The goal of this project is to pull data from movie related API's to spot trends regarding movie success.
We focused on measuring the following data:
- box office success compared to release month
- box office success compared to critic votes
- Oscar nominations/wins in regards to release month, critic votes, and box office success.
In an effort to use the most accurate and intuative data, we limited our scope to movies released from 1980 - 2017.
Barry Haygood ; Cathy Egboh ; Maya Saeidi ; Michelle Brucato
The API used for this project is TMBD (The Movie Database).
The financial CPI data used for this project was pulled from the FRED website (Federal Reserve Economic Data) as a csv file.
The Oscars data used for this project was pulled from DataHub.com as a csv file. There was an option to import the package, "datapackage", however due to installation issues, we had to go the csv route.
Pandas -- to easily import csv files and create data frames
Matplotlib -- to visualize our data findings using various graphs
Requests -- used to pull data from our API url
Json_Normalize -- to make the API data more readable
Blackcellmagic -- to auto format blocks of code for easier readability