31  Data Moves Portfolio

This text is adapted from the actual assignment I gave students in Canvas.

About the Due Date: Turn in sooner rather than later, so we have time to go around again if there are any problems.

Purpose: Demonstrate your proficiency and understanding of data moves.

Logistics: Submit a link to a Google Doc that gives me edit permission. Expect to submit several times, every time you add a new part. Note: When you resubmit, put a note near the top that tells me what you added so I don’t have to hunt!

Additional useful resource: Did you know that this book has a chapter for each data move? No? Check it out!

You have all used these data moves. This assignment documents your understanding and proficiency, not only in doing them but also in recognizing them.

For each data move, submit at least two pieces of evidence from your work, either new or from a past assignment. Include the rationale for the move: Why did you do it? What did it accomplish?

Which data moves should you do?

• Filtering
• Calculating or recoding
• Grouping
• Summarizing
• Joining (not required but cool if you can do it!)

The evidence can take any form, but here are two ideas that work:

• A snippet cut and pasted (or newly written) that shows that you did the move. There is explanatory text that points out what you did and its rationale. This text could be in a separate paragraph or in a Google Doc comment sticky. Here is an example of a short portfolio entry for grouping and summarizing.
• A screencast video showing you doing this move(s), with audio or callouts explaining what’s happening and why. One free tool for doing such videos is Loom, which works great in my experience (year 2020). You can also make screencasts using Zoom (here is a YouTube about that). Keep videos short. Note: early returns show that these videos can be extremely convincing. Viewers can tell you know what you’re doing.

You can use the same video or the same snippet to support more than one data move.

Variety of Evidence

The two or more examples for each data move should show that you can use the data move for different purposes. For example, if you’re doing summarizing, if both of your examples are about computing mean income in a new column and plotting it, they’re kinda the same. What else can you compute as a summary? (Oh, maybe a percentage, using count(), instead of a mean() thing.) The more different, the more variety, the better.

Another example: the calculating data move is sometimes more like recoding. Having one of each is a good idea!

The difference between 3 and 4

(Our projects were all graded on a 4-point scale)

A three shows that you can do the move and understand why you should use it.

A four shows that you’re more fluent in using a data move. Your examples show more variety, and are more convincing that you could use this move spontaneously in a new situation. Your explanations might show a broader overview, for example, connecting one use to another or showing how different data moves work together. An example using data we haven’t used in a big assignment (e.g., NHANES or NOAA) can help show your ability to use a data move in a new situation.