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This repository was archived by the owner on Jul 15, 2024. It is now read-only.
select
gwb.PC6 as postcode,
gwb.huisnummer,
gwb.Buurt2019 as buurt_code,
brt.Buurtnaam_2019 as buurt_naam,
gwb.Wijk2019 as wijk_code,
wijk.Wijknaam_2019K_NAAM as wijk_naam,
gwb.Gemeente2019 as gemeente_code,
gem.Gemeentenaam2019 as gemeente_naam
from `dk-open-data.cbs.pc6hnr20190801_gwb` as gwb
left join `dk-open-data.cbs.buurt2019` as brt on brt.Buurtcode_2019 = gwb.Buurt2019
left join `dk-open-data.cbs.wijk2019` as wijk on wijk.Wijkcode2019 = gwb.Wijk2019
left join `dk-open-data.cbs.gem2019` as gem on gem.Gemcode2019 = gwb.Gemeente2019
For easy access, add
cbsdataset in projectdataverbinders-datamartwith following tables:Catalog
Kerncijfers wijken and buurten
Combine data from 2013 onwards for easy historical comparison. Taking 2013 here, because earlier data has different format, so we'll leave integration of those for later.
https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/wijk-en-buurtstatistieken
Nabijheidsstatistieken
Same as above, but then for nabijheidsstatistieken from 2006 onwards
https://www.cbs.nl/nl-nl/reeksen/nabijheidsstatistieken-per-wijk-buurt
Bevolkingsstatistieken per pc4
https://opendata.cbs.nl/statline/portal.html?_la=nl&_catalog=CBS&tableId=83502NED&_theme=266
Mapping pc6huisnummer tot buurten and wijken
Using this SQL query