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Tilastokeskus
This dataset collection is an assembly of data tables sourced from the website of the Finnish agency, 'Tilastokeskuksen' (Statistics Finland). The collection includes statistical data about various regions in Finland. Each table in the collection offers a unique perspective, providing a comprehensive understanding of the subject matter. The data is organized in a table format, making it easy to interpret and analyze. As part of the collection, each table shares a relationship with the others, contributing to the overall understanding of the statistical areas under examination. The dataset was accessed through the 'Tilastokeskuksen palvelurajapinta (WFS)' (Statistics Finland's Service Interface), underscoring its reliability and accuracy. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).
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The table, which is part of a larger dataset collection, contains detailed data about AVI regions in Finland for the year 2013. This information is sourced from the Finnish website 'Tilastokeskus' (Statistics Finland). The table encompasses various types of information, including identification and geographical details.
Each row in the table represents a specific AVI region, identified by features such as a unique gid, and an avi code. The row also includes the official name of the region in multiple languages.
The geographical information about these regions is presented in several formats, including GeoJSON and Geotext. These geographic details can be used for geospatial data analytics. For example, the geom_centroid column provides the central point of the region, while the geom_center_x and geom_center_y columns provide the longitude and latitude coordinates respectively, all presented using WGS 84 coordinate reference system, with the axis order being longitude first, followed by latitude.
Each data entry includes the date it was extracted from the source, as well as a row number. These two columns, '_extract_date' and '_row_number', together uniquely identify each row.
This data can be utilized in a number of ways in data analytics. For example, the geographical data can be used to visualize the spatial distribution of the AVI regions, or to analyze spatial relationships and patterns. The data can also be used to track changes in the AVI regions over time, based on the extraction date of the data.
