如何使用ggplot填充geom_area（）图？ [英] How do I fill a geom_area() plot using ggplot?

问题描述

我有一个像这样的geom_area情节：

我想将x轴上方的所有内容变成绿色，将x轴下方的所有内容变成红色。我的数据中有一个类别列，其中包含所有正值的字符串positive和所有负值的negative字符串，所以我尝试了简单的fill = category并使用scale_fill_manual将正值设置为绿色，将负值设置为红色，但这给了我：

绿色上面的x看起来是正确的，但是轴下面的红色是不正确的。我检查了我的数据，并且没有负面数据点，它在Oct20之后着色为红色，而使用geom_point代替我获得了正确的颜色。

这是我的一个样本数据：

 创建的分数类别
 2011-10-19 21:26:19 2正数
 2011 -10-19 22:50:33 -2负
 2011-10-20 15:12:38 -2负
 2011-10-20 17:19:24 -2负
 2011-10-20 22:12:44 2正面
 2011-10-20 22:16:57 4正面
 2011-10-21 08:22:53 2正面
  

以下是我用来制作图的代码：

ggplot（data = df，aes（x = created，y = score，color = category））+ geom_point（aes（fill = category））+ scale_fill_manual（values = c（positive=绿色，负面=红色））

我的问题可能与 THI

解决方案

您需要为每个正/负片段创建一个新的分组变量。为了使转换变得更加块状，您可以先插入数据：

  require（ggplot2）
 
＃加载数据
 df = read.table（'data.txt'，header = T）
 df $ created = as.POSIXct（df $ created，tz ='UTC'）
 
＃插值数据
 lin_interp =函数（x，y，length.out = 100）{
 approx（x，y，xout = seq（min（x），max（x ），length.out = length.out））$ y 
} 
 created.interp = lin_interp（df $ created，df $ created）
 created.interp = as.POSIXct（created。 interp，origin ='1970-01-01'，tz ='UTC'）
 score.interp = lin_interp（df $ created，df $ score）
 df.interp = data.frame（created = created.interp，score = score.interp）
 
＃为每个pos / neg段创建一个分组变量
 cat.rle = rle（df.interp $ score< 0）
 df.interp $ group = rep.int（1：长度（cat.rle $长度），times = cat.rle $长度）
 
＃地块
 dev.new（宽度= 6，height = 4）
 ggplot（data = df.interp，aes（x = created，y = score，fill = score> 0，group = ）+ geom_area（）+ scale_fill_manual（values = c（'green'，'red'））
  

I have a geom_area plot that looks like this:

I want to color everything above the x-axis green and everything below the x axis red. I have a category column in my data that contains the string "positive" for all positive values and "negative" for all negative values, so I tried simply doing fill = category and using scale_fill_manual to set positive to green and negative to red, but that gives me this:

Green the above the x looks right, but the red below the axis isn't right. I've checked my data and there are no negative data points where it's coloring red after Oct20, and using geom_point instead I get the correct colors.

Here's a sample of my data:

created                 score   category
2011-10-19 21:26:19     2   positive
2011-10-19 22:50:33    -2   negative
2011-10-20 15:12:38    -2   negative
2011-10-20 17:19:24    -2   negative
2011-10-20 22:12:44     2   positive
2011-10-20 22:16:57     4   positive
2011-10-21 08:22:53     2   positive

and here's the code I'm using to make the plot:

ggplot(data = df, aes(x = created, y = score, colour = category)) + geom_point(aes(fill = category)) + scale_fill_manual(values = c("positive" = "green", "negative" = "red"))

My problem might be related to this previous question.

解决方案

You need to make a new grouping variable for each positive/negative segment. To make the transitions less "blocky", you can just first interpolate the data:

require(ggplot2)

# Load data
df = read.table('data.txt', header=T)
df$created = as.POSIXct(df$created, tz='UTC')

# Interpolate data
lin_interp = function(x, y, length.out=100) {
    approx(x, y, xout=seq(min(x), max(x), length.out=length.out))$y
}
created.interp = lin_interp(df$created, df$created)
created.interp = as.POSIXct(created.interp, origin='1970-01-01', tz='UTC')
score.interp   = lin_interp(df$created, df$score)
df.interp = data.frame(created=created.interp, score=score.interp)

# Make a grouping variable for each pos/neg segment
cat.rle = rle(df.interp$score < 0)
df.interp$group = rep.int(1:length(cat.rle$lengths), times=cat.rle$lengths)

# Plot
dev.new(width=6, height=4)
ggplot(data = df.interp, aes(x = created, y = score, fill=score>0, group=group)) + geom_area() + scale_fill_manual(values = c('green', 'red'))

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