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)
x | a data.frame |
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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 |
ggplot2
object displaying the position of missing values in the
dataframe, and the percentage of values missing and present.
vis_miss(airquality)vis_miss(airquality, cluster = TRUE)vis_miss(airquality, sort_miss = TRUE)