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fix(plugin-chart-echarts): support adhoc x-axis (#20055)
* fix(plugin-chart-echarts): support adhoc x-axis * simplify code
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@ -31,11 +31,13 @@ export const pivotOperator: PostProcessingFactory<PostProcessingPivot> = (
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) => {
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) => {
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const metricLabels = ensureIsArray(queryObject.metrics).map(getMetricLabel);
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const metricLabels = ensureIsArray(queryObject.metrics).map(getMetricLabel);
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const { x_axis: xAxis } = formData;
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const { x_axis: xAxis } = formData;
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if ((xAxis || queryObject.is_timeseries) && metricLabels.length) {
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if ((xAxis || queryObject.is_timeseries) && metricLabels.length) {
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const index = [getColumnLabel(xAxis || DTTM_ALIAS)];
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return {
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return {
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operation: 'pivot',
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operation: 'pivot',
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options: {
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options: {
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index: [xAxis || DTTM_ALIAS],
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index,
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columns: ensureIsArray(queryObject.columns).map(getColumnLabel),
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columns: ensureIsArray(queryObject.columns).map(getColumnLabel),
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// Create 'dummy' mean aggregates to assign cell values in pivot table
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// Create 'dummy' mean aggregates to assign cell values in pivot table
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// use the 'mean' aggregates to avoid drop NaN. PR: https://github.com/apache-superset/superset-ui/pull/1231
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// use the 'mean' aggregates to avoid drop NaN. PR: https://github.com/apache-superset/superset-ui/pull/1231
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@ -16,13 +16,18 @@
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* specific language governing permissions and limitationsxw
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* specific language governing permissions and limitationsxw
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* under the License.
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* under the License.
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*/
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*/
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import { DTTM_ALIAS, PostProcessingProphet } from '@superset-ui/core';
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import {
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DTTM_ALIAS,
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getColumnLabel,
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PostProcessingProphet,
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} from '@superset-ui/core';
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import { PostProcessingFactory } from './types';
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import { PostProcessingFactory } from './types';
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export const prophetOperator: PostProcessingFactory<PostProcessingProphet> = (
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export const prophetOperator: PostProcessingFactory<PostProcessingProphet> = (
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formData,
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formData,
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queryObject,
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queryObject,
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) => {
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) => {
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const index = getColumnLabel(formData.x_axis || DTTM_ALIAS);
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if (formData.forecastEnabled) {
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if (formData.forecastEnabled) {
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return {
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return {
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operation: 'prophet',
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operation: 'prophet',
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@ -33,7 +38,7 @@ export const prophetOperator: PostProcessingFactory<PostProcessingProphet> = (
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yearly_seasonality: formData.forecastSeasonalityYearly,
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yearly_seasonality: formData.forecastSeasonalityYearly,
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weekly_seasonality: formData.forecastSeasonalityWeekly,
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weekly_seasonality: formData.forecastSeasonalityWeekly,
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daily_seasonality: formData.forecastSeasonalityDaily,
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daily_seasonality: formData.forecastSeasonalityDaily,
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index: formData.x_axis || DTTM_ALIAS,
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index,
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},
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},
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};
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};
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}
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}
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@ -39,11 +39,12 @@ export const timeComparePivotOperator: PostProcessingFactory<PostProcessingPivot
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{ operator: 'mean' as NumpyFunction },
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{ operator: 'mean' as NumpyFunction },
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]),
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]),
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);
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);
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const index = [getColumnLabel(formData.x_axis || DTTM_ALIAS)];
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return {
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return {
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operation: 'pivot',
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operation: 'pivot',
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options: {
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options: {
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index: [formData.x_axis || DTTM_ALIAS],
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index,
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columns: ensureIsArray(queryObject.columns).map(getColumnLabel),
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columns: ensureIsArray(queryObject.columns).map(getColumnLabel),
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drop_missing_columns: false,
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drop_missing_columns: false,
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flatten_columns: false,
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flatten_columns: false,
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@ -136,3 +136,35 @@ test('pivot by x_axis with groupby', () => {
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},
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},
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});
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});
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});
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});
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test('pivot by adhoc x_axis', () => {
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expect(
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pivotOperator(
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{
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...formData,
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x_axis: {
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label: 'my_case_expr',
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expressionType: 'SQL',
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expression: 'case when a = 1 then 1 else 0 end',
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},
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},
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{
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...queryObject,
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columns: ['foo', 'bar'],
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},
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),
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).toEqual({
