R 在ggplot2中一起绘制两个分离的模型

我想在ggplot2中绘制两个分离的模型，为此，我尝试放置两条几何线，但不起作用。在我的例子中：

#Artificial data set
Consumption <- c(501, 502, 503, 504, 26, 27, 55, 56, 68, 69, 72, 93)
Gender <- gl(n = 2, k = 6, length = 2*6, labels = c("Male", "Female"), ordered = FALSE)
Income <- c(5010, 5020, 5030, 5040, 260, 270, 550, 560, 680, 690, 720, 930)
df3 <- data.frame(Consumption, Gender, Income)
df3

# GLM Regression 
fm1 <- glm(Consumption~Gender+Income, data=df3, family=poisson)
summary(fm1)

# ANOVA
anova(fm1,test="Chi")
       Df Deviance Resid. Df Resid. Dev  Pr(>Chi)    
NULL                      11    2467.24              
Gender  1   1200.2        10    1267.03 < 2.2e-16 ***
Income  1   1262.9         9       4.16 < 2.2e-16 ***

#Genders are different than I ajusted one model for male and another for Female

#Male model
df4<-df3[df3$Gender=="Male",]
fm2 <- glm(Consumption~Income, data=df4, family=poisson)
summary(fm2)

#Female model
df5<-df3[df3$Gender=="Female",]
fm3 <- glm(Consumption~Income, data=df5, family=poisson)
summary(fm3)

#Predict
df3 = cbind(df3, predM = predict(fm2, data=df3, type = "response"))#Estimate values for male
df3 = cbind(df3, predF = predict(fm3, data=df3, type = "response"))#Estimate values for female


#Plot
ggplot(data=df3, mapping=aes(x=Income, y=Consumption)) + 
  geom_point() +  
  geom_line(mapping=aes(y=predM,x=Income)) +
  geom_line(mapping=aes(y=predF, x=Income)) 
#

我的错误输出图是：

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任何成员，只要不创建一个模型，都可以帮助我，好吗？

我认为在男性数据上使用男性模型，在女性数据上使用女性模型会更有意义。这里有一种结合两组预测并将其与原始数据绑定的方法。然后我使用tidyr:：gather，这样实际消耗量和预测消耗量就放在同一列中，这样就更容易输入ggplot：

Predictions <- c(predict(fm2, data = df4, type = "response"),
                 predict(fm3, data = df5, type = "response"))
df3_combined <- cbind(df3, Predictions)

library(tidyverse)
df3_combined %>%
  gather(type, value, Consumption, Predictions) %>%
  ggplot(mapping=aes(x=Income, y=value, color = Gender, lty = type)) + 
  geom_point() +  geom_line()

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不清楚您期望的输出是什么。