将图例添加到geom_density R [英] Add legend to geom_density R

问题描述

我正在使用Prosper Loan数据集，并且试图在使用geom_density的同一个图中显示两个变量。
问题是，当我试图包含lengend以显示粉红色区域中的变量名称和黑暗区域中的变量名称时，它不起作用。

  library（ggplot2）
 EstimatedLoss <-c（0.5,0.2,0.3,0.4,0.8,0.5,0.2,0.3,0.4,0.8）
 EstimatedEffectiveYield <-c（0.10,0.15,0.18,0.20,0.8,0.15,0.13,0.22,0.22,0.25）
 prosper_loan < -  data.frame（EstimatedLoss，EstimatedEffectiveYield）
 ggplot（data = （aes（EstimatedLoss * 100），color ='＃e1b582'，fill ='＃e1b582'，alpha = 0.5，show.legend = TRUE）+ 
 geom_density（aes（EstimatedEffectiveYield * 100），color ='＃a2b285'，fill ='＃a2b285'，alpha = 0.7，linetype = 3，size = 1，show.legend = TRUE）+ 
 scale_y_continuous（name =Density）+ 
 scale_x_continuous（name =估计损失和实际收益率百分比）+ 
 ggtitle（'估计损失和有效收益率的百分比密度'）
  pre> 
 
 
 A m我做错了什么？
解决方案
理想情况下，您的数据应该是每行一个观察值（又名长数据）利用 ggplot2 。以下是首先使用 tidyr :: gather 转换数据的示例。一个图例会自动添加一个 fill 或 color 唯美。
  library（ggplot2）
 library（tidyr）
 library（magrittr）
 
 EstimatedLoss <-c（0.5,0.2 ，0.3,0.4,0.8,0.5,0.2,0.3,0.4,0.8）
 EstimatedEffectiveYield <-c（0.10,0.15,0.18,0.20,0.8,0.15,0.13,0.22,0.22,0.25）
 
 prosper_loan<  -  data.frame（EstimatedLoss，EstimatedEffectiveYield）％>％
 gather（key，value，EstimatedLoss：EstimatedEffectiveYield）
 
 ggplot（data = prosper_loan）+ 
 geom_density（aes（value * 100，fill = key，color = key），alpha = 0.5）+ 
 scale_fill_manual（values = c（'＃e1b582'，'＃a2b285'））+ 
 scale_color_manual（values = c（'＃e1b582'，'＃a2b285'））+ 
 scale_y_continuous（name =Density）+ 
 scale_x_continuous（name =Estimated loss and effective yield in percentage ）+ 
 ggtitle（'估计损失和有效收益率的百分比密度'）
  
  
 
I'm working with the Prosper Loan dataset and I'm trying to show two variable in the same plot using geom_density.
The problem, when I try to include the lengend to show the variable name from the pink area and the variable name from the dark area, it doesn't work.
library(ggplot2)
EstimatedLoss <-  c(0.5, 0.2,0.3,0.4,0.8,0.5, 0.2,0.3,0.4,0.8)
EstimatedEffectiveYield <- c(0.10, 0.15,0.18,0.20,0.8,0.15, 0.13,0.22,0.22,0.25)
prosper_loan <- data.frame(EstimatedLoss,EstimatedEffectiveYield)
ggplot(data = prosper_loan)
geom_density(aes(EstimatedLoss * 100), color = '#e1b582', fill = '#e1b582', alpha = 0.5, show.legend = TRUE ) +
geom_density(aes(EstimatedEffectiveYield * 100), color = '#a2b285',fill = '#a2b285', alpha = 0.7, linetype = 3, size = 1, show.legend = TRUE) +
scale_y_continuous(name = "Density")+
scale_x_continuous(name = "Estimate loss and effective yield in percentage") +
ggtitle('Density from the Estimated loss and effective yield in percentage') 
Am I doing anything wrong?
解决方案
Ideally, your data should be one observation per row (aka "long" data) to properly take advantage of ggplot2. Here's an example of first transforming the data using tidyr::gather. A legend will automatically be added with a fill or color aesthetic.
library(ggplot2)
library(tidyr)
library(magrittr)

EstimatedLoss <-  c(0.5, 0.2,0.3,0.4,0.8,0.5, 0.2,0.3,0.4,0.8)
EstimatedEffectiveYield <- c(0.10, 0.15,0.18,0.20,0.8,0.15, 0.13,0.22,0.22,0.25)

prosper_loan <- data.frame(EstimatedLoss, EstimatedEffectiveYield) %>% 
  gather(key, value, EstimatedLoss:EstimatedEffectiveYield)

ggplot(data = prosper_loan) +
  geom_density(aes(value * 100, fill = key, color = key), alpha = 0.5) +
  scale_fill_manual(values = c('#e1b582', '#a2b285')) + 
  scale_color_manual(values = c('#e1b582', '#a2b285')) +
  scale_y_continuous(name = "Density")+
  scale_x_continuous(name = "Estimate loss and effective yield in percentage") +
  ggtitle('Density from the Estimated loss and effective yield in percentage') 


                        
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