[Tut] How to Apply a Function to Each Cell in a Pandas DataFrame?

[Tut] How to Apply a Function to Each Cell in a Pandas DataFrame? - Printable Version

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[Tut] How to Apply a Function to Each Cell in a Pandas DataFrame? - xSicKxBot - 08-23-2022

How to Apply a Function to Each Cell in a Pandas DataFrame?

5/5 – (1 vote)

Problem Formulation

Given the following DataFrame

Code:
df

Code:
import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) print(df) ''' A B C D
0 1 2 2 4
1 4 8 3 1
2 2 7 1 2
3 3 5 1 2 '''

Challenge: How to apply a function

Code:
f

to each cell in the DataFrame?

For example, you may want to apply a function that replaces all odd values with the value

Code:
'odd'

Code:
import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) def f(cell): if cell%2 == 1: return 'odd' return cell # ... <Apply Function f to each cell> ... print(df) ''' A B C D
0 odd 2 2 4
1 4 8 odd odd
2 2 odd odd 2
3 odd odd odd 2 '''

Solution: DataFrame applymap()

The Pandas DataFrame

Code:
df.applymap()

method returns a new DataFrame where the function

Code:
f

is applied to each cell of the original DataFrame

Code:
df

. You can pass any function object as a single argument into the

Code:
df.applymap()

function, either defined as a lambda expression or a normal function.

Example 1: Replace Odd Values in DataFrame

Here’s an example where each cell of the DataFrame is checked against whether it is an odd value. If so, it is replaced with the string

Code:
'odd'

Code:
def f(cell): if cell%2 == 1: return 'odd' return cell df_new = df.applymap(f) print(df_new) ''' A B C D
0 odd 2 2 4
1 4 8 odd odd
2 2 odd odd 2
3 odd odd odd 2 '''

Example 2: Create Two DataFrames with Even and Odd Values Replaced

A slightly advanced example uses two lambda functions to create two new DataFrames where one has all odd and the other has all even values replaced:

Code:
import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) df_even = df.applymap(lambda x: 'odd' if x%2 else x)
df_odd = df.applymap(lambda x: x if x%2 else 'even') print(df_even) ''' A B C D
odd 2 2 4
4 8 odd odd
2 odd odd 2
odd odd odd 2 ''' print(df_odd) ''' A B C D
1 even even even
even even 3 1
even 7 1 even
3 5 1 even '''

We used the concept of a ternary operator to concisely define the replacement function using the keyword

Code:
lambda

to create a function object “on the fly”.

Recommended Tutorial: Understanding the Ternary Operator in Python

This tutorial idea was proposed by Finxter student Kyriakos.