Week 3 EDA and Dashboards

Agenda

0. Remind me to start recording.
1. Annoucements.
   • Read weekly annoucments message
2. Review last weeks HW.
3. Updating your fork with this weeks files.
4. Google slide lecture.
5. Break
6. Homework is to complete the dashboard exercise, project ideation slide, and preclass work.
   1. Optionally, complete the Exercise-DONT-EDIT-MAKE-COPY.ipynb file

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Homework For Next Week

NEW: Dashboard Exercise

Create visualizations and dashboards to analyze movie data.

See the detailed instructions in: Dashboard_Exercise.md

Quick Overview:

• Dataset: data/movie_ratings.csv (MovieLens 100k with user demographics)
• Goal: Answer 4 analytical questions using visualizations
• Tools: Streamlit (recommended), Jupyter notebooks, or other dashboard tools
• Questions:
  1. What's the breakdown of genres for the movies that were rated?
  2. Which genres have the highest viewer satisfaction (highest ratings)?
  3. How does mean rating change across movie release years?
  4. What are the 5 best-rated movies that have at least 50 ratings? At least 150 ratings?
  5. [EXTRA CREDIT] Pick 4 genres. For each genre, how does the rating change as viewer age increases?
  6. [EXTRA CREDIT] Plot number of ratings vs mean rating per genre. Is there a correlation between the volume of ratings and mean rating?
  7. [EXTRA CREDIT] We gave you a pre-cleaned genres column, the original dataset is movie_ratings_EC.csv, can you clean it yourself?

This exercise will prepare you for creating professional dashboards and telling stories with data.

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Next Week's Pre-Class Work

• Reading about SCRUM from Jira ~ 5 mins
• What is AGILE? ~ 6 mins
• What is SCRUM? ~ 20 mins
• AGILE in Data Science ~ 8 mins
• How Data Science Projects Are Implemented Using Agile Methodology ~15 mins
• OPTIONAL - Deep dive on how PyData uses AGILE in DS ~ 28 mins

OPTIONAL: Complete the Exercise-DONT-EDIT-MAKE-COPY.ipynb

Remember, make a copy of that file. Add your initials to that copy. Exercise-XX.ipynb. Then edit that file, push your changes, and add the link to the HW submission sheet. (link is on main readme and bookmarked in slack channel)

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