削减数据和访问组以绘制百分比线 [英] Cut data and access groups to draw percentile lines
问题描述
我是R的新手，所以请保持柔和。
I'm very new to R so please be gentle.
我有一个包含时间戳和一些数据的数据集。
现在我想画一个图形，其中：
I have a dataset containing timestamps and some data. Now I'd like to draw a graph where:
- 数据按例如60分钟的间隔和
- 绘制一些百分位线。
我想拥有以时间为x轴，间隙为y轴的图。
我想像框线图一样，但为了得到更好的概述-因为我的测量距离很长-我想用线代替框
I'd like to have a graph with the time as x-axis and the gap as y-axis. I imagine something like boxplot but for a better overview - since I have a long measurement - instead of boxes I'd like to have lines that connect the
- 平均值，
- 3个百分点，
- 97个百分点，
- 100百分位数
- mean values,
- 3 percentiles,
- 97 percentiles and
- 100 percentiles
以下是示例数据：
> head(B, 10)
times gaps
1 2013-06-10 15:40:02.654168 1.426180
2 2013-06-10 15:40:18.936882 2.246462
3 2013-06-10 15:40:35.215668 3.227132
4 2013-06-10 15:40:48.328785 1.331284
5 2013-06-10 15:40:53.809485 1.294128
6 2013-06-10 15:41:04.027745 2.292671
7 2013-06-10 15:41:25.876519 1.293501
8 2013-06-10 15:41:42.929280 1.342166
9 2013-06-10 15:42:11.700626 3.203901
10 2013-06-10 15:42:23.059550 1.304467
我可以使用cut来分割数据：
I can use cut to divide the data:
C <- table(cut(B, breaks="hour"))
或
C <- data.frame(cut(B, breaks="hour"))
但是我该如何绘制图形呢？我不知道如何访问组的差距值。否则我可以
But how can I draw the graph form this? I don't know how to access the gap values of the groups. Otherwise I could
quantile(C$gaps, c(.03, .5, .97, 1))
在此先感谢您的帮助
Ramon
Thanks in advance for any help Ramon
推荐答案
实心问题。我一直在梳理头发，直到找到，它描述了 plyr 的一个有趣的特征。因此，该解决方案利用ggplot，plyr，reshape2-希望是R的一个很好的介绍。如果您需要整天添加剪切，还可以通过在ddply（）中添加变量来实现。
Solid question. I was pulling my hair out until I found this which described an interesting "feature" of plyr. So this solution utilizes ggplot, plyr, reshape2- hopefully a good intro to R. If you need to add cuts through days you can also do that by adding a variable in the ddply().
library(plyr)
library(reshape2)
library(ggplot2)
Hs <- read.table(
header=TRUE, text='
dates times gaps
1 2013-06-10 15:40:02.654168 1.426180
2 2013-06-10 15:40:18.936882 2.246462
3 2013-06-10 15:40:35.215668 3.227132
4 2013-06-10 15:40:48.328785 1.331284
5 2013-06-10 15:40:53.809485 1.294128
6 2013-06-10 15:41:04.027745 2.292671
7 2013-06-10 16:41:25.876519 1.293501
8 2013-06-10 16:41:42.929280 1.342166
9 2013-06-10 16:42:11.700626 3.203901
10 2013-06-10 16:42:23.059550 1.304467')
Hs$dates <- paste(Hs$date, Hs$times, sep = " ")
Hs$dates <- strptime(Hs$date, "%Y-%m-%d %H:%M:%S")
class(Hs$dates) # "POSIXlt" "POSIXt"
Hs$h1 <- Hs$dates$hour
Hs$dates <- as.POSIXct(strptime(Hs$date, "%Y-%m-%d %H:%M:%S"))
class(Hs$dates) # "POSIXct" "POSIXt"
library(ggplot2)
ggplot(Hs, aes(factor(h1), gaps)) +
geom_boxplot(fill="white", colour="darkgreen") # easy way! Traditional boxplot.
ggplot(Hs, aes(factor(h1), gaps)) + geom_boxplot() +
stat_boxplot(coef = 1.7, fill="white", colour="darkgreen")
我不知道添加 coef = 1.7是否对您有用-
，如果不继续创建通过汇总表获取的值
I don't know if adding "coef = 1.7" works for you- if not continue further to create the values via a summary table
cuts <- c(.03, .5, .97, 1)
x <- ddply(Hs, .(h1), function (x)
{summarise(x, y = quantile(x$gaps, cuts))})
x$cuts <- cuts
x <- dcast(x, h1 ~ cuts, value.var = "y")
x.melt <- melt(x, id.vars = "h1")
以下是您要求的行以及另一个只是为了好玩的箱形图。
Here are the lines you requested plus another box plot just for fun.
ggplot(x.melt, aes(x = h1, y = value, color = variable)) + geom_point(size = 5) +
geom_line() + scale_colour_brewer(palette="RdYlBu") + xlab("hours")
ggplot(x, aes(factor(h1), ymin = 0, lower = `0.03`, middle = `0.5`,
upper = `0.97`, ymax = `1`)) +
geom_boxplot(stat = "identity", fill="white", colour="darkgreen")
希望这会有所帮助。
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