Apply a function using another array how a argument in a pandas.Series

Question

Have some way to apply a function in a pandas.Series using different values of another pandas.Series? I know that have the pandas.Series.apply(), but I need something like that:

array1 = pandas.Series([1, 2, 3, 4])
array2 = pandas.Series([5, 5, 6, 0])

def func(x, y):
    return x+y

print(array1.apply(func, args = array2))


Out:
    0 6
    1 7
    2 9
    3 4

In other words, I need apply a function in a pandas.DataFrame column by I need use another column of same pandas.DataFrame. Using the same function func:

df = pandas.DataFrame({'a': [1, 2, 3, 4], 'b': [5, 5, 6, 0]})
df['c'] = df['a'].apply(func, args = df['b'])

print(df)


Out:
       a   b   c
    0  1   5   6
    1  2   5   7
    2  3   6   9
    3  4   0   4

Thank you!

I need use the apply because I use multiprocessing like pandarallel, so I just change apply() for parallel_apply(), someone know a way to do it? Use multiprocessing with operations that use two columns?

quantummind · Accepted Answer · 2021-04-07 11:09:23Z

1

If you want to add columns from two dataframes then instead of

print(array1.apply(func, args = array2))

you can use

print(func(array1, array2))                                                                                                                                                               
0    6
1    7
2    9
3    4

If you want to add two columns of the same dataframe, you can do that simply in the following way:

df['c'] = func(df['a'], df['b']) 

print(df) 
     ...:                                                                                                                                                                                           
   a  b  c
0  1  5  6
1  2  5  7
2  3  6  9
3  4  0  4

edited Apr 7, 2021 at 11:09

answered Apr 7, 2021 at 11:03

quantummind

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1 Comment

Douglas Oliveira Over a year ago

I need use the apply because I use multiprocessing like pandarallel, so I just change apply() for parallel_apply(), have some way to do it with that you said? I just use multiprocesing using two columns of a pandas.DataFrame()

Jonny_92 · Accepted Answer · 2021-04-07 11:15:49Z

0

For the specific case you can just use:

df['c'] = df['a'] + df['c']

and for the principal function you use Numpy like in this example

df['c'] = numpy.exp(df['a']) + df['b']

answered Apr 7, 2021 at 11:15

Jonny_92

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