ABSTRACT

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners, it is useful and efficient to learn both at the same time, helping lecturers and students to teach and learn more, save time, whilst reinforcing the shared concepts and differences of the systems. This tandem learning is highly useful for students, helping them to become literate in both languages, and develop skills which will be handy after their studies. This book presumes no prior experience with computing, and is intended to be used by students from a variety of backgrounds. The side-by-side formatting of this book helps introductory graduate students quickly grasp the basics of R and Python, with the exercises providing helping them to teach themselves the skills they will need upon the completion of their course, as employers now ask for competency in both R and Python. Teachers and lecturers will also find this book useful in their teaching, providing a singular work to help ensure their students are well trained in both computer languages. All data for exercises can be found here: https://github.com/tbrown122387/r_and_python_book/tree/master/data. Instructors can access the solutions manual via the book's website.

Key features: 

- Teaches R and Python in a "side-by-side" way. 

- Examples are tailored to aspiring data scientists and statisticians, not software engineers. 

- Designed for introductory graduate students.

- Does not assume any mathematical background.

part I|110 pages

Introducing the Basics

chapter 2Chapter 1|8 pages

Introduction

chapter Chapter 2|6 pages

Basic Types

chapter Chapter 3|30 pages

R Vectors versus Numpy arrays and Pandas' Series

chapter Chapter 4|12 pages

Numpy ndarrays versus R's Matrix and array Types

chapter Chapter 5|6 pages

R's lists versus Python's lists and dicts

chapter Chapter 6|22 pages

Functions

chapter Chapter 7|10 pages

Categorical Data

chapter Chapter 8|14 pages

Data Frames

part II|72 pages

Common Tasks and Patterns

chapter 112Chapter 9|14 pages

Input and Output

chapter Chapter 10|10 pages

Using Third-Party Code

chapter Chapter 11|12 pages

Control Flow

chapter Chapter 12|18 pages

Reshaping and Combining Data Sets

chapter Chapter 13|16 pages

Visualization

part III|58 pages

Programming Styles

chapter 184Chapter 14|28 pages

An Introduction to Object-Oriented Programming

chapter Chapter 15|28 pages

An Introduction to Functional Programming