Radar Chart Card

Card type: radarChart

The radar chart card displays a radar/spider chart from tabular data. Radar charts are ideal for comparing multiple variables across different categories, such as skills assessments, performance metrics, or product comparisons.

In addition to the common parameters the radarChart card has the following configuration options:

Name	Type	Required	Default	Description
`value`	list of dict	Yes	—	The data to be plotted. Each dict represents a data point.
`fillCard`	bool	No	`false`	When set to `True`, the chart will fill the entire card space including the header area. When `False` (default), the chart will be positioned below the header.
`label_override`	dict	No	—	Optional: pretty labels for data series.
`chart_options`	dict	Yes	—	Chart configuration options. See table below.

Chart Options

Name	Type	Required	Default	Description
`xKey`	str	Yes	—	The property in each dict to use for the angle axis (categories).
`yKeys`	list of str	Yes	—	The properties in each dict to use for the radar values (can be multiple series).
`strokeKeys`	list of str	No	—	The properties in each dict to use for the stroke colors of each series.
`fillOpacity`	number	No	`0.6`	Opacity of the filled area (0-1).
`strokeWidth`	number	No	`2`	Width of the stroke line.
`dotSize`	number	No	`4`	Size of the data points (0 to hide dots).
`defaultColors`	”monochrome” or “multicolor”	No	`"monochrome"`	Fallback color scheme if no color is provided in the data.
`fontSize`	str	No	(auto)	Font size for labels/tooltips. (if not set, this scales with the card size).
`showLegend`	bool	No	`true`	Whether to show the legend below the chart.
`showGrid`	bool	No	`true`	Whether to show the polar grid.
`showAngleAxis`	bool	No	`true`	Whether to show the angle axis labels.
`margin`	dict	No	`{top: 15, right: 15, bottom: 15, left: 15}`	Chart margins.
`gridType`	”polygon” or “circle”	No	`"polygon"`	Type of polar grid to display.

Grid Types

"polygon": Hexagonal grid pattern (default)
"circle": Circular grid pattern

Examples

Simple Radar Chart

This example shows a basic radar chart for skills assessment.


import polars as pl
 
# Create some data
df = pl.DataFrame({
    "skill": ["Programming", "Design", "Analysis", "Communication", "Leadership", "Problem Solving"],
    "score": [85, 70, 90, 75, 80, 88],
})
 
# Convert to the format expected by the radar chart
data = df.to_dicts()
 
# Override labels
label_override = {
    "score": {"label": "Score"},
}
 
datacards.publish.card(
    type='radarChart',
    value=data,
    label="Skills Assessment",
    chart_options={
        "xKey": "skill",
        "yKeys": ["score"],
    },
    label_override=label_override,
    logic_view_size=(4,2),
)

Multi-Series Radar Chart

This example demonstrates multiple data series with different colors, useful for comparing different entities or time periods.


import polars as pl
 
# Create some data
df = pl.DataFrame({
    "metric": ["Speed", "Accuracy", "Efficiency", "Quality", "Innovation", "Teamwork"],
    "current": [65, 70, 30, 75, 70, 58],
    "target": [90, 85, 75, 80, 85, 70],
})
 
# Convert to the format expected by the radar chart
data = df.to_dicts()
 
# Override labels
label_override = {
    "current": {"label": "Current Performance"},
    "target": {"label": "Target Performance"},
}
 
datacards.publish.card(
    type='radarChart',
    value=data,
    label="Performance Comparison",
    chart_options={
        "xKey": "metric",
        "yKeys": ["current", "target"],
        "defaultColors": "multicolor",
    },
    label_override=label_override,
    logic_view_size=(4,2),
)

Radar Chart with Custom Colors

This example demonstrates how to specify custom colors for each data series using the strokeKeys option.


import polars as pl
 
# Create some data
df = pl.DataFrame({
    "feature": ["Design", "Performance", "Security", "Usability", "Scalability", "Cost"],
    "product_a": [85, 70, 90, 75, 30, 88],
    "product_b": [70, 85, 75, 90, 85, 70],
    "product_a_color": ["#10b981", "#10b981", "#10b981", "#10b981", "#10b981", "#10b981"],
    "product_b_color": ["#ef4444", "#ef4444", "#ef4444", "#ef4444", "#ef4444", "#ef4444"],
})
 
# Convert to the format expected by the radar chart
data = df.to_dicts()
 
# Override labels
label_override = {
    "product_a": {"label": "Product A"},
    "product_b": {"label": "Product B"},
}
 
datacards.publish.card(
    type='radarChart',
    value=data,
    label="Product Comparison",
    chart_options={
        "xKey": "feature",
        "yKeys": ["product_a", "product_b"],
        "strokeKeys": ["product_a_color", "product_b_color"],
        "fillOpacity": 0.3,
        "strokeWidth": 2,
        "dotSize": 3,
    },
    label_override=label_override,
    logic_view_size=(4,2),
)

Radar Chart with Circular Grid

This example shows a radar chart with a circular grid pattern instead of the default polygon grid.


import polars as pl
 
# Create some data
df = pl.DataFrame({
    "category": ["A", "B", "C", "D", "E", "F"],
    "value": [65, 80, 75, 90, 85, 70],
})
 
# Convert to the format expected by the radar chart
data = df.to_dicts()
 
# Override labels
label_override = {
    "value": {"label": "Value"},
}
 
datacards.publish.card(
    type='radarChart',
    value=data,
    label="Circular Grid Example",
    chart_options={
        "xKey": "category",
        "yKeys": ["value"],
        "gridType": "circle",
        "fillOpacity": 0.5,
        "showGrid": True,
    },
    label_override=label_override,
    logic_view_size=(4,2),
)