R for the Rest of Us: A Statistics-Free Introduction

Author:   David Keyes
Publisher:   No Starch Press,US
ISBN:  

9781718503328


Pages:   232
Publication Date:   25 June 2024
Format:   Paperback
Availability:   To order   Availability explained
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R for the Rest of Us: A Statistics-Free Introduction


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Full Product Details

Author:   David Keyes
Publisher:   No Starch Press,US
Imprint:   No Starch Press,US
Weight:   0.369kg
ISBN:  

9781718503328


ISBN 10:   1718503326
Pages:   232
Publication Date:   25 June 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

Table of Contents

Introduction Part 1: Visualizations Chapter 1: An R Programming Crash Course Chapter 2: Principles of Data Visualization Chapter 3: Making Your Own ggplot Theme Chapter 4: Creating Maps Chapter 5: Crafting High-Quality Tables Part 2: Reports, Presentations, and Websites Chapter 6: Writing Reports in R Markdown Chapter 7: Using Parameters to Automate Reports Chapter 8: Making Slideshows with xarigan Chapter 9: Building Websites with distill Chapter 10: Reproducible Reporting with Quarto Part 3: Automation and Collaboration Chapter 11: Accessing Online Data Chapter 12: Creating Your Own R Packages

Reviews

“Long overdue in the R ecosystem.” —Oscar Baruffa, Big Book of R “A great resource for anyone wishing to learn R without the intimidating jargon that normally comes with software books.” —Cara Thompson, Data Visualization Consultant at Building Stories with Data “David has captured some of the most compelling ways to use R for data visualization and maps, automation, reporting, and building websites.” —Tom Mock, Product Manager at Posit “An easy-to-read source of exciting case studies, relevant code snippets, and helpful explanations—no matter if you're an experienced programmer or not.” —Cédric Scherer, data visualization and information graphics designer “Demonstrates how succinctly R can be used to rapidly solve non-statistics problems.” —Bob Rudis , author of Data-Driven Security: Analysis, Visualization and Dashboards and VP of Data Science, Security Research & Detection Engineering at GreyNoise Intelligence “David Keyes delivers a comprehensive and approachable guide to R programming in R for the Rest of Us. His expertise shines through in every chapter, making complex concepts understandable and applicable. This book is a fantastic and invaluable resource for anyone working with or aspiring to work with data, regardless of their background. Highly recommended.”  —Gabriela de Queiroz, Director of AI, Microsoft; Founder of R-Ladies and AI Inclusive


“Long overdue in the R ecosystem.” —Oscar Baruffa, Big Book of R “A great resource for anyone wishing to learn R without the intimidating jargon that normally comes with software books.” —Cara Thompson, Data Visualization Consultant at Building Stories with Data “David has captured some of the most compelling ways to use R for data visualization and maps, automation, reporting, and building websites.” —Tom Mock, Product Manager at Posit “An easy-to-read source of exciting case studies, relevant code snippets, and helpful explanations—no matter if you're an experienced programmer or not.” —Cédric Scherer, data visualization and information graphics designer “Demonstrates how succinctly R can be used to rapidly solve non-statistics problems.” —Bob Rudis , author of Data-Driven Security: Analysis, Visualization and Dashboards and VP of Data Science, Security Research & Detection Engineering at GreyNoise Intelligence


Author Information

David Keyes is the founder and CEO of R for the Rest of Us (rfortherestofus.com), which offers online courses, workshops, and custom training sessions that help organizations take control of their data. He has a PhD in anthropology from UC San Diego, as well as a master's degree in education from Ohio State, and has dedicated his professional life to teaching people to embrace R as the most powerful tool for data analysis and visualization.

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