Exercise 3: Visualization Design

Important

Please shutdown your RStudio session when you’re not using it.

In the past several exercises, you’ve typically been given a lot of template code and very specific instructions. This time, we’ll do some of the same tasks, but without the training wheels.

Make your own qmd file, following the Class Standards (especially regarding the YAML header). You may use past exercises as inspiration, but avoid copy and paste except for the text in Class Standards.

Part 1

Replicate this plot, made using the ridership data from the previous exercise. Write one or two sentences about what it tells you.

Have you replicated the plot?
Are all the labels correct?
Have you set the marker size (attribute marker_size) to 3?
Have you set the marker opacity (attribute marker_opacity) to 0.5?
Have you written one or two sentences about what the plot tells you?

Part 2

Make another plot of the same variables as in Part 1, but choose a different mapping of variables to visual cues. Write a sentence about what is now easier, or harder, to see in this plot compared with the previous one.

Have you made a plot with the same variables as Part 1?
Have you chosen a different mapping of variables to visual cues?
Have you stated something that’s easier to see in this plot compared with the previous one?

Part 3

Now use the gapminder data; you may use the data from Plotly Express. The following code chunk also creates some filtered data frames that are needed for the following problems.

gapminder = px.data.gapminder()
just_usa = gapminder.query("country == 'United States'")

countries = [
  "China", "India", "United States",
  "Indonesia", "Brazil", "Pakistan",
  "Bangladesh", "Nigeria", "Japan"]

gapminder_9_countries = gapminder.query("country in @countries")

Make the following plot:

Are your axes labeled?
Does the plot have a title?
Is the line green? (The trace attribute is called line_color.)

Part 4

Make two plots of the gapmind_9_countries data. Both plots should use year, lifeExp, and country, but one should use color for country and the other should use faceting (I suggest making the facets wrap). Compare and contrast the two plots: What is easier to see in one plot compared with the other?

Are your axes labeled?
Do the plots have titles?
Do you have a plot colored by country?
Do you have a plot that’s faceted by country?
Have you stated something that’s easier to see in one plot compared with the other?

Part 5

Replicate the Gapminder “health and wealth” plot – as much as you can.

Markers are sized by pop? (you may want to use size_max to make the largest marker smaller)
Markers are colored by continent?
Animation is by year (animation_frame)?
GDP axis is log-scaled (log_x)?
Life expectancy doesn’t go off the top of the plot (range_y)?
Axes have correct labels?

Here’s what one might look like:

Reflection

At the end of your document, write a sentence or two of your overall reflections on this exercise. You may write whatever you want, but you might perhaps respond to one or two of these questions:

Was anything unclear about this assignment?
How hard was it for you? Where did you get “stuck”?
How long did it take you?
What questions or uncertainties remain?
What skills do you think you’ll need more practice with?
Did you try anything out of curiosity that you weren’t specifically asked to do?

Note

We’ll respond to these reflections in class, but only in an overall sense and only once we’ve had a chance to review them. If you have a question that needs a response, please post it on Perusall.

Submitting

Submit your rendered HTML file to Moodle. (Make sure it renders cleanly, and shows correctly on your computer.)