Pandas 1.x Cookbook - Second Edition

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.

This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.

pandas這個庫非常龐大，常常有使用者對其更令人印象深刻的功能一無所知。官方的pandas文件雖然詳盡，但並沒有提供許多有用的範例，教導如何將多個命令組合在一起，就像在實際分析中所做的那樣。這本書將引導您，就像您在專家的肩膀上觀察一樣，解決您高度可能遇到的情況。

這本新的更新和修訂版為您提供了獨特、慣用和有趣的配方，用於pandas的基礎和高級數據操作任務。一些配方著重於深入理解基本原則，或者比較和對比兩個相似的操作。其他配方將深入研究特定的數據集，在此過程中發現新的和意想不到的見解。許多高級配方結合了pandas庫中的多個不同功能，生成結果。

Matt Harrison

Matt Harrison has been using Python since 2000. He runs MetaSnake, which provides corporate training for Python and Data Science. He is the author of Machine Learning Pocket Reference, the bestselling Illustrated Guide to Python 3, and Learning the Pandas Library, among other books.

Theodore Petrou

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.

Matt Harrison

Matt Harrison自2000年以來一直在使用Python。他經營MetaSnake，為Python和數據科學提供企業培訓。他是《機器學習口袋參考》、暢銷書《Python 3圖解指南》和《學習Pandas庫》等書的作者。

Theodore Petrou

Theodore Petrou是Dunder Data的創始人，該培訓公司致力於有效地教授Python數據科學生態系統給個人和企業。在Dunder Data網站上閱讀他的教程並嘗試他的數據科學挑戰。

1. Pandas Foundations
2. Essential DataFrame Operations
3. Creating and Persisting DataFrames
4. Beginning Data Analysis
5. Exploratory Data Analysis
6. Selecting Subsets of Data
7. Filtering Rows
8. Index Alignment
9. Grouping for Aggregation, Filtration and Transformation
10. Restructuring Data into a Tidy Form
11. Combining Pandas Objects
12. Time Series Analysis
13. Visualization with Matplotlib, Pandas, and Seaborn
14. Debugging and Testing Pandas

- Pandas 基礎
- DataFrame 的基本操作
- 創建和保存 DataFrame
- 開始進行資料分析
- 探索性資料分析
- 選擇子集資料
- 過濾行
- 索引對齊
- 分組進行聚合、過濾和轉換
- 將資料重組成整潔的形式
- 結合 Pandas 物件
- 時間序列分析
- 使用 Matplotlib、Pandas 和 Seaborn 進行視覺化
- 調試和測試 Pandas