Enable column profile histogram analysis for columns of numeric types #97
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… float, integer, long, and short
sscdotopen
suggested changes
Apr 11, 2019
src/test/scala/com/amazon/deequ/profiles/ColumnProfilerTest.scala
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src/test/scala/com/amazon/deequ/profiles/ColumnProfilerTest.scala
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src/test/scala/com/amazon/deequ/profiles/ColumnProfilerTest.scala
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src/test/scala/com/amazon/deequ/profiles/ColumnProfilerTest.scala
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I checked our coding style https://github.com/databricks/scala-style-guide#indent and you are right that we dont need to indent long method invocations with 4 spaces, sorry for that. I deleted the corresponding comments. |
added 2 commits
April 11, 2019 08:35
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@sscdotopen Ok, I made those changes |
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@sscdotopen can you re-review this pr? |
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Looks good, thank you! |
paulsukow
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feature/columnProfileHistogramsFromNumericDataWithLowCardinality
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Fix for issue: #95
Description of changes:
Histogram analysis for column profiling was limited to boolean and string columns. However, it is possible to have categorical data with numerical values (ex 1 indicating male and 2 indicating female). Made changes to allow histogram analysis for columns with short, long, double, float, and integer data types
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.