如果数据大于某个值，我想在我的图表中写一些条件统计数据。
在 Jack Ryan 的帮助下（Cut data and access groups to draw percentile lines），我可以创建以下脚本，将数据分组为小时并绘制结果：
# Read example data
A <- read.csv(url('http://people.ee.ethz.ch/~hoferr/download/data-20130812.csv'))
# Libraries
library(doBy)
library(ggplot2)
library(plyr)
library(reshape2)
library(MASS)
library(scales)
# Sample size function
give.n <- function(x){
return(c(y = min(x) - 0.2, label = length(x)))
}
# Calculate gaps
gaps <- rep(NA, length(A$Timestamp))
times <- A$Timestamp
loss <- A$pingLoss
gap.start <- 1
gap.end <- 1
for(i in 2:length(A$Timestamp))
{ #For all rows
if(is.na(A$pingRTT.ms.[i]))
{ #Currently no connection
if(!is.na(A$pingRTT.ms.[i-1]))
{ #Connection lost now
gap.start <- i
}
if(!is.na(A$pingRTT.ms.[i+1]))
{ # Connection restores next time
gap.end <- i+1
gaps[gap.start] <- as.numeric(A$Timestamp[gap.end]-A$Timestamp[gap.start], units="secs")
loss[gap.start] <- gap.end - gap.start
}
}
}
H <- data.frame(times, gaps, loss)
H <- H[complete.cases(H),]
C <- H
C$dates <- strptime(C$times, "%Y-%m-%d %H:%M:%S")
C$h1 <- C$dates$hour
# Calculate percentiles
cuts <- c(1, .75, .5, .25, 0)
c <- ddply(C, .(h1), function (x) { summarise(x, y = quantile(x$gaps, cuts)) } )
c$cuts <- cuts
c <- dcast(c, h1 ~ cuts, value.var = "y")
c.melt <- melt(c, id.vars = "h1")
p <- ggplot(c.h1.melt, aes(x = h1, y = value, color = variable)) +
geom_point(size = 4) +
stat_summary(fun.data = max.n, geom = "text", fun.y = max, colour = "red", angle = 90, size=4) +
scale_colour_brewer(palette="RdYlBu", name="Percentile", guide = guide_legend(reverse=TRUE)) +
scale_x_continuous(breaks=0:23, limits = c(0,23)) +
annotation_logticks(sides = "lr") +
theme_bw() +
scale_y_log10(breaks=c(1e0,1e1,1e2,1e3,1e4), labels = trans_format("log10", math_format(10^.x)), limits=c(1e0,1e4)) +
xlab("Hour of day") + ylab("Ping gaps [s]")
p
p <- ggplot(c.m1.melt, aes(x = m1/60, y = value, color = variable)) +
geom_point(size = 1) +
stat_summary(fun.data = give.n, geom = "text", fun.y = median, angle = 90, size=4) +
stat_summary(fun.data = max.n, geom = "text", fun.y = max, colour = "red", angle = 90, size=4) +
scale_colour_brewer(palette="RdYlBu", name="Percentile", guide = guide_legend(reverse=TRUE)) +
scale_x_continuous(breaks=0:23, limits = c(0,24)) +
annotation_logticks(sides = "lr") +
theme_bw() +
scale_y_log10(breaks=c(1e0,1e1,1e2,1e3,1e4), labels = trans_format("log10", math_format(10^.x)), limits=c(1e0,1e4)) +
xlab("Time of day") + ylab("Ping gaps [s]")
p
这将创建一个每小时分组的间隙图，其中最长间隙的长度写在数据点旁边：
下面是按分钟分组的图。这个数字是不可读的，为什么我想在间隔超过 5 分钟或仅针对十个最长间隔或类似情况时添加条件统计信息。
我试图将 stat 函数更改为
max.n.filt <- function(x){
filter = 300
if ( x > filter ) {
return(c(y = max(x) + 0.4, label = round(max(10^x),2)))
} else {
return(c(y=x, label = ""))
}
}
并将其用于按分钟分组的图。但我得到了这个错误：
Error in list_to_dataframe(res, attr(.data, "split_labels")) :
Results do not have equal lengths
In addition: There were 50 or more warnings (use warnings() to see the first 50)
Error in if (nrow(layer_data) == 0) return() : argument is of length zero
Calls: print ... print.ggplot -> ggplot_gtable -> Map -> mapply -> <Anonymous>
In addition: Warning message:
Removed 6 rows containing missing values (geom_point).
此外，在每小时图中，我想在间隙长度旁边写下每小时的样本数。我想我可以在 c 数据框中添加一个新列，但不幸的是我找不到这样做的方法。
很感谢任何形式的帮助。