cleebp / movie_data

Exploratory data science work on summaries of ~42K movies scraped from wikipedia.

Hi there, I'm Brian Clee

• 📚 I received my B.S. in Computer Science from Appalachian State Univerity in 2015
  • 👨‍🔬 Minored in Mathematics, Russian Language, and Global Studies: Russian Studies
• 🔍 I received my M.S. in Computer Science from North Carolina State University in 2018
  • 🖱️ My graduate research focused on Human Computer Interaction with non-traditional displays
• 🗺️ I currently work as a Python Developer for Esri helping support Python across our platform primarily through anaconda environments
  • 🐍 I help manage and develop the 250+ conda packages on our Esri conda channel supporting python in ArcGIS Pro
  • 🕸️ Core maintainer of Esri's deep-learning-frameworks and the additional 100+ deep learning packages

---

Connect with me:

---

movie_data's Issues

logic for common_sets is flawed

Right now comparing each genre against the previous and adding to common set if it doesn't exist, i think the correct way is actually to compare each genre against all other genres O(n^2) or less time complexity if I can come up with something tricky.

top_genres.txt empty

Mysteriously empty, but things still seem to be working fine...

Feature: Compute bigrams in genre_properties

One interesting area to look into if I have the time could be computing the top bigrams for each genre to see if they give any insights into genre summary characteristics. For instance 'dead body' will almost assuredly be the top bigram for Thriller.