A Beginner’s Guide to Data Cleaning Using Pandas
Most real-world datasets are messy. Before you can run any analysis or build a model, you need to deal with missing values, strange outliers, inconsistent formatting, and incorrect data types. This post walks through the basics of data cleaning using pandas, one of the most popular Python libraries for data manipulation. We’ll use a dataset of Nairobi property listings as our example. It contains information like location, price, number of bedrooms, and date posted. Let’s get started. ...