Visualisation definition Scorecard Group

The scorecard-group chart visualisation type represents data as a collection scorecard visualisations in a group.

A scorecard is used to display:

• A snapshot value of a data point at a specific point in time.
• The data trend over time, within a user selected date range.
• The RAG score/status for the presented value.

contents

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When to use

Use scorecard group when:

• You want to display a group of scorecards
• You want multiple rows in a data subset displayed as scorecards

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How it works

A scorecard group uses multiple rows in a dataset to create the visualisation.

A scorecard group can be generated from a list, or from columns defined in a dataset. See the examples below for instruction in how to do this.

See the scorecard for details on how a scorecard works

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Definition

{
  id: 'scorecard-group-definition-example',
  type: 'scorecard-group',
  display: 'Scorecard Group title',
  description: 'scorecard-group visualisation description',
  option: {
    ...
  }
  column: {
    ...
  }
}

See the Targeting data for and how to target data with the column

Options:

See Custom buckets for options documentation

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Examples

These examples demonstrate how to present multiple rows within a dataset as a scorecard group.

Example Dataset

For these examples we will use a mocked dataset representing data quality totals.

| ts         | est_id | has_nationality | has_ethnicity | has_religion | religion_is_missing |
|------------|--------|-----------------|---------------|--------------|---------------------|
| Nov 25.    | MDI    | 21              | 91            | 54           | 63                  |
| Nov 25.    | SLI    | 34              | 21            | 12           | 12                  |
| Nov 25.    | DAI    | 86              | 64            | 36           | 87                  |
| Nov 25.    | LTI    | 23              | 63            | 87           | 54                  |
... omitted past ts data

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Scorecard group from list data

The example creates a scorecard group using values in a list. We will be showing ethnicity metrics by establishment ID.

To do this we define 2 measures

• the column we want to use as the list: est_id
• the column we want to use as the numeric value: has_ethnicity

We must also define displayValue in the measure for the numeric value:

• Informs which column the numeric value should be taken from, and which is the description column.
• instructs that the group is to be generated from a list

In this dataset we have 4 unique values for est_id, therefore we will have 4 scorecards in our group

Definition

{
  id: 'data-quality-ethnicity',
  type: 'scorecard-group',
  display: 'Ethnicity score',
  description: '',
  option: {
    useRagColour: true,
    bucket: [{ min: 0, max: 500 }, { min: 501, max: 700 }, { min: 701 }],
  },
  column: {
    key: [{ id: 'establishment_id' }],
    measure: [
      {
        id: 'establishment_id',       // defines the value to use as the scorecard title
        display: ''                   // optional prefix display value
      },
      {
        id: 'has_ethnicity',
        displayValue: true,           // defines the number value to display, that that this is a group from a list
      },
    ],
  },
}

Visualisation

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Scorecard group from columns

This example demonstrates how to create a scorecard group using columns in a dataset as scorecard titles and values. The example shows data quality metrics as a group for each establishment

• Define all columns in the measure array that you want display, with a display field to add the scorecard title
• Define the column(s) in the key array that we want to group by.

Each value in the group column will be used as new group:

• est_id is defined as our group
• est_id has 4 unique values in the dataset
• therefore we will have 4 groups - One for each value.

Definition

{
  id: 'data-quality-no-nationality',
  type: 'scorecard-group',
  display: 'Data quality scores',
  description: '',
  option: {
    bucket: [{ min: 0, max: 500 }, { min: 501, max: 700 }, { min: 701 }],
    useRagColour: true,
  },
  column: {
    key: [
      {
        id: 'est_id',
        display: 'Establishment ID',
      },
    ],
    measure: [
      {
        id: 'has_nationality',
        display: 'Has nationality',
      },
      {
        id: 'nationality_is_missing',
        display: 'Nationality is missing',
      },
      {
        id: 'religion_is_missing',
        display: 'Religion is missing',
      },
      {
        id: 'has_religion',
        display: 'Has religion',
      },
      {
        id: 'ethnicity_is_missing',
        display: 'Ethnicity is missing',
      },
      {
        id: 'has_ethnicity',
        display: 'Has ethnicity',
      },
    ],
  },
}

Visualisation

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