These notebooks provide examples of how to use cuSpatial. Some of these notebooks are designed to be self-contained with the runtime version of the RAPIDS Docker Container and RAPIDS Nightly Docker Containers and can run on air-gapped systems, while others require an additional download. You can quickly get this container using the install guide from the RAPIDS.ai Getting Started page
For a good overview of how cuSpatial works,
- Read our docs: our precompiled docs (external link) or build the docs them locally yourself in the documentation tree,
- Read our introductory blog (external link)
- Run our python demos
| Notebook Title | Data set(s) | Notebook Description | External Download (Size) |
|---|---|---|---|
| NYC Taxi Years Correlation | NYC Taxi Yellow 01/2016, 01/2017, taxi zone data | Demonstrates using Point in Polygon to correlate the NYC Taxi datasets pre-2017 lat/lon locations with the post-2017 LocationID for cross format comparisons. |
Yes (~3GB) |
| Stop Sign Counting By Zipcode Boundary | Stop Sign Locations Zipcode Boundaries USA States Boundaries | Demonstrates Quadtree Point-in-Polygon to categorize stop signs by zipcode boundaries. | Yes (~1GB) |
| Taxi Dropoff Reverse Geocoding (GTC 2023) | National Address Database NYC Taxi Zones taxi2015.csv | Reverse Geocoding of 22GB of datasets in NYC delivered for GTC 2023 | Yes (~22GB) |
Each user is responsible for checking the content of datasets and the applicable licenses and determining if suitable for the intended use.
Many more examples can be found in the RAPIDS Notebooks Contrib repository, which contains community-maintained notebooks.