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GGPlot在方面之间重新排序变量

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我有一个数据框（长格式），其中包含来自个性自我报告的数据 . 我使用ggplot2绘制了我之前运行的探索性因子分析 . 下面，我创建了原始数据框的子集 .

Here，Dan Mirman博士提出了一种绘制这类数据的好方法，我想这样做 . 所以，我已经调整了他的代码，但正如你从图像中看到的那样，情节有一个问题 . y轴上的刻度按字母顺序反向排序 . 但是，我想根据每个因素的负荷来订购这些尺度 . 例如，我认为最好的顺序可能是"A"和"IdP"，因为它们在Factor1上加载，然后"R"和"Ca"，因为它们加载在因子2上，"InP"因为它加载到因子3，而"Co"因为它加载到因子4在底部，"S"因为它在多个尺度上显示出类似的载荷 .

谁能帮我吗？我真的很感激！

library(ggplot2)
Scale <- c("A", "IdP", "R", "Ca", "S", "InP", "Co", "A", "IdP", "R", "Ca", "S", "InP", "Co", "A", "IdP", "R", "Ca", "S", "InP", "Co", "A", "IdP", "R", "Ca", "S", "InP", "Co")
Factor <- c("Factor1", "Factor1", "Factor1", "Factor1", "Factor1", "Factor1", "Factor1", "Factor2", "Factor2", "Factor2", "Factor2", "Factor2", "Factor2", "Factor2", "Factor3", "Factor3", "Factor3", "Factor3", "Factor3", "Factor3", "Factor3", "Factor4", "Factor4", "Factor4", "Factor4", "Factor4", "Factor4", "Factor4")
loading.db <- c(0.93, 0.71, -0.15,  0.00, 0.34, 0.08, 0.04, 0.02, 0.13, 0.79, 0.74, 0.43, 0.03, 0.06, -0.02, 0.30, -0.06, 0.25, 0.08, 0.66, -0.03, 0.09, -0.03, 0.18, -0.01, 0.37, -0.06, 0.62)

db <- data.frame(Scale, Factor, loading.db)

ggplot(db, aes(Scale, abs(loading.db), fill = loading.db)) + 
  facet_wrap(~ Factor, nrow = 1) +
  geom_bar(stat = "identity") +
  coord_flip() +
  scale_fill_gradient2(name = "Loading", 
                       high = "green", mid = "white", low = "yellow", 
                       midpoint = 0, guide = F) +
  xlab("Test scales") + 
  ylab("Loading Strength") +
  theme_bw(base_size = 10)

Plot Factor loadings

r ggplot2 order

1 回答

  • 1

    你只需要重新排序你的因子水平（见 levels(db$Scale) . 例如，我在这里通过查看哪些大于0.5（按因子1，...，4的顺序）对它们进行排序，然后添加那些最后遗漏了（在这种情况下是 S ） .

    lvls <- as.character(unique(db$Scale[db$loading.db > 0.5]))
lvls <- c(lvls, unique(levels(db$Scale)[!(levels(db$Scale) %in% lvls)]))

db$Scale <- factor(db$Scale, rev(lvls))

ggplot(db, aes(Scale, abs(loading.db), fill = loading.db)) + 
  facet_wrap(~ Factor, nrow = 1) +
  geom_bar(stat = "identity") +
  coord_flip() +
  scale_fill_gradient2(name = "Loading", 
                       high = "green", mid = "white", low = "yellow", 
                       midpoint = 0, guide = F) +
  xlab("Test scales") + 
  ylab("Loading Strength") +
  theme_bw(base_size = 10)

    给

    enter image description here

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