altair.FacetEncodingFieldDef#

class altair.FacetEncodingFieldDef(aggregate=Undefined, align=Undefined, bandPosition=Undefined, bin=Undefined, bounds=Undefined, center=Undefined, columns=Undefined, field=Undefined, header=Undefined, sort=Undefined, spacing=Undefined, timeUnit=Undefined, title=Undefined, type=Undefined, **kwds)#

FacetEncodingFieldDef schema wrapper

Mapping(required=[])

Parameters:
aggregateAggregate

Aggregation function for the field (e.g., "mean", "sum", "median", "min", "max", "count" ).

Default value: undefined (None)

See also: aggregate documentation.

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".

bandPositionfloat

Relative position on a band of a stacked, binned, time unit, or band scale. For example, the marks will be positioned at the beginning of the band if set to 0, and at the middle of the band if set to 0.5.

binanyOf(boolean, BinParams, None)

A flag for binning a quantitative field, an object defining binning parameters, or indicating that the data for x or y channel are binned before they are imported into Vega-Lite ( "binned" ).

If true, default binning parameters will be applied.

If "binned", this indicates that the data for the x (or y ) channel are already binned. You can map the bin-start field to x (or y ) and the bin-end field to x2 (or y2 ). The scale and axis will be formatted similar to binning in Vega-Lite. To adjust the axis ticks based on the bin step, you can also set the axis’s tickMinStep property.

Default value: false

See also: bin documentation.

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 :

  1. 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 ).

fieldField

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

See also: field documentation.

Notes: 1) Dots ( . ) and brackets ( [ and ] ) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']" ). If field names contain dots or brackets but are not nested, you can use \ to escape dots and brackets (e.g., "a\.b" and "a\[0\]" ). See more details about escaping in the field documentation. 2) field is not required if aggregate is count.

headeranyOf(Header, None)

An object defining properties of a facet’s header.

sortanyOf(SortArray, SortOrder, EncodingSortField, None)

Sort order for the encoded field.

For continuous fields (quantitative or temporal), sort can be either "ascending" or "descending".

For discrete fields, sort can be one of the following:

  • "ascending" or "descending" – for sorting by the values’ natural order in JavaScript.

  • A sort field definition for sorting by another field.

  • An array specifying the field values in preferred order. In this case, the sort order will obey the values in the array, followed by any unspecified values in their original order. For discrete time field, values in the sort array can be date-time definition objects. In addition, for time units "month" and "day", the values can be the month or day names (case insensitive) or their 3-letter initials (e.g., "Mon", "Tue" ).

  • null indicating no sort.

Default value: "ascending"

Note: null is not supported for row and column.

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)

timeUnitanyOf(TimeUnit, TimeUnitParams)

Time unit (e.g., year, yearmonth, month, hours ) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)

See also: timeUnit documentation.

titleanyOf(Text, None)

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function ( aggregate, bin and timeUnit ). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit" ). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)" ). Otherwise, the title is simply the field name.

Notes :

1) You can customize the default field title format by providing the fieldTitle property in the config or fieldTitle function via the compile function’s options.

2) If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.

typeStandardType

The type of measurement ( "quantitative", "temporal", "ordinal", or "nominal" ) for the encoded field or constant value ( datum ). It can also be a "geojson" type for encoding ‘geoshape’.

Vega-Lite automatically infers data types in many cases as discussed below. However, type is required for a field if: (1) the field is not nominal and the field encoding has no specified aggregate (except argmin and argmax ), bin, scale type, custom sort order, nor timeUnit or (2) if you wish to use an ordinal scale for a field with bin or timeUnit.

Default value:

1) For a data field, "nominal" is the default data type unless the field encoding has aggregate, channel, bin, scale type, sort, or timeUnit that satisfies the following criteria:

  • "quantitative" is the default type if (1) the encoded field contains bin or aggregate except "argmin" and "argmax", (2) the encoding channel is latitude or longitude channel or (3) if the specified scale type is a quantitative scale.

  • "temporal" is the default type if (1) the encoded field contains timeUnit or (2) the specified scale type is a time or utc scale

  • "ordinal" is the default type if (1) the encoded field contains a custom sort order, (2) the specified scale type is an ordinal/point/band scale, or (3) the encoding channel is order.

  1. For a constant value in data domain ( datum ):

  • "quantitative" if the datum is a number

  • "nominal" if the datum is a string

  • "temporal" if the datum is a date time object

Note:

  • Data type describes the semantics of the data rather than the primitive data types (number, string, etc.). The same primitive data type can have different types of measurement. For example, numeric data can represent quantitative, ordinal, or nominal data.

  • Data values for a temporal field can be either a date-time string (e.g., "2015-03-07 12:32:17", "17:01", "2015-03-16". "2015" ) or a timestamp number (e.g., 1552199579097 ).

  • When using with bin, the type property can be either "quantitative" (for using a linear bin scale) or “ordinal” (for using an ordinal bin scale).

  • When using with timeUnit, the type property can be either "temporal" (default, for using a temporal scale) or “ordinal” (for using an ordinal scale).

  • When using with aggregate, the type property refers to the post-aggregation data type. For example, we can calculate count distinct of a categorical field "cat" using {"aggregate": "distinct", "field": "cat"}. The "type" of the aggregate output is "quantitative".

  • Secondary channels (e.g., x2, y2, xError, yError ) do not have type as they must have exactly the same type as their primary channels (e.g., x, y ).

See also: type documentation.

__init__(aggregate=Undefined, align=Undefined, bandPosition=Undefined, bin=Undefined, bounds=Undefined, center=Undefined, columns=Undefined, field=Undefined, header=Undefined, sort=Undefined, spacing=Undefined, timeUnit=Undefined, title=Undefined, type=Undefined, **kwds)#

Methods

__init__([aggregate, align, bandPosition, ...])

copy([deep, ignore])

Return a copy of the object

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

resolve_references([schema])

Resolve references in the context of this object's schema or root schema.

to_dict([validate, ignore, context])

Return a dictionary representation of the object

to_json([validate, ignore, context, indent, ...])

Emit the JSON representation for this object as a string.

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