4,5,6]})

     A  B
0  NaN  1
1    2  2
2  NaN  3
3  NaN  4
4    3  5
5    4  6

how do I add column C that will take the value from column A if it's not NaN, otherwise column B's value?

     A  B  C
0  NaN  1  1
1    2  2  2
2  NaN  3  3
3  NaN  4  4
4    3  5  3
5    4  6  4

Answer

You can use the fillna() method in pandas to achieve this. Specifically, you want to fill the NaN values in column A with the corresponding values from column B. Here’s how you can do it:

Code:

import pandas as pd

# Creating the DataFrame
df = pd.DataFrame({'A': [None, 2, None, None, 3, 4], 'B': [1, 2, 3, 4, 5, 6]})

# Creating column C by filling NaN values in A with values from B
df['C'] = df['A'].fillna(df['B'])

print(df)

Output:

     A  B  C
0  NaN  1  1
1    2  2  2
2  NaN  3  3
3  NaN  4  4
4    3  5  3
5    4  6  4

Explanation:

• The fillna() method fills NaN values in the given column (A in this case) with the corresponding values from another column (B).
• The new column C will contain the values from A where they are not NaN, and from B where A has NaN.

This method is efficient and handles the replacement without needing loops or conditionals.