Amounts & Proportions

Due: Oct 11 by 11:59pm

Weight: This assignment is worth 1% of your final grade.

Purpose: learn some of the technical details of how to write code to create “good” information visualizations that follow the design principles we discussed last week. We will focus on graphing amounts and proportions.

Assessment: This assignment is graded using a check system:

  • ✔+ (110%): Responses shows phenomenal thought and engagement with the course content. I will not assign these often.
  • ✔ (100%): Responses are thoughtful, well-written, and show engagement with the course content. This is the expected level of performance.
  • ✔− (50%): Responses are hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.

Notice that this is essentially a pass/fail system. I’m not grading your writing ability and I’m not counting the number of words you write - I’m looking for thoughtful engagement. One or two sentences is not enough. Write at least a paragraph and show me that you did the readings assigned.

1. Get Organized

Download and edit this template when working through this assignment.

Then unzip the template folder (make sure you unzip it!), then open the .Rproj file to open RStudio. Open the hw6.Rmd file, take notes, and write some example code as you go through the following.

2. Readings

The readings listed below are broken into two groups:

  1. Design principles
  2. Coding techniques to implement those principles

Design principles

The design principles discussed in the following readings repeat many of the concepts we saw last week, except focused on the particular subset of charts for this week:

Coding techniques

The readings below discuss two important components that we will run into a lot in making charts: factors & facets. Factors are categorical variables, but dealing with them in R can be somewhat messy. Fortunately, we have the forcats package to help us tackle these! Facets, on the other hand, are rather straight forward to implement and offer a handy technique for creating charts when you have many different variables to consider at once.

When you go through these, take notes in your hw6.Rmd file of examples or concepts that you come across:

3. Practice Coding

To get a little extra practice developing better charts with ggplot2, go to the “Finding Data” page and on the Packages section choose a package that you find interesting. Install the package, then in a code chunk load the package with library(packageName). You can examine the data sets loaded with the package using data(package = "packageName"). Choose a data frame then make a plot illustrating a relationship in the data. Below your code chunk with your visualization, explain in a few sentences what the chart you made shows.

4. Reflect

Reflect on what you’ve learned while going through these readings and exercises. Is there anything that jumped out at you? Anything you found particularly interesting or confusing? Write at least a paragraph in your hw6.Rmd file. Here are some suggestions:

  • Discuss some of the key insights or things you found interesting in the readings or recent class periods.
  • Write about the messiest data you’ve seen.
  • Connect the course content to your own work or project you’re working on.

5. Knit

Click the “knit” button to compile your hw6.Rmd file into a html web page. Then open the hw6.html file in a web browser and proofread your report. Does all of the formatting look correct?

6. Submit

To submit this assignment, create a zip file of all the files in your R project folder for this assignment. Name the zip file hw6-netID.zip, replacing netID with your netID (e.g., hw6-jph.zip). Then copy that zip file into the “submissions” folder in your Box folder created for this class.

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