Dataframe Apply method to return multiple elements (series)

Question

import pandas as pd

Let's say I have a dataframe like so:

df = pd.DataFrame({"a":range(4),"b":range(1,5)})

it looks like this:

and a function that multiplies X by Y:

def XtimesY(x,y):
    return x*y

If I want to add a new pandas series to df I can do:

df["c"] =df.apply( lambda x:XtimesY(x["a"],2), axis =1)

It works !

Now I want to add multiple series:

I have this function:

def divideAndMultiply(x,y):
    return x/y, x*y

something like this ?:

df["e"], df["f"] = df.apply( lambda x: divideAndMultiply(x["a"],2) , axis =1)

It doesn't work !

I want the 'e' column to receive the divisions and 'f' column the multiplications !

Note: This is not the code I'm using but I'm expecting the same behavior.

Possible duplicate of Apply pandas function to column to create multiple new columns? — Federico Dorato
– Federico Dorato, Commented Oct 16, 2019 at 9:22

Sam · Accepted Answer · 2016-04-13 13:56:49Z

21

Almost there. Use zip* to unpack the function. Try this:

def divideAndMultiply(x,y):
    return x/y, x*y

df["e"], df["f"] = zip(*df.a.apply(lambda val: divideAndMultiply(val,2)))

edited Apr 13, 2016 at 13:56

answered Apr 13, 2016 at 13:43

Sam

4,09023 silver badges27 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Abbas · Accepted Answer · 2018-10-24 05:14:19Z

13

UPDATE

Updated for version 0.23 - using result_type='broadcast' for further details refer to documentation

Redefine your function like this:

def divideAndMultiply(x,y):
    return [x/y, x*y]

Then do this:

df[['e','f']] = df.apply(lambda x: divideAndMultiply(x["a"], 2), axis=1, result_type='broadcast')

You shall get the desired result:

In [118]: df
Out[118]:
   a  b  e  f
0  0  1  0  0
1  1  2  0  2
2  2  3  1  4
3  3  4  1  6

edited Oct 24, 2018 at 5:14

answered Apr 13, 2016 at 13:35

Abbas

4,0897 gold badges45 silver badges66 bronze badges

6 Comments

seaders Over a year ago

I've seen this answer multiple times, but any time I've tried, I get KeyError: "['e', 'f'] not in index. I think pandas must have changed, does it still work for you @Abbas?

Abbas Over a year ago

It still works. Follow the question and answer to reproduce the results.

seaders Over a year ago

repl.it/@seaders/SuperbIncompatibleAudacity it doesn't, not on Python 3.6 and pandas 0.23.1 - KeyError.

Abbas Over a year ago

@seaders you are right, this answer doesn't work in 0.23.1 & this answer works stackoverflow.com/a/36600318/1437877

seaders Over a year ago

Good stuff @Abbas, I just wanted to make sure I wasn't going crazy. I can't find anywhere in the docs that this was the correct way of doing things, to then be able to see they've changed it, so it's all pretty unclear!

|

Charles Plager · Accepted Answer · 2017-09-14 17:03:20Z

0

df["e"], df["f"] = zip(*df.apply( lambda x: divideAndMultiply(x["a"],2) , axis =1))

Should do the trick.

(I show this example so you can see how to use multiple columns as the input to create multiple new columns)

edited Sep 14, 2017 at 17:03

answered Jun 14, 2017 at 11:57

Charles Plager

6141 gold badge10 silver badges24 bronze badges

Comments

Dmytro Bugayev · Accepted Answer · 2018-09-28 08:33:52Z

0

the following solution to this frustratingly frustrating question works for me. I found the original suggestion in another StackOverflow post a while ago. The trick is to wrap up the return values into a Series like this:

def divideAndMultiply(x,y):
    return pd.Series([x/y, x*y])

Then this works as you wanted:

df[['e','f']] = df.apply( lambda x: divideAndMultiply(x["a"],2) , axis =1)

answered Sep 28, 2018 at 8:33

Dmytro Bugayev

68610 silver badges15 bronze badges

Collectives™ on Stack Overflow

Dataframe Apply method to return multiple elements (series)

4 Answers 4

Comments

6 Comments

Comments

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

4 Answers 4

Comments

6 Comments

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related