Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/RIEEE-EDS/cdiac-dashboard
An interactive dashboard for exploring detailed carbon emission data from fossil fuels and the manufacture of cement.
https://github.com/RIEEE-EDS/cdiac-dashboard
anthropogenic-emissions carbon-dioxide carbon-emissions climate climate-change emissions fossil-fuels ghg-emissions ghg-inventory greenhouse-gas-emissions
Last synced: 3 months ago
JSON representation
An interactive dashboard for exploring detailed carbon emission data from fossil fuels and the manufacture of cement.
- Host: GitHub
- URL: https://github.com/RIEEE-EDS/cdiac-dashboard
- Owner: RIEEE-EDS
- Created: 2023-07-14T00:33:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-29T14:12:46.000Z (8 months ago)
- Last Synced: 2024-07-29T17:26:54.385Z (5 months ago)
- Topics: anthropogenic-emissions, carbon-dioxide, carbon-emissions, climate, climate-change, emissions, fossil-fuels, ghg-emissions, ghg-inventory, greenhouse-gas-emissions
- Language: Python
- Homepage: https://datadash.appstate.edu/cdiac
- Size: 11.2 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# CDIAC at AppState Dashboard
*Author: M. W. Hefner*
This is an interactive dashboard designed to explore detailed carbon emission data from the Carbon Dioxide Information Analysis Center (CDIAC) at Appalachian State University. It uses Dash, a Python web application framework, to render the user interface in a web browser.
For more information about CDIAC at AppState, please see the [CDIAC at AppState webpage](https://energy.appstate.edu/research/work-areas/cdiac-appstate) and the "about" markdown tab of this application. For more details on contributing to this project, refer to the RIEEE environmental data scientist.
## Table of Contents
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Cloning the Repository](#cloning-the-repository)
- [Setting Up the Environment](#setting-up-the-environment)
- [Application Structure](#application-structure)
- [Running the Application Locally](#running-the-application-locally)
- [Known Issues](#known-issues)
- [Updating the Dashboard Annually](#updating-the-dashboard-annually)
## Prerequisites
Before you start, make sure you have Python 3.11 installed on your system. You can download Python from [python.org](https://www.python.org/downloads/).
## Installation
### Cloning the Repository
To get started with the CDIAC Dashboard, you'll first need to clone the repository to your local machine:
```bash
git clone https://github.com/your-repository-url/cdiac-dashboard.git
cd cdiac-dashboard
```
### Setting Up the Environment
It's recommended to use a virtual environment to manage the dependencies and isolate the project:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
```
For pip to install properly, it is necessary to have Visual Studio developer tools installed. Otherwise, requirements can be installed effectively with conda or miniconda, **which is recommended for virtual environment management** for this very reason.
## Application Structure
The application is structured as follows:
- `application.py`: The main Python script to run the Dash app. It initializes the server and layouts.
- `components/`: Contains Python modules for different parts of the application like figures, tables, and utility functions.
- `assets/`: Stores static files like stylesheets, JavaScript files, images, and markdown files.
- `Dockerfile`: Contains commands to build a Docker image for the application.
- `requirements.txt`: Lists all Python libraries that the application depends on.
### Key Components
- `components/main_container.py`: The main container that encapsulates the entire Dash layout.
- `components/figures/`: This directory contains scripts to generate the interactive charts and figures used in the dashboard.
- `components/tables/`: Handles the table views and data interactions within the dashboard.
- `components/control_panel/`: Manages the interactive control elements like dropdowns and buttons, allowing users to filter and manipulate the data displayed in the dashboard.
- `components/content_display/`: Responsible for rendering the main content views such as graphs and data tables based on user interactions with the control panel.
- `components/utils/`: Contains application constants, links to local data, database connectivity, and other useful functionality.
## Running the Application Locally
To run the application locally, ensure you are in the project's root directory and have activated your virtual environment. Start the app by running:
```bash
python application.py
```
This will start the Dash server on `http://127.0.0.1:8050/`.
## Known Issues
- Both `assets/markdown/methodology.md` and `assets/markdown/about.md` pages need to be re-written and updated, respectively. Until they are, these options have been commented out in the navigation dropdown options.
- There is a bug with the time series by source code when deployed onto the server - nations are not showing, only regions; consider mapping line-marker attributes differently. Until this is fixed, the option has been commented out in the navigation dropdown options.
## Updating the Dashboard Annually
To update the dashboard data annually:
1. Modify `components/utils/constants.py` with the new year and data file name.
2. Replace the data file in `assets/data/` with the updated dataset.
3. Update `assets/markdown/download.md` with new download information.
4. After releasing on GitHub and publishing the updated application to Zonodo, update the **application's** Zonodo DOI badge in `components/utils/constants.py`.
After these steps, your application should reflect the latest data and be ready for use.