Create block-level dataset to underlie analyses

[MaxGhenis]

Since state legislative districts are built from Census blocks, we should build a dataset at the block level that we can then aggregate as needed. It should have these columns:

• Block
• Block group
• Tract
• Upper state legislative district
• Lower state legislative district
• PUMA
• State
• Population*

* Population can probably be mapped from the 2010 Census, which has block group level population; this can then be allocated equally across blocks in a block group.

[nmrodelo]

Useful Hierarchy Diagram: https://www2.census.gov/geo/pdfs/reference/geodiagram.pdf

Data for linking Block -> Census Tract -> PUMA: https://www2.census.gov/geo/docs/maps-data/data/rel/2010_Census_Tract_to_2010_PUMA.txt

https://www.nhgis.org/user-resources/geographic-crosswalks

[MaxGhenis]

Data available is:

• Tract to PUMA
• Block to legislative district, where the block ID includes state (2 digits), county (3), tract (6), and block (4). Tract can be extracted from this.
• Population by block

End dataset:

• Block
• Block decennial Census population
• Census tract
• Legislative districts
• PUMA
• PUMA population (ACS)
• Block's adjusted population = block decennial population * ACS PUMA pop / sum(decennial population over blocks in PUMA), i.e. multiply by a PUMA/decennial adjustment factor

From here, our analysis will aggregate this dataset (outside this issue) to this level, which could have multiple rows both per PUMA and per leg district (the pair is the key):

• Legislative district (key)
• PUMA (key)
• Adjusted population (summed over blocks)