corrplot：R 面板图中的 corrplot 函数

Question

我想创建一个包含由 corrplot() 创建的不同相关图的图形。 为此，一旦我创建了图，我将它们分配给一个变量并将它们与 ggpubr:ggarrange() 对齐，但是创建的单个变量的内容为 NULL，并且当齿轮范围（正确）创建图形时，内容为空.

library(corrplot)
library(psych)
library(ggpubr)

data(iris)

res_pearson.c_setosa<-iris%>%
  filter(Species=="setosa")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

corr.a<-corrplot(res_pearson.c_setosa$r[,1:3],
         type="lower", 
         order="original", 
         p.mat = res_pearson.c_setosa$p[,1:3], 
         sig.level = 0.05, 
         insig = "blank", 
         col=col4(10), 
         tl.pos = "ld",
         tl.cex = .8, 
         tl.srt=45, 
         tl.col = "black",
         cl.cex = .8)+
  my.theme


res_pearson.c_virginica<-iris%>%
  filter(Species=="virginica")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

corr.b<-corrplot(res_pearson.c_virginica$r[,1:3],
         type="lower", 
         order="original", 
         p.mat = res_pearson.c_virginica$p[,1:3], 
         sig.level = 0.05, 
         insig = "blank", 
         col=col4(10), 
         tl.pos = "ld",
         tl.cex = .8, 
         tl.srt=45, 
         tl.col = "black",
         cl.cex = .8)+
  my.theme

ggarrange(corr.a, corr.b,
          common.legend = TRUE,
          legend = "bottom",
          ncol = 9, nrow = 1)

在网上搜索了几次之后，似乎这是第一次有人尝试创建具有多个相关图的图形。

Answer 1

您可以使用此代码par(mfrow=c(1,2))并排绘制图形，如下所示：

library(corrplot)
library(psych)
library(ggpubr)
library(dplyr)

data(iris)

res_pearson.c_setosa<-iris%>%
  filter(Species=="setosa")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

par(mfrow=c(1,2))

corr.a<-corrplot(res_pearson.c_setosa$r[,1:3],
                 type="lower", 
                 order="original", 
                 p.mat = res_pearson.c_setosa$p[,1:3], 
                 sig.level = 0.05, 
                 insig = "blank", 
                 #col=col4(10), 
                 tl.pos = "ld",
                 tl.cex = .8, 
                 tl.srt=45, 
                 tl.col = "black",
                 cl.cex = .8)


res_pearson.c_virginica<-iris%>%
  filter(Species=="virginica")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

corr.b<-corrplot(res_pearson.c_virginica$r[,1:3],
                 type="lower", 
                 order="original", 
                 p.mat = res_pearson.c_virginica$p[,1:3], 
                 sig.level = 0.05, 
                 insig = "blank", 
                 #col=col4(10), 
                 tl.pos = "ld",
                 tl.cex = .8, 
                 tl.srt=45, 
                 tl.col = "black",
                 cl.cex = .8)

^{由reprex 包(v2.0.1) 于 2022-07-13 创建}