Product

Detail what you created. What did you create, how, etc. What methods or techniques did you use? What tools and technologies were involved? Include images, code or video.

I created a visual graphic, in the style of Etsy's seller handbook that instructs potential sellers on flawed ways to get items to sell. The data was generated through Etsy's API and a python script that makes the needed requests and organizes the data. The visual graphic itself was hand-drawn, using the script's reported data. Source code for the python script and related modules are available here.

Intention

Write about the big ideas behind your project? What are the goals? Why did you make it? What are your motivations?

Context

Describe what informed your ideas and your outcome. How does your outcome relate to other work in the field? What are the precedent projects? Situate your ideas relative to work you've seen in class, or elsewhere

There's plenty of guides available to help sellers break into the Etsy market, though none (very few) of them are data-driven the way that mine is. They primarily focus on shop aesthetics and presentation, rather than "playing to trends" in the way that my graphic suggests.

Most dataviz works I've seen focus on more concrete relations such as location, time, or demographic, and tend to focus more on people and socially relevant trends. Trying to play to the fun and playful aspect of the prompt, I opted for something a little less hard-hitting.

Process

Outline your approach to the project.  How did  you arrive out the outcome? What did you research and explore? What were the design choices? What challenges were encountered and how did you resolve them? Document design decisions and challenges encountered.

I spent a lot of time deciding which dataset I wanted to use, searching mostly for preexisting datasets I could manipulate. Most of these focused on topics that I had trouble reconciling with "fun and playful", though I found them interesting. I came to Etsy nearly out of desperation, knowing that I would be pretty comfortable working with it. 

I slowly built up a modules and libraries that could process and organize the data effectively. While testing, I also came up with a flawed logic that I could use to present this data. I also pulled assets and style standards from Etsy's css, and fortunately had the font available on my computer, though I could have gotten the text from hacky Chrome developer tools methods as well.

Unfortunately I was unable to get the code working by the deadline, mostly due to the length of time needed to run the program each time. The data displayed is a mockup of what it would look like populated with real data.

Reflection

Reflect on the process of making this project. What did you learn? What would you do differently?

My biggest regret in this project is definitely trying to build a dataset myself. While the process was not difficult, it was time-consuming. I also didn't use any sort of caching of my requests, so debugging required me to make 20+ requests each time I wanted to run the script, which was by far the most annoying part. The remainder of the work was definitely decreased in quality due to the timesuck of writing the requests. I would have liked to do more interesting things with the data, but only used a very small portion of it for this project. As you can see, my data was not correct, so I had to fake data in order to indicate the idea behind my project. This is definitely not good dataviz practice, but if my data had been correct this would not have been necessary.

Attribution

Reference any sources or materials used in the documentation or composition.

Etsy API provided data

Python Requests library allowed me to interact with the API