Data
US-Breweries

US-Breweries

active ARFF GPL 2 Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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  • Computer Systems Machine Learning
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Context While brainstorming ideas for a statistics project for a course last semester, the idea of utilizing data about microbreweries came up. Unfortunately after some exploration and thought, we scrapped the idea, but I've got this data to show for it anyway. Content Data was acquired from https://www.beermonthclub.com/ and contains information about breweries available on the site as of October 1st, 2019. Name, type of brewery, address, website, and state are among the data included. Code used to scrape is available at https://github.com/brkurzawa/brewpub-scraper Acknowledgements Thanks to beermonthclub for allowing the /brewpub section to be scraped. Inspiration This data alone isn't too inspiring, but maybe it could be used as the basis for an analysis project that looks at information such as yelp reviews, or number of links to a brewery's website.

6 features

brewery_namestring2308 unique values
0 missing
typestring12 unique values
0 missing
addressstring2330 unique values
0 missing
websitestring1369 unique values
8 missing
statestring51 unique values
0 missing
state_breweriesnumeric39 unique values
0 missing

19 properties

2407
Number of instances (rows) of the dataset.
6
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
8
Number of missing values in the dataset.
8
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
16.67
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.
0.33
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.06
Percentage of missing values.

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