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simd2020v2_pw_scotland_quintile

PHS population-weighted quintile within scotland; 1 = most deprived

Table Type Nullable Category In the CSV export SQL Server type
history table (postcode_simd_history, SPD) int8 no PHS SIMD, population-weighted yes tinyint
main table (postcode_simd, SSPL) int8 no PHS SIMD, population-weighted yes tinyint

Provenance (the same in both tables)

Each table runs its own copy of the table-level checks, named .history. and .main..

Where it comes from

Input Field Condition Reaches the row by
PHS/simd2020v2_22062020.csv (pinned, SHA256 686bc9aa38b6…) SIMD2020V2CountryQuintile DataZone2011Code = DataZone

Scope: the row itself.

What was done to it: copied. Copied as published, 1 most deprived. (code: simd_ingest/core/phs.py: canonicalise_phs)

How it is checked (what each check tests; whether a build passed it is in that build's manifest.json["checks"])

  • source.hash.PHS/simd2020v2_22062020.csv: the pinned file's SHA256 equals the registry's: the bytes are exactly the ones reviewed
  • phs.2020v2.source.schema: the PHS file's header is the declared one
  • phs.2020v2.source.key_unique: each data zone appears once in the PHS file
  • cross.2020v2.same_zones: PHS and the Government publish the same data zones for the edition
  • join.<table>.phs.2020v2.every_record_matched: every record found its data zone in the edition: no empty cell
  • readback.<table>.attached_values: every attached value in the saved file is looked up again from the sources and equal
  • phs.2020v2.source.CountryQuintile.range: every published band is within its range
  • phs.2020v2.pw_scotland_quintile.monotone: after any inversion, the band never falls as the rank rises, within its geography
  • phs.2020v2.rank1_in_band1: the most deprived zone is in band 1 of every band: the direction is right
  • join.<table>.simd2020v2_pw_scotland_quintile.range: every joined band is within its range

Why: bands-are-looked-up, band-column-names-state-weighting