具有离散X的GGPLOT片段：降低未使用的级别并获得与组数成正比的量表

发布于 2025-02-04 16:30:04 字数 853 浏览 2 评论 0 原文

让我们以虹膜数据集为例。但是哦，不！我们忘了测量setosa花的花瓣...

# pivot_longer for plot
i2 <- iris %>%
  pivot_longer(-Species, names_to='parameter', values_to='measure')
i2

# deleting petal measures of setosa
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Length'),]
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Width'),]

现在我们绘制了由物种的不同参数。由于我们没有setosa的花瓣措施，因此我们使用scales ='free_x'，因此它会降低未使用的级别。因此：

ggplot(i2, aes(x=parameter, y=measure, colour=parameter)) +
  geom_point() +
  facet_wrap(~Species, nrow=1, scales='free_x')

现在，我的问题是：我希望每个图的宽度与绘制的组数量成正比，即Setosa图应比其他物种薄的两倍，因为仅绘制了两个参数。

我该如何实现？

原文

Let's take the iris dataset as example. But oh, no! We forgot to measure the petals of setosa flowers...

# pivot_longer for plot
i2 <- iris %>%
  pivot_longer(-Species, names_to='parameter', values_to='measure')
i2

# deleting petal measures of setosa
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Length'),]
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Width'),]

Now we are plotting the different parameters, faceted by species. As we do not have the petal measures for setosa, we use scales='free_x' so it drops the unused levels. As so:

ggplot(i2, aes(x=parameter, y=measure, colour=parameter)) +
  geom_point() +
  facet_wrap(~Species, nrow=1, scales='free_x')

Now, my issue is: I want the width of each plot to be proportional to the number of groups plotted, i.e. the setosa plot should be about twice thinner than the other species, as only two parameters are plotted.

How can I achieve this?

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你的笑 2025-02-11 16:30:04

在 facet_grid（）中，您可以设置 space =“ free_x” 具有比例x轴。

library(tidyverse)

# pivot_longer for plot
i2 <- iris %>%
  pivot_longer(-Species, names_to='parameter', values_to='measure')

# deleting petal measures of setosa
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Length'),]
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Width'),]

ggplot(i2, aes(x=parameter, y=measure, colour=parameter)) +
  geom_point() +
  facet_grid(~Species, scales='free_x', space = "free_x")

^{^{在2022-06-06上由 reprex软件包（v2.0.1）}}

In facet_grid(), you can set space = "free_x" to have proportional x-axes.

library(tidyverse)

# pivot_longer for plot
i2 <- iris %>%
  pivot_longer(-Species, names_to='parameter', values_to='measure')

# deleting petal measures of setosa
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Length'),]
i2 <- i2[-which(i2$Species=='setosa' & i2$parameter=='Petal.Width'),]

ggplot(i2, aes(x=parameter, y=measure, colour=parameter)) +
  geom_point() +
  facet_grid(~Species, scales='free_x', space = "free_x")