Kieran Healy - Data Visualization: A Practical Introduction [2018, PDF, ENG] torrent

Книги и журналы » Компьютерная литература » Программирование (книги)

Data Visualization: A Practical Introduction

Год издания: 2018
Автор: Kieran Healy
Жанр или тематика: Python, Data Analysis, Visualizatoin

Издательство: Princeton University Press; 1 edition
ISBN: 9780691181622
Язык: Английский

Формат: PDF
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 296

Описание: An accessible primer on how to create effective graphics from data

This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.

Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.

Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. • Provides hands-on instruction using R and ggplot2
• Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent
• Includes a library of data sets, code, and functions
[spoiler="Примеры страниц"]

[/spoiler]
[spoiler="Оглавление"]
Table of Contents Look at Data
Get Started
Make a Plot
Show the Right Numbers
Graph Tables, Add Labels, Make Notes
Work with Models
Draw Maps
Refine Your Plots
Appendix
[/spoiler]