📊 Public Data Visualizer Dashboard

This Streamlit dashboard provides an interactive platform to explore key economic indicators sourced from the FRED (Federal Reserve Economic Data) API. Users can select various data series and filter by date range to visualize historical trends and gain insights into macroeconomic movements.

Click here to open the Dashboard!

✨ Features

• Multi-Series Data Visualization: Choose from a curated list of economic indicators (e.g., Federal Funds Rate, Real GDP, Unemployment Rate, CPI, 10-Year Treasury Yield).
• Interactive Time Series Plots: Utilizes Plotly Express to generate dynamic and zoomable line charts with built-in date range selectors.
• Date Range Filtering: Customize the displayed data period using intuitive date pickers.
• Real-time Data Fetching: Integrates with the FRED API to fetch up-to-date economic data.
• Data Preprocessing: Handles data type conversions and missing value imputation (e.g., converting '.' to NaN).
• Secure API Key Handling: Utilizes Streamlit's secrets.toml for secure management of API keys.
• Informative UI: Provides descriptions and source links for each economic indicator.

🛠️ Technologies Used

• Python
• Streamlit: For building the interactive web dashboard.
• Pandas: For efficient data manipulation, cleaning, and analysis.
• Requests: For making HTTP requests to the FRED API.
• Plotly Express: For creating rich, interactive data visualizations.
• Matplotlib / Seaborn (installed but primary focus is Plotly): General plotting utilities.

🔑 API Key Setup

1. Obtain a FRED API Key:

   • Go to https://fred.stlouisfed.org/docs/api/api_key.html and follow the instructions to request a free API key.

2. Store the key securely:

   • In your project directory (public_data_visualizer), create a folder named .streamlit if it doesn't exist.
   • Inside .streamlit, create a file named secrets.toml.
   • Add your FRED API key to secrets.toml like this:

     FRED_API_KEY = "YOUR_ACTUAL_FRED_API_KEY_HERE"

     (Replace YOUR_ACTUAL_FRED_API_KEY_HERE with your actual key.)

🚀 How to Run Locally

1. Clone the repository:

   git clone [https://github.com/belohith/publicdataviz](https://github.com/belohith/publicdataviz)
   cd publicdataviz

2. Create a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: `venv\Scripts\activate`

3. Install dependencies:

   pip install streamlit pandas requests plotly matplotlib seaborn

4. Run the Streamlit app:

   streamlit run app.py

5. The application will open in your web browser, usually at http://localhost:8501.

💡 Usage

1. Select an economic indicator from the dropdown menu in the sidebar.
2. Adjust the "Start Date" and "End Date" to filter the data.
3. Interact with the Plotly chart (zoom, pan, use range selectors).

✍️ Author

Lohith Bollineni

📄 License

This project is open source and available under the MIT License.