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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

History of pandas

The basic version of pandas was built in 2008 by Wes McKinney, an MIT grad with heavy quantitative finance experience. Now a celebrity in his own right, thanks to his open source contributions and the wildly popular book called Data Analysis with Python, he was reportedly frustrated with the time he had to waste doing simple data manipulation tasks at his job, such as reading a CSV file, with the popular tools at that time. He said he quickly fell in love with Python for its intuitive and accessible nature after not finding Excel and R suitable for his needs. But he found that it was missing key features that would make it the go-to tool for data analysis—for example, an intuitive format to deal with spreadsheet data or to create new calculated columns from existing columns.

According to an interview he gave to Quartz, the design considerations and vision...

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