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Pandas: Apply function that returns multiple values to rows in pandas DataFrame

Given a Pandas DataFrame, we have to apply function that returns multiple values to rows.
Submitted by Pranit Sharma, on July 17, 2022

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Problem statement

Given a Pandas DataFrame, we have to apply function that returns multiple values to rows.

Solution approach

Whenever we want to perform some operation on the entire DataFrame, we either use apply method. It is used on the grouped objects in pandas DataFrame.

The apply() method

The apply() method passes the columns of each group in the form of a DataFrame inside the function which is described in apply() method. The function which is described inside the apply() method returns a series or DataFrame (NumPy array or even a list).

Apply function that returns multiple values to rows

To apply a function that returns multiple values to rows in pandas DataFrame, we will define a function for performing some operations on the values, and then finally we will return all the values in the form of a series.

import pandas as pd

Let us understand with the help of an example,

Python program to apply function that returns multiple values to rows in pandas DataFrame

# Importing Pandas package
import pandas as pd

# Create a dictionary
d= {'Num': [ i for i in range(10)]}

# Create DataFrame
df = pd.DataFrame(d)

# Display DataFrame
print("Original DataFrame:\n",df,"\n")

# Defining a function
def function(n):
     a=n*10
     b=n*100
     c=n*1000
     return pd.Series([a,b,c])

# Using apply method
result = df['Num'].apply(function)

# Display result
print("Result:\n",result)

Output

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