getDataInsights

3 min read

Automatically discovering interesting patterns from multi-dimensional data.

getDataInsights

(data: Datum[], options?: InsightOptions) => { insights: InsightInfo[], homogeneousInsights?: HomogeneousInsightInfo[] }

Run different algorithms from multi-dimensional data to discover interesting patterns in the data, and perform unified evaluation of different types of patterns, and return high-quality data insights based on scores.

InsightOptions configure the pipeline of Auto-Insights.

Properties	Type	Description	Default
measures	`Measure[]`	Specify the fields as measures and the corresponding aggregation methods.	All quantitative (numeric) fields
dimensions	`Dimensions[]`	Specify the dimensions involved in the calculation.	All categorical, time fields
insightTypes	`InsightType[]`	Specify the types of insight.	`['category_outlier', 'trend', 'change_point', 'time_series_outlier', 'majority','low_variance']`(All supported types)
limit	`number`	Limit on the number of insights.	30
visualization	`boolean \| VisualizationOptions`	on / off the output of visualization scheme, or visualization options.	`false`
impactMeasures	`ImpactMeasure[]`	Measures for Impact score.	none
impactWeight	`number ∈(0, 1)`	Insight score = Impact score * impactWeight + Significance * (1 - impactWeight).	`0.3`
homogeneous	`boolean`	on/off extra homogeneous insight extraction.	`false`
ignoreSubspace	`boolean`	Whether to close the search for subspaces.	`false`

VisualizationOptions Insight output visualization options

Properties	Type	Description	Default
summaryType	`text`\|`schema`	pure text or text schema to description insight summary	'text'

InsightInfo|HomogeneousInsightInfo Insight information.

Properties	Type	Description	Example
subspace	`Subspace`	The subspace of the data subject	`[{ dimension: 'Year', value: '2000' }]`(subspace: Year = 2000)
dimensions	`string[]`	The dimensions of the data subject	`['country']`
measures	`Measure[]`	The measures of the data subject	`[{ field: 'life_expect', method: 'MEAN' }]`
data	`Datum[]`	data	`[{ country: 'China', life_expect: 61 }]`
patterns	`PatternInfo[]`	The collection of patterns in the data	`[{ type: 'outlier', significance: 0.98, dimension: 'country', measure: 'life_expect', index: 5, x: 'china', y: '43' }, ...]`
visualizationSchemas	`VisualizationSchema[]`	The insight visualization scheme, including chart type, title, insight description, and chart configuration (based on G2Plot)	`[{ type: 'column_chart', caption: string, insightSummaries: string[] \| IPhrase[][], chartSchema: G2PlotConfig }]`

IPhrase Description of phrase

Phrase descriptions are distinguished by type, which is divided into text phrases and entity phrases, and entity phrases are used to mark lexical attributes. The current descriptions in the lite-insight module involve entity types such as

'metric_name': Metric Name;
'metric_value': Metric Value;
'trend_desc': Trend Description;
'dim_value': Dimension Value;

export type IPhrase = ITextPhrase | IEntityPhrase;

export interface ITextPhrase {
  type: 'text';
  value: string;
}

export interface IEntityPhrase {
  type: 'entity';
  value?: string;
  metadata?: {
    entityType: 'metric_name' | 'metric_value' | 'trend_desc' | 'dim_value';
  };
}

Usage

Specify the measures and dimensions involved in the calculation, and the number of insights returned.

import { getDataInsights } from '@antv/lite-insight';

getDataInsights(data, {
  limit: 30,
  dimensions: ['year', 'country'],
  measures: [
    { field: 'life_expect', method: 'MEAN' },
    { field: 'pop', method: 'SUM' },
    { field: 'fertility', method: 'MEAN' },
  ]
});

Set the measures of the impact score, and adjust the calculation weight of the relevant factors (significance, impact) in the calculation of the insight score.

import { getDataInsights } from '@antv/lite-insight';


getDataInsights(data, {
  impactWeight: 0.5,
  impactMeasures: [
    { field: 'life_expect', method: 'COUNT' },
    { field: 'pop', method: 'SUM' },
  ]
});

Enable the extraction of homogeneous data patterns.

import { getDataInsights } from '@antv/lite-insight';

const result = getDataInsights(data, {
  homogeneous: true
});

const { insights, homogeneousInsights } = result;
console.log(homogeneousInsights);

getDataInsightsAsync

(data: Datum[], options?: InsightOptions) => Promise<{ insights: InsightInfo[], homogeneousInsights?: HomogeneousInsightInfo[] }>

Async version of getDataInsights.