R中春季缺少月份和蓝色阴影的ggplot数据？

Question

我有以下data.frame 缺少冬季月份（11 月、12 月、1 月和 2 月）。当我ggplot 数据时，即使没有冬季月份的数据，我也看到线路已连接。我想避免在图表上绘制那些缺失的月份。另外，我想为春季（3 月、4 月、5 月）画一个蓝色阴影，表示春季。

library(tidyverse)
library(lubridate)

DF <- data.frame(Date = seq(as.Date("2001-01-01"), to = as.Date("2005-12-31"), by = "day"),
                  Obs = runif(1826,1,5), Sim = runif(1826,1,5)) %>% 
   separate(Date, into = c("Year", "Month", "Day")) %>% 
  filter(between(Month, 3,10)) %>% 
  mutate(Date = make_date(Year, Month, Day))

ggplot(data = DF, aes(x = Date))+
  geom_line(aes(y = Sim, col = "red"))+
  geom_line(aes(y = Obs, col = "blue"))

所需的输出：我正在寻找如下图，其中春季以蓝色阴影突出显示。

Answer 1

试试这个方法：

library(tidyverse)
library(lubridate)
#Data
DF <- data.frame(Date = seq(as.Date("2001-01-01"), to = as.Date("2005-12-31"), by = "day"),
                 Obs = runif(1826,1,5), Sim = runif(1826,1,5)) %>% 
  separate(Date, into = c("Year", "Month", "Day")) %>% 
  filter(between(Month, 3,10)) %>% 
  mutate(Date = make_date(Year, Month, Day))
#Create springs var
DF <- DF %>% mutate(Spring=ifelse(Month %in% c('03','04','05'),'Spring',NA)) %>%
  filter(!Month %in% c('11','12'))
#Plot
ggplot(data = DF, aes(x = Date,group=Year))+
  geom_line(aes(y = Sim, col = "red"))+
  geom_line(aes(y = Obs, col = "blue"))+
  geom_bar(stat = 'identity',aes(x=Date,y=5,fill=Spring),alpha=0.25)+
  scale_color_manual(values=c('red','blue'),
                     labels=c('Sim','Obs'))+
  scale_alpha_manual(values=c(0.5,0.5))+
  scale_fill_manual(values=c('blue','pink'),
                    limits='Spring')+
  scale_y_continuous(limits = c(NA,5),expand = c(0,0))+
  scale_x_date(breaks = as.Date(paste0(unique(format(DF$Date,'%Y-%m')),'-01')),
               date_labels = '%Y-%m',expand = c(0.05,0))+
  theme_bw()+labs(color='',fill='')+
  theme(axis.text.x = element_text(angle=90),
        strip.background = element_blank(),
        strip.text = element_blank(),
        panel.spacing = unit(-0.5, "lines"),
        panel.border = element_blank())+
  facet_wrap(.~Year,scales = 'free_x',nrow = 1)

输出：