segregation.singlegroup.HutchensSqrt

class segregation.singlegroup.HutchensSqrt(data, group_pop_var, total_pop_var, w=None, network=None, distance=None, decay=None, function='triangular', precompute=None, **kwargs)

Hutchens Square Root 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

wlibpysal.weights.KernelW, optional

lipysal spatial kernel weights object used to define an egohood

networkpandarm.Network

pandarm Network object representing the study area

distanceint

Maximum distance (in units of geodataframe CRS) to consider the extent of the egohood

decaystr

type of decay function to apply. Options include

precomputebool

Whether to precompute the pandarm Network object

Attributes:

statisticfloat

Hutchens Square Root Index

core_dataa pandas DataFrame

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

See also

segregation.rankorder.RankOrderSqrt

integrates this index across the thresholds of an ordered variable to form Reardon’s \(S^R\).

Notes

Based on Hutchens, Robert M. “One measure of segregation.” International Economic Review 45.2 (2004): 555-577.

Reference: [].

__init__(data, group_pop_var, total_pop_var, w=None, network=None, distance=None, decay=None, function='triangular', precompute=None, **kwargs)

Init.

Methods

__init__(data, group_pop_var, total_pop_var)

Init.