segregation.singlegroup.BoundarySpatialDissim

class segregation.singlegroup.BoundarySpatialDissim(data, group_pop_var, total_pop_var, w=None, standardize=True, **kwargs)[source]

Boundary-Area Dissimilarity 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

standardizebool

A condition for row standardisation of the weights matrices. If True, the values of cij in the formulas gets row standardized. For the sake of comparison, the seg R package of Hong, Seong-Yun, David O’Sullivan, and Yukio Sadahiro. “Implementing spatial segregation measures in R.” PloS one 9.11 (2014): e113767. works by default with row standardization.

Attributes:
statisticfloat

Boundary Area Index

core_dataa pandas DataFrame

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

Notes

The formula is based on Hong, Seong-Yun, David O’Sullivan, and Yukio Sadahiro. “Implementing spatial segregation measures in R.” PloS one 9.11 (2014): e113767.

Original paper by Wong, David WS. “Spatial indices of segregation.” Urban studies 30.3 (1993): 559-572.

References: [Hong et al., 2014] and [Wong, 1993].

__init__(data, group_pop_var, total_pop_var, w=None, standardize=True, **kwargs)[source]

Init.

Methods

__init__(data, group_pop_var, total_pop_var)

Init.