https://github.com/sakthivinash2/sql_paintings_casestudy

This project explores a dataset of Famous Paintings & Museums using SQL queries to answer various analytical questions.
https://github.com/sakthivinash2/sql_paintings_casestudy

case-study paintings postgresql sql

Last synced: 2 months ago
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This project explores a dataset of Famous Paintings & Museums using SQL queries to answer various analytical questions.

• Host: GitHub
• URL: https://github.com/sakthivinash2/sql_paintings_casestudy
• Owner: SAKTHIVINASH2
• License: apache-2.0
• Created: 2025-01-28T09:50:02.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2025-01-28T10:09:09.000Z (4 months ago)
• Last Synced: 2025-02-06T21:20:34.481Z (4 months ago)
• Topics: case-study, paintings, postgresql, sql
• Language: Python
• Homepage:
• Size: 56.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 🎨 SQL Paintings Case Study

This project explores a dataset of **Famous Paintings & Museums** using **SQL queries** to answer various analytical questions.

## 📂 Project Structure

- **`load_csv_files.py`**: Script to load dataset CSV files into a **PostgreSQL** database.

- **`Questions.txt`**: A list of SQL problems to solve using the dataset.

- **`Solutions.txt`**: SQL queries solving the problems.

- **`SQL Paintings Casestudy - Questions.pdf`**: PDF version of the problem statements.

## 📊 Dataset

The dataset used in this project can be found on **Kaggle**:  

🔗 [Famous Paintings Dataset](https://www.kaggle.com/datasets/mexwell/famous-paintings)

## 🛠️ Setup Instructions

1. **Database Setup**  

   - Install PostgreSQL and create a database named `painting`.

   - Update the `conn_string` in `load_csv_files.py` with your database credentials.

2. **Load Data**  

   - Download the dataset from the link above and place the CSV files in the appropriate directory.

   - Run `load_csv_files.py` to populate the database.

3. **Run Queries**  

   - Use the queries in `Solutions.txt` to analyze the data.

## ✅ SQL Problems Covered

✔️ Find paintings that are not displayed in any museum.  

✔️ Identify museums without any paintings.  

✔️ Compare asking price vs. regular price of paintings.  

✔️ Identify the most and least popular painting styles.  

✔️ Find museums that are open every day.  

✔️ Detect and remove duplicate records.  

...and many more!

## 📌 Additional Notes

- This project demonstrates SQL skills such as **JOINs, RANK, GROUP BY, and WINDOW functions**.

- Queries can be modified for different **business insights**.

## 📜 License

This project is licensed under the **Apache License 2.0**.  

See the [LICENSE](LICENSE) file for more details.

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🚀 *Happy Querying!*