Skill: Easy Pairs (R)

Category

Hiplot

When to Use

Display a matrix of plots for viewing correlation relationship and distributions of multiple variables.

Required R Packages

• GGally
• data.table
• jsonlite

Minimal Reproducible Code

# Load packages
library(GGally)
library(data.table)
library(jsonlite)

# Prepare data
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/easy-pairs/data.json")$exampleData[[1]]$textarea[[1]])
data <- as.data.frame(data)

# View data
head(data)

# Create visualization
# Easy Pairs
p <- ggpairs(data, columns = c("total_bill", "time", "tip"),
             mapping = aes_string(color = "gender")) +
  ggtitle("Easy Pairs") +
  scale_fill_manual(values = c("#3B4992FF","#EE0000FF")) +
  theme_bw() +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_text(size = 12),
        axis.text = element_text(size = 10),
        axis.text.x = element_text(angle = 0, hjust = 0.5,vjust = 1),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p

Key Parameters

• position: Position adjustment (identity, dodge, stack, fill)
• theme: Plot theme; tutorial uses theme_bw()
• fill: Maps a variable to fill color for group comparison
• color: Maps a variable to outline/point color

Tips

• Use theme_minimal() or theme_bw() for clean, publication-ready plots
• Customize color scales with scale_fill_manual() or scale_color_brewer()
• See the full tutorial for additional customization options and advanced examples

Full Tutorial

https://openbiox.github.io/Bizard/Hiplot/049-easy-pairs.html