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Custom visualizations in AI/BI dashboards

Preview

This feature is in Public Preview.

Custom visualizations let you customize charts in AI/BI dashboards beyond the built-in visualization types. Custom visualizations use the Vega-Lite library to render charts from a JSON specification.

Create a custom visualization

  1. Select a dataset.
  2. In the visualization configuration pane, select Custom Viz under the Advanced visualization section.
  3. In the Fields section, add the fields you want to use. Each field has a unique Name. Reference fields in your Vega-Lite specification using these names.
  4. Enter your Vega-Lite JSON specification in the Vega-Lite specification editor.

Step-by-step example

This example recreates the Layering Averages over Raw Values chart from the Vega-Lite example gallery.

  1. Create a dataset with the following query:

    SQL
    SELECT date, temperature AS temp_max
    FROM samples.accuweather.historical_hourly_imperial
    WHERE city_name = 'singapore'
    ORDER BY date
  2. In the visualization configuration pane, under Advanced, select Custom Viz.

  3. Select the dataset you created in the previous step.

  4. In the Fields section, add a field for the date column and set its Name to date.

  5. Add a field for the temperature column and set its Name to temp_max.

  6. Copy the following specification into the Vega-Lite specification editor.

If the x-axis is clipped, make the chart resize to its container. See Make a chart resize automatically.

Custom visualization chart example.

The following specification shows the completed example:

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"width": "container",
"height": "container",
"config": {
"autosize": { "type": "fit", "contains": "padding" }
},
"data": { "name": "databricks_query" },
"transform": [
{
"window": [{ "field": "temp_max", "op": "mean", "as": "rolling_mean" }],
"frame": [-15, 15]
}
],
"encoding": {
"x": { "field": "date", "type": "temporal", "title": "Date" },
"y": { "type": "quantitative", "scale": { "zero": false }, "axis": { "title": "Max temperature and rolling mean" } }
},
"layer": [
{
"mark": { "type": "point", "opacity": 0.3 },
"encoding": { "y": { "field": "temp_max", "title": "Max temperature" } }
},
{
"mark": { "type": "line", "color": "red", "size": 3 },
"encoding": { "y": { "field": "rolling_mean", "title": "Rolling mean of max temperature" } }
}
]
}

Reference dataset columns

There are two ways to reference columns in a Vega-Lite specification:

  • Use "field": "{columnName}". The following example assigns the xField column to the x-axis:

    JSON
    "encoding": {
    "x": { "field": "xField", "type": "quantitative" }
    }
  • In expressions, use datum["{columnName}"] or datum.{columnName}. The following example defines a new x column from the r and angle columns:

    JSON
    { "calculate": "datum.r * cos(datum.angle)", "as": "x" }

For more information, see datum in the Vega expressions documentation.

Resize a chart automatically

To make a chart resize to fit its container, add the following settings at the top level of your specification:

JSON
"width": "container",
"height": "container",
"config": {
"autosize": {
"type": "fit",
"contains": "padding"
}
}

Example chart specifications

The following specifications show charts that aren't available as built-in visualization types. For more examples, see the Vega-Lite example galleries.

Bullet chart

Bullet chart example.

Define categoryField, currentField, paceField, and targetField in the Fields section.

