Python Panda default to Null and before that it uses something else to represent missing data. Null value in general is the last thing you do when you don't know how to represent a certain type. If you have a type language with sum type and pattern matching then you don't even need null. And yes R have its own Null type so NA is separate from it.
Erlang have PID as a primitive.
I think any domain specific languages are smaller in rules and syntax, and it makes it very very easy to learn for experts and people of those domains.
So it understand the concept of missing value and works with logical operation. Also it have factor concept into the language too.
General Language may not have the tool to deal with missing value and having a library doesn't necessary means it's good as a built-in concept NA.
Python panda and such does not handle NA as beautifully as R. (http://pandas.pydata.org/pandas-docs/stable/missing_data.htm...)
Python Panda default to Null and before that it uses something else to represent missing data. Null value in general is the last thing you do when you don't know how to represent a certain type. If you have a type language with sum type and pattern matching then you don't even need null. And yes R have its own Null type so NA is separate from it.
Erlang have PID as a primitive.
I think any domain specific languages are smaller in rules and syntax, and it makes it very very easy to learn for experts and people of those domains.