introduction to data visualization part 1: tips and...
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Introduction to Data
Visualization Part 1: Developing
Skills
Reed Jones
University at Buffalo
Hosted by ALCTS, Association for Library Collections and Technical Services
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Overview
Design: Things I wanted to know when I started working with data
Chronological
No SQL needed (but it is a good thing to learn)
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What is Data Visualization?
A way of arranging data in a way that makes it easy to understand its significance.
Effective and Efficient
Typically graphical
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Get to know your data
Plan ahead
Unique identifiers
Necessary fields
Goals
Simplify data structures
Check for validation issues
Test, test, and re-test
Get another set of eyes
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Data Cleanup
Constant process
You can always go back to the data
Anticipate where errors occur
Get in the mindset
Create validation rules
Controlled vocabularies
Develop a data entry workflow
Communicate
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Types of Visualizations
Bar Graph
Comparing groups
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Types of Visualizations
Line Graph
Change over time
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Types of Visualizations
Pie Chart
Display parts of a whole
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Types of Visualizations
Scatter Plot
Relationships between two fields
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Types of Visualizations
Spider Graph/Radar Chart
Compare three or more fields
Great for relaying survey data
File:Spider Chart.svg,
2008, photo courtesy
of Ordoon
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Axis X/Y (Columns/Rows)
Most visualizations only need a 2 dimensional representation
General rule:
To get a visualization you need at least one dimension (element) to compare and one thing to
measure
The most frequent use of data visualizations have a dimension (element) on the x axis and
a measure on the y axis
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Measures vs. Dimensions
Dimensions are useful in categorizing your data
Usually qualitative
Can sometimes be numerical
Measures are calculations based on you data
Dimensions can be turned into measures
Sum
Avg
Count
Count (Distinct)
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Calculated Fields
Sometimes we have to go back to the data
Creating calculated fields sometimes makes life easier
Easy to identify the element and reuse
Visualizations process faster when using pre-made fields
Common examples
Time difference
Fiscal Year
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Filters
Now it's time to dig in!
Removes the noisy data
Contains
Equals
Is greater/less than
Begins with
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Groups
Overwhelmed by all the dimensions on your graph?
Grouping fields together into different categories can make data easier to read.
Ex: grouping academic departments into colleges
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Sets
Reusable filters that can be used on other visualizations
Best if filtering one dimension at a time
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Differentiation (Colors, Size, Shapes)
Use these tools with purpose. (not simply an aesthetic choice)
Complimentary to filtering
Think in terms of user interaction
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Labels and Keys
Keep the title short and concise
Each axis is labeled logically
Use as little labeling as possible for your data
Use unit labels (m, $, etc.)
Utilize slicers/pages for the user to interact with
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Let's Try an Example
What is the scan rate of each employee?
Is it impacted by the type of scanner used?
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Tips for When you get Stuck (Which will
Definitely Happen)
Ask, ask and ask some more
Search for the answer online
Forums and video tutorials are great!
Post questions on forums
Take a break
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Helpful Resources
Mr. Excel
Tableau Community
For those adventurous enough to try SQL
Datasets to play with
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Questions