SQL + Python Integration — Employee HR Analysis

A data analysis project that connects Python to a MySQL database using mysql-connector-python, pulls employee data into a Pandas DataFrame, and performs HR analytics with Matplotlib visualizations.

Tech Stack

• Python
• MySQL + mysql-connector-python
• Pandas
• Matplotlib
• python-dotenv (secure credentials)

Database Schema

Table: employees

Column	Type	Description
emp_id	INT	Primary key, auto increment
name	VARCHAR(100)	Employee name
department	VARCHAR(50)	Department name
salary	INT	Monthly salary
joining_date	DATE	Date of joining
is_active	BOOLEAN	Employment status

Analyses Performed

• Average salary by department
• Department-wise employee headcount
• Salary range (max - min) per department
• Active vs inactive employees
• Employees who joined after 2021
• Top 3 highest paid employees

Key Concepts Used

• MySQL connection via mysql-connector-python
• Secure credentials using .env + python-dotenv
• SQL query execution from Python
• Converting query results to Pandas DataFrame
• .dt.year for datetime filtering
• .agg() for multiple aggregations
• Groupby, sort, filter operations

How to Run

1. Clone the repo
2. Install dependencies — run in terminal: pip install mysql-connector-python pandas matplotlib python-dotenv
3. Create .env file in project root and add: DB_PASSWORD=yourpassword
4. Run company_hr.sql in MySQL Workbench to set up the database
5. Open and run analysis.ipynb top to bottom

Important

Never commit your .env file. It is listed in .gitignore.