Guided Project: Investigating Fandango Movie Ratings (Python)
- Last updated on January 31, 2025 at 6:28 AM
About this Webinar
In this webinar, we will step into the role of data journalists to analyze movie ratings data and determine if there’s evidence of bias in Fandango’s rating system. We’ll apply statistical analysis skills using Python.
Here’s what you’ll learn:
- How to explore and manipulate data using Python's powerful pandas library.
- Key statistical methods like sampling and measures of central tendency to draw meaningful insights
- Techniques for creating clear, impactful visualizations with Python's matplotlib library.
New to Python? Begin with our Python Basics for Data Analysis course to build the foundational skills needed for this project.
Before You Start: Pre-Instruction
To make the most of this project walkthrough, follow these preparatory steps:
1. Review the Project
- Start the project here.
Helpful Tips:You can review the solution file here.
New to Markdown? We recommend learning the basics to format headers and add context to your Jupyter notebook: Markdown Guide.
For file sharing and project uploads, it is important that you create a GitHub account ahead of the webinar: Sign Up on GitHub.
2. Set Up Your Workspace
- Jupyter Notebook: Install Jupyter Notebook or JupyterLab to work with the provided
.ipynbfile. Alternatively, use Google Colab for a cloud-based option that requires no installation. - Markdown Basics: Learn the essentials of Markdown to add headings and bullet points for clear documentation within your notebook.
- GitHub Setup: Create a GitHub account to follow along with the demo on uploading files.
3. Download the Resource Files
Access these datasets from inside the project and be ready to follow along:
- Fandango Score Comparison Datasets
Movie Ratings Datasets
Next Steps
- Complete the Project: Go here to start this project in-browser.
- Share Your Work: Upload your completed project to GitHub and GitHub Gists. Share it in the Dataquest Community to receive valuable feedback and connect with fellow learners.