forcats 格列奈特说
forcats包的目标是提供一套有用的工具,用各种因素解决常见的问题。
事实上,其中一个工具是通过另一个变量重新排序因素,这是绘制数据的一个非常常见的用例。我试图使用forcats来实现这一点,但在一个分面的情节中。也就是说,我希望通过其他变量重新排序一个因子,但只使用数据的一个子集。这里有个解释:
library(tidyverse)
ggplot2::diamonds %>%
group_by(cut, clarity) %>%
summarise(value = mean(table, na.rm = TRUE)) %>%
ggplot(aes(x = clarity, y = value, color = clarity)) +
geom_segment(aes(xend = clarity, y = min(value), yend = value),
size = 1.5, alpha = 0.5) +
geom_point(size = 3) +
facet_grid(rows = "cut", scales = "free") +
coord_flip() +
theme(legend.position = "none")这段代码产生的情节与我想要的接近:

但是我希望清晰轴按值进行排序,这样我就可以快速发现哪一个清晰度值最高。但是,每个方面都意味着一个不同的顺序。因此,我想选择按一个特定方面内的值来排序这个图。
当然,直接使用forcats在这种情况下是行不通的,因为它将根据所有的值,而不仅仅是特定方面的值,重新排序因子。
# Inserting this line right before the ggplot call
mutate(clarity = forcats::fct_reorder(clarity, value)) %>%然后它就产生了这个情节。

当然,它根据整个数据重新排序了因子,但是如果我希望按照“理想”裁剪的值排序这个图呢?我如何使用forcats来完成这个任务呢?
我目前的解决办法如下:
ggdf <- ggplot2::diamonds %>%
group_by(cut, clarity) %>%
summarise(value = mean(table, na.rm = TRUE))
# The trick would be to create an auxiliary factor using only
# the subset of the data I want, and then use the levels
# to reorder the factor in the entire dataset.
#
# Note that I use good-old reorder, and not the forcats version
# which I could have, but better this way to emphasize that
# so far I haven't found the advantage of using forcats
reordered_factor <- reorder(ggdf$clarity[ggdf$cut == "Ideal"],
ggdf$value[ggdf$cut == "Ideal"])
ggdf$clarity <- factor(ggdf$clarity, levels = levels(reordered_factor))
ggdf %>%
ggplot(aes(x = clarity, y = value, color = clarity)) +
geom_segment(aes(xend = clarity, y = min(value), yend = value),
size = 1.5, alpha = 0.5) +
geom_point(size = 3) +
facet_grid(rows = "cut", scales = "free") +
coord_flip() +
theme(legend.position = "none")这就产生了我想要的。

但我想知道是否有一种更优雅、更聪明的使用forcats的方法。
发布于 2019-01-30 06:50:01
如果要根据特定方面的值重新排序clarity,则必须告诉forcats::fct_reorder()这样做,例如,
mutate(clarity = forcats::fct_reorder(
clarity, filter(., cut == "Ideal") %>% pull(value)))它只使用“理想”方面的值来重新排序。
因此,
ggplot2::diamonds %>%
group_by(cut, clarity) %>%
summarise(value = mean(table, na.rm = TRUE)) %>%
mutate(clarity = forcats::fct_reorder(
clarity, filter(., cut == "Ideal") %>% pull(value))) %>%
ggplot(aes(x = clarity, y = value, color = clarity)) +
geom_segment(aes(xend = clarity, y = min(value), yend = value),
size = 1.5, alpha = 0.5) +
geom_point(size = 3) +
facet_grid(rows = "cut", scales = "free") +
coord_flip() +
theme(legend.position = "none")创建

应要求。
https://stackoverflow.com/questions/54430898
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