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An Introduction to R and Python for Data Analysis Taylor R. Brown Hardback NEW

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eBay item number:317101059447
Last updated on Jul 21, 2025 07:13:16 MYTView all revisionsView all revisions

Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
EAN
9781032203256
ISBN
1032203250
Book Title
An Introduction to R and Python for Data Analysis:
Item Height
0.63
Features
1st Edition

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032203250
ISBN-13
9781032203256
eBay Product ID (ePID)
21061245468

Product Key Features

Number of Pages
246 Pages
Language
English
Publication Name
Introduction to Rand Python for Data Analysis : a Side-by-Side Approach
Publication Year
2023
Subject
Probability & Statistics / General, General
Type
Textbook
Author
Taylor R. Brown
Subject Area
Mathematics
Format
Hardcover

Dimensions

Item Weight
23.1 Oz
Item Length
10 in
Item Width
7 in

Additional Product Features

Intended Audience
College Audience
LCCN
2022-059206
Dewey Edition
23
TitleLeading
An
Illustrated
Yes
Dewey Decimal
005.13
Table Of Content
1. Introduction 2. Basic Types 3. R vectors versus Numpy arrays and Pandas' Series 4. Numpy ndarrays Versus R's matrix and array Types 5. R's lists Versus Python's lists and dicts 6. Functions 7. Categorical Data 8. Data Frames Part 1. Introducing the Basics 10. Using Third-Party Code 11. Control Flow 12. Reshaping and Combining Data Sets 13. Visualization Part 2. Common Tasks and Patterns 14. An Introduction to Object-Oriented Programming 15. An Introduction to Functional Programming
Synopsis
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 and save time., 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., 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.
LC Classification Number
QA276.45

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