DataFrameTypeDetector now works with nil#107
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Also added relevant tests
| { #category : #testing } | ||
| DataFrameTypeDetector >> canAllBeDateAndTime: aDataSeries [ | ||
| [ aDataSeries do: #asDateAndTime ] | ||
| [ aDataSeries do: [ :ele | ele isNil ifFalse: [ ele asDateAndTime ]] ] |
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Here and in the following, I'd use ele ifNotNil: rather than ele isNil ifFalse: .
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| ^ aDataSeries | ||
| detect: [ :each | [ (regex matches: each) not ] on: Error do: [ ^ false ] ] | ||
| detect: [ :each | [ each isNil ifTrue: [ false ] ifFalse: [ (regex matches: each) not ]] on: Error do: [ ^ false ] ] |
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Simlarly: each ifNil: [ false ] ifNotNil: [...]
| DataFrameTypeDetector >> canAnyBeFloat: aDataSeries [ | ||
| ^ aDataSeries | ||
| detect: [ :each | each asNumber isFloat ] | ||
| detect: [ :each | each isNil ifTrue: [ false ] ifFalse: [ (each asNumber isFloat) ] ] |
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Simpler: each isNotNil and: [ each asNumber isFloat ].
| ^ aDataSeries collect: [ :each | each = 'true' ] | ||
| ^ aDataSeries collect: [ :each | | ||
| each isNil | ||
| ifFalse: [ each = 'true' ] ] |
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Once again: ifNotNil: is clearer than isNil ifFalse:.
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However, seeing all the following cases I wonder if it would be better to have a method #collectNonNils and use that instead of nil-testing in each particular use case.
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I'll add collectNonNils since it makes more sense. PR 102 has removeNils already so we can do dataSeries deepCopy removeNils, but one with collect would be better.
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Also added relevant tests.
Fixes #66.