segregation.singlegroup.SpatialProxProf

class segregation.singlegroup.SpatialProxProf(data, group_pop_var, total_pop_var, w=None, m=1000, **kwargs)

Spatial Proximity Profile Index.

Parameters:

datapandas.DataFrame or geopandas.GeoDataFrame, required

dataframe or geodataframe if spatial index holding data for location of interest

group_pop_varstr, required

name of column on dataframe holding population totals for focal group

total_pop_varstr, required

name of column on dataframe holding total overall population

w: libpysal.weights.W

pysal spatial weights object measuring connectivity between geographic units. If nNne, a Queen object will be created

mint

a numeric value indicating the number of thresholds to be used. Default value is 1000. A large value of m creates a smoother-looking graph and a more precise spatial proximity profile value but slows down the calculation speed.

Notes

Based on Hong, Seong-Yun, and Yukio Sadahiro. “Measuring geographic segregation: a graph-based approach.” Journal of Geographical Systems 16.2 (2014): 211-231.

Reference: [Hong and Sadahiro, 2014].

Attributes:

statisticfloat

Spatial Prox Profile Index

core_dataa pandas DataFrame

A pandas DataFrame that contains the columns used to perform the estimate.

__init__(data, group_pop_var, total_pop_var, w=None, m=1000, **kwargs)

Init.

Methods

__init__(data, group_pop_var, total_pop_var)	Init.
plot()	Plot the Spatial Proximity Profile.

plot()

Plot the Spatial Proximity Profile.