vgridpandas 1.0.8

Integration of Vgrid DGGS into Pandas and GeoPandas

VgridPandas

VgridPandas - Integrates Vgrid DGGS with GeoPandas and Pandas, inspired by H3-Pandas by Daniel Jahn.

VgridPandas supports a wide range of DGGSs, including H3, S2, A5, rHEALPix, DGGAL, DGGRID, Open-EAGGR ISEA4T, ISEA3H, EASE-DGGS, QTM, OLC, Geohash, GEOREF, MGRS, TileCode, Quadkey, Maidenhead, and GARS.

Full VgridPandas DGGS documentation is available at vgridpandas document.

To work with Vgrid in Python or CLI, use vgrid package. Full Vgrid DGGS documentation is available at vgrid document.

To work with Vgrid DGGS in QGIS, install the Vgrid Plugin.

To visualize DGGS in Maplibre GL JS, try the vgrid-maplibre library.

For an interactive demo, visit the Vgrid Homepage.

Installation

pip

pip install vgridpandas --upgrade

Key Features

• Latlong to DGGS: Convert latitude and longitude coordinates into DGGS cell IDs.

• DGGS to geo boundary: Convert DGGS cell IDs into their corresponding geographic boundaries.

• (Multi)Linestring/ (Multi)Polygon to DGGS: Convert (Multi)Linestring/ (Multi)Polygon to DGGS, supporting compact option.

• DGGS binning: Aggregate points into DGGS cells, supporting common statistics (count, min, max, etc.) and category-based groups.

• DGGS resample: Cross-grid resampling (e.g. H3 to S2) is available in the companion vgrid package via dggsresample.

Usage examples

Latlong to DGGS

import pandas as pd
from vgridpandas import h3pandas
df = pd.DataFrame({'lat': [10, 11], 'lon': [106, 107]})
resolution = 10
df = df.h3.latlon2h3(resolution, lat_col = 'lat', lat_col = 'lon')
df

| h3              |   lat |   lon |
|-----------------|-------|-------|
| 8a65a212199ffff |    10 |   106 |
| 8a65b0b68237fff |    11 |   107 |

DGGS to geo

df = df.h3.h32geo()
df

| h3              |   lat |   lon | geometry        |
|-----------------|-------|-------|-----------------|
| 8a65a212199ffff |    10 |   106 | POLYGON ((...)) |
| 8a65b0b68237fff |    11 |   107 | POLYGON ((...)) |

(Multi)Linestring/ (Multi)Polygon to DGGS

import geopandas as gpd
from vgridpandas import s2pandas

gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/main/shape/polygon.geojson')
resolution = 18
gdf_polyfill = gdf.s2.polyfill(resolution, compact = True, predicate = "intersects")
gdf_polyfill.head()
gdf_polyfill = gdf_polyfill.s2.s22geo("s2")
gdf_polyfill.plot(edgecolor = "white")

DGGS Binning

import pandas as pd
import geopandas as gpd
from vgridpandas import a5pandas
resolution = 15
df = pd.read_csv("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/csv/dist1_pois.csv")
stats = "count"
df_bin = df.a5.a5bin(resolution=resolution, stats = stats, 
                    # numeric_column="confidence",
                    # category_column="category",
                    return_geometry=True)
df_bin.plot(
    column=stats,        # numeric column to base the colors on
    cmap='Spectral_r',   # color scheme (matplotlib colormap)
    legend=True,  
    linewidth=0.2         # boundary width (optional)
)

DGGS Resample

Cross-grid resampling (e.g. H3 to S2) is available in vgrid via dggsresample. See the vgrid documentation for CLI and Python API details.

Further examples

For more examples, see the example notebooks.