Agricultural Productivity Dataset Collection

Tables

• Agricultural Productivity by YearTSV

  This table contains data on agricultural productivity over different years. The data is sourced from the website of Luke, which originates from Finland (ISO country code: FI). The table includes information such as the extract date, row number, code, and label. The data in this table can be utilized in various data analytics scenarios, such as analyzing trends in agricultural productivity over time, comparing the productivity of different agricultural codes, and identifying patterns or anomalies in the productivity labels.

• Agricultural Productivity Fact from Luke (Finland)TSV

  This table contains data on agricultural productivity. The data is sourced from the web site of Luke, which is an organization in Finland (ISO country code: FI). The table includes columns such as the extraction date, row number, year, index 2005=100, and agricultural productivity. The data in this table can be used for various data analytics purposes, such as analyzing trends in agricultural productivity over time, comparing the agricultural productivity index across different years, and studying the relationship between agricultural productivity and other variables.

• Agricultural Productivity History from Luke in FinlandTSV

  This table contains the version history of the rows from the 'agricultural_productivity__fact' table. Each row in this table represents a different version of a row in the base table. The '_start_date' column indicates the date when the row was extracted from the data source, while the '_end_date' column indicates the date when a new version of the row was extracted. If the '_end_date' column value is null, it means that the row is the most recent version. The table is sourced from the website of 'Luke', which originates from the country with the ISO country code 'fi'. The data in this table can be utilized in data analytics to analyze the historical changes in agricultural productivity over time, identify trends and patterns, conduct time series analysis, compare productivity between...

• Agricultural Productivity Index (2005-100) - Luke (Finland)TSV

  This table, sourced from the website of Luke, contains data on agricultural productivity with a dimension index of 2005100. It provides information related to the extraction date, row number, product code, and label. The data can be utilized in various data analytics applications such as analyzing trends and patterns in agricultural productivity over time, identifying the most productive agricultural products based on their codes, and categorizing agricultural products based on their labels. The data source, 'Luke', is an organization based in Finland (ISO country code 'fi').

• Version History of Agricultural Productivity by Year (Luke - Finland)TSV

  This table contains the version history of agricultural productivity data by year. It is sourced from the web site of Luke, which originates from Finland (ISO country code: fi). The table contains information about the start and end dates of each data version, along with a row number, code, and label for each record. The data in this table can be utilized in data analytics to analyze trends in agricultural productivity over time, identify changes in productivity levels, track the evolution of specific codes or labels, and perform various other analyses related to agricultural productivity by year.

• Version History of Agricultural Productivity Index for Finland from LukeTSV

  This table contains the version history of agricultural productivity data. It is sourced from the website of Luke, an organization based in Finland. The data provides information on various agricultural indexes. The table includes columns such as '_start_date' and '_end_date', which represent the extraction dates of each row from the data source. Additionally, the table contains columns '_row_number', 'code', and 'label' to identify and describe different indexes. The data in this table can be utilized for data analytics purposes, such as tracking changes in agricultural productivity over time, conducting trend analysis, comparing indexes across different periods, and identifying patterns or anomalies in agricultural productivity data.