DissimilarityIndex

adrio.acs5.DissimilarityIndex(
    self,
    majority_pop,
    minority_pop,
    *,
    fix_insufficient_population=False,
    fix_missing_population=False,
    fix_not_computable=False,
)

Calculates the Dissimilarity Index using US Census ACS 5-Year Data (group B02001). The dissimilarity index is a measure of segregation comparing two races. Typically one compares a majority to a minority race and so the names of parameters reflect this, but this relationship between races involved isn’t strictly necessary. The numerical result can be interpreted as the percentage of “minority” individuals that would have to move in order for the geographic distribution of individuals within subdivisions of a location to match the distribution of individuals in the location as a whole. ACS5 data is compiled from surveys taken during a rolling five year period, and as such are estimates.

Data is available using CensusScope geographies, from StateScope down to TractScope. Data is loaded according to the scope’s year, from 2009 to 2023. This ADRIO does not support BlockGroupScope because we the calculation of the index requires loading data at a finer granularity than the target granularity, and there is no ACS5 data below block groups.

The result is an N-shaped array of floats.

Parameters

majority_pop: RaceCategory

The race category representing the majority population for the amount of segregation.

minority_pop: RaceCategory

The race category representing the minority population within the segregation analysis.

fix_insufficient_population: Fill[np.int64] | int | Callable[[], int] | Literal[False] = False

The method to use to fix values for which there were insufficient data to report (sentinel value: -666666666). The replacement is performed on the underlying population by race data.

fix_missing_population: Fill[np.int64] | int | Callable[[], int] | Literal[False] = False

The method to use to fix missing values. The replacement is performed on the underlying population by race data.

fix_not_computable: Fill[np.float64] | float | Callable[[], float] | Literal[False] = False

The method to use to fix values for which we cannot compute a value because population numbers cannot be loaded for one or more of the populations involved.

See Also

The ACS 5-Year documentation from the US Census, and general information about the dissimilarity index.

Attributes

result_format: ResultFormat[np.float64]

Information about the format of the ADRIO’s resulting data.

This is an abstract method.

Methods

Name	Description
estimate_data	Estimate the data usage for this ADRIO in a RUME.
with_context	Constructs a clone of this instance which has access to the given context.
inspect	Produce an inspection of the ADRIO’s data for the current context.
evaluate	Evaluates the ADRIO in the current context.