START team = node:teams('name:"Manchester United"') I started out with a query which grouped the data set by day and showed the opponents that were played on that day: For additional data, make an archived data request.As I mentioned in my last post I’m trying to get the hang of the WITH statement in neo4j’s cypher query language and I found another application when trying to work out which opponents teams played on certain days. Show archived data (generally quarterly data for the last 12 months. Summary information and metrics for listings in Bergamo (good for visualisations). For additional data, make an archived data request.) Bergamo, Lombardia, Italy 31 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Belize (good for visualisations). For additional data, make an archived data request.) Belize, Belize, Belize 30 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Beijing (good for visualisations). For additional data, make an archived data request.) Beijing, Beijing, China 29 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Barwon South West, Vic (good for visualisations). For additional data, make an archived data request.) Barwon South West, Vic, Victoria, Australia 29 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Barossa Valley (good for visualisations). For additional data, make an archived data request.) Barossa Valley, South Australia, Australia 29 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Barcelona (good for visualisations). For additional data, make an archived data request.) Barcelona, Catalonia, Spain 14 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Bangkok (good for visualisations). For additional data, make an archived data request.) Bangkok, Central Thailand, Thailand 28 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Austin (good for visualisations). For additional data, make an archived data request.) Austin, Texas, United States 16 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Athens (good for visualisations). For additional data, make an archived data request.) Athens, Attica, Greece 27 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Asheville (good for visualisations). For additional data, make an archived data request.) Asheville, North Carolina, United States 19 March, 2023 ( Explore) Country/City Summary information and metrics for listings in Antwerp (good for visualisations).
For additional data, make an archived data request.) Antwerp, Flemish Region, Belgium 29 March, 2023 ( Explore) Country/City GeoJSON file of neighbourhoods of the city. Sourced from city or open source GIS files.
Summary Review data and Listing ID (to facilitate time based analytics and visualisations linked to a listing). Summary information and metrics for listings in Amsterdam (good for visualisations). Data Downloads Amsterdam, North Holland, The Netherlands 09 March, 2023 ( Explore) Country/City This data is licensed under a Creative Commons Attribution 4.0 International License.
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Quarterly data for the last year for each region is available for free download on this page, or if you are interested in monthly or archived data, you could make an archived data request.
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