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Graph your data in 30 seconds...
  • Click on an app's button below to load it.
  • Copy-paste data from spreadsheet (example data here).
  • A default graph appears in a few seconds.
  • Adjust graph via menu options. 
  • Click button to download in high-resolution form. 
histograms.png

Plot groups:

Compare and contrast different groups of individuals or measurements. 

groups.png

Plot repeated measures:

Compare and contrast different measurements taken from the same individuals. 

onerepeat.png
multiplerepeats.png
onecorrelation.png
multiplecorrelations.png

Plot associations:

Correlate different measurements taken from the same individuals. 

Gallery and Features...

Example graphs below were created by copy-pasting two or more columns of this google sheet  — daily minimum temperatures (°F) across cities for every day in 2018 — into the corresponding app above.

Screen Shot 2021-04-02 at 12.45.16 PM.pn

INDEPENDENT

GROUPS

​Features:

  • Plots Sinaplots (info)

  • Supports one-way and two-way factorial design via color or small multiiples.

  • Can change graph orientation, switching x-axis with y-axis, via single click. 

  • Can tilt group names for visibility. 

RM.png

REPEATED MEASURES:

2 measures

Features:

  • Plots 45 degree x=y line so that each dot's vertical (or horizontal) distance from that line equals the difference between the two measures. 

  • Plots means and medians. 

  • Can provide labels for each datapoint. 

  • Single-click percentile rank-ordering for outlier-robust analysis. 

Corr.png

CORRELATION:

2 measures

Features:

  • Drawn so physical slope of least-squares line exactly equals Pearson correlation coefficient. 

  • Can draw many types of curves.

  • Can visually show and download residuals for any drawn curve. 

  • Single-click percentile rank-ordering for outlier-robust analysis and visualization of Spearman correlation. 

Hist.png

HISTOGRAMS

Features:

  • Plots raincloud plots (info).

  • Can show quantiles.

MultRM.png

REPEATED MEASURES:

multiple measures

​Features:​

  • Same approach as REPEATED MEASURES: 2 measures plus...

  • Plots all pairwise comparisons among multiple measures (measure names shown in gray boxes). 

  • Can show data above gray boxes, below, or both. 

  • Can show raw or standardized differences, along with confidence intervals and N, above gray boxes, below, or both.

MultCorrs.png

CORRELATION:

multiple measures

​Features:

  • Same approach as CORRELATION: 2 measures plus...

  • Plots all pairwise relationships among multiple measures (measure names shown in gray boxes). 

  • Can show data above gray boxes, below, or both. 

  • Can show raw or standardized differences, along with confidence intervals and N, above gray boxes, below, or both.

  • Can color the scatterplots according to the strength of the correlation (aka conditional formatting). 

Most/All apps

​Features:​​​​

  • Simple menu-driven options.

  • Enhance visibility of individual datapoints (via jitter, opacity, dot type). 

  • High-resolution download as png or pdf. 

  • Default dataset pre-loaded for easy demonstrations. 

  • Demonstration temperatures dataset provided (here). 

  • Immediate plotting of best-practice graph via simple copy-paste of data from spreadsheet. 

  • Capable of plotting data with thousands of rows. 

  • Can adjust plot dimensions and labels. 

  • Multiple other features and options, explore for yourself...

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Our mission...

ShowMyData's mission is to put 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 gallery above, 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. 

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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 founder 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! 

How to cite ShowMyData when I use it in my work?
Wilmer, J. B. (2022). Data Visualization Web Apps (Version 2.0) [Web Apps]. ShowMyData. https://showmydata.org

 

 

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Founder and Principal Investigator: Prof. Jeremy Wilmer

Student contributors: Sara Cooper, June Kim, Rachel Wulff

Bonus apps and features:​​​

  • See variations on the Independent Groups app that: (1) create data from summary statistics here, (2) compute a quick d value (difference in standard deviation units) here, (3) create data from a d value here, (4) incorporate bar/line graphs here. 

  • See a high-bandwidth version of a flexible and pedagogically useful ggplot GUI here that is also available in lower-bandwidth form here, with original code here and updated code here. 

  • See an alpha version of an app to show proportions here that uses ESCI. 

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