您可以尝试这些选项中的任何一个,将您的数据重新整形为 long 并创建和附加变量,以便您可以识别类型。这里使用tidyverse函数的代码:
library(ggplot2)
library(dplyr)
library(tidyr)
#Date
df <- data.frame(Month=c(rep('Mar',4),rep('Apr',4),rep('May',2)),
spec_type=c('vid_new','vid_return','phone_charge','phone_nocharge',
'vid_new','vid_return','phone_charge','phone_nocharge',
'vid_new','vid_return'),
Count=c(7,85,595,56,237,848,2958,274,205,1079))
#Plot 1
df %>% mutate(Month=factor(Month,levels = unique(Month),ordered = T)) %>%
mutate(Dup=spec_type) %>%
separate(Dup,c('Type','Class'),sep='_') %>% select(-Class) %>%
ggplot(aes(x=Type,y=Count,fill=spec_type))+
geom_bar(stat = 'identity',position = 'stack')+
facet_wrap(.~Month,strip.position = 'bottom')+
theme(strip.placement = 'outside',
strip.background = element_blank())
输出:
或者这个:
#Plot 2
df %>% mutate(Month=factor(Month,levels = unique(Month),ordered = T)) %>%
mutate(Dup=spec_type) %>%
separate(Dup,c('Type','Class'),sep='_') %>% select(-Class) %>%
ggplot(aes(x=Type,y=Count,fill=spec_type))+
geom_bar(stat = 'identity',position = 'fill')+
facet_wrap(.~Month,strip.position = 'bottom',scales = 'free')+
theme(strip.placement = 'outside',
strip.background = element_blank())
输出:
或者这个:
#Plot 3
df %>% mutate(Month=factor(Month,levels = unique(Month),ordered = T)) %>%
mutate(Dup=spec_type) %>%
separate(Dup,c('Type','Class'),sep='_') %>% select(-Class) %>%
ggplot(aes(x=Type,y=Count,fill=spec_type))+
geom_bar(stat = 'identity',position = position_dodge2(preserve = 'single'))+
facet_wrap(.~Month,strip.position = 'bottom',scales = 'free')+
theme(strip.placement = 'outside',
strip.background = element_blank())
输出:
为了按月查看,您可以使用facet_wrap() 并以智能方式放置标签。