Pandas apply function multiple conditions to skip row

0
votes

My code without conditions works perfectly:

tqdm.pandas()    
df3[['newbhpgrad','Liqwt','IPRwt','Liq Rate','Oil Rate','Water Rate','Gas Rate','LiqNod','IPRNod']]=df3.progress_apply(lambda row:dna1(row['TEST_WHP'],
    row['WC'],row['GOR'],row['TEST_OIL'],row['TEST_BHP'],row['TEST_Pres'],row['WHP'] ),axis=1)

but after changed some data(updated), got some miscalculated values, this is because there are zeros in some columns. My goal is to keep using apply but want to add some conditions:

If any value is cero in any of the two columns in this case row['WHP'],row['TEST_OIL'] skip to next row, I tried with code below with if an else but argument pass is not working.

tqdm.pandas()     
df3[['newbhpgrad','Liqwt','IPRwt','Liq Rate','Oil Rate','Water Rate','Gas Rate','LiqNod','IPRNod']]=df3.progress_apply(lambda row:dna1(row['TEST_WHP'],
        row['WC'],row['GOR'],row['TEST_OIL'] if row['TEST_OIL']>0 else pass,row['TEST_BHP'],row['TEST_Pres'],row['WHP'] if row['WHP']>0 else pass ),axis=1)

any ideas how to achieve my gol ples, thanks in advance

pythonpandas