[FIXED] update pandas column with another column's values using .loc

Issue

I need to conditionally update ColY below if the value for ColX != 0. The difference to other examples is that I need ColY to be replaced by the values from ColX, as opposed to a string

I can replace with a string using .loc when I use the following code:

df1.loc[df1.ColX != 0, 'ColY'] = 'Example'

How can I replace the relevant ColY values with the values from ColX? I have tried things such as the below to no avail

df1.loc[df1.ColX != 0, 'ColY'] = df1.ColX

My original dataframe, df1, is:

ID  ColX   ColY
A   2024   0
B   0      2023
C   2019   0
D   2023   2024

My desired output is:

ID  ColX   ColY
A   2024   2024
B   0      2023
C   2019   2019
D   2023   2023

Solution

Just for your convenience, here's another cleaner method in my opinion, using np.where and .ne:

df['ColY'] = np.where(df['ColX'].ne(0), df['ColX'], df['ColY'])

print(df)
  ID  ColX  ColY
0  A  2024  2024
1  B     0  2023
2  C  2019  2019
3  D  2023  2023

Answered By - Erfan