Data Science · Ebook

Pandas: Data Wrangling in Python

by Shriira Press

A comprehensive, self-contained guide to pandas, the library at the heart of data work in Python — the tool that loads, cleans, reshapes, combines, and analyzes the messy tabular data of the real world before any model or chart ever sees it. If a Python data-science or machine-learning project starts with a CSV, a database table, or a spreadsheet, pandas is almost certainly the first thing it touches. This book teaches it from first principles: the Series and DataFrame, reading and writing data, selecting and cleaning, the split-apply-combine of groupby, merging and reshaping, time series, performance, and the end-to-end data-analysis workflow. It blends intuition, the concepts behind the API, and runnable code.

Contents

1. 1Preface
2. 2Chapter 1 — What Is Pandas?
3. 3Chapter 2 — Series and DataFrame: The Core Data Structures
4. 4Chapter 3 — Reading and Writing Data: I/O
5. 5Chapter 4 — Indexing and Selection: loc, iloc, and Boolean Filtering
6. 6Chapter 5 — Cleaning Data: Missing Values, Duplicates, and Types
7. 7Chapter 6 — Transforming Columns: apply, map, and Vectorized Operations
8. 8Chapter 7 — GroupBy: Split-Apply-Combine
9. 9Chapter 8 — Combining Data: Merge, Join, and Concat
10. 10Chapter 9 — Reshaping Data: Pivot, Melt, and Tidy Data
11. 11Chapter 10 — Time Series
12. 12Chapter 11 — Categorical Data, Text, and Advanced Types
13. 13Chapter 12 — Performance, Scaling, and the Ecosystem
14. 14Chapter 13 — The Data Analysis Workflow and the Profession
15. 15Appendix A — Glossary and API Quick Reference
16. 16Appendix B — Further Reading and Resources