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"width": "container",
"height": "container",
"data": { "name": "databricks_query" },
"config": {
"autosize": { "type": "fit", "contains": "padding" }
},
"transform": [
{
"fold": ["targetField", "paceField", "currentField"],
"as": ["measure_name", "measure_value"]
},
{
"calculate": "toNumber(datum.measure_value)",
"as": "measure_value"
},
{
"calculate": "{ \"targetField\": \"Target\", \"paceField\": \"Pace\", \"currentField\": \"Current\" }[datum.measure_name]",
"as": "measure_label"
},
{
"calculate": "indexof([\"Target\", \"Pace\", \"Current\"], datum.measure_label)",
"as": "measure_order"
}
],
"layer": [
{
"mark": "bar",
"params": [
{
"name": "legend_click",
"select": { "type": "point", "fields": ["measure_label"] },
"bind": "legend"
}
],
"encoding": {
"color": { "field": "measure_label" },
"opacity": { "value": 0 }
}
},
{
"transform": [{ "filter": { "param": "legend_click" } }],
"layer": [
{
"layer": [
{
"mark": { "type": "bar", "tooltip": true },
"encoding": { "color": { "field": "measure_label", "legend": null } },
"transform": [{ "filter": { "field": "measure_label", "oneOf": ["Pace"] } }]
},
{
"mark": { "type": "bar", "height": 7, "tooltip": true },
"encoding": { "color": { "field": "measure_label", "legend": null } },
"transform": [{ "filter": { "field": "measure_label", "oneOf": ["Current"] } }]
},
{
"mark": { "type": "tick", "tooltip": true, "thickness": 3 },
"encoding": { "color": { "field": "measure_label", "legend": null } },
"transform": [{ "filter": { "field": "measure_label", "oneOf": ["Target"] } }]
}
],
"encoding": {
"x": {
"field": "measure_value",
"type": "quantitative",
"stack": null,
"title": "Value",
"axis": { "orient": "bottom" }
},
"color": {
"scale": {
"domain": ["Target", "Pace", "Current"],
"range": ["#000000", "#bcbcbc", "#A66BBF"]
}
},
"order": {
"field": "measure_order",
"type": "quantitative",
"sort": "descending"
}
}
}
],
"encoding": {
"y": {
"field": "categoryField",
"type": "ordinal",
"title": "Category",
"axis": { "labelOverlap": true }
},
"tooltip": [
{ "field": "categoryField", "type": "nominal", "title": "Category" },
{ "field": "currentField", "type": "quantitative", "title": "Current" },
{ "field": "paceField", "type": "quantitative", "title": "Pace" },
{ "field": "targetField", "type": "quantitative", "title": "Target" }
]
}
}
]
}

Gauge

Gauge chart example.

Define $valueField and $totalField in the Fields section.

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v6.json",
"width": "container",
"height": "container",
"data": { "name": "databricks_query" },
"config": {
"concat": { "spacing": 0 },
"autosize": { "type": "fit", "contains": "padding" }
},
"params": [
{ "name": "ring_max", "expr": "min(width, height) / 2 - 16" },
{ "name": "ring_width", "expr": "max(12, (min(width, height) / 2) * 0.12)" },
{ "name": "ring_gap", "expr": "max(4, (min(width, height) / 2) * 0.03)" },
{ "name": "label_color", "value": "#000000" },
{ "name": "ring_background_opacity", "value": 0.3 },
{ "name": "ring0_percent", "value": 100 },
{ "name": "ring0_outer", "expr": "ring_max + 2" },
{ "name": "ring0_inner", "expr": "ring_max + 1" },
{ "name": "ring1_outer", "expr": "ring0_inner - ring_gap" },
{ "name": "ring1_inner", "expr": "ring1_outer - ring_width" },
{ "name": "ring1_middle", "expr": "(ring1_outer + ring1_inner) / 2" },
{ "name": "arc_size", "expr": "220" }
],
"transform": [
{ "as": "ratio", "calculate": "datum['$valueField'] / datum['$totalField']" },
{ "as": "_arc_start_degrees", "calculate": "360 - ( arc_size / 2 )" },
{ "as": "_arc_end_degrees", "calculate": "0 + ( arc_size / 2 )" },
{ "as": "_arc_start_radians", "calculate": "2 * 3.14 * ( datum['_arc_start_degrees'] - 360 ) / 360" },
{ "as": "_arc_end_radians", "calculate": "2 * 3.14 * datum['_arc_end_degrees'] / 360" },
{ "as": "_arc_total_radians", "calculate": "datum['_arc_end_radians'] - datum['_arc_start_radians']" },
{ "as": "_ring_start_radians", "calculate": "datum['_arc_start_radians']" },
{
"as": "_ring_end_radians",
"calculate": "datum['_arc_start_radians'] + ( datum['_arc_total_radians'] * datum['ratio'] )"
}
],
"layer": [
{
"mark": {
"type": "arc",
"color": "lightgrey",
"theta": { "expr": "datum['_arc_start_radians']" },
"radius": { "expr": "ring1_outer" },
"theta2": { "expr": "datum['_arc_end_radians']" },
"radius2": { "expr": "ring1_inner" },
"cornerRadius": 10
}
},
{
"name": "RING",
"mark": {
"type": "arc",
"theta": { "expr": "datum['_ring_start_radians']" },
"radius": { "expr": "ring1_outer" },
"theta2": { "expr": "datum['_ring_end_radians']" },
"radius2": { "expr": "ring1_inner" },
"cornerRadius": 10
},
"encoding": {
"color": {
"value": "#307E31",
"condition": [
{ "test": "datum['ratio'] < 0.33", "value": "#880808" },
{ "test": "datum['ratio'] < 0.66", "value": "#E49B0F" }
]
}
}
},
{
"mark": { "type": "text", "fontSize": 40 },
"encoding": {
"text": { "field": "$valueField" },
"color": {
"value": "#307E31",
"condition": [
{ "test": "datum['ratio'] < 0.33", "value": "#880808" },
{ "test": "datum['ratio'] < 0.66", "value": "#E49B0F" }
]
}
}
}
]
}

