📊 Datacamp Stats

Datacamp Stats is a modular Streamlit-based dashboard that analyzes learner engagement across Courses, Projects, and Tracks on DataCamp. It helps visualize learning behaviors, highlight popular technologies, and identify undervalued or overhyped content.

🚀 Currently supports HTML data downloaded from DataCamp Report Dashboard.

🔍 Dashboard Highlights

• Technologies Boosting Retention – Identifies technologies learners stick with the most.
• Top Courses & Tracks – Quick snapshot of popular learning paths.
• Quadrant Analysis – Scatter plot with completion vs start metrics:
  • Underrated Gems
  • Overhyped / Hard
  • Ideal Balance
  • Neither Here Nor There

🔮 Coming Soon

We’re expanding Datacamp Stats into a broader learner intelligence tool. Here’s what’s next:

1. 🧠 Personalized Learning Path Generator

• Automatically suggests next steps based on a user's past course completions
• Works with public profile data

2. 💼 Job-Matching via LinkedIn

• Upload or paste a job description
• Recommends most relevant DataCamp content based on skill requirements

These tools aim to make the dashboard not just reflective, but prescriptive — helping learners act on insights.

📦 Setup

1. Clone the repository:

   git clone https://github.com/your-username/datacamp-stats.git
   cd datacamp-stats

2. Install the required dependencies:

   pip install -r requirements.txt

3. Optional: Add your raw .html data files to the raw_data/ folder.
   Use the following naming convention for the files:

   • courses_N.html
   • projects_N.html
   • tracks_N.html

   where N can be any identifier (e.g., date or version number).
   Once added, process the data by running:

   python process_data.py

   This will extract the relevant data and generate CSVs in the data/ folder for use by the dashboard.

4. Start the Streamlit app:

   streamlit run app.py

🧠 Contributing

Feel free to fork, contribute, or raise issues! Whether it's a bug fix, design improvement, or a whole new feature, PRs are welcome.