Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. With this book, data scientists from the Python and R communities will learn how to speak the dialects of each language. By recognizing the strengths of working with both, you'll discover new ways to accomplish data science tasks and expand your skill set.
Authors Boyan Angelov and Rick Scavetta explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. Not only will you learn how to use Python and R together in real-world settings, but you'll also broaden your knowledge and job opportunities by working as a bilingual data scientist.
- Learn Python and R from the perspective of your current language
- Understand the strengths and weaknesses of each language
- Identify use cases where one language is better suited than the other
- Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows
- Learn how to integrate R and Python in a single workflow
- Follow a real-world case study that demonstrates ways to use these languages together
Table of contents
1. R for Pythonistas
- Up and running with R
- The perks & perils of projects & packages
- The Triumph of Tibbles
- A word about types and exploring
- Naming (internal) Things
- List the ways
- The Facts about Factors
- How to find… stuff
- Reiterations Redo
- Final Thoughts
2. Python for R users
- Question 1: Which version and build should we use?
- Question 2: What are the standard tools, and why?
- Virtual (development) environments
- Installing packages
- Question 3: How does Python, the language, compare to R?
- Descriptive statistics
- Final Thoughts
- 3. Data Format Context
- 4. Workflow Context
- Title: Python and R for the Modern Data Scientist
- Release date: September 2021
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492093336
You might also like
Python for Programmers, First Edition
The professional programmer's Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers …
Data Science from Scratch, 2nd Edition
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, …
Python Crash Course, 2nd Edition
This is the second edition of the best selling Python book in the world. Python Crash …
Python for Data Analysis, 2nd Edition
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, …