Overview
This task serves as a tutorial with microtasks for the Outreachy Project T356498 (Build a data visualization tool for the evolution of Wikipedia articles maintained by WikiProjects). Starting from this notebook try go through the steps and complete the different TODOs.
The full Outreachy project will involve more comprehensive coding than what is being asked for here (and some opportunities for additional explorations as desired). This task will introduce some of the basic concepts and give us a sense of your Python skills, how well you work with new data, documentation of your code, and description of your thinking and results. We are not expecting perfection -- give it your best shot! See this example of working with Wikidata data as an example of what a completed notebook tutorial might look like.
Set-up
- Make sure that you can login to the PAWS service with your wiki account: https://paws.wmflabs.org/paws/hub
- Using this notebook as a starting point, create your own notebook (see these instructions for forking the notebook to start with) and complete the functions / analyses. All PAWS notebooks have the option of generating a public link, which can be shared back so that we can evaluate what you did. Use a mixture of code cells and markdown to document what you find and your thoughts.
- As you have questions, feel free to add comments to this task (and please don't hesitate to answer other applicant's questions if you can help)
- If you feel you have completed your notebook, you may request feedback and we will provide high-level feedback on what is good and what is missing. To do so, send an email to your mentor with the link to your public PAWS notebook. We will try to make time to give this feedback at least once to anyone who would like it.
Evaluation
When you feel you are happy with your notebook, you should include the public link in your final Outreachy project application as a recorded contribution. You may record contributions as you go as well to track progress. The final notebook (created for the microtask) is our primary means of judging each applicant. For the notebook, we will evaluate it along a few criteria:
- Quality of code: are there bugs? is your code well-structured, commented, and easy to understand?
- Quality of notebook: is the notebook well-structured and easy to follow?
- Creativity: did you try different approaches? did you come up with interesting ideas for future analyses?
- Iteration: if you receive feedback, were you able to incorporate those changes?
Because we will likely only provide one round of feedback for each applicant, we recommend submitting the notebook when you are fairly confident it is a complete state. As noted above, you are not evaluated on the quality of your initial notebook but rather how you adapt to the feedback so it's okay to have mistakes, etc., in your notebook in the initial review and you will not be penalized for that.
If you have received feedback from the mentors, we recommend that you include a section in your final notebook briefly listing all the changes you made to address our comments.
Please remember that April 2, 2024 4pm UTC is the deadline for ALL applicants to record contributions and create a final application.
