What is Data Visualization?

Data Visualization is the online genre of turning information into charts, infographics, and diagrams, spanning serious journalism as well as comedy pieces mocking bad statistics[1].

Where did Data Visualization come from?

The discipline dates back to 17th-century statistics[4], but the online dataviz community formed around Reddit subs starting with r/visualization on March 25, 2008[3].

What does Data Visualization mean?

It means presenting data through visual formats like charts, dot plots, and infographics instead of raw tables of numbers, so patterns are easier to spot[4].

How do you use Data Visualization?

Pick a chart type that fits the data, label the axes clearly, and cite your source; r/dataisbeautiful conventions often include posting the underlying data and code in the comments[2].

Is Data Visualization still popular?

The r/dataisbeautiful sub stayed one of Reddit's biggest data communities after its February 2012 launch[2], and Xkcd's data-driven strips kept the humor genre alive across the 2010s[7].

Data Visualization

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Data Visualization is the online genre of charts, infographics, and dot plots covering everything from serious journalism to comedy pieces about bad statistics. Its internet-era community formed on Reddit in 2008 and hit critical mass with r/dataisbeautiful in 2012.

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Overview

Data Visualization refers to turning numbers and information into charts, diagrams, and infographics that can be read at a glance. The practice predates the internet by centuries4, but the online dataviz community coalesced through Reddit subs and dedicated blogs starting in 20083. Online it shows up as infographics, flowcharts, dot plots, choropleth maps, and interactive dashboards.

The style ranges from serious analytical journalism to comedy pieces mocking bad statistics. The webcomic Xkcd popularized the humorous end with strips like a September 27, 2010 dot plot mapping which adjectives get intensified with obscenities6, and a November 21, 2011 graphic charting money amounts from pocket change to national GDPs7. Statistician Tyler Vigen pushed the joke further in 2014 with Spurious Correlations, a blog of charts pairing wildly unrelated statistics that happen to track each other1.

How It Spread

The genre broke into mainstream awareness in July 2010, when data journalist David McCandless delivered a TED Talk titled 'The Beauty of Data Visualization'10. In April 2011, Visual.ly opened as a community platform where users could build their own infographics and charts from templates8.

The Reddit tipping point came on February 14, 2012, with the launch of r/dataisbeautiful, which became the default home for submitted charts and analysis threads2. Xkcd kept feeding the audience data-driven strips throughout the early 2010s6, and Tyler Vigen's 2014 Spurious Correlations blog turned correlation-versus-causation into a running gag by pairing US cheese consumption with bedsheet strangulation deaths and similar absurdities1.

By the mid-2010s dataviz was wired into online news, sports commentary, and social media discourse, with r/dataisbeautiful growing into one of Reddit's largest data-focused subs2.

How to Use This Meme

A typical dataviz post pairs a chart type suited to the data (bar for categories, line for time series, scatter for correlations, choropleth for geography) with a clear title and labeled axes. Community conventions on r/dataisbeautiful often include naming the data source in the post title and dropping the underlying data or plotting code into the comments2. Comedy dataviz in the Xkcd or Spurious Correlations mode typically flips the format by charting something absurd or trivial with fully serious axes and legends1.

Frequently Asked Questions

References (10)