A project to analyse and visualise cinema seating patterns
Website
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Medium Article
PopcornData is a website made to analyse movie trends in Singapore — from which seats people prefer to the way they like to watch different movies. The data used was scraped from the website of Shaw Theatres, one of the biggest cinema chains in Singapore, using a webscraper we built with Python and Selenium (shaw-scraper)
The data scraped was for January 2020 and using it we were able to build interesting visualisations about how people watched different movies, at different halls, theatres and timings!
Some unique visualisations include:
- Heat maps to show the most popular seats
- Animations to show the order in which seats were bought
We documented our project journey in these articles:
Obtaining the Data
https://towardsdatascience.com/popcorn-data-analysing-cinema-seating-patterns-part-1-a0b2a5c2c19a
Analysing and Visualising the Data
https://medium.com/analytics-vidhya/popcorn-data-analysing-cinema-seating-patterns-part-ii-987fbde9d363
Deployed on Heroku
- Clone the repo and navigate to the correct folder
git clone https://github.com/PopcornData/popcorn-data-website.git
cd popcorn-data-website
- Create a virtual environment
pip install virtualenv #Run this if you don't have virtualenv installed
virtualenv env
- Activate the virtual environment
env\Scripts\activate #Windows
source env/lib/activate #Mac/Linux
- Install the project requirements
pip install -r requirements.txt
- Start the Flask app
python mainapp.py
- Go to localhost:5000 on your browser to view the webapp