How to apply functions to a Dataframe with arrays within it, in Python?

Question

I hope to be clear on the questions, but let me explain me better, I have this dataframe:

import pandas as pd
  m = pd.DataFrame({'A': (1, 2, 3), 
                    'B': ([0, 1, 2], [3, 4, 5], [6, 7, 8])})

My objective is to obtain the column z which is each y-array squared plus the x-integer corresponding the position in the columns. Maybe you can get it in that way:

  m = pd.DataFrame({'A': (1, 2, 3), 
                    'B': ([1, 2, 3], [4, 5, 6], [7, 8, 9]),
                    'C': ([2, 5, 10], [18, 27, 38], [52, 67, 84])})

I can do it in R using this code:

m <- m %>% mutate(z = map2(x,y, ~map2_dbl(.x,.y, ~ (.x + .y^2))))

Is there something similar in Python? Regards

What is the issue, exactly? Have you tried anything, done any research? What does your data actually look like? Storing lists in a DataFrame is not ideal. — AMC
– AMC, Commented Apr 5, 2020 at 21:29
Hi! Thanks for the question. I know that the way I stored that data is not the best, however, this is a dataframe with is composed of different discount rates for cashflows with different periods (some have 20 years, others 10 and so on). I must to stored in that way in order to deliver the NPV and have each cashflow presented. If you know a better way to store the data, I am open to suggestions. Regards — Alí Meres Vargas
– Alí Meres Vargas, Commented Apr 7, 2020 at 0:10

yatu · Accepted Answer · 2020-04-05 16:36:43Z

2

This could get pretty inefficient by using python lists. I'd suggest you to use numpy here:

import numpy as np

m['C'] = (np.stack(m.B.values)**2 + m.A.values[:,None]).tolist()

print(m)

A          B             C
0  1  [1, 2, 3]    [2, 5, 10]
1  2  [4, 5, 6]  [18, 27, 38]
2  3  [7, 8, 9]  [52, 67, 84]

answered Apr 5, 2020 at 16:36

yatu

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1 Comment

Alí Meres Vargas Over a year ago

Hey! Thanks for the answer! That was pretty handy

BENY · Accepted Answer · 2020-04-05 16:43:14Z

2

In pandas , and since you have object in your column, which will make most of the method from pandas not work, we use for loop here. This method should be fast enough ~

m['C']=[(x + np.array(y)**2).tolist() for x , y in zip(m.A,m.B)]

edited Apr 5, 2020 at 16:43

answered Apr 5, 2020 at 16:32

BENY

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1 Comment

Alí Meres Vargas Over a year ago

Thanks for the answer. I didn't know about this zip module. Regards

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