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

vis_miss(x, cluster = FALSE, sort_miss = FALSE, show_perc = TRUE,
  show_perc_col = TRUE, large_data_size = 9e+05, warn_large_data = TRUE)

Arguments

x

a data.frame

cluster

logical. 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 arranges the columns in order of missingness

show_perc

logical. TRUE now adds in the % of missing/complete data in the whole dataset into the legend. Default value is TRUE.

show_perc_col

logical. TRUE adds in the % missing data in a given column into the x axis. Can be disabled with FALSE

large_data_size

integer default is 900000, this can be changed.

warn_large_data

logical default is TRUE

Value

ggplot2 object displaying the position of missing values in the dataframe, and the percentage of values missing and present.

See also

vis_dat()

Examples

vis_miss(airquality)
vis_miss(airquality, cluster = TRUE)
vis_miss(airquality, sort_miss = TRUE)