Based on data from NASA and NOAA, this project looks at the evolution of three of Earth's Vital Signs -- Surface Temperatures, Arctic Sea Ice Concentrations, Carbon Dioxide Levels -- indicating the rapid changes in global climate.
Part of the author's portfolio, Earth's Vital Signs is an end-to-end Data Science & Analytics project -- from ETL, data analysis & visualization to presenting the findings.
Datasets were downloaded from NASA and NOAA, most often in .HDF, a format to store and organize large amounts of data. Data was extracted and transformed using the netCDF4 library.
Data analysis and visualization was performed using Python's Numpy, Pandas and Matplotlib libraries.
The findings were presented as a website on top of a template designed by Creative Tim and hosted on Render.
- Clone the repository with the 'clone' command, or just download the zip.
$ git clone git@github.com:https://github.com/gavin-bauer/earth-vital-signs.git
- Download or Open your IDE (i.e. Atom) and start editing.
Jupyter notebooks are available for testing and reproducing analyses and visualizations in this folder and can be run directly in Google Colaboratory.
- Sign up for a Render account.
- Create a new Web Service on Render and grant Render permission to access the GitHub repository containing the project.
- On the deployment screen, pick a name for the website.
- Click Save Web Service. The website will begin building and should be live in a few minutes at the URL displayed in the Render dashboard.
- Python - Programming language
- Numpy, Pandas & Matplotlib - Data centric Python packages
- Atom - Text editor
- Google Colaboratory - Run Jupyter Notebooks in the cloud
- Render - Cloud platform to host static websites
- Gavin Bauer - Data Analyst of 5+ years experience | Current: 🦉@KeringGroup | Past: ⚡@Total, 🌱@YvesRocherFR
This project is licensed under the MIT License - see the LICENSE.md file for details
- NASA & NOAA for providing the datasets
- Creative Tim for providing the website template