,并排序
#不同按照cos2大小设定颜色梯度,也可以设置alpha梯度
fviz_pca_var(wine.pca2,axes=c(1,2),
col.var = "cos2",
gradient.cols...",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
变量分组
#人为分组
bb<-as.factor(c(rep(c("soil","micro...)#score 可视化coord
fviz_pca_ind(wine.pca2, geom=c("point","text"),
addEllipses = T,...,只需要关注方向与位置
样本在变量同侧是具有高数值,反之则值低
fviz_pca_biplot(wine.pca2, axes = c(1,2),repel = F,...rep(c("soil","plant"),6),"plant"))
)%>%ggpar(xlab="PC1",ylab="PC2",title="PCA-Biplot