Vega-Lite

A Flourish template based on Vega-Lite capable of creating all kinds of charts, and transforming data on the fly

Updated 6 years ago by Duncan Clark

How to use this template

Vega-Lite

A template to unlock the power of Vega-Lite visualisations in Flourish.

Vega-Lite lets you concisely specify interactive visualisations in JSON syntax, and has a wide range of chart types.

To build your own Vega-Lite charts in Flourish:

  • Upload your data, and update the Data binding to point to the columns for use in the visualisation.
  • Choose an example from the Vega-Lite examples gallery. Copy the JSON used in the example, and paste it into the Vega-lite code setting field.
  • Delete the $schema, description and data fields.
  • In the encoding field, update the field names to point at the names of your bound columns.

For example, if you were building a Vega-lite simple bar chart, and you had CSV data like this:

customer,sales
robin,17825
duncan,78124
tim,98724

You would need to bind columns A-B in your data, then use the following JSON:

{
  "mark": "bar",
  "encoding": {
    "x": {"field": "customer", "type": "ordinal"},
    "y": {"field": "sales", "type": "quantitative"}
  }
}

For more advanced options, see the Vega-lite documentation.

This section documents API usage specific to this template, so for an introduction we suggest you refer to the generic API documentation instead.

template: _605

version: _2

Template data

There are three different formats in which you can supply data to this template. The most convenient for you to use likely depends on the source of your data, as described below.

1. Array of arrays, and a bindings object

You can supply arrays of arrays to opts.data, which might look like:

{
    data: {
        values: [
            [ "ValuesColumn1Value1", "ValuesColumn2Value1",
            [ "ValuesColumn1Value2", "ValuesColumn2Value2",
            [ "ValuesColumn1Value3", "ValuesColumn2Value3",
            ...
        ]
    }
}

where each array of arrays represents the rows in a data sheet.

To tell the API how the values from each column should be associated with the keys that the template is expecting, you must also supply an object attached to opts.bindings. (The meanings of the keys in the bindings object are documented below.) The minimal bindings you can supply for this template are as shown in this example:

{
    template: "_605",
    version: "_2",
    bindings: {
        values: {
            
        }
    },
    data: {
        values: [
            [ "ValuesColumn1Value1", "ValuesColumn2Value1",
            [ "ValuesColumn1Value2", "ValuesColumn2Value2",
            [ "ValuesColumn1Value3", "ValuesColumn2Value3",
            ...
        ]
    }
}

All possible bindings that you can supply are shown in this example:

{
    template: "_605",
    version: "_2",
    bindings: {
        values: {
            cols: [0, 1, ...], // index(es) of column(s) in your data
        }
    },
    data: {
        values: [
            [ "ValuesColumn1Value1", "ValuesColumn2Value1",
            [ "ValuesColumn1Value2", "ValuesColumn2Value2",
            [ "ValuesColumn1Value3", "ValuesColumn2Value3",
            ...
        ]
    }
}

2. Array of objects with arbitrary keys, and a bindings object

This format is most likely useful when you have data from an external source, such as CSV data loaded from d3-dsv. You should supply this attached to the opts.data, which might look like:

{
        values: [
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            ...
        ]
    }

... but with the keys being the column headers from your source data instead. You must also supply an object attached to opts.bindings. The minimal bindings you can supply for this template are as shown in this example:

{
    template: "_605",
    version: "_2",
    bindings: {
        values: {
            
        }
    },
    data: {
        values: [
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            ...
        ]
    }
}

All possible bindings that you can supply are shown in this example:

{
    template: "_605",
    version: "_2",
    bindings: {
        values: {
            cols: ["ValuesHeader1", "ValuesHeader2", ...],
        }
    },
    data: {
        values: [
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            { "ValuesHeader1": ..., "ValuesHeader2": ..., ... },
            ...
        ]
    }
}

(As before, the keys containing "Header" would be replaced by column names from your data source.)

3. Array of objects with template-defined keys

There is an alternative format you can use, which is likely to be easier to use if your data is not from a spreadsheet source. With this alternative format you supply your data to the template as an array of objects, attached to opts.data, where the keys must be those used by the template, as documented below. In this case there is no need to supply a bindings object, since the key names are already those expected by the template. The required properties in the data object are as follows (scroll down for a description of what each property is):

{
    template: "_605",
    version: "_2",
    data: {
    values: [
        {
            cols: [...]
        },
        ...
    ]
},
    ...
}

And the full list of all possible properties is as follows:

{
    template: "_605",
    version: "_2",
    data: {
    values: [
        {
            cols: [...]
        },
        ...
    ]
},
    ...
}

Meanings of the template data keys:

  • values.cols: Columns for use in the visualisation

Template settings

Options for opts.state.

Settings

spec code

Vega-Lite code. The Vega-Lite configuration code (in JSON format). To copy a example from the Vega-Lite gallery just paste in the code here, delete the “data”, “width” and “height” properties and update the “field” properties to match column names in your spreadsheet.

header_title string

Title.

header_subtitle string

Subtitle.

header_margin number

Margin.

header_color color

Color.

header_align string

Text align.

Allowed values:

  • left (fa-align-left)
  • center (fa-align-center)
  • right (fa-align-right)

Multi-chart layout

multichart_margin_horizontal number

Horizontal space. How much horizontal space to leave for axes, legends, etc

multichart_margin_vertical number

Vertical space. How much vertical space to leave for axes, legends, etc;