This week's dataset is a wine-enthusiast ratings dataset from Kaggle. H/t to Georgios Karamanis for sharing this week's dataset as an Issue on our GitHub! If you want to submit a dataset, please drop a link and some context as an issue. Thanks!
An article with some interesting graphs (different dataset) can be found here. They found some clear relationships, but it also appears that cost is factored into their rating system. How does the Wine Enthusiast ratings scale compare?
wine_ratings <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2019/2019-05-28/winemag-data-130k-v2.csv")
| variable | class | description |
|---|---|---|
| country | character | Country of origin |
| description | character | Flavors and taste profile as written by reviewer |
| designation | character | The vineyard within the winery where the grapes that made the wine are from |
| points | double | The number of points WineEnthusiast rated the wine on a scale of 1-100 (though they say they only post reviews for wines that score >=80) |
| price | double | The cost for a bottle of the wine |
| province | character | The province or state that the wine is from |
| region_1 | character | The wine growing area in a province or state (ie Napa) |
| taster_name | character | The taster/reviewer |
| title | character | The title of the wine review, which often contains the vintage (year) |
| variety | character | Grape type |
| winery | character | The winery that made the wine |