Investigating Netflix Movies

This project analyzes patterns in Netflix’s movie catalog to understand how runtimes, genres, and release trends have shifted over time. The goal is to turn raw title data into insights that help explain how the platform’s content library is evolving.

Problem

With thousands of titles on Netflix, it's difficult to see how the catalog is changing over time. Viewers notice trends anecdotally, but Netflix does not publish clear summaries of runtime patterns, genre distribution, or how new releases differ from older ones. A structured analysis helps reveal these shifts.

Approach

I explored Netflix’s movie dataset to identify key trends in:

• Movie runtimes
• Genres and category distribution
• Release year patterns

The intent was not to evaluate individual movies, but to paint a broader picture of how Netflix curates its movie catalog. The analysis focuses on visualization and exploratory methods to highlight patterns that are easy for viewers, analysts, or content strategists to understand.

Outcome

The project provides a clear overview of how Netflix’s movie library is evolving.
Key findings include:

• Movie runtimes show meaningful clustering, with more modern titles trending slightly shorter.
• Certain genres dominate Netflix’s recent catalog, while others appear less frequently.
• The distribution of release years suggests shifts in licensing, streaming strategies, and viewer demand.

These insights can support content research, recommendation systems, and platform strategy decisions.

Dataset

The project uses the Netflix movie dataset, which includes:

• Title and genre
• Release year
• Movie duration
• Auxiliary color-coding file for visual categorization

The dataset allows for runtime comparison, genre grouping, and timeline insights.

Project Steps

1. Data Loading and Cleaning

• Loaded Netflix dataset and color mapping file
• Filtered for movies only
• Cleaned and standardized runtime and category fields

2. Exploratory Data Analysis (EDA)

• Histogram of movie runtimes
• Scatterplot of release year vs. runtime
• Genre and category comparisons
• Highlighted noteworthy outliers and clusters

3. Visual Insights

Key visual questions explored:

• How long are Netflix movies on average?
• Are movies getting longer or shorter over time?
• Which genres dominate the platform?
• How does release year affect movie characteristics?

Visuals