在R中的箱形图中添加不同的百分位数

本文介绍了在R中的箱形图中添加不同的百分位数的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述 我是R的新手，最近用它来制作一些BoxLots。我还在我的boxplot中添加了平均值和标准偏差。我想知道是否可以在不同的百分位数上添加某种刻度标记或圆圈。比方说，如果我想在每个HOUR boxplot中标记第85个，第90个百分点，有没有办法做到这一点？我的数据包括在每小时和一小时内以兆瓦为单位的一年的装载量。我的输出包括每个月每个小时24个箱形图。我每个月都在做一次，因为我不确定是否有办法一次运行所有96个（每个月，平日/周末，4个不同的区域）箱形图。 JANWD< -read.csv（C：\\我的电脑 \\ MWBox2.csv） JANWD.df< -data.frame（JANWD） JANWD.sub< -subset（JANWD.df，MONTH< 2& weekend ==NO） KeepCols< -c（Hour，Houston_Load） HWD< - JANWD.sub [，KeepCols] sd< -tapply （HWD $ Houston_Load，HWD $ Hour，sd）表示< -tapply（HWD $ Houston_Load，HWD $ Hour，mean） boxplot（Houston_Load〜Hour，data = HWD，xlab =WEEKDAY HOURS，ylab =MW Differnce，ylim = c（-10,20），smooth = TRUE，col =bisque，range = 0） points（sd，pch = 22，col =blue） points（means，pch = 23，col =red） ＃输出用于运行1月份boxplot的数据的子集休斯顿 str（HWD）'data.frame'：504 obs。 2个变量：`$小时：int 1 2 3 4 5 6 7 8 9 10 ...'`$ Houston_Load：num 1.922 2.747 -2.389 0.515 1.922 ...' ＃原始数据的$ OUTPUT str（JANWD）'data.frame'：8783 obs。 9个变量： $日期：因子w / 366个等级1/1/2012，1/10/2012，..：306 306 306 306 306 306 306 306 306 306 ... `$ Hour：int 1 2 3 4 5 6 7 8 9 10 ...'`$ MONTH：int 8 8 8 8 8 8 8 8 8 ...'`$周末：因子W / 2级别NO，YES：1 1 1 1 1 1 1 1 1 1''`$ TOTAL_LOAD：num 0.607 5.111 6.252 7.607 0.607 ...' $ $ Houston_Load：num -2.389 0.515 1.922 2.747 -2.389 ...'`$ North_Load：num 2.95 4.14 3.55 3.91 2.95 ...'`$ South_Load：num -0.108 0.267 0.54 0.638 - 0.108 ...'`$ West_Load：num 0.154 0.193 0.236 0.311 0.154 ...' 解决方案以下是一种使用 quantile（）来计算相关百分位数的方法。我使用 rug（）添加标记。 set.seed 1） X boxplot（X，yaxt =n） ##计算所需分位数 qntl ##将它们作为左边的 rug（qntl，side = 2，col =blue ，lwd = 2） ##添加方框和轴轴（2） box（） $ b 更新：为了响应OP提供 str（）输出，这里是一个类似于OP必须处理的数据的例子： set.seed（1）## make reproducible HWD< - data.frame（Hour = rep（0:23,10）， Houston_Load = rnorm（24 * 10）） 现在假设您希望每个小时的第85百分位和第90百分位数的分位数？如果是这样，我们需要按照前面显示的 Hour 并通过 quantile（）进行计算。 quants quantile，probs = c （0.85,0.9）） 给出： R> （HWD $ Houston_Load，列表（HWD $小时））， +分位数，probs = c（0.85,0.9）） R>数量 0 1 2 3 4 5 6 85％0.3576510 0.8633506 1.581443 0.2264709 0.4164411 0.2864026 1.053742 90％0.6116363 0.9273008 2.109248 0.4218297 0.5554147 0.4474140 1.366114 7 8 9 10 11 12 13 14 85％0.5352211 0.5175485 1.790593 1.394988 0.7280584 0.8578999 1.437778 1.087101 90％0.8625322 0.5969672 1.830352 1.519262 0.9399476 1.1401877 1.763725 1.102516 15 16 17 18 19 20 21 85％0.6855288 0.4874499 0.5493679 0.9754414 1.095362 0.7936225 1.824002 90％0.8737872 0.6121487 0.6078405 1.0990935 1.233637 0.9431199 2.175961 22 23 85％1.058648 0.6950166 90％1.145783 0.8436541 现在我们可以在箱形图的x个位置绘制标记 boxplot（Houston_Load〜Hour，data = HWD，axes = FALSE） xlocs< - 1： 24 ##在哪里绘制标记 tickl y1 = quants [，i]， x1 = rep（xlocs [i] + 0.15,2），y1 = quants [，i]， col = c （xlab =Hour，ylab =Houston Load）轴（1，at = xlocs， labels = xlocs - 1） axis（2） box（） legend（bottomleft，legend = paste（c（0.85，0.90），quantile） ， bty =n，lty =solid，lwd = 2，col = c（red，blue）） 得到的数字应该如下所示： I am failry new to R and recently used it to make some Boxplots. I also added the mean and standard deviation in my boxplot. I was wondering if i could add some kind of tick mark or circle in different percentile as well. Let's say if i want to mark the 85th, $ 90th percentile in each HOUR boxplot, is there a way to do this? My data consist of a year worth of loads in MW in each hour & My output consist of 24 boxplots for each hour for each month. I am doing each month at a time because i am not sure if there is a way to run all 96(Each month, weekday/weekend , for 4 different zones) boxplots at once. Thanks in advance