在每个类别的x轴内覆盖geom_line-ggplot2 [英] Overlay geom_line within a categorical x axis for each group - ggplot2
问题描述
我想绘制一个这样的情节:
I want to make a plot like this:
这些框代表连续变量在组内的分布；红色圆圈是表示所有实际观察值的点.到现在为止还挺好.使用具有整体美感的 geom_boxplot + geom_point ，这将很简单.
The boxes would represent the distribution of a continuous variable within groups; the red circles are the points showing all of the actual observations. So far, so good. This would be simple with geom_boxplot + geom_point with a group aesthetic.
这是两个转折点:
- 这些点的水平位置不是随机抖动.相反，它们是利用连续X轴而不是分类轴的X-Y坐标
- 该线是适合这些点的趋势线.
- The horizontal position of the points are not a random jitter. They are instead an X-Y coordinate utilizing a continuous X axis instead of a categorical axis
- The line is a trendline that is fit on those points.
某些情况:该图显示了产品的使用情况(Y轴)与允许的使用情况(X).X轴组是互斥的，离散的层，在本质上是使用的无限连续变量.例如EG，1-4、5-9、10-20等.从视觉的角度来看，绘制这些组中的连续图像对我来说并不疯狂，这有意义吗?但是我不知道如何开始让 ggplot2 同意我的想法.
Some context:
This plot is showing usage of a product (Y axis) vs allowed usage (X). The X axis groups are mutually exclusive, discrete tiers on what is essentially an infinite, continuous variable for usage. EG, 1-4, 5-9, 10-20, etc. It doesn't feel crazy to me from a visual standpoint to plot the continuous within those groups, does that make sense? But I have no idea how I'd get started on getting ggplot2 to agree with me.
我的偏好是使箱形图在X轴上均匀分布，但是如果我需要从连续的轴开始，并且各组在X轴上占据比例的空间，那么我会安定下来为此(可能使用了记录轴，以防止将下部狭窄的组完全弄脏.
这应该作为示例数据:
df <- structure(list(usage = c(1L, 4L, 2L, 5L, 4L, 1L, 2L, 98L, 9L,
4L, 6L, 6L, 1L, 2L, 2L, 2L, 3L, 2L, 5L, 1L), allowed = c(2, 20,
3, 3, 5, 5, 1, 1, 1, 5, 10, 5, 7, 12, 2, 5, 23, 10, 5, 2), id = c(1055L,
2155L, 6637L, 11068L, 2070L, 8524L, 9157L, 5963L, 7593L, 3470L,
3557L, 7469L, 9142L, 408L, 9446L, 1552L, 4788L, 7233L, 8464L,
2188L), group = c("A", "B", "A", "A", "A", "A", "A", "A", "A",
"A", "B", "A", "B", "B", "A", "A", "B", "B", "A", "A")), row.names = c(NA,
-20L), class = c("tbl_df", "tbl", "data.frame"))
推荐答案
这是我为您准备的:
# you had some values that were = 98 in usage and throwing everything off..
df <- df %>% dplyr::filter(usage < 50)
p <-
ggplot(df, aes(allowed, usage)) +
geom_boxplot(aes(group=group)) +
geom_point() +
geom_smooth(alpha=0, method='lm') +
facet_wrap(~group, scales='free_x', strip.position = 'bottom') +
theme_classic() +
theme(
axis.text.x = element_blank(), # remove x axis text
axis.ticks.x = element_blank(), # remove tick marks on x axis
axis.title.x = element_blank(), # remove title for axis
strip.background = element_blank(), # no box on facet label
strip.placement = 'outside', # facet label is outside axis line
strip.text = element_text(size=12),
panel.spacing.x = unit(0, 'pt') # remove space between facets
)
p
一般的想法是考虑到您这里有2个x轴.要绘制点的主轴是 df $ allowed ，然后您要根据 df $ group 进行分组.我在这里想到的最简单的解决方案是，将 df $ group 的每个值都视为一个单独的方面，然后将其缝"起来.通过将小平面之间的间距设置为零，将小平面合并在一起.似乎运作良好.
The general idea is to consider that you kind of have 2 x axes here. The primary axis by which you want to plot your points is df$allowed, whereas you then want to group based on df$group. The easiest solution I can think of here was to treat each value of df$group as a separate facet, and then "stitch" the facets together by setting the space in-between them to zero. Seems to work well.
否则，这里唯一的注释是，框可能太靠近，以至于您不喜欢-区分一组要区别于另一组的要点.由于每个组都是一个构面，因此是一个完全独立的图，因此您可以挤压"图块.通过添加/扩展每个构面的主要x轴将这些框放在一起，如下所示:
The only comment here otherwise is that the boxes might be a bit too close together for your liking - making discrimination of the points of one group to be distinguished from another. Since each group is a facet, and therefore a completely separate plot, you can "squish" the boxes together by adding/expanding the primary x axis for each facet like so:
p + scale_x_continuous(expand=expansion(mult=c(0.8)))
注意:我必须删除一些使用中的超高值，以便能够正确地实际查看您的图.我想这是复制数据(像缺失值)的产物.
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