altair.FacetChart#

class altair.FacetChart(data=Undefined, facet=Undefined, spec=Undefined, align=Undefined, autosize=Undefined, background=Undefined, bounds=Undefined, center=Undefined, columns=Undefined, config=Undefined, datasets=Undefined, description=Undefined, name=Undefined, padding=Undefined, params=Undefined, resolve=Undefined, spacing=Undefined, title=Undefined, transform=Undefined, usermeta=Undefined, **kwds)#

A Chart with layers within a single panel

__init__(data=Undefined, facet=Undefined, spec=Undefined, align=Undefined, autosize=Undefined, background=Undefined, bounds=Undefined, center=Undefined, columns=Undefined, config=Undefined, datasets=Undefined, description=Undefined, name=Undefined, padding=Undefined, params=Undefined, resolve=Undefined, spacing=Undefined, title=Undefined, transform=Undefined, usermeta=Undefined, **kwds)#

Refer to TopLevelFacetSpec

Mapping(required=[data, facet, spec])

Parameters:

dataanyOf(Data, None)

An object describing the data source. Set to null to ignore the parent’s data source. If no data is set, it is derived from the parent.

facetanyOf(FacetFieldDef, FacetMapping)

Definition for how to facet the data. One of: 1) a field definition for faceting the plot by one field 2) An object that maps row and column channels to their field definitions

specanyOf(LayerSpec, UnitSpecWithFrame)

A specification of the view that gets faceted.

alignanyOf(LayoutAlign, RowColLayoutAlign)

The alignment to apply to grid rows and columns. The supported string values are "all", "each", and "none".

For "none", a flow layout will be used, in which adjacent subviews are simply placed one after the other.
For "each", subviews will be aligned into a clean grid structure, but each row or column may be of variable size.
For "all", subviews will be aligned and each row or column will be sized identically based on the maximum observed size. String values for this property will be applied to both grid rows and columns.

Alternatively, an object value of the form {"row": string, "column": string} can be used to supply different alignments for rows and columns.

Default value: "all".

autosizeanyOf(AutosizeType, AutoSizeParams)

How the visualization size should be determined. If a string, should be one of "pad", "fit" or "none". Object values can additionally specify parameters for content sizing and automatic resizing.

Default value : pad

backgroundanyOf(Color, ExprRef)

CSS color property to use as the background of the entire view.

Default value: "white"

boundsenum(‘full’, ‘flush’)

The bounds calculation method to use for determining the extent of a sub-plot. One of full (the default) or flush.

If set to full, the entire calculated bounds (including axes, title, and legend) will be used.
If set to flush, only the specified width and height values for the sub-view will be used. The flush setting can be useful when attempting to place sub-plots without axes or legends into a uniform grid structure.

Default value: "full"

centeranyOf(boolean, RowColboolean)

Boolean flag indicating if subviews should be centered relative to their respective rows or columns.

An object value of the form {"row": boolean, "column": boolean} can be used to supply different centering values for rows and columns.

Default value: false

columnsfloat

The number of columns to include in the view composition layout.

Default value : undefined – An infinite number of columns (a single row) will be assumed. This is equivalent to hconcat (for concat ) and to using the column channel (for facet and repeat ).

Note :

This property is only for:

the general (wrappable) concat operator (not hconcat / vconcat )
the facet and repeat operator with one field/repetition definition (without row/column nesting)

2) Setting the columns to 1 is equivalent to vconcat (for concat ) and to using the row channel (for facet and repeat ).

configConfig

Vega-Lite configuration object. This property can only be defined at the top-level of a specification.

datasetsDatasets

A global data store for named datasets. This is a mapping from names to inline datasets. This can be an array of objects or primitive values or a string. Arrays of primitive values are ingested as objects with a data property.

descriptionstring

Description of this mark for commenting purpose.

namestring

Name of the visualization for later reference.

paddinganyOf(Padding, ExprRef)

The default visualization padding, in pixels, from the edge of the visualization canvas to the data rectangle. If a number, specifies padding for all sides. If an object, the value should have the format {"left": 5, "top": 5, "right": 5, "bottom": 5} to specify padding for each side of the visualization.

