Python and R in Statistics and Data Science

Nethal Jajo

ISBN 10: 6206845648 / ISBN 13: 9786206845645

Published by LAP LAMBERT Academic Publishing Dez 2023, 2023

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -This book provides a guide to Python codes and corresponding R codes for data connectivity, manipulation, and analysis as both are useful today. This will supplement and enrich both the Python and R users' libraries and will support learners/teachers who are using one platform and intending to learn/teach the other.Our goal in writing this book is to help users to translate what they know on Python into an efficient working knowledge of R and vice versa as quickly and easily as possible. We point out how they differ using terminology which is familiar for both Python and R users. One can find any R function by looking up its counterpart in Python and vice versa.This book is aimed for students, academics, professionals and interested people in general who know both Python and R. However, we explain both Python and R codes for statistics and data science, so the readers can easily move from one software to another. This book does not include writing functions or developing packages in Python or R, it is about using the exiting functions or packages in statistics and data science.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.

Seller Inventory # 9786206845645

Bibliographic Details

• Title: Python and R in Statistics and Data Science
• Publisher: LAP LAMBERT Academic Publishing Dez 2023
• Publication Date: 2023
• Language: English
• ISBN 10: 6206845648
• ISBN 13: 9786206845645
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 107 grams

About this title

Synopsis

This book provides a guide to Python codes and corresponding R codes for data connectivity, manipulation, and analysis as both are useful today. This will supplement and enrich both the Python and R users’ libraries and will support learners/teachers who are using one platform and intending to learn/teach the other.Our goal in writing this book is to help users to translate what they know on Python into an efficient working knowledge of R and vice versa as quickly and easily as possible. We point out how they differ using terminology which is familiar for both Python and R users. One can find any R function by looking up its counterpart in Python and vice versa.This book is aimed for students, academics, professionals and interested people in general who know both Python and R. However, we explain both Python and R codes for statistics and data science, so the readers can easily move from one software to another. This book does not include writing functions or developing packages in Python or R, it is about using the exiting functions or packages in statistics and data science.