r语言 - 添加到 ggplot 平均值和 SD 图

Question

我想寻求帮助。 我正在尝试在一张图上绘制数据及其平均值和 SD 值。但是我收到此错误

eval(substitute(list(...((，_data， parent.frame((( 中的错误：
找不到对象 'x'

首先，我将数据划分为区间，并使用摘要计算区间的平均值和SD值。比我试图绘制数据点(该部分有效(并将平均值和 SD 值图添加到前一个图(这里我失败了(。

请帮助我解决此问题。

UPD：好的，我想我应该在ss数据集上使用stat_summary。只是目前不知道该怎么做。任何建议将不胜感激。

这是我的代码：

#Data
s <- data.frame(L5=rnorm(1686, mean=0.3, sd=1.5),
GLDAS=rnorm(1686, mean=0.25, sd=0.8))
#1 ) 
#Divide data into 0.02 intervals
breaks = seq(from = 0, to = max(s$GLDAS)+0.02, by = 0.02)  #intervals
s$group <- cut(s$GLDAS, 
breaks = breaks, 
labels = seq(from = 1, to = length(breaks)-1, by = 1), 
#create label
right = FALSE) 
#Assign labels to a value equal to the middle of the interval
pos <- seq(from = breaks[1]+0.02/2, to = max(breaks)-0.02/2, by = 0.02)
group <-  seq(from = 1, to = length(breaks)-1, by = 1)
poss <- cbind.data.frame(pos,group)
ss <- merge(s, poss, by = "group")
#Calculate summary
Summary <- ss %>% # 
group_by(pos) %>%   # the grouping variable
summarise(mean = mean(L5),  # calculates the mean of each group
sd = sd(L5), # calculates the standard deviation of each group
n = n(),  # calculates the sample size per group
SE = sd(L5)/sqrt(n())) # calculates the standard error of each group
2)        #Plot data points
p2 <- ggplot()+
geom_point(data = s, aes(x = GLDAS, y = L5)) +
#geom_smooth(method = "lm", se=FALSE, color="black",
#           formula = my.formula) +
stat_poly_eq(formula = my.formula, size = 4,
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~")),
parse = TRUE) +  geom_point()+
geom_abline(intercept=0, slope=1)+
xlim (0,0.6) + ylim(0,0.6) +  labs(x="GLDAS [mm/hr]", y="L5 [mm/hr]" ) +
theme(text = element_text(size=16))
3)        #plot mean and SD values
p2 + geom_line(data = Summary, aes(x=pos, y=mean), color='blue') +
geom_point(data = Summary, aes(x=pos, y=mean), color='blue')+
geom_errorbar(data = Summary, aes(ymin=mean-sd, ymax=mean+sd), width=.01,
position=position_dodge(0.005), color='blue')

Answer 1

我想我已经知道了，我不需要使用摘要，有内置函数。

p2 <- ggplot()+
geom_point(data = ss, aes(x = GLDAS, y = L5)) +
stat_poly_eq(formula = my.formula, size = 4,
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~")),
parse = TRUE) +  geom_point()+
geom_abline(intercept=0, slope=1)+
xlim (0,0.5) + ylim(0,0.5) +  labs(x="GLDAS [mm/hr]", y="L5 [mm/hr]" ) +
theme(text = element_text(size=16))
p <- p2 + stat_summary(data = ss, aes(x = pos, y = L5),
fun.y = 'mean', fun.ymin = function(x) 0, geom = 'point', 
position = 'dodge') +
stat_summary(data = ss, aes(x = pos, y = L5), 
fun.y = mean,
fun.ymin = function(y) mean(y) - sd(y), 
fun.ymax = function(y) mean(y) + sd(y), 
color = "red", 
geom ="pointrange",show.legend = FALSE)
p