Autoplotter Tutorial -

auto_notes(data) <- "Temperature above 29°C drives bleaching, mitigated by shading treatment." Those notes appeared in the report’s appendix. Alia had to re-run the same plots weekly as new data arrived. autoplotter worked inside dplyr pipelines:

auto_scatter(data, x = temperature, y = bleaching_score, color = treatment) + geom_smooth(method = "lm", se = FALSE) + labs(title = "Bleaching increases with temperature, worse in control") Still one line of code for the plot, but now custom. Her PI said: “Can you send me all the key relationships by tomorrow?” autoplotter tutorial

Alia ran:

She never wrote a ggplot from scratch for exploration again. Her PI said: “Can you send me all

She needed to explore relationships fast. But making 50+ plots in ggplot2 manually? No time. “There has to be a function that just… plots everything smartly.” That’s when she found autoplotter . # install.packages("autoplotter") # hypothetical library(autoplotter) library(ggplot2) # autoplotter builds on it data <- read.csv("coral_bleaching_2025.csv") The magic function auto_plot(data) No time