Statistical Areas Municipal 1000K 2017 Dataset Collection
Source
Tilastokeskus
Description
This dataset collection comprises a set of data tables sourced from 'Tilastokeskus' (Statistics Finland), a website based in Finland. Each table is organized in a structured format, embodying a collection of related data in the form of columns and rows. The dataset collection encapsulates valuable statistical information, with data drawn from the Statistics Finland's web feature service (WFS). This makes the dataset collection a crucial resource for comprehensive analyses and research. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).
Keywords
No keywords
Municipalities 2017 (1:1 000 000) - Table from Finnish Statistical Dataset Collection 2017
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Description
The table is a component of a larger dataset that represents 'Municipalities 2017' on a scale of 1:1 000 000. The data was sourced from the 'Statistics Centre' (Tilastokeskus) in Finland. The table contains a range of columns, each serving a unique purpose in providing detailed and comprehensive information.
Key columns include '_extract_date' and '_row_number', which respectively provide the date of data extraction and the row number in the extracted data. Together, these columns uniquely identify each row of data.
The table also includes several geographic data columns, starting with 'geom_', which provide valuable information for geospatial data analytics. The geographic coordinates are presented using the WGS 84 coordinate reference system, with the axis order being longitude first, followed by latitude.
Other important columns include 'kunta', 'name', 'namn', 'nimi', and 'vuosi', providing municipality-specific details such as the municipality code, name in different languages and the year the data represents.
The data in this table could be utilized in various ways in data analytics. For instance, the geographic data can be used to visualize the distribution of municipalities across Finland, potentially revealing patterns in population distribution or other geographic trends. Furthermore, the '_extract_date' and '_row_number' can be used to track changes in the data over time, providing insights into the evolution of these municipalities. Finally, the municipality-specific details can be leveraged to perform comparative studies among different municipalities, or even to study the linguistic representation in these areas.