Autoplotter Tutorial May 2026

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:

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) autoplotter tutorial

I’ve structured it like a data analyst’s journey from confusion to insight. Dr. Alia Khan, a marine biologist, stared at a CSV file named coral_bleaching_2025.csv . It had 14 columns: site , temperature , salinity , light_intensity , bleaching_score , date , depth_m , turbidity , nitrates , ph , algae_cover , fish_diversity , treatment , and recovery_days . But making 50+ plots in ggplot2 manually