This function will return a vector, with the same length as the number of rows of the provided data frame, corresponding to the average mahalanobis distances of each row from the whole data set.

1 |

`data` |
A data frame |

`keep.NA` |
Ensure that every row with missing data remains NA in the output? TRUE by default. |

`robust` |
Attempt to compute mahalanobis distance based on robust covariance matrix? FALSE by default |

This is useful for finding anomalous observations, row-wise.

It will convert any categorical variables in the data frame into numerics as long as they are factors. For example, in order for a character column to be used as a component in the distance calculations, it must either be a factor, or converted to a factor.

A vector of observation-wise mahalanobis distances.

`insist_rows`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
maha_dist(mtcars)
maha_dist(iris, robust=TRUE)
library(magrittr) # for piping operator
library(dplyr) # for "everything()" function
# using every column from mtcars, compute mahalanobis distance
# for each observation, and ensure that each distance is within 10
# median absolute deviations from the median
mtcars %>%
insist_rows(maha_dist, within_n_mads(10), everything())
## anything here will run
``` |

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