for help.JANWD <-read.csv("C:\\My Directory\\MWBox2.csv")JANWD.df<-data.frame(JANWD)JANWD.sub <-subset(JANWD.df, MONTH < 2 & weekend == "NO")KeepCols <-c("Hour" , "Houston_Load")HWD <- JANWD.sub[ ,KeepCols]sd <-tapply(HWD$Houston_Load, HWD$Hour, sd)means <-tapply(HWD$Houston_Load, HWD$Hour, mean)boxplot(Houston_Load ~ Hour, data=HWD, xlab="WEEKDAY HOURS", ylab="MW Differnce", ylim= c(-10, 20), smooth=TRUE ,col ="bisque", range=0)points(sd, pch = 22, col= "blue")points(means, pch=23, col ="red")#Output of the subset of data used to run boxplot for month january in Houston str(HWD)'data.frame': 504 obs. of 2 variables: `$ Hour : int 1 2 3 4 5 6 7 8 9 10 ...' `$ Houston_Load: num 1.922 2.747 -2.389 0.515 1.922 ...'#OUTPUT of the original datastr(JANWD)'data.frame': 8783 obs. of 9 variables: $ Date : Factor w/ 366 levels "1/1/2012","1/10/2012",..: 306 306 306 306 306 306 306 306 306 306 ... `$ Hour : int 1 2 3 4 5 6 7 8 9 10 ...'` $ MONTH : int 8 8 8 8 8 8 8 8 8 8 ...' `$ weekend : Factor w/ 2 levels "NO","YES": 1 1 1 1 1 1 1 1 1 1 ...' `$ TOTAL_LOAD : num 0.607 5.111 6.252 7.607 0.607 ...' `$ Houston_Load: num -2.389 0.515 1.922 2.747 -2.389 ...' `$ North_Load : num 2.95 4.14 3.55 3.91 2.95 ...' `$ South_Load : num -0.108 0.267 0.54 0.638 -0.108 ...' `$ West_Load : num 0.154 0.193 0.236 0.311 0.154 ...' 解决方案 Here is one way, using quantile() to compute the relevant percentiles for you. I add the marks using rug().set.seed(1)X <- rnorm(200)boxplot(X, yaxt = "n")## compute the required quantilesqntl <- quantile(X, probs = c(0.85, 0.90))## add them as a rgu plot to the left hand siderug(qntl, side = 2, col = "blue", lwd = 2)## add the box and axesaxis(2)box()Update: In response to the OP providing str() output, here is an example similar to the data that the OP has to hand:set.seed(1) ## make reproducibleHWD <- data.frame(Hour = rep(0:23, 10), Houston_Load = rnorm(24*10))Now get I presume you want ticks at 85th and 90th percentiles for each Hour? If so we need to split the data by Hour and compute via quantile() as I showed earlier:quants <- sapply(split(HWD$Houston_Load, list(HWD$Hour)), quantile, probs = c(0.85, 0.9))which gives:R> quants <- sapply(split(HWD$Houston_Load, list(HWD$Hour)),+ quantile, probs = c(0.85, 0.9))R> quants 0 1 2 3 4 5 685% 0.3576510 0.8633506 1.581443 0.2264709 0.4164411 0.2864026 1.05374290% 0.6116363 0.9273008 2.109248 0.4218297 0.5554147 0.4474140 1.366114 7 8 9 10 11 12 13 1485% 0.5352211 0.5175485 1.790593 1.394988 0.7280584 0.8578999 1.437778 1.08710190% 0.8625322 0.5969672 1.830352 1.519262 0.9399476 1.1401877 1.763725 1.102516 15 16 17 18 19 20 2185% 0.6855288 0.4874499 0.5493679 0.9754414 1.095362 0.7936225 1.82400290% 0.8737872 0.6121487 0.6078405 1.0990935 1.233637 0.9431199 2.175961 22 2385% 1.058648 0.695016690% 1.145783 0.8436541Now we can draw marks at the x locations of the boxplotsboxplot(Houston_Load ~ Hour, data = HWD, axes = FALSE)xlocs <- 1:24 ## where to draw markstickl <- 0.15 ## length of marks usedfor(i in seq_len(ncol(quants))) { segments(x0 = rep(xlocs[i] - 0.15, 2), y0 = quants[, i], x1 = rep(xlocs[i] + 0.15, 2), y1 = quants[, i], col = c("red", "blue"), lwd = 2)}title(xlab = "Hour", ylab = "Houston Load")axis(1, at = xlocs, labels = xlocs - 1)axis(2)box()legend("bottomleft", legend = paste(c("0.85", "0.90"), "quantile"), bty = "n", lty = "solid", lwd = 2, col = c("red", "blue"))The resulting figure should look like this: 这篇关于在R中的箱形图中添加不同的百分位数的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！