Data
Worldwide-Meat-Consumption

Worldwide-Meat-Consumption

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context Meat consumption is related to living standards, diet, livestock production and consumer prices, as well as macroeconomic uncertainty and shocks to GDP. Compared to other commodities, meat is characterised by high production costs and high output prices. Meat demand is associated with higher incomes and a shift - due to urbanisation - to food consumption changes that favour increased proteins from animal sources in diets. While the global meat industry provides food and a livelihood for billions of people, it also has significant environmental and health consequences for the planet. This dataset was refreshed in 2018, with world meat projections up to 2026 are presented for beef and veal, pig, poultry, and sheep. Meat consumption is measured in thousand tonnes of carcass weight (except for poultry expressed as ready to cook weight) and in kilograms of retail weight per capita. Carcass weight to retail weight conversion factors are: 0.7 for beef and veal, 0.78 for pig meat, and 0.88 for both sheep meat and poultry meat. Excludes Iceland but includes all EU 28 member countries. Content The csv file has 5 columns: LOCATION = the country code name SUBJECT = The type of meat(pig, beef, etc) TIME = the year the data was recorded MEASURE = the measure used to show the value VALUE = The value, according to the measure Acknowledgements https://data.oecd.org/agroutput/meat-consumption.htm OECD/FAO (2017), OECD-FAO Agricultural Outlook, OECD Agriculture statistics (database). doi: dx.doi.org/10.1787/agr-outl-data-en (Accessed on 24 January 2018) Inspiration Ask questions such as: What country had the most meat consumption? What years had the most worldwide meat consumption? Is there any correlation between the type of meat and the amount being consumed?

5 features

LOCATIONstring48 unique values
0 missing
SUBJECTstring4 unique values
0 missing
MEASUREstring2 unique values
0 missing
TIMEnumeric37 unique values
0 missing
Valuenumeric11383 unique values
0 missing

19 properties

13760
Number of instances (rows) of the dataset.
5
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
2
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
40
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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