Python-SQL Project

This repository contains a Python and SQL integration project where Python is used to connect with an SQL database, execute queries, and perform data processing or analysis. The project illustrates how to combine Python programming with SQL database operations for real-world data tasks.

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Repository Contents

File / Folder	Description
Python_SQL.ipynb	Python files or Jupyter notebooks that connect to and query the SQL database.
Python-SQL.sql	SQL script files containing queries for database creation, data insertion, and analysis.
README.md	This file — project overview and instructions.
LICENSE	License information (if included).

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Project Overview

This project demonstrates how to use Python to interact with an SQL database for data retrieval, manipulation, and analysis. It shows how to:

• Connect Python to a database (such as MySQL, PostgreSQL, or SQLite)
• Execute SQL queries from Python
• Fetch and process data using Python tools like pandas
• Analyze or visualize results (if included)

Using Python and SQL together is a common practice in data analytics, data engineering, and backend development roles.

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Topics Covered

In this project you will learn:

1. Database Connection with Python

   • Establishing connection to a database from Python code.

2. Executing SQL Queries in Python

   • Running SELECT, INSERT, UPDATE, DELETE queries using Python interfaces.

3. Data Retrieval & Processing

   • Fetching results from SQL and manipulating them in Python (e.g., with pandas).

4. Basic Data Analysis (Optional)

   • Performing simple analysis or summarization on fetched data.

5. Integrating Python & SQL for Automation

   • Automating database tasks using Python scripts or notebooks.

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How to Use

1. Clone the Repository:

   git clone https://github.com/Priyadarshini-Padhi/Python-SQL-Project.git
   

2. Install Dependencies:

   pip install pandas mysql-connector-python

(Adjust according to your requirements file if present.)

3. Configure Database:

   Create a database and update connection credentials in the Python code.

4. Run the Python Scripts or Notebook:

   Execute the notebooks or scripts to connect, query, and process data

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License

This project is licensed under the MIT License — see the LICENSE file for details.