04 rhealpix

rHEALPixPandas key features¶

You can try out vgridpandas by using the cloud-computing platforms below without having to install anything on your computer:

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.

Install vgridpandas¶

Uncomment the following line to install vgridpandas.

In [1]:

# %pip install vgridpandas

# %pip install vgridpandas

Latlon to rHEALPix¶

In [2]:

import pandas as pd
from vgridpandas import rhealpixpandas
df = pd.read_csv('https://github.com/uber-web/kepler.gl-data/raw/master/nyctrips/data.csv')
df = df.head(100)
df = df.rename({'pickup_longitude': 'lon', 'pickup_latitude': 'lat'}, axis=1)[['lon', 'lat', 'passenger_count']]
resolution = 11
df = df.rhealpix.latlon2rhealpix(resolution)
df.head()

import pandas as pd from vgridpandas import rhealpixpandas df = pd.read_csv('https://github.com/uber-web/kepler.gl-data/raw/master/nyctrips/data.csv') df = df.head(100) df = df.rename({'pickup_longitude': 'lon', 'pickup_latitude': 'lat'}, axis=1)[['lon', 'lat', 'passenger_count']] resolution = 11 df = df.rhealpix.latlon2rhealpix(resolution) df.head()

Out[2]:

	lon	lat	passenger_count	rhealpix	rhealpix_res
0	-73.993896	40.750111	1	P01127645811	11
1	-73.976425	40.739811	1	P01127657310	11
2	-73.968704	40.754246	5	P01127654506	11
3	-73.863060	40.769581	5	P01127750407	11
4	-73.945541	40.779423	1	P01127706706	11

rHEALPix to geo boundary¶

In [3]:

df = df.rhealpix.rhealpix2geo()
df.head()

df = df.rhealpix.rhealpix2geo() df.head()

Out[3]:

	lon	lat	passenger_count	rhealpix	rhealpix_res	geometry
0	-73.993896	40.750111	1	P01127645811	11	POLYGON ((-73.99431 40.75041, -73.9938 40.7504...
1	-73.976425	40.739811	1	P01127657310	11	POLYGON ((-73.97653 40.74018, -73.97602 40.740...
2	-73.968704	40.754246	5	P01127654506	11	POLYGON ((-73.96891 40.75439, -73.9684 40.7543...
3	-73.863060	40.769581	5	P01127750407	11	POLYGON ((-73.86323 40.76975, -73.86272 40.769...
4	-73.945541	40.779423	1	P01127706706	11	POLYGON ((-73.94604 40.77998, -73.94554 40.779...

(Multi)Linestring/ (Multi)Polygon to rHEALPix¶

In [4]:

from vgridpandas import rhealpixpandas
import geopandas as gpd

gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson')
resolution = 11
gdf_polyfill = gdf.rhealpix.polyfill(resolution, compact = True, predicate = "intersects", explode = False)
gdf_polyfill.head()
gdf_polyfill = gdf_polyfill.rhealpix.rhealpix2geo("rhealpix")
gdf_polyfill.plot(edgecolor = "white")

from vgridpandas import rhealpixpandas import geopandas as gpd gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson') resolution = 11 gdf_polyfill = gdf.rhealpix.polyfill(resolution, compact = True, predicate = "intersects", explode = False) gdf_polyfill.head() gdf_polyfill = gdf_polyfill.rhealpix.rhealpix2geo("rhealpix") gdf_polyfill.plot(edgecolor = "white")

Out[4]:

<Axes: >

rHEALPix point binning¶

In [5]:

import pandas as pd
import geopandas as gpd
from vgridpandas import rhealpixpandas
resolution = 10
df = pd.read_csv("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/csv/dist1_pois.csv")
# df = gpd.read_file("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/dist1_pois.geojson")
df.head()
stats = "count"
df_bin = df.rhealpix.rhealpixbin(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)
)

import pandas as pd import geopandas as gpd from vgridpandas import rhealpixpandas resolution = 10 df = pd.read_csv("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/csv/dist1_pois.csv") # df = gpd.read_file("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/dist1_pois.geojson") df.head() stats = "count" df_bin = df.rhealpix.rhealpixbin(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) )

Out[5]:

<Axes: >