Pandas in Action MEAP V07 | Pandas in Action

A Hands-On Guide to pandas, Built for Data People

Pandas in Action is a tutorial for pandas, the open-source Python library that has become a workhorse for sorting, cleaning, joining, aggregating, and exploring data. Boris Paskhaver writes for readers who know their way around spreadsheets but may not consider themselves software engineers. The core argument is simple: if you can think through an Excel formula, you can learn to think through pandas code. 💻

From Spreadsheet Clicks to Python Commands

Moving from Excel to pandas is not just a change of tool; it is a change of mental model. Instead of pointing and clicking, you issue commands. That shift demands precision, but it also opens the door to reusable workflows, deeper customization, and reproducible analysis. Paskhaver meets Excel users where they are, comparing pandas with graphical spreadsheet applications and explaining why code can be better suited to large, repetitive, or multi-step data tasks.

What the Early Access Edition Covers 📊

This MEAP Version 7 manuscript follows a structured path through the library:

• An introduction to pandas, its history, and its place in Python’s data science ecosystem
• The Series object and essential Series methods
• The DataFrame object and techniques for filtering rows and columns
• Working with text data
• MultiIndex DataFrames, reshaping, pivoting, and the GroupBy object
• Merging, joining, and concatenating datasets
• Dates, times, imports, exports, and configuration options
• Visualization, plus appendices on installation, Python basics, and NumPy

Who Will Get the Most From It?

Readers coming from Excel, Google Sheets, or another tabular tool will find the transition mapped out carefully. Data analysts who want to move beyond manual reporting, students learning Python for data work, and professionals who need to clean or combine datasets will find a practical sequence here. The book does not assume advanced programming experience, though some familiarity with spreadsheets and basic data concepts will help.

Why the MEAP Version Matters

Manning Early Access gives readers a look at the book before the final edition is complete. This Version 7 manuscript contains the material as it stood at that stage, including the planned chapter structure and appendices. For learners who want to start working with pandas now, it offers a substantial tutorial while being clear that it is not the final published release.

Build Confidence One DataFrame at a Time 🐼

Pandas rewards experimentation. Each chapter moves from concepts to commands, and the book’s bundled datasets give readers something concrete to manipulate. If you have ever wanted to automate a repetitive report, clean a messy table without endless manual edits, or simply understand why pandas is so widely used, this early access guide gives you a focused place to begin.