DesignSafe developed and maintains the CyberInfrastructure for the Natural Hazards Engineering Research Infrastructure, NHERI, program. This webinar series covers the basics of scientific computing using the DesignSafe JupyterHub. The DesignSafe Data Depot contains more than 1 PB of data related to natural hazards. The DesignSafe JupyterHub facilitates interaction with the data in the cloud without requiring users to download large datasets.
The first webinar demonstrates how to access published datasets in the Data Depot through the JupyterHub, using an earthquake ground motion dataset as an example. We clean the data using Pandas, plot desired quantities using Matplotlib, and perform numerical computing using Numpy. The second webinar builds upon the first by applying advanced regression and machine learning methods to the dataset.
Maintained by Charlie Dey, University of Texas at Austin, and Scott J. Brandenberg, University of California, Los Angeles
- Webinar 1: Working with published data
- Using DesignSafe JupyterHub
- Interacting with data published in DesignSafe Data Depot
- Using Pandas to read CSV files and clean data
- Converting Pandas data into Numpy arrays
- Using Matplotlib to plot selected data
- Performing multi-linear regression using Numpy matrix operations
BSD 3-Clause License - See LICENSE
Webinar 1:
