is.na10 is a helper function for creating heatmaps to diagnose missing value patterns. It is similar to is.na but instead of returning a logical TRUE/FALSE vector (or matrix) it returns a numeric 1/0 output. This enables the heatmaply function to be used on the data.

is.na10(x, ...)

Arguments

x

a vector, matrix or data.frame.

...

not used.

Value

Returns a numeric (instead of a logical) variable/matrix of 1 (missing) or 0 (not missing) values (hence the name is.na10) while still preserving the attributes resulted from running is.na.

These are useful for funnelling into a heatmap (see the examples).

See also

is.na, the grid_gap parameter in heatmaply.

Examples

if (FALSE) { x <- mtcars x <- data.frame(x) x$am <- factor(x$am) x$vs <- factor(x$vs) set.seed(2017-01-19) x[sample(nrow(x))[1:6],sample(ncol(x))[1:6]] <- NA # nice grey colors from here: https://github.com/njtierney/visdat/blob/master/R/vis_miss_ly.R x %>% is.na10 %>% heatmaply( colors = c("grey80", "grey20"), dendrogram = "none") x %>% is.na10 %>% heatmaply( colors = c("grey80", "grey20"), k_col = 2, k_row = 2) heatmaply(is.na10(airquality), grid_gap = 1, colors = c("grey80", "grey20"), k_col = 2, k_row = 2) }