OpenML
Updated-Wine-Enthusiast-Reviews

Updated-Wine-Enthusiast-Reviews

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context I built it on https://www.kaggle.com/zynicide/wine-reviews updating the scraper fetching fresh data. Content All wine reviews from winemag.com for 2017-2020 years. Duplicates are cleared, vintage parsed from title. NV means non-vintage. Acknowledgments Thanks Zack Thoutt for the base scraper and original data

15 features

countrystring43 unique values
5 missing
descriptionstring81090 unique values
0 missing
designationstring29478 unique values
21321 missing
pointsnumeric21 unique values
0 missing
pricenumeric336 unique values
4647 missing
provincestring366 unique values
5 missing
region_1string1049 unique values
12913 missing
region_2string19 unique values
49894 missing
taster_namestring19 unique values
150 missing
taster_photostring19 unique values
150 missing
taster_twitter_handlestring16 unique values
1076 missing
titlestring80460 unique values
0 missing
varietystring708 unique values
0 missing
vintagestring56 unique values
0 missing
winerystring12832 unique values
0 missing
Show all 15 features

19 properties

NumberOfInstances
81115
Number of instances (rows) of the dataset.
NumberOfFeatures
15
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
90161
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
59110
Number of instances with at least one value missing.
NumberOfNumericFeatures
2
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
13.33
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
72.87
Percentage of instances having missing values.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfMissingValues
7.41
Percentage of missing values.
Show all 19 properties

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