How birnawa246-ai/netflix_data_analysis works
This is a notebook-based movie-data analysis project, not a deployed application. Its documented workflow loads the CSV, inspects and cleans the records, analyzes vote-average categories, genres, and popularity, then visualizes patterns and derives findings. The README documents these stages and the CSV-loading example; no notebook source excerpts were available, so the graph reflects documented behavior rather than verified implementation details.
Main entry points: netfilx.ipynb Clean data · mymoviedb.csv Movie dataset
Components 10
Data preparation
- Load data
netfilx.ipynb - Inspect records
netfilx.ipynb - Clean data
netfilx.ipynb
Movie analysis
- Vote categories
netfilx.ipynb - Genre analysis
netfilx.ipynb - Popularity analysis
netfilx.ipynb
Results and visuals
- Visualizations
netfilx.ipynb - Insights
netfilx.ipynb
Other components
- Analyst
- Movie dataset
mymoviedb.csv
Connections 13
- Analyst → Load data: runs notebook
- Movie dataset → Load data: loads records
- Load data → Inspect records: provides data
- Inspect records → Clean data: guides cleaning
- Clean data → Vote categories: categorizes votes
- Clean data → Genre analysis: analyzes genres
- Clean data → Popularity analysis: ranks popularity
- Vote categories → Visualizations: visualizes ratings
- Genre analysis → Visualizations: visualizes genres
- Popularity analysis → Visualizations: visualizes patterns
- Vote categories → Insights: informs findings
- Genre analysis → Insights: informs findings
- Popularity analysis → Insights: informs findings