STA/OPR 9750 clintavarghese MiniProject #02

[clintavarghese]

Hi, @michaelweylandt!

I've uploaded my work for MiniProject #02 - check it out!

https://clintavarghese.github.io/STA9750-2024-FALL/mp02.html

[michaelweylandt]

Thanks @clintavarghese !

Peer Feedback:

• @greazyz
• @velasco23
• @laurencardieri
• @ayrama

It is now time for the peer feedback round for Mini-Project 02. Please review @clintavarghese's submission for this mini-project and provide peer feedback.

Using the rubric at https://michael-weylandt.com/STA9750/miniprojects/mini02.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-Project 01.

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 @clintavarghese, but you are of course welcome to initiate a discussion.

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

Submission URL should be: https://clintavarghese.github.io/STA9750-2024-FALL/mp02.html

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

Thanks! @michaelweylandt

CC: @charles-ramirez

[Gautam-1-R]

Hy @clintavarghese,

Here your feedback:

1. Written Presentation: 8/10 The report is well-written, and the points come across clearly. A bit more detail in some of the explanations would really help.

2. Project Structure: 9/10 The project is well-structured, and the tasks are clearly stated. The flow from section to section is logical and easy to follow.

3. Formatting & Display: 9/10 The visuals look good, and information is conveyed well. Using titles and improving some of the labels would make them clearer.

4. Code Quality: 9/10 The code logically makes sense and executes without bugs. More descriptive variable names would aid in readability.

5. Data Preparation: 10/10 Fine work on data preparation! The dataset is well-organized and hence provides an extremely sound foundation to your analysis.

Overall: 45/50

[velasco23]

@clintavarghese

Written Communication: 7/10 - In task 2 question 2, your code is set to 1908 but your answer states "There are 111 individuals who were born in the year 1911.". Most likely, a typo but it has potential to create confusion. In Task 3, question 4, I would suggest to add a little of what the question is and why you chose Tom Hank. For example, why is he your favorite actor? Towards the end of your report you were mentioning movies only but had not filtered out tv series/episodes which might have skewed your results.

Project Skeleton: 10/10 - Good table of contents

Formatting & Display: 9/10 - Personally, I would not have a wordcloud graph to show "Highest Rated Series". I would suggest a bar graph, however, the execution was flawless. Your animated graph was really good!

Code Quality: 8/10 - The functions you created stood out, because these functions can be reused in future project with the same or different data. Essentially you made your work useable for the future. In task 3, question 5, I would filter to only include movies since the aim is to make a successful movie. TV episodes/series might add some deviation to your mean/quartiles. In task 4 question 1, we see drama overtakes all other categories. I am curious if you applied a movie filter to this data or if the data is skewed because tv series were included.

Data Preparation: 10/10 - Automatic.

total: 44/50 Good Job!

[clintavarghese]

Thank you @velasco23 for taking the time to evaluate my project.

I will add a few details on why I picked Tom Hanks. Sorry, It was a typo for 1911, instead, it should be 1908. I will make those changes and update you. For Task 3 Q5, my understanding was it is asking to give metrics for all projects and not only movies["Come up with a numerical threshold for a project to be a ‘success’; that is, determine a value such that movies above are all “solid” or better."].

Can you be more specific on how you would give a bar graph to show highly rated series instead of a table?

For Task4 Q1, I have filtered the data for only movies:

And from Task 4 onwards, I am only looking at movies. There is a dataset created for MOVIES and for some tasks, I have used the function "Identify_title" to filter only Movies. I hope that explains.

[velasco23]

@clintavarghese ah okay, I was confused bc in task 3 q 5, you have what makes a movie "solid" and then your results in the table show TV episodes as well.

[clintavarghese]

@velasco23 Thank you for pointing out the typos, I have made the changes that you suggested.

[laurencardieri]

Hi @clintavarghese

The following is my feedback:

Written Communication: 9/10: The intro had a really good hook that would draw a reader in. I also believe you had a good flow of explaining what you did. However, I feel like there could have been more explanation of what was being done, especially while answering the questions in task 2.

Project Skeleton: 9/10: The project followed everything that the professor requested. You did however miss one question, the Happy Days one, and added one that was not on the list, the find projects of any director or actor one.

Formatting & Display: 12/10 (+2 Extra Credit): I really enjoyed how you formatted your project! I liked the table of contents at the beginning and the folded code that followed throughout the project. The graphics used were also very cool and attractive, especially the word cloud, different types of images to portray data, and even the one that changes over time. Lastly, the creation of the poster was very creative and a great addition! Good work.

Code Quality: 7/10: There were a few things that could be approved on in the code quality. Firstly, for the questions such as Mark Hamill's top for movies or the top/bottom projects, I recommend to slice only what is required. For example, for the top projects, you sliced 50 when only 5-10 were required, and 20 for the least when only 3-5 was required. This could speed up your process when rendering by not working your computer as hard, and it restrains your data to only what is required. Also, your chart for your lower rating movies on your metric was not ordered in a descending order by your new rating, but rather by something else. Lastly, for your Tom Hanks chart, I would recommend only restricting his works to show movies in relation to your metric, as that is what we were assessing. Other than that, everything looked great!

Data Preparation: 10/10

Total Rating: 47/10

Great Work!

[clintavarghese]

Hi @laurencardieri ,

Thanks for taking time to go through my project.

I will definitely add more comments for task 2, if that would help understand better.

"Also, your chart for your lower rating movies on your metric was not ordered in a descending order by your new rating, but rather by something else." Task 3 Q2 we have to take in account large numbers of IMDb votes that score poorly on your success metric. So, I arranged(desc(numVotes))|>filter(new_rating<5)|>slice() . Else, movies with less number of votes and low rating will be shown.

"Lastly, for your Tom Hanks chart, I would recommend only restricting his works to show movies in relation to your metric, as that is what we were assessing." Task 3,Q3 is to Choose a prestige actor or director and confirm that they have many projects with high scores on your success metric. Since it does not mention only movies, I have included all the projects that Tom Hanks being part of.

Hope these explanation gives a different perspective.

[greazyz]

Hi @clintavarghese, You're an 8 year IMDb member! That's a cool fun fact. This mini-project must've been extra fun!

Written Communication (10): I like the table of contents. Everything was connected and each step was explained. The backticks for table names and elements made it easy to read. I will be incorporating more of that in my own reports. Project Skeleton (11): You went beyond by not only looking for Mark Hamil's famous projects, but you also created a function find _projects to be able to search any actor and director. Formatting (11): Everything was clear and easy to navigate. You explored using different visualizations: word cloud, animate function, box plot, and line graph. Code Quality (10) Data Prep (10)

Total: 52/50

[clintavarghese]

@greazyz Thanks a lot for your feedback.