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operation: 'pivot',
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options: {
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index: ['my_case_expr'],
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columns: ['foo', 'bar'],
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aggregates: {
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'count(*)': { operator: 'mean' },
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'sum(val)': { operator: 'mean' },
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},
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drop_missing_columns: false,
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flatten_columns: false,
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reset_index: false,
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},
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});
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});
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@ -98,3 +98,36 @@ test('should do prophetOperator over named column', () => {
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},
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},
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});
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});
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});
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});
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test('should do prophetOperator over adhoc column', () => {
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expect(
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prophetOperator(
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{
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...formData,
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x_axis: {
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label: 'my_case_expr',
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expressionType: 'SQL',
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expression: 'case when a = 1 then 1 else 0 end',
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},
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forecastEnabled: true,
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forecastPeriods: '3',
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forecastInterval: '5',
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forecastSeasonalityYearly: true,
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forecastSeasonalityWeekly: false,
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forecastSeasonalityDaily: false,
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},
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queryObject,
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),
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).toEqual({
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operation: 'prophet',
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options: {
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time_grain: 'P1Y',
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periods: 3.0,
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confidence_interval: 5.0,
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yearly_seasonality: true,
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weekly_seasonality: false,
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daily_seasonality: false,
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index: 'my_case_expr',
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},
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});
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});
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@ -135,3 +135,44 @@ test('should pivot on x-axis', () => {
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},
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},
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});
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});
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});
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});
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test('should pivot on adhoc x-axis', () => {
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expect(
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timeComparePivotOperator(
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{
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...formData,
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comparison_type: 'values',
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time_compare: ['1 year ago', '1 year later'],
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x_axis: {
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label: 'my_case_expr',
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expressionType: 'SQL',
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expression: 'case when a = 1 then 1 else 0 end',
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},
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},
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queryObject,
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),
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).toEqual({
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operation: 'pivot',
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options: {
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aggregates: {
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'count(*)': { operator: 'mean' },
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'count(*)__1 year ago': { operator: 'mean' },
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'count(*)__1 year later': { operator: 'mean' },
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'sum(val)': {
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operator: 'mean',
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},
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'sum(val)__1 year ago': {
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operator: 'mean',
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},
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'sum(val)__1 year later': {
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operator: 'mean',
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},
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},
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drop_missing_columns: false,
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columns: ['foo', 'bar'],
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index: ['my_case_expr'],
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flatten_columns: false,
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reset_index: false,
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},
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});
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});
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@ -23,6 +23,7 @@ import {
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DataRecordValue,
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DataRecordValue,
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DTTM_ALIAS,
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DTTM_ALIAS,
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GenericDataType,
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GenericDataType,
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getColumnLabel,
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getNumberFormatter,
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getNumberFormatter,
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isEventAnnotationLayer,
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isEventAnnotationLayer,
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isFormulaAnnotationLayer,
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isFormulaAnnotationLayer,
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@ -141,7 +142,8 @@ export default function transformProps(
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const colorScale = CategoricalColorNamespace.getScale(colorScheme as string);
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const colorScale = CategoricalColorNamespace.getScale(colorScheme as string);
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const rebasedData = rebaseForecastDatum(data, verboseMap);
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const rebasedData = rebaseForecastDatum(data, verboseMap);
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const xAxisCol = verboseMap[xAxisOrig] || xAxisOrig || DTTM_ALIAS;
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const xAxisCol =
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verboseMap[xAxisOrig] || getColumnLabel(xAxisOrig || DTTM_ALIAS);
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const rawSeries = extractSeries(rebasedData, {
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const rawSeries = extractSeries(rebasedData, {
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fillNeighborValue: stack && !forecastEnabled ? 0 : undefined,
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fillNeighborValue: stack && !forecastEnabled ? 0 : undefined,
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xAxis: xAxisCol,
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xAxis: xAxisCol,
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