I want to insert a new column into a data.frame, which value is TRUE when there is at least one missing value in the row and FALSE otherwise.

For that problem, `apply` is a a perfect use case:

###  EDIT - added example

```
tab <- data.frame(a = 1:10, b = c(NA, letters[2:10]), c = c(LETTERS[1:9], NA))

tab$missing <- apply(tab, 1, function(x) any(is.na(x)))

```

However, I loaded the [strict](https://github.com/hadley/strict) package, and got this error: `apply() coerces X to a matrix so is dangerous to use with data frames.Please use lapply() instead.`

I know that I can safely ignore this error, however, I was wondering if there was a way to code it using one of the tidyverse packages, **in a simple manner**. I tried unsuccessfully with dplyr:

```
tab %>% 
  rowwise() %>% 
  mutate(missing = any(is.na(.), na.rm = TRUE))

```