#  Movie Profitability Analysis - EDA Summary

## Dataset Overview
This project explores the **“Movies Metrics, Features and Statistics”** dataset from Kaggle.  
The dataset contains **6,569 movies** and **32 features**, including:

- Production Budget  
- Worldwide & Domestic Gross  
- Running Time  
- Genre  
- Creative Type  
- Production Method  
- Ratings and Release Date  

The goal is to understand which **pre-release factors** influence a movie’s ability to generate **positive profit**.

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##  Prediction Question
**Can we predict whether a movie will be profitable using only pre-release features such as budget, runtime, genre, and production characteristics?**

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##  Target Variable
Binary classification target:

- **is_profitable = 1** → if *Worldwide Gross > Production Budget*  
- **is_profitable = 0** → otherwise  

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#  Exploratory Data Analysis (EDA)

Below are the research questions and the insights based on the dataset’s visualizations.

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## 1. How does production budget influence profitability?

### **Visualization:** Profit vs. Production Budget  
*[Profit X Budget](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Budget.png)*

### **Insight**
- A clear **positive correlation** exists between budget and profit.  
- Higher-budget films tend to achieve **higher profit**, but with larger variance.  
- Budget is a **strong predictor** of financial success.

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## 2. How does genre affect profitability?

### **Visualization:** Profitability Rate by Genre  
*[Profit X Genre](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Genre.png)*

### **Insight**
The most profitable genres:

- **Adventure** (highest)  
- **Horror**  
- **Romantic Comedy**  
- **Action**  

Less profitable genres include Drama and Documentary.

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## 3. How does running time correlate with profitability?

### **Visualization:** Running Time Density (Profitable vs. Not)  
*[Profit X Running Time](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Running%20Time%20.png)*

### **Insight**
- Profitable movies tend to be slightly **longer** (around 105–120 minutes).  
- Extremely long films are less common but can still be profitable.  
- Running time has a **weak-to-moderate** influence on profit.

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## 4. How does production method influence profitability?

### **Visualization:** Average Profit by Production Method  
*[Profit X Production Method](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Production%20Method.png)*

### **Insight**
Highest profit methods:

- **Animation + Live Action**  
- **Digital Animation**  
- **Hand Animation**

Lower profitability:

- **Stop-Motion**, **Live Action**, **Multiple Methods**, **Rotoscoping**

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# Key Insights Summary

### Strong Predictors of Profitability  
- Production Budget  
- Genre  
- Creative Type  
- Production Method  

### Moderate Predictor  
- Running Time  

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# Final Summary
This analysis shows that **pre-release movie characteristics** can be used to meaningfully predict profitability.  
The strongest indicators are **budget**, **genre**, and **production method**, while running time offers additional but weaker predictive value.

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# Project Files

Below is a complete list of all files used throughout this project:

## Dataset Files
- **movies_dataset.csv** — Original dataset downloaded from Kaggle  
- **movies_cleaned.csv** — Cleaned version after handling missing values and removing duplicates  

## Notebook Files
- **Leelu_EDA_&_Dataset.ipynb** — Main notebook containing:
  - Data loading  
  - Data cleaning  
  - Target variable creation (`is_profitable`)  
  - Full Exploratory Data Analysis (EDA)  
  - Visualizations and insights  

## Visualization Outputs
(Images included in the README)

- **Profit X Budget.png** — Profit vs. Production Budget  
- **Profit X Running Time.png** — Running Time Density (Profitable vs. Not Profitable)  
- **Profit X Genre.png** — Profitability by Genre  
- **Profit X Production Method.png** — Average Profit by Production Method  

## Documentation
- **README.md** — Project summary and final results documentation  
- **[Presentation Video](https://www.youtube.com/watch?v=9TbwMmHUUXw)** 
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# Author
**Leelu Alfi**  
Reichman University - Data Science Track  
2025