03 a5

A5Pandas key features¶

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

Install vgridpandas¶

In [1]:

# %pip install vgridpandas

# %pip install vgridpandas

Latlong to A5¶

In [2]:

import pandas as pd
from vgridpandas import a5pandas
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 = 16
df = df.a5.latlon2a5(resolution)
df.head()

import pandas as pd from vgridpandas import a5pandas 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 = 16 df = df.a5.latlon2a5(resolution) df.head()

Out[2]:

	lon	lat	passenger_count	a5_res
a5
2610738938000000	-73.993896	40.750111	1	16
2610762d18000000	-73.976425	40.739811	1	16
26107685e8000000	-73.968704	40.754246	5	16
26107bde88000000	-73.863060	40.769581	5	16
2610730008000000	-73.945541	40.779423	1	16

A5 to geo boundary¶

In [3]:

df = df.a5.a52geo()
df.head()

df = df.a5.a52geo() df.head()

Out[3]:

	lon	lat	passenger_count	a5_res	geometry
a5
2610738938000000	-73.993896	40.750111	1	16	POLYGON ((-73.9936 40.74975, -73.99276 40.7499...
2610762d18000000	-73.976425	40.739811	1	16	POLYGON ((-73.97742 40.73934, -73.97652 40.739...
26107685e8000000	-73.968704	40.754246	5	16	POLYGON ((-73.96812 40.75402, -73.96727 40.754...
26107bde88000000	-73.863060	40.769581	5	16	POLYGON ((-73.86343 40.76952, -73.86252 40.769...
2610730008000000	-73.945541	40.779423	1	16	POLYGON ((-73.9443 40.77974, -73.94521 40.7797...

(Multi)Linestring/ (Multi)Polygon to A5¶

In [4]:

import geopandas as gpd
from vgridpandas import a5pandas
gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson')
resolution = 16
gdf_polyfill = gdf.a5.polyfill(resolution, compact = False, predicate = "intersects", explode = True)
gdf_polyfill.head()
gdf_polyfill = gdf_polyfill.a5.a52geo("a5")
gdf_polyfill.plot(edgecolor = "white")

import geopandas as gpd from vgridpandas import a5pandas gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson') resolution = 16 gdf_polyfill = gdf.a5.polyfill(resolution, compact = False, predicate = "intersects", explode = True) gdf_polyfill.head() gdf_polyfill = gdf_polyfill.a5.a52geo("a5") gdf_polyfill.plot(edgecolor = "white")

Out[4]:

<Axes: >

A5 point binning¶

In [5]:

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")
# df = gpd.read_file("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/dist1_pois.geojson")
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)
)

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") # df = gpd.read_file("https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/dist1_pois.geojson") 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) )

Out[5]:

<Axes: >