🌍 Commodity Dashboard with Proportional Symbol Map

This project is a Dash-based web application that visualizes commodity trading data across different countries. It features a proportional symbol map where the size of the circles is proportional to the total value of goods (totvalue) for each destination country. The dashboard allows users to filter the data by commodity type, destination country, and date range. The filtered data is displayed in a table, and the map is dynamically updated to reflect the filtered results.

🛠️ Features

Interactive Map: A world map with proportional circles showing the total value of goods shipped to each destination country.
Dynamic Filters:
- Commodity Type: Filter by specific commodities.
- Destination Country: Filter by specific destination countries.
- Date Range: Select a custom date range to filter the data.
Data Table: Display the filtered data in a table format.
Responsive Design: The dashboard resizes to fit different screen sizes.

🚀 How to Run the Project

1. Clone the Repository

First, clone this repository to your local machine:

git clone https://github.com/yourusername/commodity-dashboard.git
cd commodity-dashboard

2. Set up a Virtual Environment (Optional but Recommended)

It's good practice to use a virtual environment to manage dependencies:

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

3. Install Dependencies

Install the required Python packages from the requirements.txt file:

pip install -r requirements.txt

4. Run the Application

After installing the dependencies, you can run the app using:

python app.py

This will start the Dash server, and you can open the dashboard by navigating to http://127.0.0.1:8050/ in your web browser.

Alteranatively, the code is also available in app_notebook.ipynb.

5. Interact with the Dashboard

Use the dropdown filters and the date picker to filter the data.
The map will update to reflect the filtered results.
The filtered data is also displayed in a table below the map.

⚙️ Project Customization

Data: You can modify the data by replacing or editing the country_lat_long and commodity_codes dictionaries in the code.
Map Customization: The map projection, color schemes, and other layout elements can be customized using Plotly’s geo and scatter_geo options.

🧑‍💻 Technologies Used

Dash: A Python web framework for building analytical web applications.
Plotly: A graphing library to create interactive, web-ready visualizations.
Pandas: For data manipulation and analysis.
Faker: A library for generating fake data (used in generating random data for the dashboard).
Python 3.8+

barrychocolate/python_dashboard