Comparison of the number of observed vs expected responses in the DVS 2020 Census per country based on population.

Comparison of percentages of respondents who have indicated a given job frustration grouped into years of different experience.

Chart and map of the usage and relationship of data visualization tools in different regions.

Information on Purdue Libraries open access publication fund.

Likert is an R package designed to help analyzing and visualizing Likert type items. It has been developped by Jason Bryer and Kim Speerschneider.

This barplot comes from the demo page and has been sent by Carlos Ortega.

It allows to analyse the reading attitudes from a panel of people. Each line represents a question. The barplot explains the feeling of people concerning this question.

# library
library(likert) 
 
# Use a provided dataset
data(pisaitems) 
items28 <- pisaitems[, substr(names(pisaitems), 1, 5) == "ST24Q"] 
 
# Build plot
p <- likert(items28) 
plot(p)

Graphs of how groups of different experience levels differ in software use, job frustrations, and more.

Graphic of circles to visualize ways people learn data visualizations.

if you don't pay for an account you have to give credit somewhere on the infographic.

stock photos some do cost. Should choose high resolution.

build a color scheme Color brewer

use for study orientation.

study recruitment

study timeline

posters

This checklist is meant to be used as a diagnostic guide to identify elements of evaluation reports that could be enhanced using graphic design best practices and/or the assistance of a graphic design expert. Suggestions are best suited for those using standard Microsoft Word software.

This checklist is meant to be used as a guide for the development of high impact data visualizations. Rate each aspect of the data visualization by circling the most appropriate number, where 2 points means the guideline was fully met, 1 means it was partially met, and 0 means it was not met at all. n/a should not be used frequently, but reserved for when the guideline truly does not apply. For example, a pie chart has no axes lines or tick marks to rate. If the guidelines has been broken intentionally to make a point, rate it n/a and deduct those points from the total possible. Refer to the Data Visualization Anatomy Chart on the last page for guidance on vocabulary and the Resources at the end for more details.   by Stephanie Evergreen & Ann K. Emery May 2016

Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate data findings. This comprehensive how-to guide functions as a set of blueprints—supported by research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. Delivered in Evergreen’s humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for making the chosen graph in Excel. 

Link to pinterest board on Awesome Annual Reports

Think outside the box with these 11 visual dashboard ideas from SAS.

Compelling Infographic Templates

Library of Infographic Templates

Free Infographic Templates and Designs