Cinematic Trends
Exploring Movie Metadata and Viewer Preferences
An interactive data visualization project analyzing TMDB movie datasets
Explore ProjectProject Overview
This data analysis project uses TMDB movie datasets to explore viewer preferences, genre popularity, and movie ratings trends. We analyze patterns and relationships in the film industry to uncover insights about what makes movies successful and appealing to audiences.
Problem Statement
Our project aims to answer key questions about the film industry:
- How do genre ratings vary across different viewer segments?
- Does runtime influence viewer perception and ratings?
- What patterns exist in viewer behavior and preferences?
- How do budget and revenue relate to critical and audience reception?
Dataset Description
We analyzed two primary datasets from Kaggle:
- movies_metadata.csv: Contains information about movies including budget, revenue, genres, languages, and ratings
- ratings.csv: Contains user ratings for various movies
These datasets were cleaned, merged, and processed to create our visualization datasets.
Project Workflow
Data Collection
TMDB datasets from Kaggle
Data Preprocessing
Cleaning, merging, and transformation
Analysis
Statistical analysis and pattern identification
Visualization
Power BI and interactive web visualizations
Visualization Highlights
Revenue vs Budget
Exploring the relationship between movie budgets and box office returns over time
View Analysis