Question

我正在尝试找到一个合适的展示来说明学校课程内和课程内的各种属性。每个班级只有15-30个数据点（学生）。

现在我倾向于一个没有胡须的盒子图，只显示1.，2。 3.四分位数+数据点更多，例如1个人口SD +/-样本中位数。

我能这样做。

但是 - 我需要向一些老师展示这个图表，以便衡量他们最喜欢什么。我想将我的图表与普通的箱线图进行比较。但是，如果只有一个异常值，或者例如，正常的箱形图看起来是相同的。 5个异常值处于相同值。在这种情况下，这将是一个交易破坏者。

e.g。

test <-structure(list(value = c(3, 5, 3, 3, 6, 4, 5, 4, 6, 4, 6, 4, 
4, 6, 5, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 5, 6, 6, 4, 3, 5, 4, 
6, 5, 6, 4, 5, 5, 3, 4, 4, 6, 4, 4, 5, 5, 3, 4, 5, 8, 8, 8, 8, 
9, 6, 6, 7, 6, 9), places = structure(c(1L, 2L, 1L, 1L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 
2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 
2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 
1L, 2L, 2L, 1L, 2L, 1L), .Label = c("a", "b"), class = "factor")), .Names = c("value", 
"places"), row.names = c(NA, -60L), class = "data.frame")

ggplot(test, aes(x=places,y=value))+geom_boxplot()

这里有两个异常值（“a”，9） - 但只显示了一个“点”。

所以我的问题：如何抖动异常值。而且 - 你会为这种数据建议什么样的显示？

Answer 1

你可以重新定义功能

GeomBoxplot$draw<-function (., data, ..., outlier.colour = "black", outlier.shape = 16, 
    outlier.size = 2, outlier.jitter=0) 
{
    defaults <- with(data, data.frame(x = x, xmin = xmin, xmax = xmax, 
        colour = colour, size = size, linetype = 1, group = 1, 
        alpha = 1, fill = alpha(fill, alpha), stringsAsFactors = FALSE))
    defaults2 <- defaults[c(1, 1), ]
        if (!is.null(data$outliers) && length(data$outliers[[1]] >= 
        1)) {
            pp<-position_jitter(width=outlier.jitter,height=0)
            p<-pp$adjust(data.frame(x=data$x[rep(1, length(data$outliers[[1]]))], y=data$outliers[[1]]),.scale)
        outliers_grob <- GeomPoint$draw(data.frame(x=p$x, y = p$y, colour = I(outlier.colour), 
            shape = outlier.shape, alpha = 1, size = outlier.size, 
            fill = NA), ...)
    }
    else {
        outliers_grob <- NULL
    }
    with(data, ggname(.$my_name(), grobTree(outliers_grob, GeomPath$draw(data.frame(y = c(upper, 
        ymax), defaults2), ...), GeomPath$draw(data.frame(y = c(lower, 
        ymin), defaults2), ...), GeomRect$draw(data.frame(ymax = upper, 
        ymin = lower, defaults), ...), GeomRect$draw(data.frame(ymax = middle, 
        ymin = middle, defaults), ...))))
}

ggplot(test, aes(x=places,y=value))+geom_boxplot(outlier.jitter=0.05)

这是临时解决方案。当然，就OOP而言，您应该创建一个GeomBoxplot的子类并覆盖该函数。这很简单，因为ggplot2很不错。

===添加了例如子类定义===

GeomBoxplotJitterOutlier <- proto(GeomBoxplot, {
   draw <- function (., data, ..., outlier.colour = "black", outlier.shape = 16, 
    outlier.size = 2, outlier.jitter=0) {
# copy the body of function 'draw' above and paste here.
}

  objname <- "boxplot_jitter_outlier"
  desc <- "Box and whiskers plot with jittered outlier"
  guide_geom <- function(.) "boxplot_jitter_outlier"

})
geom_boxplot_jitter_outlier <- GeomBoxplotJitterOutlier$build_accessor()

然后你就可以使用你的子类了：

ggplot(test, aes(x=places,y=value))+geom_boxplot_jitter_outlier(outlier.jitter=0.05)

Answer 2

似乎已接受的答案不再适用，因为ggplot2已更新。经过网上搜索后，我发现了以下内容：http://comments.gmane.org/gmane.comp.lang.r.ggplot2/3616 - 看看Winston Chang的回复 -

他使用ddply分别计算异常值，然后使用

绘制它们

geom_dotplot()

在geom_boxplot（）上禁用了异常值输出：

 geom_boxplot(outlier.colour = NA)

以下是上述网址的完整代码：

# This returns a data frame with the outliers only
find_outliers <- function(y, coef = 1.5) {
   qs <- c(0, 0.25, 0.5, 0.75, 1)
   stats <- as.numeric(quantile(y, qs))
   iqr <- diff(stats[c(2, 4)])

   outliers <- y < (stats[2] - coef * iqr) | y > (stats[4] + coef * iqr)

   return(y[outliers])
}


library(MASS)  # Use the birthwt data set from MASS

# Find the outliers for each level of 'smoke'
library(plyr)
outlier_data <- ddply(birthwt, .(smoke), summarise, lwt = find_outliers(lwt))


# This draws an ordinary box plot
ggplot(birthwt, aes(x = factor(smoke), y = lwt)) + geom_boxplot()


# This draws the outliers using geom_dotplot
ggplot(birthwt, aes(x = factor(smoke), y = lwt)) +
   geom_boxplot(outlier.colour = NA) +
#also consider:
#  geom_jitter(alpha = 0.5, size = 2)+
   geom_dotplot(data = outlier_data, binaxis = "y",
                stackdir = "center", binwidth = 4)

