Correlation visualisations
Correlation Visualisations
A useful way to visualise and explore features in a dataset is by looking at how different features correlate with each other. Supposed we have a dataset of wines:
> head(df)
fixed.acidity volatile.acidity citric.acid residual.sugar chlorides free.sulfur.dioxide total.sulfur.dioxide density pH sulphates alcohol quality type
1 7.4 0.70 0.00 1.9 0.076 11 34 0.9978 3.51 0.56 9.4 5 red
2 7.8 0.88 0.00 2.6 0.098 25 67 0.9968 3.20 0.68 9.8 5 red
3 7.8 0.76 0.04 2.3 0.092 15 54 0.9970 3.26 0.65 9.8 5 red
4 11.2 0.28 0.56 1.9 0.075 17 60 0.9980 3.16 0.58 9.8 6 red
5 7.4 0.70 0.00 1.9 0.076 11 34 0.9978 3.51 0.56 9.4 5 red
6 7.4 0.66 0.00 1.8 0.075 13 40 0.9978 3.51 0.56 9.4 5 red
> Its correlation matrix can be obtained by:
> corrplot(cor(df[, sapply(df, is.numeric)],use="complete.obs"), method = "number", type='upper')
> 