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Mastering pandas

You're reading from   Mastering pandas A complete guide to pandas, from installation to advanced data analysis techniques

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Product type Paperback
Published in Oct 2019
Publisher
ISBN-13 9781789343236
Length 674 pages
Edition 2nd Edition
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Author (1):
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Ashish Kumar Ashish Kumar
Author Profile Icon Ashish Kumar
Ashish Kumar
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Overview of Data Analysis and pandas FREE CHAPTER
2. Introduction to pandas and Data Analysis 3. Installation of pandas and Supporting Software 4. Section 2: Data Structures and I/O in pandas
5. Using NumPy and Data Structures with pandas 6. I/Os of Different Data Formats with pandas 7. Section 3: Mastering Different Data Operations in pandas
8. Indexing and Selecting in pandas 9. Grouping, Merging, and Reshaping Data in pandas 10. Special Data Operations in pandas 11. Time Series and Plotting Using Matplotlib 12. Section 4: Going a Step Beyond with pandas
13. Making Powerful Reports In Jupyter Using pandas 14. A Tour of Statistics with pandas and NumPy 15. A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates 16. Data Case Studies Using pandas 17. The pandas Library Architecture 18. pandas Compared with Other Tools 19. A Brief Tour of Machine Learning 20. Other Books You May Enjoy

Summary

We live in a big data era characterized by the four V's- volume, velocity, variety, and veracity. The volume and velocity of data are set to increase for the foreseeable future. Companies that can harness and analyze big data to extract information and take actionable decisions based on this information will be the winners in the marketplace. Python is a fast-growing, user-friendly, extensible language that is very popular for data analysis.

pandas is a core library of the Python toolkit for data analysis. It provides features and capabilities that make it much easier and faster than many other popular languages, such as Java, C, C++, and Ruby.

Thus, given the strengths of Python outlined in this chapter as a choice for the analysis of data and the popularity it has gained from users, contributors, and industry leaders, data analysis practitioners utilizing Python...

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