Python - Pandas applying regex to replace values

Given a Pandas DataFrame, we have to apply regex to replace values.
Submitted by Pranit Sharma, on July 30, 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.

Regex (Regular Expression)

A special format string is used for searching and filtering in pandas DataFrame rows.

The regex or a regular expression is simply a group of characters or special characters which follows a particular pattern with the help of which we can search and filter pandas DataFrame rows.


  • 'K.*' : It will filter all the records which start with the letter 'K'.
  • 'A.*' : It will filter all the records which start with the letter 'A'.

To replace a value using regex or by comparing the value by regex, we will use DataFrame[col].str.replace() method, inside which we will define our regex to compare.

Let us understand with the help of an example,

Python code for applying regex to replace values

# Importing pandas package
import pandas as pd

# Creating a dictionary
d = {'Col':['$1100,000*','$40000 string created']}

# Creating a dataframe
df = pd.DataFrame(d)

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

# Using regex comparison
df['Col'] = df['Col'].str.replace(r'\D+', '', regex=True).astype('int')

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


Example: Applying regex to replace values

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