Radar chart

Radar chart example.

Define $key and $value in the Fields section.

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"width": "container",
"height": "container",
"config": {
"autosize": { "type": "fit", "contains": "padding" }
},
"data": { "name": "databricks_query" },
"transform": [
{ "window": [{ "op": "row_number", "as": "category" }] },
{ "calculate": "datum.category - 1", "as": "category" },
{
"joinaggregate": [
{ "op": "count", "as": "numCategories" },
{ "op": "max", "field": "$value", "as": "maxValue" }
]
},
{ "calculate": "2 * PI * datum.category / datum.numCategories", "as": "angle" },
{ "calculate": "100 * datum['$value'] / datum.maxValue", "as": "r" },
{ "calculate": "datum.r * cos(datum.angle)", "as": "x" },
{ "calculate": "datum.r * sin(datum.angle)", "as": "y" },
{ "calculate": "110 * cos(datum.angle)", "as": "label_x" },
{ "calculate": "110 * sin(datum.angle)", "as": "label_y" }
],
"layer": [
{
"transform": [
{ "joinaggregate": [{ "op": "count", "as": "numCategories" }] },
{ "aggregate": [{ "op": "max", "field": "numCategories", "as": "numCategories" }] },
{ "calculate": "[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]", "as": "cats" },
{ "flatten": ["cats"], "as": ["cat"] },
{ "filter": "datum.cat <= datum.numCategories" },
{ "calculate": "2 * PI * datum.cat / datum.numCategories", "as": "angle" },
{ "calculate": "100 * cos(datum.angle)", "as": "x" },
{ "calculate": "100 * sin(datum.angle)", "as": "y" }
],
"mark": { "type": "line", "color": "#ddd", "strokeWidth": 1 },
"encoding": {
"x": { "field": "x", "type": "quantitative", "scale": { "domain": [-120, 120] }, "axis": null },
"y": { "field": "y", "type": "quantitative", "scale": { "domain": [-120, 120] }, "axis": null },
"order": { "field": "cat" }
}
},
{
"transform": [
{ "joinaggregate": [{ "op": "count", "as": "numCategories" }] },
{ "aggregate": [{ "op": "max", "field": "numCategories", "as": "numCategories" }] },
{ "calculate": "[20,40,60,80,100]", "as": "levels" },
{ "flatten": ["levels"], "as": ["level"] },
{ "calculate": "[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]", "as": "cats" },
{ "flatten": ["cats"], "as": ["cat"] },
{ "filter": "datum.cat <= datum.numCategories" },
{ "calculate": "2 * PI * datum.cat / datum.numCategories", "as": "angle" },
{ "calculate": "datum.level", "as": "r" },
{ "calculate": "datum.r * cos(datum.angle)", "as": "x" },
{ "calculate": "datum.r * sin(datum.angle)", "as": "y" }
],
"mark": { "type": "line", "color": "#ddd", "strokeWidth": 1 },
"encoding": {
"x": { "field": "x", "type": "quantitative" },
"y": { "field": "y", "type": "quantitative" },
"detail": { "field": "level" },
"order": { "field": "cat" }
}
},
{
"mark": { "type": "line", "color": "#9467bd", "strokeWidth": 2, "interpolate": "linear-closed" },
"encoding": {
"x": { "field": "x", "type": "quantitative" },
"y": { "field": "y", "type": "quantitative" },
"order": { "field": "category" }
}
},
{
"mark": { "type": "point", "filled": true, "size": 50, "color": "#9467bd" },
"encoding": {
"x": { "field": "x", "type": "quantitative" },
"y": { "field": "y", "type": "quantitative" }
}
},
{
"mark": { "type": "text", "fontSize": 14, "fontWeight": "bold" },
"encoding": {
"x": { "field": "label_x", "type": "quantitative" },
"y": { "field": "label_y", "type": "quantitative" },
"text": { "field": "$key", "type": "nominal" }
}
}
],
"view": { "stroke": null }
}

Radial chart

Radial chart example.

