Learn essential data cleaning techniques in Pandas through a comprehensive Python tutorial that covers fundamental operations for preparing and transforming datasets. Master key data cleaning concepts including duplicate removal, column management, string manipulation with strip functions, phone number standardization, column splitting, value replacement, handling null values, and data filtering. Work with practical examples using a customer call list dataset while following along with provided code samples and resources on GitHub. Gain hands-on experience implementing these crucial data cleaning skills that form the foundation of effective data analysis workflows in Python.
Data Cleaning with Python Pandas - A Complete Tutorial
Overview
Syllabus
Intro
First Look at Data
Removing Duplicates
Dropping Columns
Strip
Cleaning/Standardizing Phone Numbers
Splitting Columns
Standardizing Column Values using Replace
Fill Null Values
Filtering Down Rows of Data
Outro
Taught by
Alex the Analyst
