Basic Filtering
Explore fundamental filtering methods in Pandas, including single and multiple condition filters and negation. Understand how to apply these techniques effectively to select and exclude data based on complex criteria for improved data analysis.
Filtering
One of the most useful features in Pandas is the ability to filter elements from a Series or DataFrame using very simple expressions. You may want to select travelers originating from specific countries in a travel dataset, or patients with specific health conditions in a medical dataset. In all such cases, you’re bound to use the filtering feature of Pandas in your data analysis.
Basics
The first, and easiest, method to filter elements in a DataFrame is using the square brackets [] notation. This allows you to filter rows based on one or multiple conditions.
Example 1
You ...