如何在ggplot中为独立图层缩放颜色？ [英] How to scale colour in ggplot for independent layer?

问题描述

我有一个数据集，记录了三座建筑物的能源使用情况。我有一个可以从钻石组中模拟出来的融化的数据框：

  data < -  melt（diamonds [，c（ 'depth'，'table'，'cut'，'color'）]，id = c（'cut'，'color'））
  

基本上，我从三个不同的建筑物（7个颜色因子）获得每个月的加热（'深度'）和冷却（'桌子'）数据。我想在每个月的条形图（'cut'）中并排绘制三个建筑物（7个颜色因素）。

我希望表示冷却（'表'）或加热（'深度'）的条形根据建筑物（颜色因子）改变其阴影，按月份（'cut'）分组。这是钻石数据可视化的一种不好的方式，但对于建筑物来说，它们应该很好地工作，因为它们的加热和冷却月份通常不会重叠。到目前为止，我有：

  p < -  ggplot（data，
 aes（color，value，group = cut ））
p < -  p + geom_bar（stat ='identity'，
 position ='dodge'，
 aes（fill = variable））
 print（p）
  

我试着玩scale_fill_manual，但想不出一个可行的策略：

$ b （'＃0000FF'，'＃0033FF'，'＃0066FF'，'＃FF0000'，'＃FF3300'，'＃FF3300' ＃FF6600'）

p < - p + scale_fill_manual（values = colors，
group = data $ variable）

解决方案

有了一些诡计，这是可能的。派生一个基于钻石的数据集是非常好的，但我想用一个更小的数据集

  set.seed（1234 ）
 data < -  
 expand.grid（month = month.abb，
 building = c（Building A，Building B，Building C），
 hc = c（Heating，Cooling））
 data $ value < -  rnorm（nrow（data），60,10）
  

您希望您的填充颜色基于变量（ hc ）和建筑物（<$ c $

  ggplot（data，aes（building ，value，group = month））+ 
 geom_bar（stat ='identity'，
 position ='dodge'，
 aes（fill = interaction（building，hc）））
  

我们可以选择代表不同颜色的颜色，使其更像您所想。我使用了 RColorBrewer 调色板的蓝调和红色中间。

 颜色<-c（＃FC9272，＃FB6A4A，＃EF3B2C，＃9ECAE1， ＃6BAED6，＃4292C6）
＃library（RColorBrewer）
＃colors <-c（brewer.pal（9，Reds）[4：6]，bre​​wer。 pal（9，Blues）[4：6]）
  

并使用 scale_fill_manual 来分配这些颜色。

  ggplot（data，aes（building，value，group =月））+ 
 geom_bar（stat ='identity'，
 position ='dodge'，
 aes（fill = interaction（building，hc）））+ 
 scale_fill_manual =颜色）
  

真正的诀窍是让图例变得更加复杂。我只列出了2个关卡（中间建筑的颜色），并给他们不同的名字（和图例中的不同标题）。

  ggplot（data，aes（building，value，group = month））+ 
 geom_bar（stat ='identity'，
 position ='dodge'，
 aes（fill = building（building，hc）））+ 
 scale_fill_manual（Heating / cooling，
 values = colors，
 breaks = c（Building B.Heating，Building B.Cooling ），
 labels = c（Heating，Cooling））
  

< img src =https://i.stack.imgur.com/EWtcq.pngalt =在这里输入图片描述>

I have a data set that documents the energy use of three buildings. I have a melted data frame that can be mimicked from the diamonds set:

data <- melt(diamonds[,c('depth','table','cut','color')],id=c('cut','color'))

Essentially, I have heating ('depth') and cooling ('table') data for each month('cut') from three different buildings (7 'color' factors). I would like to plot the three buildings (7 'color' factors) side by side in a bar plot for each month ('cut').

I want the bars representing either cooling ('table') or heating ('depth') to vary their shade based on the building ('color' factor) while remaining grouped by month ('cut'). This is a bad way to visualize the diamonds data, but should work well for buildings as their heating and cooling months typically don't overlap. So far I have:

p <- ggplot(data,
        aes(color,value,group=cut))
p <- p + geom_bar(stat = 'identity',
              position = 'dodge',
              aes(fill = variable))
print(p)

I tried playing with scale_fill_manual, but couldn't think of a strategy that works:

colours <- c('#0000FF', '#0033FF', '#0066FF', '#FF0000', '#FF3300', '#FF6600')

p <- p + scale_fill_manual(values = colours,
                           group = data$variable)

解决方案

With some trickery, it is possible. Deriving a data set based on diamonds was very good, but I want to work with a smaller data set

set.seed(1234)
data <-
expand.grid(month = month.abb,
            building = c("Building A", "Building B", "Building C"),
            hc = c("Heating", "Cooling"))
data$value <- rnorm(nrow(data), 60, 10)

You want your fill colour to be based both on the variable (hc) and the building (building), so set it to that interaction.

ggplot(data, aes(building,value,group=month)) + 
  geom_bar(stat = 'identity',
           position = 'dodge',
           aes(fill = interaction(building, hc)))

We can pick colors that represent different near shades to make these more like what you want. I used the middle of the "Blues" and "Reds" of the RColorBrewer palettes.

colours <- c("#FC9272", "#FB6A4A", "#EF3B2C", "#9ECAE1", "#6BAED6", "#4292C6")
# library("RColorBrewer")
# colours <- c(brewer.pal(9,"Reds")[4:6], brewer.pal(9,"Blues")[4:6])

and used scale_fill_manual to assign these colours.

ggplot(data, aes(building,value,group=month)) + 
  geom_bar(stat = 'identity',
           position = 'dodge',
           aes(fill = interaction(building, hc))) +
  scale_fill_manual(values=colours)

The real trickery is in making the legend less convoluted. I just list 2 of the levels (the middle building in terms of color) and give them different names (and a different title for the legend).

ggplot(data, aes(building,value,group=month)) + 
  geom_bar(stat = 'identity',
           position = 'dodge',
           aes(fill = interaction(building, hc))) +
  scale_fill_manual("Heating/cooling",
                    values=colours,
                    breaks=c("Building B.Heating", "Building B.Cooling"),
                    labels=c("Heating", "Cooling"))

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