20% of Pandas Functions for Data Scientists to Use 80% of the Time

Maximizing Efficiency: The 20% of Pandas Functions Every Data Scientist Should Know

“Efficiency is doing things right; effectiveness is doing the right things.” — Peter Drucker

Have you ever found yourself drowning in data and struggling to find the right tools to analyze and manipulate it efficiently? As a data scientist, you are likely familiar with Pandas, a popular Python library for data manipulation and analysis. With over 200 functions available, it can be challenging to determine which ones to prioritize to maximize efficiency and productivity.

In this article, we will explore the essential 20% of Pandas functions that every data scientist should know. We will provide examples and insights on how to use these functions effectively and offer tips on how to avoid common mistakes. By mastering these essential functions, data scientists can significantly reduce their workload and focus on what matters most — generating insights.

Let’s dive in!

The Pareto Principle and Pandas Functions