Pandas Cookbook. Practical recipes for scientific computing, time series and exploratory data analysis using Python - Third Edition - Helion
Tytuł oryginału: Pandas Cookbook. Practical recipes for scientific computing, time series and exploratory data analysis using Python - Third Edition
ISBN: 9781836205869
stron: 463, Format: ebook
Data wydania: 2024-10-01
Księgarnia: Helion
Cena książki: 125,10 zł (poprzednio: 139,00 zł)
Oszczędzasz: 10% (-13,90 zł)
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.
With this latest edition unlock the full potential of pandas 2.x onwards. Whether you're a beginner or an experienced data analyst, this book offers a wealth of practical recipes to help you excel in your data analysis projects. This cookbook covers everything from fundamental data manipulation tasks to advanced techniques for handling big data, visualization, and more. Each recipe is designed to address common real-world challenges, providing clear explanations and step-by-step instructions to guide you through the process.
Explore cutting-edge topics such as idiomatic pandas coding, efficient handling of large datasets, and advanced data visualization techniques. Whether you're looking to sharpen or expand your skills, the Pandas Cookbook is your essential companion for mastering data analysis and manipulation with pandas 2.x, and beyond
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Spis treści
Pandas Cookbook. Practical recipes for scientific computing, time series, and exploratory data analysis using Python - Third Edition eBook -- spis treści
- 1. pandas Foundations
- 2. Selection and Assignment
- 3. Data Types
- 4. The pandas I/O System
- 5. Algorithms and How to Apply Them
- 6. Visualization
- 7. Reshaping DataFrames
- 8. Group By
- 9. Temporal Data Types and Algorithms
- 10. General Usage and Performance Tips
- 11. The pandas Ecosystem