CODEWITHSUNDEEP
pythonpandasapply
Stefano
Stefano

Reputation: 137

Is there a way to use apply() to create two columns in pandas dataframe?

I have a function returning a tuple of values, as an example:

def dumb_func(number):
    return number+1,number-1

I'd like to apply it to a pandas DataFrame

df=pd.DataFrame({'numbers':[1,2,3,4,5,6,7]})
test=dumb_df['numbers'].apply(dumb_func)

The result is that test is a pandas series containing tuples. Is there a way to use the variable test or to remplace it to assign the results of the function to two distinct columns 'number_plus_one' and 'number_minus_one' of the original DataFrame?

Upvotes: 0

Views: 76

Answers (2)

SimonR
SimonR

Reputation: 1824

df[['number_plus_one', 'number_minus_one']] = pd.DataFrame(zip(*df['numbers'].apply(dumb_func))).transpose()

To understand, try taking it apart piece by piece. Have a look at zip(*df['numbers'].apply(dumb_func)) in isolation (you'll need to convert it to a list). You'll see how it unpacks the tuples one by one and creates two separate lists out of them. Then have a look what happens when you create a dataframe out of it - you'll see why the transpose is necessary. For more on zip, see here : docs.python.org/3.8/library/functions.html#zip

Upvotes: 1

SUDHEER TALLURI
SUDHEER TALLURI

Reputation: 168

Method 1: When you don't use dumb function,

df[['numbers_plus_one','numbers_minus_one']]=pd.DataFrame(df.apply(lambda x: (x[0]+1,x[0]-1),axis=1).values.tolist())

Method 2: When you have test(i.e. series of tuples you mentioned in question)

df[['numbers_plus_one','numbers_minus_one']]=pd.DataFrame(test.values.tolist())

I hope this is helpful

Upvotes: 0

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