Default value : 5

paramsList(TopLevelParameter)

Dynamic variables or selections that parameterize a visualization.

resolveResolve

Scale, axis, and legend resolutions for view composition specifications.

spacinganyOf(float, RowColnumber)

The spacing in pixels between sub-views of the composition operator. An object of the form {"row": number, "column": number} can be used to set different spacing values for rows and columns.

Default value : Depends on "spacing" property of the view composition configuration ( 20 by default)

titleanyOf(Text, TitleParams)

Title for the plot.

transformList(Transform)

An array of data transformations such as filter and new field calculation.

usermetaDict

Optional metadata that will be passed to Vega. This object is completely ignored by Vega and Vega-Lite and can be used for custom metadata.

$schemastring

URL to JSON schema for a Vega-Lite specification. Unless you have a reason to change this, use https://vega.github.io/schema/vega-lite/v5.json. Setting the $schema property allows automatic validation and autocomplete in editors that support JSON schema.

Methods

`__init__`([data, facet, spec, align, ...])	Refer to `TopLevelFacetSpec`
`add_params`(*params)	Add one or more parameters to the chart.
`add_selection`(*selections)	'add_selection' is deprecated.
`configure`([arc, area, aria, autosize, axis, ...])	Refer to `Config`
`configure_arc`([align, angle, aria, ...])	Refer to `RectConfig`
`configure_area`([align, angle, aria, ...])	Refer to `AreaConfig`
`configure_axis`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisBand`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisBottom`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisDiscrete`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisLeft`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisPoint`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisQuantitative`([aria, ...])	Refer to `AxisConfig`
`configure_axisRight`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisTemporal`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisTop`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisX`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisXBand`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisXDiscrete`([aria, ...])	Refer to `AxisConfig`
`configure_axisXPoint`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisXQuantitative`([aria, ...])	Refer to `AxisConfig`
`configure_axisXTemporal`([aria, ...])	Refer to `AxisConfig`
`configure_axisY`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisYBand`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisYDiscrete`([aria, ...])	Refer to `AxisConfig`
`configure_axisYPoint`([aria, bandPosition, ...])	Refer to `AxisConfig`
`configure_axisYQuantitative`([aria, ...])	Refer to `AxisConfig`
`configure_axisYTemporal`([aria, ...])	Refer to `AxisConfig`
`configure_bar`([align, angle, aria, ...])	Refer to `BarConfig`
`configure_boxplot`([box, extent, median, ...])	Refer to `BoxPlotConfig`
`configure_circle`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_concat`([columns, spacing])	Refer to `CompositionConfig`
`configure_errorband`([band, borders, extent, ...])	Refer to `ErrorBandConfig`
`configure_errorbar`([extent, rule, size, ...])	Refer to `ErrorBarConfig`
`configure_facet`([columns, spacing])	Refer to `CompositionConfig`
`configure_geoshape`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_header`([format, formatType, ...])	Refer to `HeaderConfig`
`configure_headerColumn`([format, formatType, ...])	Refer to `HeaderConfig`
`configure_headerFacet`([format, formatType, ...])	Refer to `HeaderConfig`
`configure_headerRow`([format, formatType, ...])	Refer to `HeaderConfig`
`configure_image`([align, angle, aria, ...])	Refer to `RectConfig`
`configure_legend`([aria, clipHeight, ...])	Refer to `LegendConfig`
`configure_line`([align, angle, aria, ...])	Refer to `LineConfig`
