The Art of Data Visualization with ggplot2 : The TidyTuesday Cookbook
Book Details
Format
Paperback / Softback
ISBN-10
1032766239
ISBN-13
9781032766232
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Sep 21st, 2026
Print length
392 Pages
Ksh 10,250.00
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The visualizations in this book are not necessarily always the most effective choice of visualization for the data and relationship shown. Rather, this book aims to show you examples of the end-to-end process of creating data visualizations, with a focus on the technical details of building them in R.
Data visualization can be a very effective and efficient means of communicating information. Visualizing data typically serves one of two purposes: (i) as part of exploratory analysis to help uncover discrepancies in data and identify interesting relationships to measure; or (ii) to communicate key insights and messages to a broader audience. The case-study nature of this book means it covers both aspects, though it focuses mostly on the second. Choosing an appropriate type of visualization and making careful choices about design can clarify the message it is meant to convey to a reader. The visualizations in this book are not necessarily always the most effective choice of visualization for the data and relationship shown. Rather, this book aims to show you examples of the end-to-end process of creating data visualizations, with a focus on the technical details of building them in R. This book is primarily aimed at those who wish to develop their data visualization skills in R. Readers of this book may find a basic knowledge of R, more specifically of the tidyverse ecosystem, useful - although all code used in examples is fully explained. Readers do not need to be experienced in ggplot2, though this book will also be of interest to those who are. This book will also be of interest to those who are already familiar with R (including ggplot2), and wish to develop their skills in designing data visualizations further. It will also interest those who already design data visualizations using other tools, and want to learn how to do the equivalent in R.
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