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README.md
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#
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##
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This project explores the **“Movies Metrics, Features and Statistics”** dataset from Kaggle.
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The dataset contains **6,569 movies** and **32 features**, including:
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---
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##
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**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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---
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##
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Binary classification target:
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---
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#
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Below are the research questions and the insights based on the dataset’s visualizations.
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---
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## 1
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### **Visualization:** Profit vs. Production Budget
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*[Profit X Budget](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Budget.png)*
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---
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## 2
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### **Visualization:** Profitability Rate by Genre
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*[Profit X Genre](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Genre.png)*
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---
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## 3
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### **Visualization:** Profitability Rate by Creative Type
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*[Profit X Creative Type](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Creative%20Type%20.png)*
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---
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## 4
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### **Visualization:** Running Time Density (Profitable vs. Not)
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*[Profit X Running Time](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Running%20Time%20.png)*
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---
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## 5
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### **Visualization:** Average Profit by Production Method
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*[Profit X Production Method](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Production%20Method.png)*
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---
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#
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### Strong Predictors of Profitability
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- Production Budget
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---
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#
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This analysis shows that **pre-release movie characteristics** can be used to meaningfully predict profitability.
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The strongest indicators are **budget**, **genre**, **creative type**, and **production method**, while running time offers additional but weaker predictive value.
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---
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Below is a complete list of all files used throughout this project:
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##
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- **movies_dataset.csv** — Original dataset downloaded from Kaggle
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- **movies_cleaned.csv** — Cleaned version after handling missing values and removing duplicates
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##
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- **Leelu_EDA_&_Dataset.ipynb** — Main notebook containing:
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- Data loading
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- Data cleaning
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- **Profit X Creative Type.png** — Profitability by Creative Type
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- **Profit X Production Method.png** — Average Profit by Production Method
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##
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- **README.md** — Project summary and final results documentation
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---
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#
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**Leelu Alfi**
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Reichman University - Data Science Track
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2025
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# Movie Profitability Analysis - EDA Summary
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## Dataset Overview
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This project explores the **“Movies Metrics, Features and Statistics”** dataset from Kaggle.
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The dataset contains **6,569 movies** and **32 features**, including:
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---
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## Prediction Question
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**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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---
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## Target Variable
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Binary classification target:
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- **is_profitable = 1** → if *Worldwide Gross > Production Budget*
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---
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# Exploratory Data Analysis (EDA)
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Below are the research questions and the insights based on the dataset’s visualizations.
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---
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## 1. How does production budget influence profitability?
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### **Visualization:** Profit vs. Production Budget
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*[Profit X Budget](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Budget.png)*
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---
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## 2. How does genre affect profitability?
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### **Visualization:** Profitability Rate by Genre
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*[Profit X Genre](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Genre.png)*
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---
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## 3. How does creative type impact profitability?
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### **Visualization:** Profitability Rate by Creative Type
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*[Profit X Creative Type](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Creative%20Type%20.png)*
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---
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## 4. How does running time correlate with profitability?
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### **Visualization:** Running Time Density (Profitable vs. Not)
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*[Profit X Running Time](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Running%20Time%20.png)*
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---
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## 5. How does production method influence profitability?
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### **Visualization:** Average Profit by Production Method
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*[Profit X Production Method](https://huggingface.co/datasets/Leelu1002/Movie_Profitability_Analysis/resolve/main/Profit%20X%20Production%20Method.png)*
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---
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# Key Insights Summary
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### Strong Predictors of Profitability
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- Production Budget
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---
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# Final Summary
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This analysis shows that **pre-release movie characteristics** can be used to meaningfully predict profitability.
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The strongest indicators are **budget**, **genre**, **creative type**, and **production method**, while running time offers additional but weaker predictive value.
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---
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# Project Files
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Below is a complete list of all files used throughout this project:
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## Dataset Files
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- **movies_dataset.csv** — Original dataset downloaded from Kaggle
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- **movies_cleaned.csv** — Cleaned version after handling missing values and removing duplicates
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## Notebook Files
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- **Leelu_EDA_&_Dataset.ipynb** — Main notebook containing:
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- Data loading
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- Data cleaning
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- **Profit X Creative Type.png** — Profitability by Creative Type
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- **Profit X Production Method.png** — Average Profit by Production Method
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## Documentation
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- **README.md** — Project summary and final results documentation
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---
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# Author
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**Leelu Alfi**
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Reichman University - Data Science Track
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2025
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