在分类数据变量展示时，如果能在边缘展示直方图就更完美了。下面我们就来学习下用ggExtra来 添加边缘直方图（marginal histograms）。

环境配置

library(tidyverse)
library(ggExtra)
theme_set(theme_bw(16)) #设置背景色为dark-on-light，基础字体为16
library(palmerpenguins)
colnames(penguins)

## [1] "species"           "island"            "bill_length_mm"   
## [4] "bill_depth_mm"     "flipper_length_mm" "body_mass_g"      
## [7] "sex"               "year"

基础绘图

p1 <- penguins %>% 
  ggplot(aes(bill_length_mm,body_mass_g,color=species))+
  geom_point()+
  theme(legend.position = "none")
p1

边缘直方图

ggMarginal(p1,type = "histogram",groupColour = TRUE,groupFill = TRUE)

ggMarginal核心参数：

ggMarginal(p, data, x, y, type = c("density", "histogram", "boxplot", "violin", "densigram"), margins = c("both", "x", "y"), ..., groupColour = FALSE,groupFill = FALSE)

p: ggplot2 scatterplot对象，如果未提供，需要data,x和y

type:边缘图形展示的方式，有density,histogram,boxplot，densigram类型

margins:需要哪个边缘进行展示，x轴，y轴或者都展示

groupColour: 按照group着色

groupFill: 按照group填充

#当需要加图注时最好在左侧，这样显得比较合理，否则边缘图夹在中间，显得不太协调。
p2 <- penguins %>% 
  ggplot(aes(bill_length_mm,body_mass_g,color=species))+
  geom_point()+
  theme(legend.position = "left")
ggMarginal(p2,type = "histogram",groupColour = TRUE,groupFill = TRUE)

Session Info

sessionInfo()

## R version 4.0.3 (2020-10-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936 
## [2] LC_CTYPE=Chinese (Simplified)_China.936   
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C                              
## [5] LC_TIME=Chinese (Simplified)_China.936    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] palmerpenguins_0.1.0 ggExtra_0.9          forcats_0.5.0       
##  [4] stringr_1.4.0        dplyr_1.0.2          purrr_0.3.4         
##  [7] readr_1.4.0          tidyr_1.1.2          tibble_3.0.4        
## [10] ggplot2_3.3.2        tidyverse_1.3.0     
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.5        lubridate_1.7.9.2 assertthat_0.2.1  digest_0.6.27    
##  [5] mime_0.9          R6_2.5.0          cellranger_1.1.0  backports_1.2.0  
##  [9] reprex_0.3.0      evaluate_0.14     httr_1.4.2        pillar_1.4.7     
## [13] rlang_0.4.9       readxl_1.3.1      rstudioapi_0.13   miniUI_0.1.1.1   
## [17] rmarkdown_2.5     labeling_0.4.2    munsell_0.5.0     shiny_1.5.0      
## [21] broom_0.7.2       compiler_4.0.3    httpuv_1.5.4      modelr_0.1.8     
## [25] xfun_0.19         pkgconfig_2.0.3   htmltools_0.5.0   tidyselect_1.1.0 
## [29] fansi_0.4.1       crayon_1.3.4      dbplyr_2.0.0      withr_2.3.0      
## [33] later_1.1.0.1     grid_4.0.3        jsonlite_1.7.1    xtable_1.8-4     
## [37] gtable_0.3.0      lifecycle_0.2.0   DBI_1.1.0         magrittr_2.0.1   
## [41] scales_1.1.1      cli_2.2.0         stringi_1.5.3     farver_2.0.3     
## [45] fs_1.5.0          promises_1.1.1    xml2_1.3.2        ellipsis_0.3.1   
## [49] generics_0.1.0    vctrs_0.3.5       tools_4.0.3       glue_1.4.2       
## [53] hms_0.5.3         prettydoc_0.4.0   fastmap_1.0.1     yaml_2.2.1       
## [57] colorspace_2.0-0  rvest_0.3.6       knitr_1.30        haven_2.3.1

参考链接：

https://datavizpyr.com/how-to-make-scatterplot-with-marginal-histograms-in-r/