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[explore] proper filtering of NULLs and '' (#4651)
* [WiP] [explore] proper filtering of NULLs and ''
TODO: handling of Druid equivalents
* Unit tests
* Some refactoring
* [druid] fix 'Unorderable types' when col has nuls
Error "unorderable types: str() < int()" occurs when grouping by a
numerical Druid colummn that contains null values.
* druid/pydruid returns strings in the datafram with NAs for nulls
* Superset has custom logic around get_fillna_for_col that fills in the
NULLs based on declared column type (FLOAT here), so now we have a mixed
bag of type in the series
* pandas chokes on pivot_table or groupby operations as it cannot sorts
mixed types
The approach here is to stringify and fillna('<NULL>') to get a
consistent series.
* typo
* Fix druid_func tests
* Addressing more comments
* last touches
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@@ -1,6 +1,6 @@
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import { it, describe } from 'mocha';
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import { expect } from 'chai';
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import { isTruthy } from '../../../src/utils/common';
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import { isTruthy, optionFromValue } from '../../../src/utils/common';
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describe('utils/common', () => {
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describe('isTruthy', () => {
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@@ -40,4 +40,14 @@ describe('utils/common', () => {
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expect(isTruthy('false')).to.equal(false);
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});
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});
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describe('optionFromValue', () => {
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it('converts values as expected', () => {
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expect(optionFromValue(false)).to.deep.equal({ value: false, label: '<false>' });
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expect(optionFromValue(true)).to.deep.equal({ value: true, label: '<true>' });
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expect(optionFromValue(null)).to.deep.equal({ value: '<NULL>', label: '<NULL>' });
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expect(optionFromValue('')).to.deep.equal({ value: '', label: '<empty string>' });
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expect(optionFromValue('foo')).to.deep.equal({ value: 'foo', label: 'foo' });
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expect(optionFromValue(5)).to.deep.equal({ value: 5, label: '5' });
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});
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});
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});
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