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epymorph.adrio.lodes

ADRIOs that access the US Census LODES files for commuting data.

JobType module-attribute 

JobType = Literal[
    "All Jobs",
    "Primary Jobs",
    "All Private Jobs",
    "Private Primary Jobs",
    "All Federal Jobs",
    "Federal Primary Jobs",
]

A job type that LODES provides subtotals for.

AgeRange module-attribute 

AgeRange = Literal['29 and Under', '30_54', '55 and Over']

Age ranges that LODES provides subtotals for.

EarningRange module-attribute 

EarningRange = Literal[
    "$1250 and Under", "$1251_$3333", "$3333 and Over"
]

Earning ranges that LODES provides subtotals for.

Industry module-attribute 

Industry = Literal[
    "Goods Producing", "Trade Transport Utility", "Other"
]

Job industries that LODES provides subtotals for.

Commuters 

Commuters(
    *,
    year: int | None = None,
    job_type: JobType = "All Jobs",
)

Bases: _LodesADRIOMixin, ADRIO[int64, int64]

Loads data from the US Census Bureau's Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data product, version 8. LODES provides counts of individuals living in one location and working in another, and various subtotals are available.

The product aggregates to 2020 census blocks, so this ADRIO can work with scopes from state-granularity down to block-group-granularity. The geography year must be 2020, however the data itself is computed yearly from 2002 through 2022.

The result is an NxN matrix of integers, with residency location on the first axis and work location on the second axis.

Parameters:

  • year (int | None, default: None ) –

    The year for the commuting data. Defaults to the year in which the simulation time frame starts.

  • job_type (JobType, default: 'All Jobs' ) –

    The job category used to filter commuters.

CommutersByAge 

CommutersByAge(
    age_range: AgeRange,
    *,
    year: int | None = None,
    job_type: JobType = "All Jobs",
)

Bases: _LodesADRIOMixin, ADRIO[int64, int64]

Loads data from the US Census Bureau's Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data product, version 8. LODES provides counts of individuals living in one location and working in another, and various subtotals are available.

The product aggregates to 2020 census blocks, so this ADRIO can work with scopes from state-granularity down to block-group-granularity. The geography year must be 2020, however the data itself is computed yearly from 2002 through 2022.

This ADRIO filters by age groups of the workers. The result is an NxN matrix of integers, with residency location on the first axis and work location on the second axis.

Parameters:

  • age_range (AgeRange) –

    The age range used to filter commuters.

  • year (int | None, default: None ) –

    The year for the commuting data. Defaults to the year in which the simulation time frame starts.

  • job_type (JobType, default: 'All Jobs' ) –

    The job category used to filter commuters.

CommutersByEarnings 

CommutersByEarnings(
    earning_range: EarningRange,
    *,
    year: int | None = None,
    job_type: JobType = "All Jobs",
)

Bases: _LodesADRIOMixin, ADRIO[int64, int64]

Loads data from the US Census Bureau's Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data product, version 8. LODES provides counts of individuals living in one location and working in another, and various subtotals are available.

The product aggregates to 2020 census blocks, so this ADRIO can work with scopes from state-granularity down to block-group-granularity. The geography year must be 2020, however the data itself is computed yearly from 2002 through 2022.

This ADRIO filters by the monthly earning bracket of the workers. The result is an NxN matrix of integers, with residency location on the first axis and work location on the second axis.

Parameters:

  • earning_range (EarningRange) –

    The monthly earnings range used to filter commuters.

  • year (int | None, default: None ) –

    The year for the commuting data. Defaults to the year in which the simulation time frame starts.

  • job_type (JobType, default: 'All Jobs' ) –

    The job category used to filter commuters.

CommutersByIndustry 

CommutersByIndustry(
    industry: Industry,
    *,
    year: int | None = None,
    job_type: JobType = "All Jobs",
)

Bases: _LodesADRIOMixin, ADRIO[int64, int64]

Loads data from the US Census Bureau's Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data product, version 8. LODES provides counts of individuals living in one location and working in another, and various subtotals are available.

The product aggregates to 2020 census blocks, so this ADRIO can work with scopes from state-granularity down to block-group-granularity. The geography year must be 2020, however the data itself is computed yearly from 2002 through 2022.

This ADRIO filters by the job industry of the workers. The result is an NxN matrix of integers, with residency location on the first axis and work location on the second axis.

Parameters:

  • industry (Industry) –

    The industry used to filter commuters.

  • year (int | None, default: None ) –

    The year for the commuting data. Defaults to the year in which the simulation time frame starts.

  • job_type (JobType, default: 'All Jobs' ) –

    The job category used to filter commuters.