Answer 3

鉴于数据点数量较少，您希望绘制所有点，而不仅仅是异常值。这将有助于找出箱线图内点的分布。

你可以使用geom_jitter来做到这一点，但是请注意box_plot已经为异常值绘制了点，所以为了不显示它们两次，你需要用geom_boxplot(outlier.shape = NA)关闭boxplot的异常值显示。

library("ggplot2")

test <-structure(list(value = c(3, 5, 3, 3, 6, 4, 5, 4, 6, 4, 6, 4, 4, 6, 5, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 5, 6, 6, 4, 3, 5\
, 4, 6, 5, 6, 4, 5, 5, 3, 4, 4, 6, 4, 4, 5, 5, 3, 4, 5, 8, 8, 8, 8, 9, 6, 6, 7, 6, 9), places = structure(c(1L, 2L, 1L, 1L, 1L\
, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, \
1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L), .Label = c("a", "b"), class =\
 "factor")), .Names = c("value", "places"), row.names = c(NA, -60L), class = "data.frame")

# adding a level that you will use latter for giving colors
l <- rep(c(10,20,30,40,50,60), 10)
test$levels<-l

# [1]
# original plot
ggplot(test, aes(x=places,y=value))+geom_boxplot()

# [2]
# plot with outlier from boxplot and the points jittered to see
# distribution (outliers and the same point from position jitter would be
# counted twice for each different height)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot() +  geom_jitter(position=position_jitter(width=0.1, height=0))

# [3]
# make wider the jitter to avoid overplotting because there are a lot
# of points with the same value, also remove the outliers from boxplot
# (they are plotted with the geom_jitter anyway)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0))

# [4]
# adding colors to the points to see if there is a sub-pattern in the distribution
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0), aes(colour=levels))

# [5]
# adding a bit of vertical jittering
# jittering (a good option for a less discrete datasets)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0.05), aes(colour=levels))

# [6]
# finally remember that position_jitter makes a jittering of a 40% of
# the resolution of the data, so if you forget the height=0 you will
# have a total different picture
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.2))

enter image description here

Answer 4

这能满足您的需求吗？抖动开始的限制不是自动的，但它是一个开始。

g = ggplot(test, aes(x = places,y = value))

g + geom_boxplot(outlier.colour = rgb(0,0,0,0)) + geom_point(data = test[test$value > 8,], position = position_jitter(width = .4))

Answer 5

代码居住不再有效。对于当前版本的ggplot2，我使用了以下类：

DrawGeomBoxplotJitterOutlier <- function(data, panel_params, coord, ...,
                                         outlier.jitter.width=NULL, 
                                         outlier.jitter.height=0,
                                         outlier.colour = NULL, 
                                         outlier.fill = NULL,
                                         outlier.shape = 19, 
                                         outlier.size = 1.5, 
                                         outlier.stroke = 0.5,
                                         outlier.alpha = NULL) {
  boxplot_grob <- ggplot2::GeomBoxplot$draw_group(data, panel_params, coord, ...)
  point_grob <- grep("geom_point.*", names(boxplot_grob$children))
  if (length(point_grob) == 0)
    return(boxplot_grob)

  ifnotnull <- function(x, y) ifelse(is.null(x), y, x)

  if (is.null(outlier.jitter.width)) {
    outlier.jitter.width <- (data$xmax - data$xmin) / 2
  }

  x <- data$x[1]
  y <- data$outliers[[1]]
  if (outlier.jitter.width > 0 & length(y) > 1) {
    x <- jitter(rep(x, length(y)), amount=outlier.jitter.width)
  }

  if (outlier.jitter.height > 0 & length(y) > 1) {
    y <- jitter(y, amount=outlier.jitter.height)
  }

  outliers <- data.frame(
    x = x, y = y,
    colour = ifnotnull(outlier.colour, data$colour[1]),
    fill = ifnotnull(outlier.fill, data$fill[1]),
    shape = ifnotnull(outlier.shape, data$shape[1]),
    size = ifnotnull(outlier.size, data$size[1]),
    stroke = ifnotnull(outlier.stroke, data$stroke[1]),
    fill = NA,
    alpha = ifnotnull(outlier.alpha, data$alpha[1]),
    stringsAsFactors = FALSE
  )
  boxplot_grob$children[[point_grob]] <- ggplot2::GeomPoint$draw_panel(outliers, panel_params, coord)



  return(boxplot_grob)
}

GeomBoxplotJitterOutlier <- ggplot2::ggproto("GeomBoxplotJitterOutlier", 
                                             ggplot2::GeomBoxplot, 
                                             draw_group = DrawGeomBoxplotJitterOutlier)

geom_boxplot_jitter_outlier <- function(mapping = NULL, data = NULL, 
                                        stat = "boxplot", position = "dodge",
                                        ..., outlier.jitter.width=0, 
                                        outlier.jitter.height=NULL,
                                        na.rm = FALSE, show.legend = NA, 
                                        inherit.aes = TRUE) {
  ggplot2::layer(
    geom = GeomBoxplotJitterOutlier, mapping = mapping, data = data,
    stat = stat, position = position, show.legend = show.legend,
    inherit.aes = inherit.aes, params = list(na.rm = na.rm,
      outlier.jitter.width=outlier.jitter.width,
      outlier.jitter.height=outlier.jitter.height, ...))
}

如果ggplot2 boxplot中有多个异常值，则抖动

5 个答案: