An Introduction to R and Python for Data Analysis: A Side-By-Side Approach - Rilegato

Brown, Taylor R.

 
9781032203256: An Introduction to R and Python for Data Analysis: A Side-By-Side Approach
Rilegato
ISBN 10: 1032203250 ISBN 13: 9781032203256
Casa editrice: Chapman and Hall/CRC, 2023

Sinossi

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

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Taylor R. Brown is an assistant professor of statistics at the University of Virginia. His research interests include state space models, particle filtering, and Markov chain Monte Carlo algorithms. He obtained his Ph.D. in statistics from the University of Virginia.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Chapman and Hall/CRC
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
1032203250
ISBN 13 
9781032203256
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
246
Contatto del produttore
non disponibile
Persona responsabile
non disponibile