Visdat

Authors

[Editor] Hu Zheng;

[Contributors]

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Visdat plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:

https://hiplot.cn/basic/visdat?lang=en

Setup

  • System Requirements: Cross-platform (Linux/MacOS/Windows)

  • Programming language: R

  • Dependent packages: visdat; ggplot2; dplyr; patchwork

# Install packages
if (!requireNamespace("visdat", quietly = TRUE)) {
  install.packages("visdat")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}
if (!requireNamespace("dplyr", quietly = TRUE)) {
  install.packages("dplyr")
}
if (!requireNamespace("patchwork", quietly = TRUE)) {
  install.packages("patchwork")
}

# Load packages
library(visdat)
library(ggplot2)
library(dplyr)
library(patchwork)

Data Preparation

# Load data
data <- read.delim("files/Hiplot/182-visdat-data.txt", header = T)

# View data
head(data)
  RowNames Ozone Solar.R Wind Temp Month Day
1        1    41     190  7.4   67     5   1
2        2    36     118  8.0   72     5   2
3        3    12     149 12.6   74     5   3
4        4    18     313 11.5   62     5   4
5        5    NA      NA 14.3   56     5   5
6        6    28      NA 14.9   66     5   6

Visualization

# Visdat
add_palette <- function (p) {
  ## add color palette
  p <- p + scale_fill_manual(values = c("#3B4992FF", "#EE0000FF"))
}
pobj <- list()
pobj[["p1"]] <- add_palette(vis_dat(data)) + ggtitle(':vis_dat')
pobj[["p2"]] <- add_palette(vis_guess(data)) + ggtitle(':vis_guess')
pobj[["p3"]] <- vis_miss(data, cluster = T, sort_miss = T) + ggtitle(':vis_miss')
pobj[["p4"]] <- add_palette(vis_expect(data, ~.x >= 20 )) + ggtitle(':vis_expect')
pobj[["p5"]] <- vis_cor(data) + 
  scale_fill_gradientn(colours = c("#0571B0", "#92C5DE", "#F4A582", "#CA0020")) +
  ggtitle(':vis_cor')
pobj[["p6"]] <- data %>%
      select_if(is.numeric) %>%
      vis_value() + ggtitle(':vis_value')
pobj[["p6"]] <- pobj[["p6"]] + 
  scale_fill_gradientn(colours = c("#0571B0","#92C5DE","#F7F7F7","#F4A582",
                                   "#CA0020"))

pstr <- paste0(sprintf("pobj[[%s]]", 1:length(pobj)), collapse = " + ")
p <- eval(parse(text = 
  sprintf("%s + plot_layout(ncol = 2) +
plot_annotation(tag_levels = 'A')", pstr)))

p
FigureΒ 1: Visdat