How to divide on Zero in Pandas Dataframe and make 1 column out of 2-CodePudding

I did spend few hours on Google but was not able to find solution for my issue. I'm receiving dataframe like this:

col1         col2     col3 
2022-03-01   234       0
2022-03-01   342       67
2022-03-01   0         0
2022-03-01   0         23

I need to divide Col2 on Col3 and result should look like this:

col1         col4 
2022-03-01   0      
2022-03-01   5.1
2022-03-01   0        
2022-03-01   0

How I can do that ?? With functions like divide or / I'm always getting error: decimal./DivizionByZero

I did try to find any solution but in Google there is always basic stuff, like divide just number on number, not on Zero etc.

Thank you,

CodePudding user response：

If no decimals replace infinite values to 0 and then missing values:

import numpy as np

df['col4'] = df['col2'].div(df['col3']).replace(np.inf,0).fillna(0)
print (df)
         col1  col2  col3      col4
0  2022-03-01   234     0  0.000000
1  2022-03-01   342    67  5.104478
2  2022-03-01     0     0  0.000000
3  2022-03-01     0    23  0.000000

Solution with decimals:

If possible convert to integers:

df['col4'] = df['col2'].astype(int).div(df['col3'].astype(int)).replace(np.inf,0).fillna(0)
print (df)
         col1 col2 col3      col4
0  2022-03-01  234    0  0.000000
1  2022-03-01  342   67  5.104478
2  2022-03-01    0    0  0.000000
3  2022-03-01    0   23  0.000000

If not, replace 0 to 1 and then set 0 if at least in one column is 0:

df['col4'] = df['col2'].div(df['col3'].replace(0, 1)).mask(df[['col2', 'col3']].eq(0).any(1), 0)
print (df)
         col1 col2 col3                           col4
0  2022-03-01  234    0                              0
1  2022-03-01  342   67  5.104477611940298507462686567
2  2022-03-01    0    0                              0
3  2022-03-01    0   23                              0