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ShowMyData's mission is to empower you to transform data into knowledge, whether that data is from...
yourself - exercise; sleep; screen-time
your research - multi-million dollar clinical trial; high school science fair project
your workplace - job satisfaction; website traffic
your classroom - physics lab; quiz scores
your world - health; entertainment; money; environment
We do this by putting simple, elegant, powerful, best-practice data visualization tools at your fingertips in the form of free, easy-to-use, web apps. Simply copy-and-paste your data, adjust a few options, and, voilá, you have your graph. Then download that graph in a high-resolution form that is suitable for detailed examination, presentation, or publication.
Our core design principle, illustrated by the graphs just below, is simple yet surprisingly uncommon: Show the data (all of it). Not just means (bar graphs), selected percentiles (boxplots), or even the shapes of distributions (violin plots, bean plots). Every data point. Because the clearest thinking and the deepest insights must inevitably come from seeing what is really there.
Example graphs: Daily minimum temperatures (°F) for every day in 2018 in two U.S. cities
The principle that the best graphs show individual data points is not new. This principle has been articulated repeatedly over the years, perhaps most famously by Edward Tufte, who began his classic 1983 book, "The Visual Display of Quantitative Information," with the statement: "Show the data." Yet to show the data well - without obscuring some data points behind others, without losing the forest for the trees - requires carefully-designed tools such as the ones we provide here.
We want to hear from you. Tell us how you use these apps; what you like about them; what you dislike about them; how to make them better. You may directly email ShowMyData's creator and principal investigator, Prof. Jeremy Wilmer, at jwilmer [at] wellesley [dot] edu. Your input helps us to maximize ShowMyData’s value as a public resource for answering questions, big or small, mundane or world-changing, with data!
Compare and contrast different groups of individuals or measurements.
Correlate different measurements taken from the same individuals.
Here is a video that introduces an earlier, somewhat less powerful version of Correlation: 2 measures
Compare and contrast different measurements taken from the same individuals.
Principal Investigator: Jeremy Wilmer
Development team: Sara Cooper, June Kim, Rachel Wulff
As a convenience, we have posted here a higher-bandwidth version of a flexible and pedagogically useful ggplot GUI that is also available in lower-bandwidth form here, with original code here and updated code here.
A new and improved independent groups app is on its way; in the meantime, the current version is adapted with thanks from BoxPlotR project.
All apps are currently offered as beta versions while they are being actively developed and enhanced.