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

Brown, Taylor R.

 
9781032203256: An Introduction to R and Python for Data Analysis: A Side-By-Side Approach
Couverture rigide
ISBN 10 : 1032203250 ISBN 13 : 9781032203256
Editeur : Chapman & Hall/CRC, 2023

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, 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

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Chapman & Hall/CRC
Date d'édition
2023
Langue
anglais
ISBN 10 
1032203250
ISBN 13 
9781032203256
Reliure
Relié
Nombre de pages
246
Coordonnées du fabricant
non disponible
Personne responsable
non disponible