H3 expressions for Polars¶
Polars H3 brings fast, Polars-native H3 indexing, inspection, traversal, hierarchy, edge, vertex, and metric operations to your dataframes.
import polars as pl
import polars_h3 as plh3
df = pl.DataFrame(
{
"latitude": [37.7749],
"longitude": [-122.4194],
}
).with_columns(
h3_cell=plh3.latlng_to_cell(
"latitude",
"longitude",
resolution=7,
)
)
Why Polars H3?¶
- Polars-native expressions. Compose H3 operations inside
select,with_columns, lazy queries, and the rest of the Polars expression API. - Rust-backed execution. H3 operations run in the Polars plugin engine without Python-level row loops.
- Flexible cell representations. Use
UInt64,Int64, or string H3 indexes where supported. PreferUInt64in performance-sensitive pipelines. - Focused H3 coverage. Work with cells, hierarchy, traversal, directed edges, vertices, metrics, and WKT/WKB polygon coverage without requiring a Polars geometry dtype.
Find what you need¶
| If you want to… | Start here |
|---|---|
| Install the package and run a first query | Getting started |
| Understand expressions, index types, and function families | User guide |
| Look up a function signature or return type | API reference |
| Draw cells on an interactive map | Graphing |
Polars H3 is powered by h3o and built for the Polars ecosystem.