segregation.singlegroup.SpatialProximity

class segregation.singlegroup.SpatialProximity(data, group_pop_var, total_pop_var, alpha=0.6, beta=0.5, **kwargs)[source]

Spatial Proximity 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

alphafloat

A parameter that estimates the extent of the proximity within the same unit. Default value is 0.6

betafloat

A parameter that estimates the extent of the proximity within the same unit. Default value is 0.5

metricstring. Can be ‘euclidean’ or ‘haversine’. Default is ‘euclidean’.

The metric used for the distance between spatial units. If the projection of the CRS of the geopandas DataFrame field is in degrees, this should be set to ‘haversine’.

Attributes:
statisticfloat

Spatial Proximity Index

core_dataa pandas DataFrame

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

Notes

Based on Massey, Douglas S., and Nancy A. Denton. “The dimensions of residential segregation.” Social forces 67.2 (1988): 281-315.

The pairwise distance between unit i and itself is (alpha * area_of_unit_i) ^ beta.

Reference: [Massey and Denton, 1988].

__init__(data, group_pop_var, total_pop_var, alpha=0.6, beta=0.5, **kwargs)[source]

Init.

Methods

__init__(data, group_pop_var, total_pop_var)

Init.