Week 2: Other Plots to Level Up Your Data Visualizations

Stat 431

Time Estimates:
     Videos: 0 min
     Readings: 15 min
     Activities: 0 min
     Check-ins: 1

Beyond the Basics of Data Visualization

Historically, there have been 5 plot types that are considered basic or foundational:

  1. Histograms
  2. Boxplots
  3. Barcharts
  4. Scatterplots
  5. Line graphs (or time series plots)

We are of the opinion that line graphs are really just scatterplots with a little extra definition, but acknowledge the first four as core plot types.

While you may have never been explicitly told these are the basic plot types, hopefully this list is not surprising to you. It’s likely the case that, similar to the normal distribution, you knew about and were using these before you even knew their names…possibly through Excel or something back before you had taken any statistics coursework.

But then once you hit your first statistics class, these were the first official plot types you added to your data visualization tool belt. Strangely, there has probably been a disconnect between this short introduction to plotting and every other data visualization you’ve ever seen. Whenever I see a new graphic containing data I find myself wondering the following things:

  • How do I create that graphic myself?
  • Does that graphic or plot type have a name, or what would I call it?
  • How reproducible is the graphic? How dependent on the data is the graphic?
  • Where would I have learned about creating this graphic and where can I go to find out more?

…and then we found it!

From Data to Visualization

This site is not necessarily exhaustive, but provides a fan-freaking-tastic guide to a plethora of different data visualizations and situations when they’d be most useful:

Required Reading: Data To Viz

Note that not only does this site give you a wonderful flowchart for determining which graphs are likely most appropriate for your data, but also gives information about the code to generate those visualizations as well!

Check-In 1: Data Visualization Preparation

Datasets can contain many variables of different types. Just because variables of certain types exist in your dataset does not mean you will be visualizing all of them. It’s still up to you/us to explore and decide on what story we’re going to tell with our data.

  1. Assuming we’ve decided to visualize one of the categorical variables in our dataset, which of the following is a plot type we could use that’s not in the core listed above:
  • Violin Plot
  • Treemap
  • Bubble Plot
  • Stream Graph
  1. What package does this site suggest for creating interactive maps in R?
  • ggmap
  • maps
  • leaflet
  • mapdata

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