vis_expect visualises certain conditions or values in your data. For example, If you are not sure whether to expect -1 in your data, you could write: vis_expect(data, ~.x == -1), and you can see if there are times where the values in your data are equal to -1. You could also, for example, explore a set of bad strings, or possible NA values and visualise where they are using vis_expect(data, ~.x %in% bad_strings) where bad_strings is a character vector containing bad strings like N A N/A etc.

vis_expect(data, expectation, show_perc = TRUE)



a data.frame


a formula following the syntax: ~.x {condition}. For example, writing ~.x < 20 would mean "where a variable value is less than 20, replace with NA", and ~.x %in% {vector} would mean "where a variable has values that are in that vector".


logical. TRUE now adds in the % of expectations are TRUE or FALSE in the whole dataset into the legend. Default value is TRUE.


a ggplot2 object

See also


dat_test <- tibble::tribble( ~x, ~y, -1, "A", 0, "B", 1, "C", NA, NA ) vis_expect(dat_test, ~.x == -1)
# NOT RUN { vis_expect(airquality, ~.x == 5.1) # explore some common NA strings common_nas <- c( "NA", "N A", "N/A", "na", "n a", "n/a" ) dat_ms <- tibble::tribble(~x, ~y, ~z, 1, "A", -100, 3, "N/A", -99, NA, NA, -98, "N A", "E", -101, "na", "F", -1) vis_expect(dat_ms, ~.x %in% common_nas) # }