A subset related to the white variant of the Portuguese "Vinho Verde" wine,
containing physicochemical information (fixed.acidity, volatile.acidity,
citric.acid, residual.sugar, chlorides, free.sulfur.dioxide,
total.sulfur.dioxide , density, pH, sulphates and alcohol)
and sensory (quality).
winequalityA data frame with 1,250 rows and 12 columns:
fixed acidity
volatile acidity
citric acid
residual sugar
chlorides
free sulfur dioxide
total sulfur dioxide
density
pH
sulphates
alcohol
median of at least 3 evaluations of wine quality carried out by experts, who evaluated them between 0 (very bad) and 10 (very excellent)
UCI Machine Learning Repository: https://archive.ics.uci.edu/dataset/186/wine+quality.
For more details, consult https://www.vinhoverde.pt/en/ or the reference Cortez et al. (2009).
Cortez, P., Cerdeira, A., Almeida, F., Matos, T., & Reis, J. (2009). Modeling wine preferences by data mining from physicochemical properties. Decision Support Systems, 47(4), 547-553.
str(winequality)
#> 'data.frame': 1250 obs. of 12 variables:
#> $ fixed.acidity : num 6.8 7.1 6.9 7.5 8.6 7.7 5.4 6.8 6.1 5.5 ...
#> $ volatile.acidity : num 0.37 0.24 0.32 0.23 0.36 0.28 0.59 0.16 0.28 0.28 ...
#> $ citric.acid : num 0.47 0.34 0.13 0.49 0.26 0.63 0.07 0.36 0.27 0.21 ...
#> $ residual.sugar : num 11.2 1.2 7.8 7.7 11.1 11.1 7 1.3 4.7 1.6 ...
#> $ chlorides : num 0.071 0.045 0.042 0.049 0.03 0.039 0.045 0.034 0.03 0.032 ...
#> $ free.sulfur.dioxide : num 44 6 11 61 43.5 58 36 32 56 23 ...
#> $ total.sulfur.dioxide: num 136 132 117 209 171 179 147 98 140 85 ...
#> $ density : num 0.997 0.991 0.996 0.994 0.995 ...
#> $ pH : num 2.98 3.16 3.23 3.14 3.03 3.08 3.34 3.02 3.16 3.42 ...
#> $ sulphates : num 0.88 0.46 0.37 0.3 0.49 0.44 0.57 0.58 0.42 0.42 ...
#> $ alcohol : num 9.2 11.2 9.2 11.1 12 8.8 9.7 11.3 12.5 12.5 ...
#> $ quality : int 5 4 5 7 5 4 6 6 8 5 ...