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

Product typeBook

Published inAug 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781800209763

Edition1st Edition

Languages

Python

Concepts

Statistics

Authors (6):

Peter Farrell

Alvaro Fuentes

Ajinkya Sudhir Kolhe

Quan Nguyen

Alexander Joseph Sarver

Marios Tsatsos

View More author details

Summary

This chapter went through the core tools for data science and statistical computing in Python, namely, NumPy for linear algebra and computation, pandas for tabular data processing, and Matplotlib and Seaborn for visualization. These tools will be used extensively in later chapters of this book, and they will prove useful in your future projects. In the next chapter, we will go into the specifics of a number of statistical concepts that we will be using throughout this book and learn how to implement them in Python.

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Authors (6)

Peter Farrell

Peter Farrell learned to program from the Logo code in Seymour Paperts Mindstorms. A student introduced him to Python and he never looked back. In 2015, he self-published Hacking Math Class with Python on applying Python programming to learning and teaching high-school math. In 2019, No Starch Press published his second book, Math Adventures with Python. In his books, he also presents 21st-century topics, such as Cellular Automata, 3D Graphics, and Genetic Algorithms. Currently, he teaches Python and Math in the Dallas, Texas area.
Read more about Peter Farrell

Alvaro Fuentes

Alvaro Fuentes is a senior data scientist with a background in applied mathematics and economics. He has more than 14 years of experience in various analytical roles and is an analytics consultant at one of the ‘Big Three' global management consulting firms, leading advanced analytics projects in different industries like banking, technology, and consumer goods. Alvaro is also an author and trainer in analytics and data science and has published courses and books, such as 'Become a Python Data Analyst' and 'Hands-On Predictive Analytics with Python'. He has also taught data science and related topics to thousands of students both on-site and online through different platforms such as Springboard, Simplilearn, Udemy, and BSG Institute, among others.
Read more about Alvaro Fuentes

Ajinkya Sudhir Kolhe

Ajinkya Sudhir Kolhe is a programmer working for a tech company in the Bay area. He holds a M.S. in Computer Science and has experience in the tech industry of 5+ years. His area of interests include problem solving, analytics and applications in Python.
Read more about Ajinkya Sudhir Kolhe

Quan Nguyen

Quan Nguyen, the author of the first edition of this book, is a Python programmer with a strong passion for machine learning. He holds a dual degree in mathematics and computer science, with a minor in philosophy, earned from DePauw University. Quan is deeply involved in the Python community and has authored multiple Python books, contributing to the Python Software Foundation and regularly sharing insights on DataScience portal. He is currently pursuing a Ph.D. in computer science at Washington University in St. Louis.
Read more about Quan Nguyen

Alexander Joseph Sarver

Alexander Joseph Sarver is an ambitious data scientist and content creator with 6 years of mathematical teaching experience.
Read more about Alexander Joseph Sarver

Marios Tsatsos

Marios Tsatsos has 8+ years of experience in research in Physics, analytical thinking, modeling, problem solving and decision making.
Read more about Marios Tsatsos

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