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Questions.pdf`**: PDF version of the problem statements.\n\n## 📊 Dataset\n\nThe dataset used in this project can be found on **Kaggle**:  \n🔗 [Famous Paintings Dataset](https://www.kaggle.com/datasets/mexwell/famous-paintings)\n\n## 🛠️ Setup Instructions\n\n1. **Database Setup**  \n   - Install PostgreSQL and create a database named `painting`.\n   - Update the `conn_string` in `load_csv_files.py` with your database credentials.\n\n2. **Load Data**  \n   - Download the dataset from the link above and place the CSV files in the appropriate directory.\n   - Run `load_csv_files.py` to populate the database.\n\n3. **Run Queries**  \n   - Use the queries in `Solutions.txt` to analyze the data.\n\n## ✅ SQL Problems Covered\n\n✔️ Find paintings that are not displayed in any museum.  \n✔️ Identify museums without any paintings.  \n✔️ Compare asking price vs. regular price of paintings.  \n✔️ Identify the most and least popular painting styles.  \n✔️ Find museums that are open every day.  \n✔️ Detect and remove duplicate records.  \n...and many more!\n\n## 📌 Additional Notes\n\n- This project demonstrates SQL skills such as **JOINs, RANK, GROUP BY, and WINDOW functions**.\n- Queries can be modified for different **business insights**.\n\n## 📜 License\n\nThis project is licensed under the **Apache License 2.0**.  \nSee the [LICENSE](LICENSE) file for more details.\n\n---\n\n🚀 *Happy Querying!*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsakthivinash2%2Fsql_paintings_casestudy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsakthivinash2%2Fsql_paintings_casestudy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsakthivinash2%2Fsql_paintings_casestudy/lists"}