Pro Data Visualization using R and JavaScript [Barker 2013-06-17].pdf

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Contents at a Glance
About the Author �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½xiii
About the Technical Reviewer �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½
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Acknowledgments �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½
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Chapter 1: Background �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½1
Chapter 2: R Language Primer �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½25
Chapter 3: A Deeper Dive into R �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½47
Chapter 4: Data Visualization with D3 �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½65
Chapter 5: Visualizing Spatial Data from Access Logs �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½85
Chapter 6: Visualizing Data Over Time �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½111
Chapter 7: Bar Charts �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½133
Chapter 8: Correlation Analysis with Scatter Plots �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½157
Chapter 9: Visualizing the Balance of Delivery and Quality with
Parallel Coordinates �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½177
Index �½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½�½193
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Chapter 1
Background
There is a new concept emerging in the field of web development: using data visualizations as communication tools.
This concept is something that is already well established in other fields and departments. At the company where
you work, your finance department probably uses data visualizations to represent fiscal information both internally
and externally; just take a look at the quarterly earnings reports for almost any publicly traded company. They are
full of charts to show revenue by quarter, or year over year earnings, or a plethora of other historic financial data.
All are designed to show lots and lots of data points, potentially pages and pages of data points, in a single easily
digestible graphic.
Compare the bar chart in Google’s quarterly earnings report from back in 2007 (see Figure
1-1)
to a subset of the
data it is based on in tabular format (see Figure
1-2).
Figure 1-1.
Google Q4 2007 quarterly revenue shown in a bar chart
1
Chapter 1
BaCkground
Figure 1-2.
Similar earnings data in tabular form
The bar chart is imminently more readable. We can clearly see by the shape of it that earnings are up and
have been steadily going up each quarter. By the color-coding, we can see the sources of the earnings; and with the
annotations, we can see both the precise numbers that those color-coding represent and what the year over year
percentages are.
With the tabular data, you have to read labels on the left, line up the data on the right with those labels, do your
own aggregation and comparison, and draw your own conclusions. There is a lot more upfront work needed to take
in the tabular data, and there exists the very real possibility of your audience either not understanding the data
(thus creating their own incorrect story around the data) or tuning out completely because of the sheer amount of
work needed to take in the information.
It’s not just the Finance department that uses visualizations to communicate dense amounts of data. Maybe your
Operations department uses charts to communicate server uptime, or your Customer Support department uses graphs
to show call volume. Whatever the case, it’s about time Engineering and Web Development got on board with this.
As a department, group, and industry we have a huge amount of relevant data that is important for us to first be
aware of so that we can refine and improve what we do; but also to communicate out to our stakeholders,
to demonstrate our successes or validate resource needs, or to plan tactical roadmaps for the coming year.
Before we can do this, we need to understand what we are doing. We need to understand what data visualizations
are, a general idea of their history, when to use them, and how to use them both technically and ethically.
What Is Data Visualization?
OK, so what exactly is data visualization? Data visualization is the art and practice of gathering, analyzing, and
graphically representing empirical information. They are sometimes called
information graphics,
or even just
charts
and
graphs.
Whatever you call it, the goal of visualizing data is to tell the story in the data. Telling the story is
predicated on understanding the data at a very deep level, and gathering insight from comparisons of data points in
the numbers.
There exists syntax for crafting data visualizations, patterns in the form of charts that have an immediately known
context. We devote a chapter to each of the significant chart types later in the book.
Time Series Charts
Time series charts
show changes over time. See Figure
1-3
for a time series chart that shows the weighted popularity
of the keyword “Data Visualization” from Google Trends (http://www.google.com/trends/).
2
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