Question

我目前正试图在绘图中的两条线之间的阴影区域着色。这两行显示了95％-CI的上限和下限（手动计算）。由于数据是长格式，因此我不知道它是如何工作的。

非常感谢！

我的代码如下：

saisonEsiegFavgLT = data.frame(Saison0719,EsiegFavgT,ciTobergrenze,ciTuntergrenze,EsiegFavgL,ciLobergrenze,ciLuntergrenze)

saisonEsiegFavgLTlong = gather(saisonEsiegFavgLT, Variable,Wert,2:7)

ggplot(saisonEsiegFavgLTlong,aes(x=Saison0719,y=Wert, color=Variable))+ 
geom_line()+
geom_vline(xintercept=2011, size = 0.35)+
scale_y_continuous(name="Gewinnwahrscheinlichkeit",limits = c(0.55,0.775),breaks=c(0.55,0.575,0.6,0.6,0.625,0.65,0.675,0.7,0.725,0.75))+
scale_x_continuous(name = "Saison", limits = c(2007, 2018), breaks = c(2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018))+
ggtitle("Gewinnwahrscheinlichkeit mit Konfidenzintervall")+
theme(panel.background = element_rect(fill = "white", colour = "black"))+   theme(panel.grid.major = element_line(size = 0.25, linetype = 'solid', colour = "light grey"))+
theme(axis.ticks = element_line(size = 1))+
theme(plot.title = element_text(lineheight=.8, face="bold"))+  scale_color_manual(values=c("grey80","grey80","grey40","grey40","red","blue"))

saisonEsiegFavgLTlong <-
structure(list(Saison0719 = c(2007, 2008, 2009, 2010, 2011, 2012, 
2013, 2014, 2015, 2016, 2017, 2018, 2019, 2007, 2008, 2009, 2010, 
2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2007, 2008, 
2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 
2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 
2018, 2019, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 
2016, 2017, 2018, 2019, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 
2014, 2015, 2016, 2017, 2018, 2019), Variable = c("EsiegFavgT", 
"EsiegFavgT", "EsiegFavgT", "EsiegFavgT", "EsiegFavgT", "EsiegFavgT", 
"EsiegFavgT", "EsiegFavgT", "EsiegFavgT", "EsiegFavgT", "EsiegFavgT", 
"EsiegFavgT", "EsiegFavgT", "ciTobergrenze", "ciTobergrenze", 
"ciTobergrenze", "ciTobergrenze", "ciTobergrenze", "ciTobergrenze", 
"ciTobergrenze", "ciTobergrenze", "ciTobergrenze", "ciTobergrenze", 
"ciTobergrenze", "ciTobergrenze", "ciTobergrenze", "ciTuntergrenze", 
"ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", 
"ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", 
"ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", "ciTuntergrenze", 
"EsiegFavgL", "EsiegFavgL", "EsiegFavgL", "EsiegFavgL", "EsiegFavgL", 
"EsiegFavgL", "EsiegFavgL", "EsiegFavgL", "EsiegFavgL", "EsiegFavgL", 
"EsiegFavgL", "EsiegFavgL", "EsiegFavgL", "ciLobergrenze", "ciLobergrenze", 
"ciLobergrenze", "ciLobergrenze", "ciLobergrenze", "ciLobergrenze", 
"ciLobergrenze", "ciLobergrenze", "ciLobergrenze", "ciLobergrenze", 
"ciLobergrenze", "ciLobergrenze", "ciLobergrenze", "ciLuntergrenze", 
"ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze", 
"ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze", 
"ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze", "ciLuntergrenze"
), Wert = c(0.638927795928336, 0.698588187947984, 0.706230083587847, 
0.707126891565955, 0.699203318195154, 0.693360727135652, 0.687412868319888, 
0.687450746141389, 0.690637150540309, 0.693002300477765, 0.701409867328994, 
0.690955678315586, 0.701316603798209, 0.7380033, 0.7581055, 0.7336691, 
0.7160483, 0.7179448, 0.7002121, 0.69301, 0.6934737, 0.6974439, 
0.7000579, 0.7108203, 0.6982045, 0.746395, 0.5679567, 0.6614517, 
0.6942799, 0.6910243, 0.6915419, 0.6856829, 0.6764988, 0.6793202, 
0.6810342, 0.6876637, 0.6924067, 0.6801805, 0.6525103, 0.679381874197023, 
0.681149895302252, 0.680447320039109, 0.68006830661108, 0.67862952569516, 
0.678008783433529, 0.678318569398466, 0.680982606038272, 0.681764982799431, 
0.679404748114889, 0.682053794287606, 0.681870613272628, 0.68572137704311, 
0.694119, 0.6853184, 0.6824217, 0.6897519, 0.7081499, 0.6832167, 
0.7053931, 0.6974306, 0.6851235, 0.6929936, 0.7125557, 0.6946072, 
0.6966152, 0.668361, 0.6686594, 0.6772183, 0.6420841, 0.6562843, 
0.6715409, 0.665196, 0.6613874, 0.6657847, 0.6558008, 0.6683817, 
0.6762716, 0.6768077)), row.names = c(NA, -78L), class = "data.frame")

Answer 1

您需要的是geom_ribbon，为此，您需要定义ymin（下限）和ymax（上限）。现在，您无法从长格式中读取此信息。不确定要如何标记图形，因此，我展示的第一个解决方案是无需过多更改即可快速修复的问题：

# had to do this to get your data back
df<- spread(saisonEsiegFavgLTlong,Variable,Wert)
# put your L in one frame and T in another frame
# give each of them a group
df_L <- df[,c("Saison0719","EsiegFavgL","ciLobergrenze","ciLuntergrenze")]
colnames(df_L) <- c("Saison0719","EsiegFavg","obergrenze","untergrenze")
df_L$group = "EsiegFavgL"
df_T <- df[,c("Saison0719","EsiegFavgT","ciTobergrenze","ciTuntergrenze")]
colnames(df_T) <- c("Saison0719","EsiegFavg","obergrenze","untergrenze")
df_T$group = "EsiegFavgT"

# combine, and we create a similar group, used to label your CI
plotdf <- rbind(df_L,df_T)
plotdf$ci_group <- sub("EsiegFavg","CI_",plotdf$group)

#plot like before

ggplot(plotdf,aes(x=Saison0719,y=EsiegFavg))+
geom_line(aes(col=group)) + 
geom_ribbon(aes(ymin=untergrenze,ymax=obergrenze,fill=ci_group),
alpha=0.4,linetype="dotted",col="grey60") + 
scale_color_manual(values=c("red","blue"))+
scale_fill_manual(values=c("grey80","grey40"))

ContentType

该解决方案有点混乱，因此最好从正确的格式开始：

    class App extends React.Component {

      constructor(props) {
        super(props);
        this.state = {
          messageContent: 'placeholder'
        }
      }

      setMessage = (data) => {
        this.setState({messageContent : data});
      }

      render() {

        return (
          <div className="App">
            <button id='butt' onClick= {() => this.setMessage('test')} />
            <Notification message = {this.state.messageContent} />
          </div>
        );
      }

    }

    class Notification extends React.Component {

      render () {
        const {message} = this.props;
        return (
          <div id='noti'>
            {message}
          </div>
        )
      }

    }

线之间的阴影区域； ggplot

1 个答案: