altair.BinParams

class altair.BinParams(anchor=Undefined, base=Undefined, binned=Undefined, divide=Undefined, extent=Undefined, maxbins=Undefined, minstep=Undefined, nice=Undefined, step=Undefined, steps=Undefined, **kwds)

BinParams schema wrapper.

Binning properties or boolean flag for determining whether to bin data or not.

Parameters:

anchorfloat

A value in the binned domain at which to anchor the bins, shifting the bin boundaries if necessary to ensure that a boundary aligns with the anchor value.

Default value: the minimum bin extent value

basefloat

The number base to use for automatic bin determination (default is base 10).

Default value: 10

binnedbool

When set to true, Vega-Lite treats the input data as already binned.

divideSequence[float]

Scale factors indicating allowable subdivisions. The default value is [5, 2], which indicates that for base 10 numbers (the default base), the method may consider dividing bin sizes by 5 and/or 2. For example, for an initial step size of 10, the method can check if bin sizes of 2 (= 10/5), 5 (= 10/2), or 1 (= 10/(5*2)) might also satisfy the given constraints.

Default value: [5, 2]

extentdict, Sequence[float], BinExtent, ParameterExtent

A two-element ([min, max]) array indicating the range of desired bin values.

maxbinsfloat

Maximum number of bins.

Default value: 6 for row, column and shape channels; 10 for other channels

minstepfloat

A minimum allowable step size (particularly useful for integer values).

nicebool

If true, attempts to make the bin boundaries use human-friendly boundaries, such as multiples of ten.

Default value: true

stepfloat

An exact step size to use between bins.

Note: If provided, options such as maxbins will be ignored.

stepsSequence[float]

An array of allowable step sizes to choose from.

__init__(anchor=Undefined, base=Undefined, binned=Undefined, divide=Undefined, extent=Undefined, maxbins=Undefined, minstep=Undefined, nice=Undefined, step=Undefined, steps=Undefined, **kwds)

Methods

__init__([anchor, base, binned, divide, ...])
copy([deep, ignore])	Return a copy of the object.
from_dict(dct[, validate])	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, indent, sort_keys, ...])	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.