07 qtm

QTMPandas 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 QTM¶

In [ ]:

import pandas as pd
from vgridpandas import qtmpandas
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.qtm.latlon2qtm(resolution)
df.head()

import pandas as pd from vgridpandas import qtmpandas 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.qtm.latlon2qtm(resolution) df.head()

Out[ ]:

	lon	lat	passenger_count	qtm_res
qtm
2022030230110311	-73.993896	40.750111	1	16
2022030230113320	-73.976425	40.739811	1	16
2022030233221012	-73.968704	40.754246	5	16
2022030233011022	-73.863060	40.769581	5	16
2022030233223330	-73.945541	40.779423	1	16

QTM to geo boundary¶

In [3]:

df = df.qtm.qtm2geo()
df.head()

df = df.qtm.qtm2geo() df.head()

Out[3]:

	lon	lat	passenger_count	qtm_res	geometry
qtm
2022030230110311	-73.993896	40.750111	1	16	POLYGON ((-73.99364 40.74829, -73.99247 40.751...
2022030230113320	-73.976425	40.739811	1	16	POLYGON ((-73.97353 40.7373, -73.97236 40.7400...
2022030233221012	-73.968704	40.754246	5	16	POLYGON ((-73.97144 40.75378, -73.96647 40.753...
2022030233011022	-73.863060	40.769581	5	16	POLYGON ((-73.86128 40.76752, -73.86009 40.770...
2022030233223330	-73.945541	40.779423	1	16	POLYGON ((-73.94594 40.7785, -73.94097 40.7785...

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

In [4]:

import geopandas as gpd
from vgridpandas import qtmpandas

gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson')
resolution = 19
gdf_polyfill = gdf.qtm.polyfill(resolution, predicate = "intersects", compact = True, explode = True)
gdf_polyfill = gdf_polyfill.qtm.qtm2geo(qtm_column = "qtm")
gdf_polyfill.plot(edgecolor = "white")

import geopandas as gpd from vgridpandas import qtmpandas gdf = gpd.read_file('https://raw.githubusercontent.com/opengeoshub/vopendata/refs/heads/main/shape/polygon.geojson') resolution = 19 gdf_polyfill = gdf.qtm.polyfill(resolution, predicate = "intersects", compact = True, explode = True) gdf_polyfill = gdf_polyfill.qtm.qtm2geo(qtm_column = "qtm") gdf_polyfill.plot(edgecolor = "white")

Out[4]:

<Axes: >

QTM point binning¶

In [6]:

import geopandas as gpd
from vgridpandas import qtmpandas
resolution = 17

# 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.qtm.qtmbin(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 geopandas as gpd from vgridpandas import qtmpandas resolution = 17 # 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.qtm.qtmbin(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[6]:

<Axes: >