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The Statistics and Calculus with Python Workshop

You're reading from  The Statistics and Calculus with Python Workshop

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209763
Pages 740 pages
Edition 1st Edition
Languages
Concepts
Authors (6):
Peter Farrell Peter Farrell
Profile icon Peter Farrell
Alvaro Fuentes Alvaro Fuentes
Profile icon Alvaro Fuentes
Ajinkya Sudhir Kolhe Ajinkya Sudhir Kolhe
Profile icon Ajinkya Sudhir Kolhe
Quan Nguyen Quan Nguyen
Profile icon Quan Nguyen
Alexander Joseph Sarver Alexander Joseph Sarver
Profile icon Alexander Joseph Sarver
Marios Tsatsos Marios Tsatsos
Profile icon Marios Tsatsos
View More author details

Table of Contents (14) Chapters

Preface
1. Fundamentals of Python 2. Python's Main Tools for Statistics 3. Python's Statistical Toolbox 4. Functions and Algebra with Python 5. More Mathematics with Python 6. Matrices and Markov Chains with Python 7. Doing Basic Statistics with Python 8. Foundational Probability Concepts and Their Applications 9. Intermediate Statistics with Python 10. Foundational Calculus with Python 11. More Calculus with Python 12. Intermediate Calculus with Python Appendix

Python's Other Statistics Tools

In the previous chapter, we considered Python's three main libraries, which make up the majority of a common data science/scientific computing pipeline: NumPy for multi-dimensional matrix computation, pandas for tabular data manipulation, and Matplotlib for data visualization.

Along the way, we have also discussed a number of supporting tools that complement those three libraries well; they are seaborn for the implementation of complex visualizations, SciPy for statistical and scientific computing capability, and scikit-learn for advanced data analysis needs.

Needless to say, there are also other tools and libraries that, even though they did not fit into our discussions well, offer unique and powerful capabilities for particular tasks in scientific computing. In this section, we will briefly consider some of them so that we can gain a comprehensive understanding of what Python tools are available for which specific tasks.

These tools...

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