Try and Except in Pandas operations - how to do it?-CodePudding

So I wrote a code that divides a column by another column:

df['division'] = df['numerator']/df['denominator']

But since the 'denominator' is a result of other calculations, sometimes it is equal to 0. When that is the case, of course we get errors. To prevent that I used try and except like so:

Try:
   df['division'] = df['numerator']/df['denominator']
Except: 
   df['division'] = 0

BUT I think that this doesn't work as I thought it would, since if we get any exceptions ALL the values will be 0 in the division column.

I solved it with:

np.where(df['denominator'] !=0, do_the_thing, 0)

But I wonder if 0 was not the only cause of an exception, what would I do? Is there an efficient way to check exceptions in line by line operations?

Thanks in advance.

CodePudding user response：

if you still want to use try and except and make it specifically for your zero division you can try this :

try:
    df['division'] = df['numerator']/df['denominator']
except ZeroDivisionError:
    df['division'] = 0

This way, you can except only that type of error and live the others raise errors

Something like this ? Please adjust it to your liking as we don't have the df

for index, row in df.iterrows():
    try:
        row['division'] = row['numerator']/row['denominator']
    except ZeroDivisionError:
        row['division'] = 0