Data Science Fundamentals Pocket Primer

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.


FEATURES:



Includes a concise introduction to Python 3 and linear algebra


Provides a thorough introduction to data visualization and regular expressions


Covers NumPy, Pandas, R, and SQL


Introduces probability and statistical concepts


Features numerous code samples throughout


Companion files with source code and figures



1: Working with Data

2: Introduction to Probability and Statistics

3: Linear Algebra Concepts

4: Introduction to Python

5: Introduction to NumPy

6: Introduction to Pandas

7: Introduction to R

8: Regular Expressions

9: SQL and NoSQL

10: Data Visualization

Index