Define $valueField and $colorField in the Fields section.

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v6.json",
"width": "container",
"height": "container",
"config": {
"autosize": { "type": "fit", "contains": "padding" }
},
"data": { "name": "databricks_query" },
"transform": [
{
"aggregate": [{ "op": "sum", "field": "$valueField", "as": "total" }],
"groupby": ["$colorField"]
},
{
"window": [{ "op": "rank", "as": "rank" }],
"sort": [{ "field": "total", "order": "descending" }]
}
],
"layer": [
{
"mark": { "type": "arc", "innerRadius": 20, "stroke": "#fff" }
}
],
"encoding": {
"theta": {
"field": "total",
"type": "quantitative",
"scale": { "type": "sqrt" },
"stack": true,
"sort": "descending"
},
"radius": { "field": "total", "scale": { "type": "sqrt", "zero": true } },
"color": {
"field": "$colorField",
"type": "nominal",
"title": "Sub-Category",
"sort": { "field": "total", "order": "descending" },
"legend": { "orient": "right" }
},
"tooltip": [
{ "field": "$colorField", "type": "nominal", "title": "Sub-Category" },
{ "field": "total", "type": "quantitative", "title": "Sales" }
]
},
"view": { "stroke": null }
}

Sunburst chart

Sunburst chart example.

Define outerGroupField, innerGroupField, and sizeField in the Fields section.

JSON specification

JSON
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"width": "container",
"height": "container",
"data": { "name": "databricks_query" },
"config": {
"autosize": { "type": "fit", "contains": "padding" }
},
"transform": [
{ "calculate": "datum['outerGroupField']", "as": "OUTSIDE" },
{ "calculate": "datum['innerGroupField']", "as": "INSIDE" },
{ "calculate": "datum.OUTSIDE + '-' + datum.INSIDE", "as": "OUT_IN" },
{ "calculate": "toNumber(datum['sizeField'])", "as": "SIZE" }
],
"resolve": {
"scale": { "color": "independent" },
"legend": { "color": "independent" }
},
"layer": [
{
"mark": {
"type": "arc",
"tooltip": true,
"innerRadius": { "expr": "min(width, height)/9" },
"outerRadius": { "expr": "min(width, height)/3" }
},
"encoding": {
"theta": { "field": "SIZE", "type": "quantitative", "stack": true },
"color": {
"field": "OUT_IN",
"type": "ordinal",
"sort": "ascending",
"title": "Inner Grouping",
"scale": {
"range": [
"#1DF9B9",
"#1DE5B9",
"#1DD1B9",
"#1DBDB9",
"#1DA9B9",
"#3DF23B",
"#3DDA3B",
"#3DC23B",
"#3DAA3B",
"#3D923B"
]
}
},
"order": { "field": "OUT_IN", "sort": "ascending" },
"tooltip": [
{ "field": "OUTSIDE", "type": "nominal", "title": "Outer Grouping" },
{ "field": "INSIDE", "type": "nominal", "title": "Inner Grouping" },
{ "field": "SIZE", "type": "quantitative", "title": "Count" }
]
}
},
{
"transform": [
{
"aggregate": [{ "op": "sum", "field": "SIZE", "as": "total_users" }],
"groupby": ["OUTSIDE"]
}
],
"mark": {
"type": "arc",
"tooltip": true,
"innerRadius": { "expr": "min(width, height)/3" }
},
"encoding": {
"theta": {
"field": "total_users",
"type": "quantitative",
"stack": true,
"sort": "ascending",
"title": "Users Count"
},
"color": {
"field": "OUTSIDE",
"type": "ordinal",
"sort": "ascending",
"title": "Outer Grouping",
"scale": { "range": ["#1DD1B9", "#3DC23B"] }
},
"order": { "field": "OUTSIDE", "sort": "ascending" },
"tooltip": [
{ "field": "OUTSIDE", "type": "nominal", "title": "Outer Grouping" },
{ "field": "total_users", "type": "quantitative", "title": "Count" }
]
}
}
]
}

Limitations

  • Treemap charts aren't supported. Vega-Lite doesn't support treemaps.