FPM #3: Drafting Visualizations

Note

FPM #3 is the the third step in working towards your final project, which is meant to combine nearly all of the course learning outcomes. You’ll begin drafting the visualizations that will become part of your final infographic.

Description

I. Review the final project instructions

Begin by rereading the final project description in full to remind yourself of the goals and requirements.

II. Create drafting-viz.qmd

Create an file named, drafting-viz.qmd within your lastName-eds240-infographic repo and add appropriate YAML fields. You’ll completing all sections of this assigment (Parts III-VI) here.

III. Some pre-planning

Before you start drafing your viz, answer the following questions:

• 1. Restate the questions you hope to answer with your inforgraphic. This should include one overarching question (think of this as driving the overall theme of your infographic) and at least three subquestions (each of which will be addressed by your infographic’s component visualizations). Have these questions changed at all since FPM #1? If yes, how so?

• 2. Explain which variables from your data set(s) you will use to answer the above questions, and how.

Important – be specific here!

For example, let’s say I’m interested in how Lyme disease incidence is changing over time for states X, Y and Z. An appropriate explanation of variables might look something like this:

“I have two data sets, one containing population estimates by state from the {tidycensus} package, and another from the CDC containing lyme disease case counts by county and year. After wrangling / joining these data sets, I was able to calculate disease incidence as cases per 100k people at the state level. Doing so provides me with three variables to visualize: time (years), disease incidence (cases per 100k people), and state.”

• 3. In FPM #2, you created some exploratory data viz to better understand your data. You may already have some ideas of how you plan to formally visualize your data, but it’s incredibly helpful to look at visualizations by other creators for inspiration. Find at least two data visualizations that you could (potentially) borrow / adapt pieces from. Download and embed them into your drafting-viz.qmd file, and explain which elements you might borrow (e.g. the graphic form, legend design, layout, etc.).

Tip: Remember to check out the Resources page for lots of great inspiration!!

It lists tons of really wonderful websites, tutorials, and links to the repos / websites of some seriously incredible data viz creators. This is an excellent place to start when looking for inspiration.

Tip: Embedding images into a .qmd file

There are a number of ways to render an image in .qmd file. Two ways I find easiest are:

1. Using knitr::include_graphics() in a code chunk (if you’re using R). Here are the chunk options I often specify:

```{r}
#| eval: true
#| echo: false
#| fig-align: "center"
#| out-width: "100%"
#| fig-alt: "Alt text here"
knitr::include_graphics("path/to/image")
```

2. Using Markdown syntax:

![](file/path/to/image){fig-alt="Alt text goes here"}

IV. Hand-draw your anticipated visualizations

Before you begin coding, it’s a super useful practice to sketch out your anticipated visualizations by hand. This Medium article does a great job summarizing why this step matters.

• Hand-draw your anticipated visualizations, then take a photo of your drawing(s) and embed it in your rendered drafting-viz.qmd file – note that these are not exploratory visualizations, but rather your plan for your final visualizations that you will eventually polish and include in your infographic.

Open me for an example!

Here’s a great example of some hand-sketched visualizations, by Marine Kochuten (MEDS 2025). Marina also chose to sketch a potential layout of her final infographic:

And if you’re curious how the final infographic turned out:

V. Recreate your hand-drawn visualizations using code

Mock up all of your hand drawn visualizations using code. We understand that you will continue to iterate on these into FPM #4 (particularly after receiving feedback), but by the end of FPM #3, you should:

• have your data plotted (if you’re experimenting with a graphic form(s) that was not explicitly covered in class, we understand that this may take some more time to build; you should have as much put together as possible)
• use appropriate strategies to highlight / focus attention on a clear message
• include appropriate text such as titles, captions, axis labels (note: you may eventually convert some text, such as titles and captions, into annotations or text elements on your infographic; it’s still helpful to include titles, etc. on these stand-alone visualizations now, to provide your peer reviewers and instructional team with necessary context)
• experiment with colors and typefaces / fonts
• create a presentable / aesthetically-pleasing theme (e.g. (re)move gridlines / legends as appropriate, adjust font sizes, etc.)

VI. Answer a few last questions about your work and progress

• 1. What are the key insights you want your infographic to communicate, and how will your design choices help highlight and support those messages?

• 2. What challenges did you encounter or anticipate encountering as you continue to build / iterate on your visualizations in R? If you struggled with mocking up any of your three visualizations, describe those challenges here.

• 3. What ggplot extension tools / packages do you need to use to build your visualizations? Are there any that we haven’t covered in class that you’ll be learning how to use for your visualizations?

• 4. What feedback do you need from the instructional team and / or your peers to ensure that your intended message and key insights are clear?

Rubric (specifications)

To receive a “Satisfactory” mark for FPM #3:

• Answer all Part III questions. There are no strict length requirements for the free-response questions, however we expect that you answer them thoughtfully and fully. Your inspiration images (question #3) should be embedded correctly (and if using R code to embed them, apply the correct code chunk options to suppress the code itself from rendering).
• Include all three hand-sketched visualizatons, and optionally a tentative sketch of your full infographic (Part IV). At a minimum, you must include three visualizations + any text (e.g. titles, axis labels, group labels) necessary for providing context. You don’t need to be an artist, but your drawings and text should be clear enough for your instructors to understand.
• Include all three code-based visualizations (Part IV). These do not need to be in their perfect final form, but you should strive for complete visualizations as best you can. At a miminum, you should be able to check each of the five checkboxes listed under Part V. If you’re unable to figure out how to implement pieces of these visualizations successfully using code, be sure to describe in writing where you’re headed. All code used to build your visualizations must be visible in your rendered PDF (e.g. make sure code chunks remain expanded).
• Code in Part IV should follow appropriate styling conventions and include clear, informative annotations. We will not enforce any particular code style guide (you may use conventions from prior courses if you prefer; we recommend following these conventions from the Tidyverse style guide if you’re unsure where to start). You don’t need to explain every line, but your annotations should make it easy to follow your thinking and understand important decisions in your code.
• Answer all four Part VI questions. There are no strict length requirements for free-response questions, however we expect that you answer them thoughtfully and fully.
• Ensure that everything described above is included in your neatly-organized and polished drafting-viz.qmd file – this includes appropriate document YAML (at a minimum, title, author, date), clearly labeled sections, appropriately-formatted prose, appropriate code chunk options (e.g. code should render and execute, but warnings and messages should be suppressed, long data frames should not be printed out, etc.)
• Render drafting-viz.qmd as a PDF. Double check that all of your outputs, code, and prose are visible.
• Upload your PDF to Gradescope by 11:59pm on Sun 02/22/2026.
• Submit a Generative AI Statement of Use for FPM #3 by 11:59pm on Sun 02/22/2026.