Neither of those use cases actually works.
Consider the following partial class hierarchy from my Smalltalk system:
Object
VectorSpace
Complex
Quaternion
Magnitude
MagnitudeWithAddition
DateAndTime
QuasiArithmetic
Duration
Number
AbstractRationalNumber
Integer
"Richard O'Keefe" writes:
> My difficulty is that from a statistics/data science perspective,
> it doesn't seem terribly *useful*.
There are two common use cases in my experience:
1) Error checking, most frequently right after reading in a dataset.
A quick look at the data types of all colu
Hi Balaji,
> Thanks for pointing this out. You are right with how the data types are
> calculated, similar to collection >> commonSuperClass. But this time, it is
> calculated only during the creation of DataFrame once and for all.
That sounds good.
> A nil value, or a Series of nil values yield
What are the current options for logging?
Beacon seems to be the most modern one, but the Github repository
doesn't seem very active (maybe it forked somewhere else).
Given that the logs might come from different worker images, is there
something that can work via HTTP or similar? (it is, forward
I am not quite sure what the point of the datatypes feature is.
x := nil.
aSequence do: [:each |
each ifNotNil: [
x := x ifNil: [each class] ifNotNil: [x commonSuperclassWith: each class]]].
doesn't seem terribly complicated.
My difficulty is that from a statistics/data science perspective
