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# The art and science of data visualization
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## Sponsor: The Zuri Group
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<img src=assets/img/zuri.png style="width:700px">
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## The John Snow map
<img src=assets/img/snow.jpg style="width:600px">
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## Snow, with modern tools
<iframe src="http://walkerke.github.io/maps/snow_cholera.html" height="575" width="850" scrolling="no" frameBorder="0"></iframe>
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## Why visualize data?
* Visualization can _generate hypotheses_, _reveal insights_, and _communicate information_
* Visualizations can be _exploratory_ or _explanatory_ - and there is not always a clear difference between the two!
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## Static charts
<img src=assets/img/stacked.png style="width: 750px">
Data source: United Nations
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## Interactive charts
<iframe src="http://bl.ocks.org/walkerke/raw/d21e1e6daf487943468f/" width="825" height="500" seamless frameborder = "0"></iframe>
<span class="footnote">Data source: United Nations</span>
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## Exploratory vs. explanatory visualization
<iframe width='100%' height='600' frameborder='0' src='http://kwalkertcu.cartodb.com/viz/dfe2d3b2-a0da-11e4-a315-0e4fddd5de28/embed_map' allowfullscreen webkitallowfullscreen mozallowfullscreen oallowfullscreen msallowfullscreen></iframe>
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## The data analysis process (H. Wickham)
<img src=assets/img/analysis.png style="width: 850px">
Source: Alan Smith
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## Anscombe's Quartet
<iframe src="http://bl.ocks.org/alansmithy/raw/07218980d8bac3689104/" height="500" width="800" scrolling="no" frameBorder="0"></iframe>
<span class="footnote">Source: [Alan Smith](http://bl.ocks.org/alansmithy/07218980d8bac3689104)</span>
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## Visualization: an art and science
* Practitioners must strike a balance between the _art_ and _science_ of data visualization
* This means that visualizations must both:
+ Be visually appealing
+ Maintain fidelity to the structure of the data
* Accomplishing both can be a challenge!
Sequential
Diverging
Qualitative
When in doubt, consult ColorBrewer (http://colorbrewer2.org/)
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## Color
* __Sequential__
<img src=assets/img/sequential.PNG style="width: 600px">
* __Diverging__
<img src=assets/img/diverging.PNG style="width: 600px">
* __Qualitative__
<img src=assets/img/qualitative.PNG style="width: 600px">
When in doubt, consult ColorBrewer (<http://colorbrewer2.org/>)
Source: Kirk Goldsberry/Grantland.com
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## Good use of color
<img src=assets/img/curry.jpg style="width: 700px">
<span class="footnote">Source: Kirk Goldsberry/Grantland.com</span>
Source: Kenneth Field/Cartonerd
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## Poor use of color
<img src=assets/img/badmap.png style="width: 800px">
<span class="footnote">Source: Kenneth Field/[Cartonerd](http://cartonerd.blogspot.com)</span>
Source: FlowingData.com
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## Inaccurate representation of data
<img src=assets/img/foxbar.jpeg style="width: 800px">
<span class="footnote">Source: [FlowingData.com](http://flowingdata.com/2014/04/04/fox-news-bar-chart-gets-it-wrong/)</span>
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## Where to start the Y-axis?
<iframe src="http://plot.ly/~walkerke/57" width="800" height="500" seamless scrolling="no" frameBorder="0"></iframe>
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## What is wrong with this chart?
<img src=assets/img/3dpie.png style="width: 950px">
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## Alternative representation
<img src=assets/img/ls2014.png style="width: 800px">
Source: XKCD
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## Correlation means...
<img src=http://imgs.xkcd.com/comics/correlation.png style="width: 800px">
<span class="footnote">Source: [XKCD](http://xkcd.com/552/)</span>
Source: tylervigen.com
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## Spurious correlations
<img src=assets/img/spurious.png style="width: 800px">
<span class="footnote">Source: [tylervigen.com](http://www.tylervigen.com/view_correlation?id=1703)</span>
Possible questions to address:
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## Visualization for development
Possible questions to address:
* Where are our donors coming from - and do we have people in the right places?
* Are there relationships between donor characteristics/activities and donor volume?
* What relationships/networks exist between donors?
For (many) data visualization tools, pick two of the following three:
However, there are many different tools available for different use cases
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## Data visualization tools
For (many) data visualization tools, pick __two__ of the following three:
* Free to use
* Data & visualizations stored on your own machine or server
* Gentle learning curve
However, there are many different tools available for different use cases
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## Tool demonstration: Tableau
<img src=http://upload.wikimedia.org/wikipedia/commons/0/01/Tableau_Software_Logo_Small.png style="width: 800px">
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## Tool demonstration: RStudio
<img src=http://www.rstudio.com/wp-content/uploads/2014/07/RStudio-Logo-Blue-Gradient.png style="width: 800px">
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## Questions?
* Web: http://personal.tcu.edu/kylewalker
* Email: kyle.walker@tcu.edu
* Link to this presentation: http://personal.tcu.edu/kylewalker/big12dev/
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