由于corrplot包画图存在一些问题，比如图像不美观，以及title显示不出，等等
于是有了ggplot2 的扩展系列
ggcorrplot包 专门画相关系数矩阵图： https://github.com/kassambara/ggcorrplot
GGally 包： 对ggplot2进行了更多的扩展，其中包括相关系数图： http://ggobi.github.io/ggally/index.html#alterations
ggcorrplot包
library(ggcorrplot)
library(purrr)
data(mtcars)
corr <- cor(mtcars) # 相关系数矩阵
corr %>% head()
#> mpg cyl disp hp drat wt
#> mpg 1.0000000 -0.8521620 -0.8475514 -0.7761684 0.6811719 -0.8676594
#> cyl -0.8521620 1.0000000 0.9020329 0.8324475 -0.6999381 0.7824958
#> disp -0.8475514 0.9020329 1.0000000 0.7909486 -0.7102139 0.8879799
#> hp -0.7761684 0.8324475 0.7909486 1.0000000 -0.4487591 0.6587479
#> drat 0.6811719 -0.6999381 -0.7102139 -0.4487591 1.0000000 -0.7124406
#> wt -0.8676594 0.7824958 0.8879799 0.6587479 -0.7124406 1.0000000
#> qsec vs am gear carb
#> mpg 0.41868403 0.6640389 0.5998324 0.4802848 -0.5509251
#> cyl -0.59124207 -0.8108118 -0.5226070 -0.4926866 0.5269883
#> disp -0.43369788 -0.7104159 -0.5912270 -0.5555692 0.3949769
#> hp -0.70822339 -0.7230967 -0.2432043 -0.1257043 0.7498125
#> drat 0.09120476 0.4402785 0.7127111 0.6996101 -0.0907898
#> wt -0.17471588 -0.5549157 -0.6924953 -0.5832870 0.4276059
# Compute a matrix of correlation p-values
p.mat <- cor_pmat(mtcars) # 计算矩阵之间的相关性p—值
p.mat %>% head()
#> mpg cyl disp hp drat
#> mpg 0.000000e+00 6.112687e-10 9.380327e-10 1.787835e-07 1.776240e-05
#> cyl 6.112687e-10 0.000000e+00 1.802838e-12 3.477861e-09 8.244636e-06
#> disp 9.380327e-10 1.802838e-12 0.000000e+00 7.142679e-08 5.282022e-06
#> hp 1.787835e-07 3.477861e-09 7.142679e-08 0.000000e+00 9.988772e-03
#> drat 1.776240e-05 8.244636e-06 5.282022e-06 9.988772e-03 0.000000e+00
#> wt 1.293959e-10 1.217567e-07 1.222320e-11 4.145827e-05 4.784260e-06
#> wt qsec vs am gear
#> mpg 1.293959e-10 1.708199e-02 3.415937e-05 2.850207e-04 5.400948e-03
#> cyl 1.217567e-07 3.660533e-04 1.843018e-08 2.151207e-03 4.173297e-03
#> disp 1.222320e-11 1.314404e-02 5.235012e-06 3.662114e-04 9.635921e-04
#> hp 4.145827e-05 5.766253e-06 2.940896e-06 1.798309e-01 4.930119e-01
#> drat 4.784260e-06 6.195826e-01 1.167553e-02 4.726790e-06 8.360110e-06
#> wt 0.000000e+00 3.388683e-01 9.798492e-04 1.125440e-05 4.586601e-04
#> carb
#> mpg 1.084446e-03
#> cyl 1.942340e-03
#> disp 2.526789e-02
#> hp 7.827810e-07
#> drat 6.211834e-01
#> wt 1.463861e-02
## 相关矩阵可视化
ggcorrplot(corr)# #method默认为square
ggcorrplot(corr, method = "circle")
## 重新排序相关矩阵
#### 使用分层聚类
ggcorrplot(corr, hc.order = TRUE, outline.col = "white")
## 相关图布局的类型
ggcorrplot(corr, hc.order = TRUE, type = "lower",outline.col = "white")#下三角矩阵图
ggcorrplot(corr, hc.order = TRUE, type = "upper",outline.col = "white")#上三角矩阵图
## 更改颜色以及主题
#### colors参数
ggcorrplot(corr, hc.order = TRUE, type = "lower",
outline.col = "white",
ggtheme = ggplot2::theme_gray,
colors = c("#6D9EC1", "white", "#E46726"))
## 添加相关系数
#### 设置参数lab = TRUE
ggcorrplot(corr, hc.order = TRUE, type = "lower",lab = TRUE)#添加相关系数, 设置参数lab = TRUE
## 增加显著性水平，不显著的话就不添加了
#### 设置参数p.mat
ggcorrplot(corr, hc.order = TRUE,type = "lower", p.mat = p.mat) # 增加显著性水平,设置参数p.mat
ggcorrplot(corr, p.mat = p.mat, hc.order=TRUE, type = "lower", insig = "blank")# 将不显著的色块设置成空白
## 可以添加标题，像ggplot2那样添加标题， 这样好看一些
ggcorrplot(corr)+ggtitle("mtcars的相关矩阵图")+ theme(plot.title = element_text(hjust = 0.5))
sessionInfo()
#> R version 4.0.2 (2020-06-22)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Mojave 10.14.5
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] zh_CN.UTF-8/zh_CN.UTF-8/zh_CN.UTF-8/C/zh_CN.UTF-8/zh_CN.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] purrr_0.3.4 ggcorrplot_0.1.3 ggplot2_3.3.2
#>
#> loaded via a namespace (and not attached):
#> [1] Rcpp_1.0.5 pillar_1.4.6 compiler_4.0.2 plyr_1.8.6
#> [5] tools_4.0.2 digest_0.6.25 evaluate_0.14 lifecycle_0.2.0
#> [9] tibble_3.0.3 gtable_0.3.0 pkgconfig_2.0.3 rlang_0.4.7
#> [13] yaml_2.2.1 blogdown_0.20 xfun_0.17 withr_2.2.0
#> [17] stringr_1.4.0 dplyr_1.0.1 knitr_1.29 generics_0.0.2
#> [21] vctrs_0.3.2 grid_4.0.2 tidyselect_1.1.0 glue_1.4.1
#> [25] R6_2.4.1 rmarkdown_2.3 bookdown_0.20 reshape2_1.4.4
#> [29] farver_2.0.3 magrittr_1.5 scales_1.1.1 ellipsis_0.3.1
#> [33] htmltools_0.5.0 colorspace_1.4-1 labeling_0.3 stringi_1.4.6
#> [37] munsell_0.5.0 crayon_1.3.4