Update README.md

README.md

@@ -129,7 +129,35 @@ This analysis shows that **pre-release movie characteristics** can be used to me
 The strongest indicators are **budget**, **genre**, **creative type**, and **production method**, while running time offers additional but weaker predictive value.
 
 ---
+# 📂 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 Creative Type.png** — Profitability by Creative Type  
+- **Profit X Production Method.png** — Average Profit by Production Method  
+
+## 📝 Documentation
+- **README.md** — Project summary and final results documentation  
+
+---
 # ✍️ Author
 **Leelu Alfi**  
 Reichman University - Data Science Track