Julia: Support `isapprox` with `missing` values
Currently calling isapprox with missing results in a MethodError:
julia> isapprox(missing, missing)
ERROR: MethodError: no method matching isapprox(::Missing, ::Missing)
It's also worth noting that if missing values will be supported by isapprox we may want to also introduce a missings keyword to the function to mirror the nans keyword:
The keyword argument
nansdetermines whether or not NaN values are considered equal (defaults to false)
missing data
omus
>All comments
It seems like if either argument is missing then the answer should be missing, which matches ==.
StefanKarpinski
on 12 Jul 2018
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Most helpful comment
It seems like if either argument is
missingthen the answer should bemissing, which matches==.