Explore how the IT job market is evolving by analyzing LinkedIn job postings.
We track job role trends, in-demand skills, salary distributions, and location-based demand using real-world data.

📊 Dataset on Kaggle

• 🔍 Identify trending and declining IT roles over time
• 🧠 Discover the most in-demand skills (e.g., Python, AWS, SQL)
• 💰 Compare salary ranges by job title and geography
• 📍 Highlight hotspots for tech job demand

IT-TRENDING-JOBS/
│
├── notebooks/
│   ├── 1_data_load.ipynb        ← Load & inspect data
│   ├── 2_data_cleaning.ipynb    ← Clean missing/dirty data
│   └── 3_data_analysis.ipynb    ← Analyze roles, skills, salaries
│
├── scripts/
│   └── functions.py             ← Utility functions for reuse
│
├── main.ipynb                   ← Master pipeline notebook
├── .gitignore                   ← Ignore checkpoints, venv, etc.
├── README.md                    ← Project overview & usage
└── requirements.txt             ← Project dependencies

1. Clone the repo

git clone https://github.com/yourusername/IT-TRENDING-JOBS.git
cd IT-TRENDING-JOBS

2. (Optional) Create a virtual environment

python -m venv venv
source venv/bin/activate      # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Launch Jupyter Notebook

jupyter notebook

• 📈 Time-series plots of job postings by category (monthly/quarterly)
• 🧠 Top 10 in-demand skills
• 💰 Salary distribution by city and role
• 🌍 Location heatmaps showing tech job demand

Source: Kaggle – LinkedIn Job Postings
File Used: postings.csv

Key Columns:

• job_title
• location
• company
• posted_date
• salary_range
• skills
• description

Your Name
GitHub: @varsha199

This project is licensed under the MIT License.
Feel free to use, fork, or contribute!