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Advanced pandas—Going Beyond the Basics

String Methods—Basic Transformations and Checks

Explore how to apply pandas string methods for basic text transformations such as changing case with lower, upper, title, and casefold. Understand methods to validate string data with is-prefix checks to ensure data quality. This lesson helps you manage and verify textual data efficiently in pandas DataFrames.

We'll cover the following...

Introduction

In this lesson, we’ll explore the many capabilities and methods for working with string data type values in pandas DataFrames. We’ll first do a quick refresher of the basic transformation and checks of string values based on the following 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

The pandas DataFrame for the dataset can be viewed below:

Python 3.10.4
# Convert all DataFrame columns to string type
df = df.astype('string')
# View DataFrame of mock customer dataset
print(df)
print('=' * 40)
print(df.dtypes)

String accessors

Given that pandas DataFrames are a collection of Series objects, string values in these columns can be accessed via the str accessor. The str accessor provides a set of vectorized string methods that can be used to manipulate strings in a DataFrame. These string methods generally have names that match the ...