[英]R - Adding legend to ggplot graph for regression lines
I do a Multiple Linear Regression in R, where I want to add a simple legend to a graph (ggplot).我在 R 中进行了多重线性回归,我想在图中添加一个简单的图例(ggplot)。 The legend should show the points and fitted lines with their corresponding colors.
图例应显示点和拟合线及其对应的 colors。 So far it works fine (without legend):
到目前为止它工作正常(没有图例):
ggplot() +
geom_point(aes(x = training_set$R.D.Spend, y = training_set$Profit),
col = 'red') +
geom_line(aes(x = training_set$R.D.Spend, y = predict(regressor, newdata = training_set)),
col = 'blue') +
geom_line(aes(x = training_set$R.D.Spend, y = predict(regressor_sig, newdata = training_set)),
col = 'green') +
ggtitle('Multiple Linear Regression (Training set)') +
xlab('R.D.Spend [k$]') +
ylab('Profit of Venture [k$]')
How can I add a legend here most easily?如何最轻松地在此处添加图例?
I tried the solutions from similar question, but did not succeed ( add legend to ggplot2 | Add legend for multiple regression lines from different datasets to ggplot )我尝试了类似问题的解决方案,但没有成功( 将图例添加到 ggplot2 | 将来自不同数据集的多条回归线的图例添加到 ggplot )
So, I appended my original model like this:所以,我像这样附加了我原来的 model :
ggplot() +
geom_point(aes(x = training_set$R.D.Spend, y = training_set$Profit),
col = 'p1') +
geom_line(aes(x = training_set$R.D.Spend, y = predict(regressor, newdata = training_set)),
col = 'p2') +
geom_line(aes(x = training_set$R.D.Spend, y = predict(regressor_sig, newdata = training_set)),
col = 'p3') +
scale_color_manual(
name='My lines',
values=c('blue', 'orangered', 'green')) +
ggtitle('Multiple Linear Regression (Training set)') +
xlab('R.D.Spend [k$]') +
ylab('Profit of Venture [k$]')
But here I am getting the error of "Unknown colour name: p1".但在这里我收到“未知颜色名称:p1”的错误。 which makes somewhat sense, as I do not define p1 above.
这有点道理,因为我没有在上面定义 p1 。 How can I make the ggplot recognise my intended legend?
如何让 ggplot 识别我想要的图例?
Move col
into the aes
and then you can set the color using scale_color_manual
:将
col
移动到aes
中,然后您可以使用scale_color_manual
设置颜色:
library(ggplot2)
set.seed(1)
x <- 1:30
y <- rnorm(30) + x
fit <- lm(y ~ x)
ggplot2::ggplot(data.frame(x, y)) +
geom_point(aes(x = x, y = y)) +
geom_line(aes(x = x, y = predict(fit), col = "Regression")) +
scale_color_manual(name = "My Lines",
values = c("blue"))
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