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chricannon / STA9750-2024-FALL

Projects from STA9750 - Fall 2024
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STA9750 chricannon MiniProject #03 #4

Open chricannon opened 1 week ago

chricannon commented 1 week ago

Hi @michaelweylandt!

I've uploaded my work for MiniProject #3 - check it out!

https://chricannon.github.io/STA9750-2024-FALL/mp03.html

michaelweylandt commented 1 week ago

Thanks @chricannon !

Peer Feedback:

It is now time for the peer feedback round for Mini-Project 03. Please review @chricannon's submission for this mini-project and provide peer feedback.

Using the rubric at https://michael-weylandt.com/STA9750/miniprojects/mini03.html#rubric, please grade their submission out of a total of 50 points. Note that this rubric is slightly different than that used for Mini-Projects 01 and 02.

For each of the five categories, please give them a separate score and provide a total (sum) score across the entire assignment. Feel free to assign extra credit if you feel it is warranted (following the rubric).

If you give a score of less than 5 for any category, please provide a suggestion for improvement. (You can also give suggestions for any element they did well - more feedback is always great!)

As you go through this peer feedback exercise, think about what you particularly like about this submission and how you can incorporate that approach in your future work. If something is particularly insightful or creative, give some kudos!

Evaluators: This should take you around 15 minutes per peer feedback. You are not required to engage in substantial back-and-forth with @chricannon, but you are of course welcome to initiate a discussion.

@chricannon: please engage fully with your peers. They are here to help you!

Submission URL should be: https://chricannon.github.io/STA9750-2024-FALL/mp03.html

Feel free to link to other repos, the course documentation, or other useful examples.

Thanks! @michaelweylandt

CC: @charles-ramirez

thanhtdao922 commented 1 week ago

Hi @chricannon !

I really like how you added the photo summaries from the Institute for Mathematics and Democracies and other sources; those are really nice and add a lot of context .

Written Communication: 8/10

Your logic is solid and I see no writing issues. Next time, I would recommend bolding the answers just to further highlight your findings.

Project Skeleton: 9/10

You completed everything well and correctly, and all your responses were very insightful.

Formatting and Display: 8/10

All of your graphs are really impressive, and I can see the effort you put in. I don’t know if this was on purpose, but for consistency’s sake, next time make the “Abstract” and “Background” sections headings? And I think displaying some of your data in a table to supplement your visualizations would really add strength to your findings. (Side note did you ever figure out what caused those weird blank space chunks? I'm just curious)

Code Quality: 7/10

Your code runs well, I just recommend adding comments in there to better orient the reader. While you provide a lot of context throughout the report, I think comments within the code will really help.

Data Preparation: 8/10

Code is imported and prepared well, and automated with URLs.

+8 points for creating the animated map from 2000 to 2020 elections. Super impressive!

Your final score is 48/50. Good job!

bleuuuz commented 1 week ago

Hi @chriscannon

Congratulations on finishing mp03 and sharing!

Written Communication: 11/10 Project reads super well with no issues + the additional colored graphics help keep the reader engaged so I gave a bonus point for that.

Project Skeleton: 10/10 All parts of the project were completed. Nice job!

Formatting and Display: 9/10 Graphs are great and also nice job on creating an animated map with the number of electoral votes for each state! Not sure what is happening with the white spaces in task #5.

Code Quality: 8/10 Code runs well but additional comments would make reading it and understanding much easier for the audience. (Especially if they do not have coding experience)

Data Preparation: 10/10 Code importing is automated and no issues here.

Total grade: 48/50 Nice job on the project!

On Thu, Nov 14, 2024 at 2:52 PM Michael Weylandt @.***> wrote:

Thanks @chricannon https://github.com/chricannon !

Peer Feedback:

It is now time for the peer feedback round for Mini-Project 03. Please review @chricannon https://github.com/chricannon's submission for this mini-project and provide peer feedback.

Using the rubric at https://michael-weylandt.com/STA9750/miniprojects/mini03.html#rubric, please grade their submission out of a total of 50 points. Note that this rubric is slightly different than that used for Mini-Projects 01 and 02.

For each of the five categories, please give them a separate score and provide a total (sum) score across the entire assignment. Feel free to assign extra credit if you feel it is warranted (following the rubric).

If you give a score of less than 5 for any category, please provide a suggestion for improvement. (You can also give suggestions for any element they did well - more feedback is always great!)

As you go through this peer feedback exercise, think about what you particularly like about this submission and how you can incorporate that approach in your future work. If something is particularly insightful or creative, give some kudos!

Evaluators: This should take you around 15 minutes per peer feedback. You are not required to engage in substantial back-and-forth with @chricannon https://github.com/chricannon, but you are of course welcome to initiate a discussion.

@chricannon https://github.com/chricannon: please engage fully with your peers. They are here to help you!

Submission URL should be: https://chricannon.github.io/STA9750-2024-FALL/mp03.html

Feel free to link to other repos, the course documentation, or other useful examples.

Thanks! @michaelweylandt https://github.com/michaelweylandt

CC: @charles-ramirez https://github.com/charles-ramirez

— Reply to this email directly, view it on GitHub https://github.com/chricannon/STA9750-2024-FALL/issues/4#issuecomment-2477285617, or unsubscribe https://github.com/notifications/unsubscribe-auth/BK75UXCC65TRRCDFGUFIBLD2AT5PBAVCNFSM6AAAAABRX7XMDSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDINZXGI4DKNRRG4 . You are receiving this because you were mentioned.Message ID: @.***>

Victor-Louie commented 1 week ago

hi @chricannon

Please see the below review.

Written Communication: 10 The introduction is well-written and the narrative flows well, and the structure effectively guides me through the report. I really liked the additional images in the beginning as they helped me be more engaged.

Project Skeleton: 10 All tasks were completed correctly. The answers for each task are very clear.

Formatting and Display: 9 The graphs are well-made and have a simple format. Amazing work that you got the map to be animated. I see that for the Alaska and Hawaii codes, there is a big blank space, I believe that was meant to collapse until the drop-down was clicked.

Code Quality: 10 The code works perfectly. It is concise and to the point, and I liked how the code is initially hidden until clicked.

Data preparation: 10 Data import is fully-automated - download from web sources

total = 49

Well done!

CristelKZuniga commented 5 days ago

Hello @chricannon

Excellent job on completing MP03!!

I really liked how you included a brief and illustrative introduction about the voting system in the US. I found it very helpful for the audience who may not be familiar with how the election process works.

Written Communication: (10/10) The project is well-structured, and it’s easy to understand the introduction, results, and findings after each task. The tables and plots are well-labeled. Overall, your project looks great. You provided excellent analysis after each finding.

Project Skeleton: (10/10) The project meets all the requirements and tasks outlined by the professor, and even goes beyond. I also noticed that you included Alaska and Hawaii in the plot, as well as the state abbreviations—great job!

Formatting & Display: (10/10) I like how you chose to “hide” the code so it doesn’t distract or confuse the audience. The outputs of your code, such as dataframes, are well-formatted as tables, which makes the information more audience-friendly. The pictures at the beginning are a great summary, as well as the different types of plots utilized.

Code Quality: (10/10) Excellent quality— all tasks were completed successfully.

Data Preparation: (10/10) I appreciate how you provided the source links for the datasets and explained the general content of each one. Based on the code and output, it seems you did a great job downloading, cleaning, and preparing the data.

Total: (50/50)