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📊 Streamlit Dashboard Tutorial

Welcome to the Interactive Dashboard Tutorial using Streamlit! This project is designed to teach students the fundamentals of building interactive web dashboards with Python.

🎯 Learning Objectives

By the end of this tutorial, students will understand:

  1. Basic Streamlit Components: How to use widgets, layouts, and displays
  2. Data Visualization: Creating interactive charts and plots
  3. User Interface Design: Building intuitive dashboard layouts
  4. Data Analysis: Performing exploratory data analysis through interactive tools
  5. Code Organization: Structuring a Streamlit application

🚀 Quick Start

Prerequisites

  • Python 3.8 or higher
  • Basic knowledge of Python and pandas

Installation

  1. Clone or download this project

  2. Create a virtual environment (recommended):

    python -m venv streamlit_env
    source streamlit_env/bin/activate  # On Windows: streamlit_env\Scripts\activate
  3. Install dependencies:

    pip install streamlit pyplot
  4. Run the dashboard:

    streamlit run streamlit_dashboard_tutorial.py
  5. Open your browser to http://localhost:8501

Key Streamlit Concepts Demonstrated

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

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Class on Data Science in Practice

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