Poster will be a review of the need for the pyplaces package, scope of the package, common usage with examples, and future scope.
Need: Datasets in the geoparquet format can often be hard to access for users(academics, planners) that aren't adapted to ingesting data using Apache Arrow or SQL(via DuckDB, etc). This package bridges that gap by providing a way to access these large datasets with one line of Python code with and address or bounding box.
Scope: Geoparquet datasets that are freely available. Currently: Overture Maps, Foursquare Open Places, and OSM Layercake(soon). pyplaces aims to allow users to access prior versions of these datasets as well.
Common usage: Each dataset has a suite of functions(get from bounding box, place or address), poster will contain common examples for a few of the datasets. Looking at the dataset schema is another common use. Advanced use for datasets with places: categories table for each places dataset can be searched via a find categories function that can be used to filter the places data. Basic examples mapped on folium(or other similar medium) will be included.
Future scope: non implemented features that are up and coming will also be listed