我有一个数据集，其中 X 值是从 1 到千分之几的整数，并且想要绘制平均值 Y 以及围绕该平均值的离散度度量。我遇到的问题是缺少一些 X 值。因此，当使用 geom_line 和 geom_ribbon 函数时，绘图是连续的，我找不到办法让它在没有数据的地方留下空白。
这是一个可重现的模型示例。
data.1 <-read.csv(text = "
Treatment, X, Y_value
A,1,120.5
B,1,123.6
C,1,100.4
A,2,120.9
B,2,123.9
C,2,101.0
A,3,122.3
B,3,126.6
C,3,102.3
A,6,124.8
B,6,128.0
C,6,105.5
A,7,129.5
B,7,129.4
C,7,108.9
A,8,132.9
B,8,130.6
C,8,113.9
A,9,137.6
B,9,136.0
C,9,115.3
A,10,138.4
B,10,139.6
C,10,118.9
A,11,143.9
B,11,145.9
C,11,126.6
")
data.1 <- data.1 %>% group_by(X) %>% summarise(mean.y = mean(Y_value),
sd.y = sd(Y_value))
library(ggplot2)
ggplot(data.1, aes(X, mean.y)) +
geom_line(color="red") +
geom_ribbon(aes(ymin=mean.y-sd.y, ymax=mean.y+sd.y), alpha=0.4) +
scale_x_continuous(limits=c(0,11), breaks = c(seq(min(0),max(11), length.out = 12)))+
theme_bw() …我有这个样本数据集：
library(dplyr)
library(ggplot2)
data.1 <-read.csv(text = "
sampling_date,value
3/4/2021,5
3/5/2021,5.181818182
3/6/2021,5.363636364
3/7/2021,5.545454545
3/8/2021,5.727272727
3/9/2021,5.909090909
3/10/2021,6.090909091
3/11/2021,6.272727273
3/12/2021,6.454545455
3/13/2021,6.636363636
3/14/2021,6.818181818
3/15/2021,7
3/16/2021,7.047619048
3/17/2021,7.095238095
3/18/2021,7.142857143
3/19/2021,7.19047619
3/20/2021,7.238095238
3/21/2021,7.285714286
3/22/2021,7.333333333
3/23/2021,7.380952381
3/24/2021,7.428571429
3/25/2021,7.476190476
3/26/2021,7.523809524
3/27/2021,7.571428571
3/28/2021,7.619047619
3/29/2021,7.666666667
3/30/2021,7.714285714
3/31/2021,7.761904762
4/1/2021,7.80952381
4/2/2021,7.857142857
4/3/2021,7.904761905
4/4/2021,7.952380952
4/5/2021,8
4/6/2021,8
4/7/2021,8
4/8/2021,7.9
4/9/2021,7.8
4/10/2021,7.7
4/11/2021,7.6
4/12/2021,7.5
4/13/2021,7.4
4/14/2021,7.3
4/15/2021,7.2
4/16/2021,7.1
4/17/2021,7
4/18/2021,7.090909091
4/19/2021,7.181818182
4/20/2021,7.272727273
4/21/2021,7.363636364
4/22/2021,7.454545455
4/23/2021,7.545454545
4/24/2021,7.636363636
4/25/2021,7.727272727
4/26/2021,7.818181818
4/27/2021,7.909090909
4/28/2021,8
4/29/2021,8
4/30/2021,8
5/1/2021,8
5/2/2021,8
") %>% mutate(sampling_date = as.Date(sampling_date, format = '%m/%d/%Y'))
该图显示它达到最大值，然后下降，然后再次增加。
ggplot(data.1)+
geom_point(aes(x=sampling_date, y=value), …