一种总是躲避直方图的方法?
使用 ggplot2,我创建了一个直方图,其中一个因子在水平轴上,另一个因子用于填充颜色,使用躲避位置.我的问题是填充因子有时只为水平因子的值取一个值,并且没有什么可以躲避条形占据整个宽度.有没有办法让它不躲闪,以便所有条宽都相同?或者等效地绘制 0?
Using ggplot2 I'm creating a histogram with a factor on the horizontal axis and another factor for the fill color, using a dodged position. My problem is that the fill factor sometimes takes only one value for a value of the horizontal factor, and with nothing to dodge the bar takes up the full width. Is there a way to make it dodge nothing so that all bar widths are the same? Or equivalently to plot the 0's?
例如
ggplot(data = mtcars, aes(x = factor(carb), fill = factor(gear))) +
geom_histogram(position = "dodge")
这个答案有几个想法.在新版本发布之前也被问到了,所以也许有什么改变?使用方面(也显示在此处)我不喜欢我的情况,尽管我想编辑数据并使用 geom_bar
可以工作,但感觉不优雅.此外,当我无论如何尝试刻面时
This answer has a couple ideas. It was also asked before the new version was released, so maybe something changed? Using facets (also shown here) I don't like for my situation, though I suppose editing the data and using geom_bar
could work, but it feels inelegant. Moreover, when I tried facetting anyway
ggplot(mtcars, aes(x = factor(carb), fill = factor(gear))) +
geom_bar() + facet_grid(~factor(carb))
我收到错误layout_base(data, cols, drop = drop) 中的错误:至少一层必须包含用于刻面的所有变量"
I get the error "Error in layout_base(data, cols, drop = drop): At least one layer must contain all variables used for facetting"
我想我可以生成一个计数数据框,然后使用 geom_bar
,
I suppose I could generate a data frame of counts and then use geom_bar
,
mtcounts <- ddply(subset(mtcars, select = c("carb", "gear")),
.fun = count, .variables = c("carb", "gear"))
填写不存在 0 的级别.有谁知道这是否可行,或者是否有更好的方法?
filling out the levels that aren't present with 0's. Does anyone know if that would work or if there's a better way?
更新 geom_bar
需要stat = "identity"
我不确定这对您来说是否为时已晚,但请参阅最近帖子的答案这里也就是说,我会按照 Joran 的建议预先计算 ggplot
调用之外的计数并使用 geom_bar
.与其他帖子的答案一样,计数分两步获得:首先,使用 dcast
获得计数的交叉表;其次,melt
交叉制表.
I'm not sure if this is too late for you, but see the answer to a recent post here
That is, I'd take Joran's advice to pre-calculate the counts outside the ggplot
call and to use geom_bar
. As with the answer to other post, the counts are obtained in two steps: first, a crosstabulation of counts is obtained using dcast
; then second, melt
the crosstabulation.
library(ggplot2)
library(reshape2)
dat = dcast(mtcars, factor(carb) ~ factor(gear), fun.aggregate = length)
dat.melt = melt(dat, id.vars = "factor(carb)", measure.vars = c("3", "4", "5"))
dat.melt
(p <- ggplot(dat.melt, aes(x = `factor(carb)`, y = value, fill = variable)) +
geom_bar(stat = "identity", position = "dodge"))
图表: