CODEWITHSUNDEEP
python-3.xpandasdataframe
NathanaëlBeau
NathanaëlBeau

Reputation: 1152

Use pandas.apply with multiple arguments to return several columns

I am trying to preprocess a dataset with pandas. I want to use a function with multiple arguments (one from a column of the dataframe, others are variables) which returns several outputs like this:

def preprocess(Series,var1,var2,var3,var4):
   return 1,2,3,4

I want to use the native pandas.apply to use this function on one column of my dataframe like this:

import pandas as pd

df = pd.DataFrame([[4, 9]] * 3, columns=['A', 'B'])

df['C'], df['D'], df['E'], df['F'] = df.apply(lambda x: preprocess(x['A'], 1, 2, 3, 4), axis=1)

But the last line gives me the following error:

ValueError: not enough values to unpack (expected 4, got 3)

I understand my last line returns one tuple of 4 values (1,2,3,4) per line whereas I wanted to get each of these values in the columns C, D, etc.

How can I perform this?

Upvotes: 0

Views: 193

Answers (1)

Quang Hoang
Quang Hoang

Reputation: 150735

You need to re-write your function to return a series, that way, apply returns a dataframe:

def preprocess(Series,var1,var2,var3,var4):
    return pd.Series([1,2,3,4])

Then your code would run and return

   A  B  C  D  E  F
0  4  9  0  1  2  3
1  4  9  0  1  2  3
2  4  9  0  1  2  3

Update: Without rewrite of the function:

processed = df.apply(lambda x: preprocess(x['A'], 1, 2, 3, 4), axis=1)
df['C'], df['D'], df['E'], df['F'] = np.array(processed.to_list()).T

Upvotes: 1

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