Title: Data Sourcing Challenge

Preparing and sourcing data from APIs to produce a recommendation system to find movie reviews and related movie titles based on individual preferences.

Description: Sourcing Data for AI Projects

This project involved sourcing movie data from two APIs: The New York Times Article Search and The Movie Database. The New York Times API results are used to construct the requests for the Movie Database API. Once the data has been collected from both APIs, it is merged, cleaned, and then exported to a CSV file to be used as a recommendation system to help people find movie reviews and related movies. This is completed as follows:

• Part 1: Access the New York Times API

  • Extract and prepare relevant data using the New York Times Article Search API documentation

• Part 2: Access The Movie Database API

  • Extract and prepare relevant data using The Movie Database API documentation

• Part 3: Merge and Clean the Data for Export

  • Merge and clean the data, and export it for future use

References Used

To complete this project, I relied heavily on class notes and activities focused on securely accessing APIs with keys to extract data and set up environment variables across various operating systems. I also took advantage of Xpert Learning Assistant to help with coding errors, including but not limited to, working through various try and except clauses. Finally, I utilized Pandas DataFrame documentation to find and rework functions specific to merging and cleaning the data.