Cargando…

Better Data Visualizations : A Guide for Scholars, Researchers, and Wonks /

Now more than ever, content must be visual if it is to travel far. Readers everywhere are overwhelmed with a flow of data, news, and text. Visuals can cut through the noise and make it easier for readers to recognize and recall information. Yet many researchers were never taught how to present their...

Descripción completa

Detalles Bibliográficos
Autor principal: Schwabish, Jonathan (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Columbia University Press, [2021]
Temas:
Acceso en línea:Texto completo
Texto completo

MARC

LEADER 00000nam a22000005i 4500
001 DEGRUYTERUP_9780231550154
003 DE-B1597
005 20221201113901.0
006 m|||||o||d||||||||
007 cr || ||||||||
008 221201t20212021nyu fo d z eng d
020 |a 9780231550154 
024 7 |a 10.7312/schw19310  |2 doi 
035 |a (DE-B1597)566437 
040 |a DE-B1597  |b eng  |c DE-B1597  |e rda 
041 0 |a eng 
044 |a nyu  |c US-NY 
072 7 |a COM089000  |2 bisacsh 
082 0 4 |a 001.4/226  |2 23 
084 |a ST 320  |2 rvk  |0 (DE-625)rvk/143657: 
100 1 |a Schwabish, Jonathan,   |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Better Data Visualizations :  |b A Guide for Scholars, Researchers, and Wonks /  |c Jonathan Schwabish. 
264 1 |a New York, NY :   |b Columbia University Press,   |c [2021] 
264 4 |c ©2021 
300 |a 1 online resource :  |b 533 color charts, graphs, and illustrations. 1 table 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 0 |t Frontmatter --   |t CONTENTS --   |t INTRODUCTION --   |t PART ONE: PRINCIPLES OF DATA VISUALIZATION --   |t 1. VISUAL PROCESSING AND PERCEPTUAL RANKINGS --   |t 2. FIVE GUIDELINES FOR BETTER DATA VISUALIZATIONS --   |t 3. FORM AND FUNCTION: LET YOUR AUDIENCE'S NEEDS DRIVE YOUR DATA VISUALIZATION CHOICES --   |t PART TWO: CHART TYPES --   |t 4. COMPARING CATEGORIES --   |t 5. TIME --   |t 6. DISTRIBUTION --   |t 7. GEOSPATIAL --   |t 8. RELATIONSHIP --   |t 9. PART-TO-HOLE --   |t 10. QUALITATIVE --   |t 11. TABLES --   |t PART THREE: DESIGNING AND REDESIGNING YOUR VISUAL --   |t 12. DEVELOPING A DATA VISUALIZATION STYLE GUIDE --   |t 13. REDESIGNS --   |t CONCLUSION --   |t APPENDIX 1: DATA VISUALIZATION TOOLS --   |t APPENDIX 2: FURTHER READING AND RESOURCES --   |t Acknowledgments --   |t References --   |t Index 
506 0 |a restricted access  |u http://purl.org/coar/access_right/c_16ec  |f online access with authorization  |2 star 
520 |a Now more than ever, content must be visual if it is to travel far. Readers everywhere are overwhelmed with a flow of data, news, and text. Visuals can cut through the noise and make it easier for readers to recognize and recall information. Yet many researchers were never taught how to present their work visually. This book details essential strategies to create more effective data visualizations. Jonathan Schwabish walks readers through the steps of creating better graphs and how to move beyond simple line, bar, and pie charts. Through more than five hundred examples, he demonstrates the do's and don'ts of data visualization, the principles of visual perception, and how to make subjective style decisions around a chart's design. Schwabish surveys more than eighty visualization types, from histograms to horizon charts, ridgeline plots to choropleth maps, and explains how each has its place in the visual toolkit. It might seem intimidating, but everyone can learn how to create compelling, effective data visualizations. This book will guide you as you define your audience and goals, choose the graph that best fits for your data, and clearly communicate your message. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Dez 2022) 
650 0 |a Information visualization. 
650 0 |a Visual analytics. 
650 7 |a COMPUTERS / Data Visualization.  |2 bisacsh 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t Columbia University Press Complete eBook-Package 2021  |z 9783110739077 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t EBOOK PACKAGE COMPLETE 2021 English  |z 9783110754001 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t EBOOK PACKAGE COMPLETE 2021  |z 9783110753776  |o ZDB-23-DGG 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t EBOOK PACKAGE Engineering, Computer Sciences 2021 English  |z 9783110754070 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t EBOOK PACKAGE Engineering, Computer Sciences 2021  |z 9783110753837  |o ZDB-23-DEI 
856 4 0 |u https://doi.uam.elogim.com/10.7312/schw19310  |z Texto completo 
856 4 0 |u https://degruyter.uam.elogim.com/isbn/9780231550154  |z Texto completo 
912 |a 978-3-11-073907-7 Columbia University Press Complete eBook-Package 2021  |b 2021 
912 |a 978-3-11-075400-1 EBOOK PACKAGE COMPLETE 2021 English  |b 2021 
912 |a 978-3-11-075407-0 EBOOK PACKAGE Engineering, Computer Sciences 2021 English  |b 2021 
912 |a EBA_CL_CHCOMSGSEN 
912 |a EBA_EBKALL 
912 |a EBA_ECL_CHCOMSGSEN 
912 |a EBA_EEBKALL 
912 |a EBA_ESTMALL 
912 |a EBA_PPALL 
912 |a EBA_STMALL 
912 |a GBV-deGruyter-alles 
912 |a PDA12STME 
912 |a PDA13ENGE 
912 |a PDA18STMEE 
912 |a PDA5EBK 
912 |a ZDB-23-DEI  |b 2021 
912 |a ZDB-23-DGG  |b 2021