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ggplot2优雅的给图形添加渐变背景
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❝本节来介绍如何给图形添加渐变色背景，通过两个案例来进行展示；数据及代码已经上传小编的VIP群,
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加载R包
library(tidyverse)
library(grid)
library(RColorBrewer)
library(ggh4x)
library(scales)
library(aplot)
导入数据
sports <- read_tsv("sports.xls")
数据清洗
plot_data <- sports %>%
select(exp_men, exp_women, sports) %>%
drop_na() %>%
filter(exp_men!= 0,exp_women!= 0) %>%
group_by(sports) %>%
summarise(mean_exp_men=mean(exp_men),
mean_exp_women=mean(exp_women)) %>%
mutate(mean_exp_diff=mean_exp_men - mean_exp_women) %>%
select(sports,mean_exp_diff) %>%
mutate(sports=fct_reorder(sports, mean_exp_diff),
less=as.factor(mean_exp_diff<0)) %>%
arrange(less,mean_exp_diff) %>%
rownames_to_column(var="group")
定义因子
plot_data$group <- factor(plot_data$group,levels =plot_data$group)
构建渐变色系
g <- rasterGrob(brewer.pal(n = 8,name = "RdBu")[5:8],width=unit(1,"npc"), height = unit(1,"npc"),
interpolate = TRUE)
h <- rasterGrob(blues9[1], width=unit(1,"npc"), height = unit(1,"npc"), interpolate = TRUE)
f<- rasterGrob(brewer.pal(n = 8,name = "RdBu")[3:4], width=unit(1,"npc"), height = unit(1,"npc"),
interpolate = TRUE)
数据可视化-1
p1 <- ggplot(data=plot_data,mapping=aes(x=mean_exp_diff,y=group,colour = less))+
annotation_custom(g,xmin=-Inf,xmax=Inf,ymin=0,ymax=11)+
annotation_custom(h,xmin=-Inf,xmax=Inf,ymin=11,ymax=22)+
annotation_custom(f, xmin=-Inf,xmax=Inf,ymin=22,ymax=Inf)+
geom_point(size=4) +
geom_segment(aes(yend=group,xend=0),size=1)+
scale_x_continuous(labels=unit_format(unit="K",scale=1e-3,sep=""),
limits=c(-600000,600000),expand=c(0,0),
guide = "axis_truncated") +
scale_colour_manual(values=c("#008080","#4b0082"))+
labs(x=NULL,y=NULL)+
theme_void()+
theme(axis.line.x = element_line(),
legend.position = "non")
数据可视化-2
p2 <- plot_data %>% select(1,2) %>% mutate(type="A",group=as.numeric(group)) %>%
mutate(type2=case_when(group <= 11 ~ "A",group > 11& group<=22 ~"B",
group > 22 ~"C")) %>%
ggplot(aes(type,group))+
annotation_custom(g,xmin=-Inf,xmax=Inf,ymin=0,ymax=11)+
annotation_custom(h,xmin=-Inf,xmax=Inf,ymin=11,ymax=22)+
annotation_custom(f, xmin=-Inf,xmax=Inf,ymin=22,ymax=Inf)+
geom_text(aes(type,group,label=sports,color=type2),size=4,show.legend = F)+
scale_colour_manual(values=c("#8C0C25","#008080","#4b0082"))+
theme_void()
拼图
p1 %>% insert_left(p2,width = .4)
数据可视化-3
❝上面是按分组分别进行了渐变色设置，下面介绍一种直接简单粗暴添加背景色的方法
❞
p1 <- ggplot(data=plot_data,mapping=aes(x=mean_exp_diff,y=group,colour = less))+
geom_point(size=4) +
geom_segment(aes(yend=group,xend=0),size=1)+
scale_x_continuous(labels=unit_format(unit="K",scale=1e-3,sep=""),
limits=c(-600000,600000),expand=c(0,0),
guide = "axis_truncated") +
scale_colour_manual(values=c("#008080","#4b0082"))+
labs(x=NULL,y=NULL)+
theme_void()+
theme(axis.line.x = element_line(),
legend.position = "non")
p2 <- plot_data %>% select(1,2) %>% mutate(type="A",group=as.numeric(group)) %>%
mutate(type2=case_when(group <= 11 ~ "A",group > 11& group<=22 ~"B",
group > 22 ~"C")) %>%
ggplot(aes(type,group))+
geom_text(aes(type,group,label=sports,color=type2),size=4,show.legend = F)+
scale_colour_manual(values=c("#8C0C25","#008080","#4b0082"))+
theme_void()
p1 %>% insert_left(p2,width = .4)
❝以上部分为图形构建内容，下面开始构建色系添加背景
❞
reds <- colorRampPalette(brewer.pal(11,"RdBu"))(21)
grid.raster(scales::alpha(reds, 0.5), width = unit(1, "npc"), height = unit(1,"npc"),interpolate = TRUE)
数据获取
❝本节介绍到此结束，可以看到通过渐变色背景的添加图形增加了一股朦胧感；「有需要获取本篇数据的欢迎转发此文档到朋友圈，30分钟后公众号后台截图给小编」,添加小编微信时请备注来意以便高效处理
❞