Data Visualization: A Practical Introduction. Questo articolo non è disponibile.
Lingua: inglese
Editore: Princeton University Press, 2018
- Brossura
- Usato

Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
Venditore AbeBooks dal 2 luglio 2009
Condizione: Usato - Molto buono
EUR 11,45
Descrizione dell’articolo da parte del venditore
May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Codice articolo G0691181624I4N00
- Titolo
- Data Visualization: A Practical Introduction
- Autore
- Healy, Kieran
- Editore
- Princeton University Press
- Anno di pubblicazione
- 2018
- Condizione
- Very Good
- Sovraccoperta
- No Jacket
- Rilegatura
- Paperback
- Lingua
- inglese
- ISBN 10
- 0691181624
- ISBN 13
- 9780691181622
- Peso dell'articolo
- 1,6 libbre
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
"Riassunto" può appartenere a un’altra edizione di questo titolo.
Informazioni sull’autore
"Descrizione articolo" può appartenere a un’altra edizione di questo titolo.