34. 面积图绘制

---

清除当前环境中的变量

rm(list=ls())

设置工作目录

setwd("C:/Users/Dell/Desktop/R_Plots/34area/")

使用ggplot2包绘制面积图

# 加载所需的R包
library(ggplot2)

# 构建示例数据
xValue <- 1:50
yValue <- cumsum(rnorm(50))
data <- data.frame(xValue,yValue)
# 查看示例数据
head(data)
##   xValue      yValue
## 1      1  0.23272473
## 2      2 -0.43662890
## 3      3 -0.07695937
## 4      4 -1.64320298
## 5      5 -2.32700864
## 6      6 -3.02549140

# 使用geom_area()函数绘制基础面积图
ggplot(data, aes(x=xValue, y=yValue)) +
  geom_area()

image.png

# 添加填充颜色，边界线和点，更换主题
ggplot(data, aes(x=xValue, y=yValue)) +
  geom_area(fill="#69b3a2", alpha=0.6) +
  geom_line(color="black", size=1.5) +
  geom_point(size=3, color="red") +
  theme_minimal() +
  ggtitle("Evolution of something")

image.png

# 绘制堆叠面积图
library(dplyr)
## Warning: package 'dplyr' was built under R version 3.6.3
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

# 构建示例数据
time <- as.numeric(rep(seq(1,7),each=7))  # x Axis
value <- runif(49, 10, 100)               # y Axis
group <- rep(LETTERS[1:7],times=7)        # group, one shape per group
data <- data.frame(time, value, group)
head(data)
##   time    value group
## 1    1 89.38125     A
## 2    1 98.02650     B
## 3    1 89.63381     C
## 4    1 96.27630     D
## 5    1 44.17764     E
## 6    1 97.44857     F

# 绘制基础堆叠面积图
ggplot(data, aes(x=time, y=value, fill=group)) + 
  geom_area()

image.png

# 指定顺序进行堆叠
data$group <- factor(data$group, levels=c("B", "A", "D", "E", "G", "F", "C"))

# Plot again
ggplot(data, aes(x=time, y=value, fill=group)) + 
  geom_area(color="black",alpha=0.6,size=1) + theme_bw()

image.png

# 更换填充色和主题
library(viridis)
## Loading required package: viridisLite

ggplot(data, aes(x=time, y=value, fill=group)) + 
  geom_area(alpha=0.6 , size=.5, colour="white") +
  scale_fill_viridis(discrete = T) +
  theme_minimal() + 
  ggtitle("The race between ...")

image.png

# 进行分面展示
ggplot(data, aes(x=time, y=value, fill=group)) + 
  geom_area(alpha=0.6 , size=.8, colour="black") +
  scale_fill_viridis(option = "C",discrete = T) +
  theme_classic() + facet_wrap(.~group,ncol = 3)

image.png

sessionInfo()
## R version 3.6.0 (2019-04-26)
## 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] viridis_0.5.1     viridisLite_0.3.0 dplyr_1.0.2       ggplot2_3.3.2    
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.5       knitr_1.23       magrittr_1.5     tidyselect_1.1.0
##  [5] munsell_0.5.0    colorspace_1.4-1 R6_2.4.0         rlang_0.4.7     
##  [9] stringr_1.4.0    tools_3.6.0      grid_3.6.0       gtable_0.3.0    
## [13] xfun_0.8         withr_2.1.2      htmltools_0.3.6  yaml_2.2.0      
## [17] digest_0.6.20    lifecycle_0.2.0  tibble_2.1.3     crayon_1.3.4    
## [21] gridExtra_2.3    purrr_0.3.2      vctrs_0.3.2      glue_1.4.2      
## [25] evaluate_0.14    rmarkdown_1.13   labeling_0.3     stringi_1.4.3   
## [29] compiler_3.6.0   pillar_1.4.2     generics_0.0.2   scales_1.0.0    
## [33] pkgconfig_2.0.2