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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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Toc

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

This chapter was a quick tour of the power of NumPy and showed a glimpse of how it makes life easier while working with pandas. Some of the highlights from the chapter were as follows:

  • A NumPy array is a versatile data structure used for containing multidimensional homogeneous data.

  • There are a variety of methods available for slicing/dicing, creating, and manipulating an array in the NumPy package.

  • NumPy arrays have practical applications such as being the building blocks of linear algebra operations and a tool to manipulate multidimensional array data such as images and audio.

  • Arrays (or matrices) are the computational blocks used in advanced mathematical models such as neural networks.

  • NumPy arrays are the precursors of some of the essential data structures in pandas, namely Series.

  • Series are very similar to arrays. Series are one-dimensional. A...

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