Python Pandas apply function with series data as argument

Question

I am using apply function to process name1 column. I can pass in a fix value like 8 into the function but I wish to use the value (num_of_bit) from each row to process name1 column. When I use the code as below, I will get the error. I understand why I got this error but I do not know how to achieve what I want.

def signedProcessing(input,num_of_bit):
    if input < (2**num_of_bit)/2:
        input += 256
    return input

out_df.loc[out_df['range_type'] == "SIGNED", [name1]] = out_df[out_df['range_type']=="SIGNED"][name1].apply(signedProcessing,num_of_bit=out_df[out_df['range_type'] == "SIGNED"]['num_of_bit'])

The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

It looks like you should use pd.Series.where instead of applying. — Henry Yik
– Henry Yik, Commented Sep 12, 2020 at 6:49

Yashar · Accepted Answer · 2020-09-12 10:35:14Z

1

If I understand the question correctly and you need to change the 'name1' value by the applying the function, where the 'range_type' is 'SIGNED', then you are not passing the 'num_of_bit' to apply, so it tries to use the whole column for each row. I suggest using a lambda function:

out_df.loc['name1'] = out_df[['name1', 'num_of_bit', 'range_type']].apply(lambda x: signedProcessing(x.name1, x.num_of_bits) if x.range_type=='SIGNED' else x.name1, axis=1)

This will change the 'name1' value on each row that has a 'SIGNED' range_type to the signedProcessing(value of name1, value of num_of_bits). If the range_type is something else, it won't change the name1 value.

answered Sep 12, 2020 at 10:35

Yashar

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