This copy has clearly been enjoyed� expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.

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Dati bibliografici

Titolo

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

Editore

Columbia University Press

Data di pubblicazione

2021

Lingua

Inglese

ISBN 10

0231193114

ISBN 13

9780231193115

Rilegatura

Brossura

Condizione

acceptable

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Descrizione articolo

Riassunto

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.

Informazioni sull?autore

Jonathan Schwabish is an economist and writer, teacher, and creator of policy-relevant data visualizations. He helps nonprofits, research institutions, and governments at all levels improve how they communicate their work and findings to their colleagues, partners, clients, and constituents. He is the author of Better Presentations: A Guide for Scholars, Researchers, and Wonks (Columbia, 2016).

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