Data
Chocolate-Bar-Ratings

Chocolate-Bar-Ratings

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context Chocolate is one of the most popular candies in the world. Each year, residents of the United States collectively eat more than 2.8 billions pounds. However, not all chocolate bars are created equal! This dataset contains expert ratings of over 1,700 individual chocolate bars, along with information on their regional origin, percentage of cocoa, the variety of chocolate bean used and where the beans were grown. Flavors of Cacao Rating System: 5= Elite (Transcending beyond the ordinary limits) 4= Premium (Superior flavor development, character and style) 3= Satisfactory(3.0) to praiseworthy(3.75) (well made with special qualities) 2= Disappointing (Passable but contains at least one significant flaw) 1= Unpleasant (mostly unpalatable) Each chocolate is evaluated from a combination of both objective qualities and subjective interpretation. A rating here only represents an experience with one bar from one batch. Batch numbers, vintages and review dates are included in the database when known. The database is narrowly focused on plain dark chocolate with an aim of appreciating the flavors of the cacao when made into chocolate. The ratings do not reflect health benefits, social missions, or organic status. Flavor is the most important component of the Flavors of Cacao ratings. Diversity, balance, intensity and purity of flavors are all considered. It is possible for a straight forward single note chocolate to rate as high as a complex flavor profile that changes throughout. Genetics, terroir, post harvest techniques, processing and storage can all be discussed when considering the flavor component. Texture has a great impact on the overall experience and it is also possible for texture related issues to impact flavor. It is a good way to evaluate the makers vision, attention to detail and level of proficiency. Aftermelt is the experience after the chocolate has melted. Higher quality chocolate will linger and be long lasting and enjoyable. Since the aftermelt is the last impression you get from the chocolate, it receives equal importance in the overall rating. Overall Opinion is really where the ratings reflect a subjective opinion. Ideally it is my evaluation of whether or not the components above worked together and an opinion on the flavor development, character and style. It is also here where each chocolate can usually be summarized by the most prominent impressions that you would remember about each chocolate. Acknowledgements These ratings were compiled by Brady Brelinski, Founding Member of the Manhattan Chocolate Society. For up-to-date information, as well as additional content (including interviews with craft chocolate makers), please see his website: Flavors of Cacao Inspiration Where are the best cocoa beans grown? Which countries produce the highest-rated bars? Whats the relationship between cocoa solids percentage and rating?

9 features

Company__(Maker-if_known)string416 unique values
0 missing
Specific_Bean_Origin_or_Bar_Namestring1039 unique values
0 missing
REFnumeric440 unique values
0 missing
Review_Datenumeric12 unique values
0 missing
Cocoa_Percentstring45 unique values
0 missing
Company_Locationstring60 unique values
0 missing
Ratingnumeric13 unique values
0 missing
Bean_Typestring40 unique values
888 missing
Broad_Bean_Originstring99 unique values
74 missing

19 properties

1795
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
962
Number of missing values in the dataset.
911
Number of instances with at least one value missing.
3
Number of numeric attributes.
0
Number of nominal attributes.
0.01
Number of attributes divided by the number of instances.
33.33
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.
50.75
Percentage of instances having missing values.
Average class difference between consecutive instances.
5.95
Percentage of missing values.

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