Dianne Finch, visiting assistant professor of communications at Elon University, presented "Data Visualization: A Hands-On Primer for Business Journalists." This training took place during the Society of American Business Editors and Writers' Spring Conference in Phoenix, March 27, 2014. Sponsored by the Donald W. Reynolds National Center for Business Journalism, this hands-on workshop was geared toward journalists with little to no experience in creating data visualizations. For more information about training for journalists, please visit http://businessjournalism.org.

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Data Visualization
Dianne M. Finch
Elon University
@dmfinch

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› @dmfinch / #SABEWDataViz
› I will tweet URLs that you’ll need
› Or show them on screen
› Sign in to geocommons.com
› Sign in to Google. Go to Drive.
› Make sure you have Google Fusion.

3. What We’ll Cover
› Data and Encoding Overview
› Charts and Junk Charts
› Google Fusion – New Network Graph Tool
› Map
› Geocommons – Lat/Long and Map
› Custom Icons
› Google API – A timeline
› Google API – How to manipulate code
without knowing code.
› Other stuff if time!

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8. Data-ink Ratio
› More data – less ink!
› Save the ink for infographics and text –
add those to the same web page to help
tell the story!
› See:
› http://www.infovis-wiki.net/index.php/Data-
Ink_Ratio

10. Data – most essential component
› You’ve downloaded a CSV or XLS or JSON.
› Does your data reflect any trends? Any outliers?
› Did you vet your data? Talk to the source? Check for errors?
› Did you look for spelling issues (John Smith and Jon Smith)
› Are there redundant rows? One header row?
› Do you need more data to clarify your story?
› What is the simplest and clearest chart you could use?
› Try using a sketchpad to draw circles, lines, texture, legends.

11. is not Absolute, is variable, is uncertain
needs context
is often biased (politics and agendas)
is often sampled (census)
doesn’t tell a whole story
requires skepticism
is error-prone (humans enter it – and they are
often bored and unfocused)
Data….

12. Data types
› Nominal
› Ordinal
› Quantitative

13. So We Evaluate, filter, clean,
question and attribute our data
SEE: Harvard Business Review

14. Data Cleaning with Excel –
Lynda.com
› Using absolute and relative cell references
Entering data using AutoFill and other techniques
› Restricting input using validation rules
› Sorting worksheet data
› Creating a custom sort order
› Filtering worksheet data
› Introducing Excel formulas and functions
› Adding a formula to a cell
› Introducing arithmetic operators
› Using absolute and relative cell references
› Joining text in cells with concatenation
› Summarizing data using an IF function
› Creating formulas to count cells
› Importing data from comma separated value (CSV) or text files
› Introducing PivotTable reports (all 10 items in this category)

15. Chart design last step – and
there are many choices
› Position along a common scale e.g. scatter plot
› Position on identical but nonaligned scales e.g.
multiple scatter plots
› Length e.g. bar chart
› Angle & Slope (tie) e.g. pie chart
› Area e.g. bubbles
› Volume, density, and color saturation (tie) e.g. heatmap
› Color hue e.g. newsmap

16. A look at the good ones
› Arab Spring
› Simple and Clear
› Google Chart Gallery
› NYT-Nursing Homes
› Flu
› Guns and Games
› Other

17. Google Fusion
• Produce a network graph
• Produce a map
• Embed both in a web page
NOTE: WE DIDN’T HAVE TIME FOR THIS IN THE SESSION. I’VE INCLUDED
THE CSV Fbmutual.csv so that you can try it. Quite easy!

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Find .CSV file to import

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22. SABEW 2014Click red button to create a chart

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Click for network graph

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Set to share publicly

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Change to
“public”
Click “done”

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31. See HTML template
Make a copy!

32. Google API
“Serving” Viz Via Web Pages
Not everything can be run
from local computers

33. Hosted Sites
You will need a web server to place your pages
and images (png, svg, jpg, html)
Today we are using a Bluehost site.
All web servers make files inside “public_html”
available to everyone

34. Sign into: geocommons.com
Yellowdollar.png (you will use my hosted site)
coin_us_dollar.png (you will use my hosted site)
SABEWlist.csv

35. Maps and Layers and Custom
Icons!

36. Google API
› Programming: JavaScript
› Copy/paste without programming
› Tweak using intuitive options

37. Google API
› Programming: JavaScript
› Copy/paste without programming
› Tweak using intuitive options

38. Try this
› Latitude Longitude
› Tableau – take a peak
› Build layers on maps
› Add more custom icons

39. Geocommons Steps to
produce “geocoded” CSV
› Clean your data in Excel
› Save as a CSV
› Upload the file to Geocommons
› Choose to “geocode” - add latitude and
longitude
› Save your new CSV file (download from
Geocommons with new “geo” fields)
› Save your new KML file (it will open in
Google Earth)

40. Geocommons Maps
› Upload CSV to geocommons
› Choose to geocode
› Go through steps. Make sure you add the date on the screen that
has several questions.
› Save your newly uploaded file.
› Choose “Make a Map”
› As we saw in the session – the map shows up with your data.
› Click on the CSV filename on the right to open the “styling” section.
› Change the colors, shapes and tooltips.
› Try adding layers to the map by locating another CSV that you’ve
uploaded. Or – choose one that someone else uploaded, such as
census data on income.
› ***Make sure that you are using data that is trustworthy and vetted
when you use datasets found on Geocommons. You’ll need to look
into it, do some spot checking, or contact the creator. There is a lot
of census data available on Geocommons.