Welcome to the Interactive Dashboard Tutorial using Streamlit! This project is designed to teach students the fundamentals of building interactive web dashboards with Python.
By the end of this tutorial, students will understand:
- Basic Streamlit Components: How to use widgets, layouts, and displays
- Data Visualization: Creating interactive charts and plots
- User Interface Design: Building intuitive dashboard layouts
- Data Analysis: Performing exploratory data analysis through interactive tools
- Code Organization: Structuring a Streamlit application
- Python 3.8 or higher
- Basic knowledge of Python and pandas
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Clone or download this project
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Create a virtual environment (recommended):
python -m venv streamlit_env source streamlit_env/bin/activate # On Windows: streamlit_env\Scripts\activate
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Install dependencies:
pip install streamlit pyplot
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Run the dashboard:
streamlit run streamlit_dashboard_tutorial.py
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Open your browser to
http://localhost:8501
| Component | Purpose | Code Example |
|---|---|---|
st.selectbox() |
Dropdown selection | Dataset and feature selection |
st.multiselect() |
Multiple selections | Feature selection for analysis |
st.slider() |
Range selection | Number of features to display |
st.columns() |
Layout organization | Side-by-side visualizations |
st.tabs() |
Content organization | Different analysis sections |
st.metric() |
Key performance indicators | Dataset statistics |
@st.cache_data |
Performance optimization | Data loading caching |