vis_miss: Visualize missingness in a dataframe

In rnoaa: 'NOAA' Weather Data from R

Visualize missingness in a dataframe

Description

Gives you an at-a-glance ggplot of the missingness inside a dataframe, colouring cells according to missingness, where black indicates a present cell and grey indicates a missing cell. As it returns a ggplot object, it is very easy to customize and change labels, and so on.

Usage

vis_miss(x, cluster = FALSE, sort_miss = FALSE)

Arguments

x	a data.frame
cluster	logical TRUE/FALSE. TRUE specifies that you want to use hierarchical clustering (mcquitty method) to arrange rows according to missingness. FALSE specifies that you want to leave it as is.
sort_miss	logical TRUE/FALSE. TRUE arranges the columns in order of missingness.

Details

vis_miss visualises a data.frame to display missingness. This is taken from the visdat package, currently only available on github: https://github.com/tierneyn/visdat

Examples

## Not run: 
  monitors <- c("ASN00003003", "ASM00094299")
  weather_df <- meteo_pull_monitors(monitors)
  vis_miss(weather_df)

## End(Not run)

rnoaa documentation built on April 27, 2023, 9:08 a.m.