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scatter-chart

Design
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Configure scatter plots in drizzle-cube dashboards for correlation and distribution analysis. Use when creating scatter plots, correlation charts, or distribution visualizations.

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Scatter Chart Configuration

Configure scatter plots for drizzle-cube dashboards. Scatter charts show relationships between two variables, revealing correlations and distributions.

Chart Type

chartType: 'scatter'

Basic Configuration

{
  id: 'scatter-1',
  title: 'Salary vs Experience',
  query: JSON.stringify({
    dimensions: [
      'Employees.yearsOfService',
      'Employees.salary',
      'Employees.name'
    ]
  }),
  chartType: 'scatter',
  chartConfig: {
    xAxis: ['Employees.yearsOfService'],
    yAxis: ['Employees.salary']
  },
  x: 0, y: 0, w: 8, h: 5
}

Chart Configuration (chartConfig)

xAxis (X Variable)

  • Type: string[]
  • Purpose: Dimension/measure for X axis
  • Example: ['Employees.yearsOfService']

yAxis (Y Variable)

  • Type: string[]
  • Purpose: Dimension/measure for Y axis
  • Example: ['Employees.salary']

series (Grouping)

  • Type: string[]
  • Purpose: Dimension for color grouping
  • Example: ['Departments.name']

Examples

Correlation Analysis

{
  id: 'price-demand',
  title: 'Price vs Demand',
  query: JSON.stringify({
    dimensions: [
      'Products.price',
      'Products.unitsSold',
      'Products.name'
    ]
  }),
  chartType: 'scatter',
  chartConfig: {
    xAxis: ['Products.price'],
    yAxis: ['Products.unitsSold']
  },
  x: 0, y: 0, w: 8, h: 5
}

Multi-Category Scatter

{
  id: 'performance-scatter',
  title: 'Performance by Department',
  query: JSON.stringify({
    dimensions: [
      'Employees.productivity',
      'Employees.satisfaction',
      'Employees.name',
      'Departments.name'
    ]
  }),
  chartType: 'scatter',
  chartConfig: {
    xAxis: ['Employees.productivity'],
    yAxis: ['Employees.satisfaction'],
    series: ['Departments.name']
  },
  displayConfig: {
    showLegend: true
  },
  x: 0, y: 0, w: 10, h: 6
}

Use Cases

  • Correlation Analysis: Find relationships between variables
  • Distribution Patterns: Identify clustering
  • Outlier Detection: Spot anomalies
  • Multi-Variable Comparison: Compare multiple factors

Related Skills

  • Use bubble-chart for three-variable analysis
  • Use line-chart for trend analysis