ML Regression in ggplot2
How to make ML Regression Plots in ggplot2 with Plotly.
Plotly Studio: Transform any dataset into an interactive data application in minutes with AI. Try Plotly Studio now.
Linear regerssion plot
Sometimes it's nice to quickly visualise the data that went into a simple linear regression, especially when you are performing lots of tests at once. Here is a quick solution with ggplot2.
library(plotly)
library(ggplot2)
data(iris)
p <- ggplot(iris, aes(x = Petal.Width, y = Sepal.Length)) +
geom_point() +
stat_smooth(method = "lm", col = "red")
ggplotly(p)
Disaplay additional statistics
You can create a quick function to pull the data out of a linear regression, and return important values (R-squares, slope, intercept and P value) at the top of a nice ggplot graph with the regression line.
library(plotly)
library(ggplot2)
data(iris)
ggplotRegression <- function (fit) {
ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
geom_point() +
stat_smooth(method = "lm", col = "red") +
labs(title = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 5),
"Intercept =",signif(fit$coef[[1]],5 ),
" Slope =",signif(fit$coef[[2]], 5),
" P =",signif(summary(fit)$coef[2,4], 5)))
}
fit1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
p <- ggplotRegression(fit1)
ggplotly(p)
What About Dash?
Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash for R at https://dashr.plot.ly/installation.
Everywhere in this page that you see fig
, you can display the same figure in a Dash for R application by passing it to the figure
argument of the Graph
component from the built-in dashCoreComponents
package like this:
library(plotly)
fig <- plot_ly()
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... )
library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)
app <- Dash$new()
app$layout(
htmlDiv(
list(
dccGraph(figure=fig)
)
)
)
app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)