`configure_mark`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_point`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_projection`([center, clipAngle, ...])	Refer to `ProjectionConfig`
`configure_range`([category, diverging, ...])	Refer to `RangeConfig`
`configure_rect`([align, angle, aria, ...])	Refer to `RectConfig`
`configure_rule`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_scale`([bandPaddingInner, ...])	Refer to `ScaleConfig`
`configure_selection`([interval, point])	Refer to `SelectionConfig`
`configure_square`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_text`([align, angle, aria, ...])	Refer to `MarkConfig`
`configure_tick`([align, angle, aria, ...])	Refer to `TickConfig`
`configure_title`([align, anchor, angle, ...])	Refer to `TitleConfig`
`configure_trail`([align, angle, aria, ...])	Refer to `LineConfig`
`configure_view`([clip, continuousHeight, ...])	Refer to `ViewConfig`
`copy`([deep, ignore])	Return a copy of the object
`display`([renderer, theme, actions])	Display chart in Jupyter notebook or JupyterLab
`from_dict`(dct[, validate, _wrapper_classes])	Construct class from a dictionary representation
`from_json`(json_string[, validate])	Instantiate the object from a valid JSON string
`interactive`([name, bind_x, bind_y])	Make chart axes scales interactive
`project`([type, center, clipAngle, ...])	Add a geographic projection to the chart.
`properties`(**kwargs)	Set top-level properties of the Chart.
`repeat`([repeat, row, column, layer, columns])	Return a RepeatChart built from the chart
`resolve_axis`([x, y])	Refer to `AxisResolveMap`
`resolve_legend`([angle, color, fill, ...])	Refer to `LegendResolveMap`
`resolve_references`([schema])	Resolve references in the context of this object's schema or root schema.
`resolve_scale`([angle, color, fill, ...])	Refer to `ScaleResolveMap`
`save`(fp[, format, ...])	Save a chart to file in a variety of formats
`serve`([ip, port, n_retries, files, ...])	'serve' is deprecated.
`show`([embed_opt, open_browser])	Show the chart in an external browser window.
`to_dict`(args, *kwargs)	Convert the chart to a dictionary suitable for JSON export
`to_html`([base_url, output_div, ...])
`to_json`([validate, ignore, context, indent, ...])	Emit the JSON representation for this object as a string.
`transform_aggregate`([aggregate, groupby])	Add an `AggregateTransform` to the schema.
`transform_bin`([as_, field, bin])	Add a `BinTransform` to the schema.
`transform_calculate`([as_, calculate])	Add a `CalculateTransform` to the schema.
`transform_density`(density[, as_, bandwidth, ...])	Add a `DensityTransform` to the spec.
`transform_filter`(filter, **kwargs)	Add a `FilterTransform` to the schema.
`transform_flatten`(flatten[, as_])	Add a `FlattenTransform` to the schema.
`transform_fold`(fold[, as_])	Add a `FoldTransform` to the spec.
`transform_impute`(impute, key[, frame, ...])	Add an `ImputeTransform` to the schema.
`transform_joinaggregate`([joinaggregate, groupby])	Add a `JoinAggregateTransform` to the schema.
`transform_loess`(on, loess[, as_, bandwidth, ...])	Add a `LoessTransform` to the spec.
`transform_lookup`([lookup, from_, as_, default])	Add a `DataLookupTransform` or `SelectionLookupTransform` to the chart
`transform_pivot`(pivot, value[, groupby, ...])	Add a `PivotTransform` to the chart.
`transform_quantile`(quantile[, as_, groupby, ...])	Add a `QuantileTransform` to the chart
`transform_regression`(on, regression[, as_, ...])	Add a `RegressionTransform` to the chart.
`transform_sample`([sample])	Add a `SampleTransform` to the schema.
`transform_stack`(as_, stack, groupby[, ...])	Add a `StackTransform` to the schema.
`transform_timeunit`([as_, field, timeUnit])	Add a `TimeUnitTransform` to the schema.
`transform_window`([window, frame, groupby, ...])	Add a `WindowTransform` to the schema
`validate`(instance[, schema])	Validate the instance against the class schema in the context of the rootschema.
`validate_property`(name, value[, schema])	Validate a property against property schema in the context of the rootschema