If you've just started your journey in data analytics, this guide walks you through how to use Pandas, Python's most popular data manipulation library, to clean real-world datasets. Every example here comes from projects I've actually worked on, including a Kenyan hospital operations dataset and a Nairobi housing statistics dataset.
What is Pandas?
Pandas is an open-source Python library built for data manipulation and analysis. Think of it as a supercharged Excel, but inside Python; you can load, filter, clean, transform, and summarize data all in code.
It gives you two core data structures:
Series a single column of data:
