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Visualize missingness in a dataframe

Source: R/vis_miss.R
vis_miss.Rd

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

if (FALSE) { # \dontrun{
  monitors <- c("ASN00003003", "ASM00094299")
  weather_df <- meteo_pull_monitors(monitors)
  vis_miss(weather_df)
} # }