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Advanced pandas—Going Beyond the Basics

String Methods—Find, Extract, and Replace

Explore pandas string methods such as find, rfind, findall, extract, and replace to manage and transform text data effectively. Understand how to locate substrings, extract regex matches, and perform replacements with flexibility for regex and case sensitivity. This lesson equips you to handle complex text data within DataFrames for improved data manipulation workflows.

We'll cover the following...

Introduction

We continue the exploration of commonly used string methods by looking at the methods for finding, extracting, and replacing text. As before, we’ll use the mock customer dataset from an e-commerce platform.

Preview of Mock E-Commerce Customer Dataset

customer_id

title

first_name

last_name

ip_address

email

264-42-4576

Mr

gino

Crowdson

82.48.134.48/5

gcrowdson0@tamu.edu

165-49-2539

Ms

hailey

kirsche

61.122.97.13/13

ekirsche1@rambler.ru

763-23-7634

Dr

Viviyan

Peschet

253.140.11.162/2

rpeschet@ning.com

Note that the columns in the DataFrame for this dataset have already been converted into StringDtype.

Find

The find() method in pandas is used to search for a substring within each element of a DataFrame column and return the starting index of its first occurrence. Let’s say we want to search for the string 76 in the customer_id column with the code below:

Python 3.10.4
# Find lowest index of substring occurrence

df['find'] = df['customer_id'].str.find('76')



# View output

print(df[['customer_id', 'find']])

The output above shows the index positions where the substring 76 first occurs:

  • For the string value (264-42-4576) in the first row, the substring is first found at the index 9.

  • For the string value (165-49-2539) in the second row, the substring isn’t found, so a value of ...