DataFrameTypeDetector now works with nil #107
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Also added relevant tests
| ifFound: [ false ] | ||
| ifNone: [ true ]. | ||
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| { #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: .
| @@ -32,49 +32,51 @@ DataFrameTypeDetector >> canAllBeNumber: aDataSeries [ | |||
| regex := '^[-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?$' asRegex. | |||
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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: [...]
| on: Error do: [ ^ false ]. | ||
| ^ true | ||
| ] | ||
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| { #category : #testing } | ||
| 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.
Also added relevant tests.
Fixes #66.