ggplot图与观察结果不一致答案

【问题标题】：ggplot graph inconsistent with observationsggplot图与观察结果不一致
【发布时间】：2022-01-16 07:31:52
【问题描述】：

我尝试创建一个可视化 4 个变量演变的图表。然而，产生的 ggplot 与观察结果不一致。这里可能有什么问题？

Data <- data.frame(
Wind = c(236,325,470,615,647,821),
Hard_coal= c(591,811,667,681,532,344),
Gas= c(883,841,472,731,678,680),
Bio = c(883,841,811,731,678,680),
year= c("2015","2016","2017","2018","2019","2020"))


#create the plot

ggp <- ggplot(Data, aes(year))+geom_line(aes(y = Wind, (size = 1.5)), group = 1)+geom_line(aes(y = Hard_coal), group = 2)+geom_line(aes(y = Gas), group = 3)+geom_line(aes(y = Bio), group = 4)+scale_x_discrete()

#情节

ggp

【问题讨论】：

标签： r ggplot2

【解决方案1】：

您必须以tidy 格式重塑数据

library(tidyverse)

Data <- data.frame(
  Wind = c(236,325,470,615,647,821),
  Hard_coal= c(591,811,667,681,532,344),
  Gas= c(883,841,472,731,678,680),
  Bio = c(883,841,811,731,678,680),
  year= c("2015","2016","2017","2018","2019","2020"))

Data %>% 
  pivot_longer(-year) %>% 
  ggplot(aes(x = year, y = value, color = name, group = name, linetype = name)) +
  geom_line(size = 1.5)

^{由reprex package (v2.0.0) 于 2021 年 12 月 12 日创建}

【讨论】：

太棒了，谢谢！

【解决方案2】：

我用facet_wrap()调整了x轴

library(ggplot2)
library(reshape)

df_melt<-melt(df, id.vars=c("Year"))
df_melt<-as.data.frame(df_melt)


ggplot(df_melt, aes(x=Year, y=value, group=variable)) +  
  geom_line(aes(color=variable), size=3, show.legend = FALSE) +
  facet_wrap(~as.factor(variable) )+
  labs(x="Year", y="Value", title="") + 
  theme_bw()+
  theme(plot.title = element_text(hjust = 0.5,  face="bold", size=20, color="black")) + 
  theme(axis.title.x = element_text(family="Times", face="bold", size=16, color="black"))+
  theme(axis.title.y = element_text(family="Times", face="bold", size=16, color="black"))+
  theme(axis.text.x = element_text( hjust = 1,  face="bold", size=14, color="black") )+
  theme(axis.text.y = element_text( hjust = 1,  face="bold", size=14, color="black") )+
  theme(plot.title = element_text(hjust = 0.5))+
  theme(strip.text = element_text(family="Times", face="bold", size=16, color="black"))

您可能想要突出显示特定点，请使用geom_vline()

df_melt<-melt(df, id.vars=c("Year"))
df_melt<-as.data.frame(df_melt)


ggplot(df_melt, aes(x=Year, y=value, group=variable)) +  
  geom_line(aes(color=variable), size=3, show.legend = FALSE) +
  geom_vline(xintercept = c("2016", "2019"),col = "black", lwd = 2, lty=2) +
  facet_wrap(~as.factor(variable) )+
  labs(x="Year", y="Value", title="") + 
  theme_bw()+
  theme(plot.title = element_text(hjust = 0.5,  face="bold", size=20, color="black")) + 
  theme(axis.title.x = element_text(family="Times", face="bold", size=16, color="black"))+
  theme(axis.title.y = element_text(family="Times", face="bold", size=16, color="black"))+
  theme(axis.text.x = element_text( hjust = 1,  face="bold", size=14, color="black") )+
  theme(axis.text.y = element_text( hjust = 1,  face="bold", size=14, color="black") )+
  theme(plot.title = element_text(hjust = 0.5))+
  theme(strip.text = element_text(family="Times", face="bold", size=16, color="black"))

【讨论】：