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cndy17 / STA9750-2024-FALL

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Issue for MP03 #4

Open cndy17 opened 1 week ago

cndy17 commented 1 week ago

Hi @michaelweylandt!

I've created my MP02 website - check it out!

https://cndy17.github.io/STA9750-2024-FALL/mp03.html

michaelweylandt commented 1 week ago

Thanks @cndy17 !

Peer Feedback:

It is now time for the peer feedback round for Mini-Project 03. Please review @cndy17'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 @cndy17, but you are of course welcome to initiate a discussion.

@cndy17: please engage fully with your peers. They are here to help you!

Submission URL should be: https://cndy17.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

bleuuuz commented 6 days ago

Hi @cndy!

Congrats on your project and thanks for sharing!

Written Communication: 7/10 Overall, your written work flows well and without grammatical errors. I think you could improve the written aspect of your site by adding some context for task number 3 since it seems to be mostly/all code. Adding a description or why your charts are important would help make the report flow better and engage the audience.

Project Skeleton: 10/10 All parts of project accounted for. Great job!

Formatting and Display: 10/10 Overall graphics and charts are great but the "Impact of Fusion voting on elections" could use some context/numbers. The graphic displays that fusion voting has only impacted a small number of elections but its hard to tell because the scale on the right goes from 0-200. Perhaps adding in the number it has impacted about the bar chart would make it easier to understand. Other than that great job adding Alaska and Hawaii!

Code Quality: 10/10 Code is clean and has comments which makes it easy to understand.

Data Preparation: 10/10 No issues here, data prep is automated.

Total Grade: 47/50 Nice job!

On Thu, Nov 14, 2024 at 2:54 PM Michael Weylandt @.***> wrote:

Thanks @cndy17 https://github.com/cndy17 !

Peer Feedback:

It is now time for the peer feedback round for Mini-Project 03. Please review @cndy17 https://github.com/cndy17'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 @cndy17 https://github.com/cndy17, but you are of course welcome to initiate a discussion.

@cndy17 https://github.com/cndy17: please engage fully with your peers. They are here to help you!

Submission URL should be: https://cndy17.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/cndy17/STA9750-2024-FALL/issues/4#issuecomment-2477289544, or unsubscribe https://github.com/notifications/unsubscribe-auth/BK75UXEBEHM5LRMFXXQUS332AT5YJAVCNFSM6AAAAABRXVILWOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDINZXGI4DSNJUGQ . You are receiving this because you were mentioned.Message ID: @.***>

mussakone commented 4 days ago

Hello @cndy17 I reviewed your mini project 3 and here is what I think:

Written Communication: 8/10 Your written communication shows your understanding of the topic and flows with no errors. Every task except some like task 3, you did have some form of written communication so we are not juts looking at a code or a map. I would suggest including some explanation everywhere and maybe even having the task number as a header as well.

Project Skeleton: 10/10 Completed all parts of the project accurately.

Formatting and Display: 8/10 There wasn't an animated map but your maps were still good in all task and answered the question that you were trying to solve. Your tables and figures were full of information as well that was accurate along with the code you typed. Project is very presentable.

Code Quality: 10/10 Code is accurate and clean alongside your outputs. Captions made them more clear.

Data Preparation: 10/10 Data prep is automated

Overall: 46/50

chricannon commented 4 days ago

Hi @cndy17,

Excellent job on MP #03. I found your project very impressive and engaging!

Written Communication: 9/10. I appreciate how your formatted your writing - the use of bolding goes a long way when reading through projects with code, visualizations, and writing. Specifically, in the section titled "Evaluating Fairness of ECV Allocation Schemes", I appreciate how in depth you went to explain each of the different electoral college allocation methods, with each different method bolding. Some visualizations are missing commentary and would benefit from a brief explanation of the results, so took off 1 point here.

Project Skeleton: 10/10 You completed every task, showing either a table or visualization output (or both) for each. Great job!!

Formatting & Display: 12/10. Great formatting on all tables and visuals. I appreciate the consistency of using blue and red throughout, as you displayed results for democrat versus republican. I also liked how many different types of graphs you used. Adding a picture of the survey from the Pew Research Center article at the end was a nice touch.

Your "US Presidential Election Results by State and Year" facet map for each election is awesome. This was a nice alternative to an animation, and this is the only one I saw completed this way. I like being able to see all election results in front of me - giving 2 points extra credit for this.

Code Quality: 10/10 Code is flawless. Extra appreciation for your use of code folding. Especially given the number of visualizations and elaborate explanation you have, folding the code makes reading through your project painless.

Data Preparation: 10/10 Data import is fully automated and efficient.

Total: 51/50

Cdiallo77 commented 3 days ago

Hello @cndy17

Written Communication: 8/10 You mostly explained the steps for each code but not your findings.

Project Structure: 10/10 The objective is to answer all the question and you did deliver perfectly.

Formatting & Display: 10/10 Graphs and visuals are exceptional - Awesome job

Code Quality: 10/10 The code line are well-organized and you commented each step.

Data Preparation: 10/10

Overall:48/50

Great job!