ML Regression in ggplot2

How to make ML Regression Plots in ggplot2 with Plotly.

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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)