Exploring Data Visually - Data Points: Visualization That Means Something - page 481

more adventurous, you snorkel or go deep-sea diving. Even then you don't
swim the entire ocean. You explore a little bit at a time, and what you learn
during one dive carries over to the next. People drown in the ocean, but when
you drown in data, you still get more chances to learn and try again.

Note: Early exploration of a dataset can be
overwhelming, because you don't know where
to start. Ask questions about the data and let
your curiosities guide you.

To start, ask yourself what you want to know about the data.
Your answer doesn't need to be complex or profound. Just
make it less vague than, “I want to know what the data looks
like.” The more specific you are the more direction you get.
Maybe you want to know the best or worst thing (such as a
country, sports team, or school) in your data, so you explore
rankings, and if you have multiple variables, you decide what makes some-
thing good and something bad. If you have time series data, you might want
to know if something has improved or gotten worse over the past decade.

For example, journalist Tim De Chant explores world population densities, as
shown in Figure 4-2, and was curious how large a city might be if everyone
who lived in the world had the same amount of space. A straightforward
method could be to directly map population density around the world, but
De Chant put it into a more relatable perspective.

When you ask questions about your data, you give yourself a place to start,
and if you're lucky, as you investigate, you'll come up with more questions,
and then you dig into those. Coming up with and answering potential ques-
tions a user might have while you explore also provides focus and purpose,
and helps farther along in the design process when you make graphics for a
wider audience.

WHAT VISUALIZATION METHODS SHOULD YOU USE?

As you saw in the previous chapter, there are many chart options and com-
binations of visual cues to choose from. It's easy to obsess over picking the
right chart for your data, but during the early stages of exploration, it's more
important to see your data from different angles and to drill down to what
matters for your project.

Make multiple charts, compare all your variables, and see if there are interesting
bits that are worth a closer look. Look at your data as a whole and then zoom
in on categories and individual data points.