Data Visualization
Brittany Fong | @bfongdata
bfongdata.com
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Tableau Ambassador
DC User Group
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Why data viz?
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Data Viz Tools
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PowerBI
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A History of Data Visualization
1844 The New York Daily Tribune
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1968 New York Times
2012 Five Thirty Eight
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2016 The Upshot
1900 Chicago Tribune
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2013 Periscopic
1901 The Chicago Tribune
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2016 NFL Game Center
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2016 Five Thirty Eight
Question
Data
Audience
Creation
Building a data viz
Start with a question
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What is the purpose/goal of the visualization?
What questions are the visualizations going to answer?
How should people feel?
What data do you have?
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Is there a unique identifier?
What level of detail is the data at?
Do you need to bring in additional data/tables?
What is the quality of the data?
Cater to your audience
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What level of detail do they want to see?
How complex can the visualizations be?
Create a sketch
Pull out a pencil and paper to get the ideas flowing
How will the visualization be viewed? (mobile, print, web)
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Common Data Visualization Graphs
Bar Chart
Used for: Comparing categories
Other variations: stacked bar, nested bar, paired bar, multiple bars
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Line Graph
Used for: Viewing trends over time
Other variations: year over year trends, add trend line
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Scatterplot
Use for: Comparing two measures to see how they relate to each other
Other variations: add trend line, create quadrants
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Histogram
Use for: Viewing the distribution of values
Ex: Most common number of units sold per order (3 and 2)
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Heat Map
Used for: Comparing values by a set color palette
Other Variations: maps
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Cartogram
Used for: Geographically mapping a value by color
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Less common Data Visualization Graphs
Gantt Chart
Used for: Viewing duration over time
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Bump Chart
Used for: Viewing category's rank over time
Other variations: slope chart (comparison from beginning to end)
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Unit Chart
Used for: Viewing overall trends in addition to unit level details
Other variations: scatterplot, dot plot, strip plot
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Bullet Graph
Used for: Comparing two measures
Other variations: Add indicator colors to background
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Data Visualization Best Practices
Why are best practices important?
So we don't end up here!
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viz.wtf
Ease of Understanding
Make the visualization as easy as possible to read and understand
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Axes
Keep axes clear and consistent
Avoid skipping numbers and Always start from 0
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Color
Accessibility - Color Blind (508 Compliant) and make sure your colors have enough contrast (black and white print out)
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Clear Labels
Titles, sub-titles, axes, legends, data source, outliers (if necessary)
Try the 30 second test
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Context
How do I know if this number is good or bad? I need some sort of reference.
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vs
Keep it simple
Don't add colors when it's not necessary
If it doesn't help explain the visual get rid of it
Don't add too many labels
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Check your work
Does the visualization logically make sense? If you must use a pie chart it better add up to 100%
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Use the right graph
Jon Schwabish's Graphic Continuum
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What can I do?
Style Guides with Brand compliant color palettes
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Example Dashboards
Title Text
Lindsey Poulter @datavizlinds
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Marc Soares @marc_soares
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Chantilly Jaggernauth @chanjagg
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Brittany Fong
@bfongdata
Data Visualization Resources
Color palettes
pinterest.com
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colorbrewer2.org
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color.adobe.com
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vischeck.com
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Data wrangling
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Data viz examples and information
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Dear Data (dear-data.com)
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Makeover Monday (http://www.makeovermonday.co.uk/)
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Flowing Data (flowingdata.com)
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The Functional Art (http://www.thefunctionalart.com/)
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Storytelling with Data (http://www.storytellingwithdata.com/gallery/)
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Tableau Public (public.tableau.com)
Data viz resources
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Tableau Website Training Videos
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(https://www.tableau.com/learn/training)
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Tableau Community (forums, knowledge base, white papers)
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https://www.tableau.com/learn/training
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Tableau User Groups (local, internal, and subject specific)
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dctug.com
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Twitter
Visualize your data and influence the world!
Brittany Fong
bfongdata.com
bfongdata@gmail.com
Data Visualization
By bfongdata
Data Visualization
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