Data
Alcohol-Consumption-in-Russia-(1998-2016)

Alcohol-Consumption-in-Russia-(1998-2016)

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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Context This is Alcohol Consumption in Russia (1998-2016) Dataset. It contains values of consumption for wine, beer, vodka, brandy and champagne. Content Dataset has 1615 rows and 7 columns. Keys for columns: "year" - year (1998-2016) "region" - name of a federal subject of Russia. It could be oblast, republic, krai, autonomous okrug, federal city and a single autonomous oblast "wine" - sale of wine in litres by year per capita "beer" - sale of beer in litres by year per capita "vodka" - sale of vodka in litres by year per capita "champagne" - sale of champagne in litres by year per capita "brandy" - sale of brandy in litres by year per capita Acknowledgements (UIISS) - Unified interdepartmental information and statistical system Inspiration You can analyze the relationships between various years, find best regions by each feature and compare them.

7 features

yearnumeric19 unique values
0 missing
regionstring85 unique values
0 missing
winenumeric210 unique values
63 missing
beernumeric796 unique values
58 missing
vodkanumeric313 unique values
61 missing
champagnenumeric107 unique values
63 missing
brandynumeric76 unique values
66 missing

19 properties

1615
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
311
Number of missing values in the dataset.
66
Number of instances with at least one value missing.
6
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
85.71
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
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.
0
Percentage of binary attributes.
4.09
Percentage of instances having missing values.
Average class difference between consecutive instances.
2.75
Percentage of missing values.

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