bokeh.transform¶
Helper functions for applying client-side computations such as
transformations to data fields or ColumnDataSource
expressions.
- cumsum(field: str, include_zero: bool = False) Expr [source]¶
Create a
DataSpec
dict to generate aCumSum
expression for aColumnDataSource
.Examples
p.wedge(start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'), ...)
will generate a
CumSum
expressions that sum the"angle"
column of a data source. For thestart_angle
value, the cumulative sums will start with a zero value. Forend_angle
, no initial zero will be added (i.e. the sums will start with the first angle value, and include the last).
- dodge(field_name: str, value: float, range: Range | None = None) Field [source]¶
Create a
DataSpec
dict that applies a client-sideDodge
transformation to aColumnDataSource
column.- Parameters
- Returns
dict
- factor_cmap(field_name: str, palette: Sequence[ColorLike], factors: Factors, start: float = 0, end: float | None = None, nan_color: ColorLike = 'gray')[source]¶
Create a
DataSpec
dict that applies a client-sideCategoricalColorMapper
transformation to aColumnDataSource
column.- Parameters
field_name (str) – a field name to configure
DataSpec
withpalette (seq[color]) – a list of colors to use for colormapping
factors (seq) – a sequences of categorical factors corresponding to the palette
start (int, optional) – a start slice index to apply when the column data has factors with multiple levels. (default: 0)
end (int, optional) – an end slice index to apply when the column data has factors with multiple levels. (default: None)
nan_color (color, optional) – a default color to use when mapping data from a column does not succeed (default: “gray”)
- Returns
dict
- factor_hatch(field_name: str, patterns: Sequence[str], factors: Factors, start: float = 0, end: float | None = None) Field [source]¶
Create a
DataSpec
dict that applies a client-sideCategoricalPatternMapper
transformation to aColumnDataSource
column.- Parameters
field_name (str) – a field name to configure
DataSpec
withpatterns (seq[string]) – a list of hatch patterns to use to map to
factors (seq) – a sequences of categorical factors corresponding to the palette
start (int, optional) – a start slice index to apply when the column data has factors with multiple levels. (default: 0)
end (int, optional) – an end slice index to apply when the column data has factors with multiple levels. (default: None)
- Returns
dict
Added in version 1.1.1
- factor_mark(field_name: str, markers: Sequence[str], factors: Factors, start: float = 0, end: float | None = None) Field [source]¶
Create a
DataSpec
dict that applies a client-sideCategoricalMarkerMapper
transformation to aColumnDataSource
column.Note
This transform is primarily only useful with
scatter
, which can be parameterized by glyph type.- Parameters
field_name (str) – a field name to configure
DataSpec
withmarkers (seq[string]) – a list of markers to use to map to
factors (seq) – a sequences of categorical factors corresponding to the palette
start (int, optional) – a start slice index to apply when the column data has factors with multiple levels. (default: 0)
end (int, optional) – an end slice index to apply when the column data has factors with multiple levels. (default: None)
- Returns
dict
- jitter(field_name: str, width: float, mean: float = 0, distribution: JitterRandomDistributionType = 'uniform', range: Range | None = None) Field [source]¶
Create a
DataSpec
dict that applies a client-sideJitter
transformation to aColumnDataSource
column.- Parameters
field_name (str) – a field name to configure
DataSpec
withwidth (float) – the width of the random distribution to apply
mean (float, optional) – an offset to apply (default: 0)
distribution (str, optional) –
"uniform"
or"normal"
(default:"uniform"
)range (Range, optional) – a range to use for computing synthetic coordinates when necessary, e.g. a
FactorRange
when the column data is categorical (default: None)
- Returns
dict
- linear_cmap(field_name: str, palette: Sequence[ColorLike], low: float, high: float, low_color: ColorLike | None = None, high_color: ColorLike | None = None, nan_color: ColorLike = 'gray') Field [source]¶
Create a
DataSpec
dict that applyies a client-sideLinearColorMapper
transformation to aColumnDataSource
column.- Parameters
field_name (str) – a field name to configure
DataSpec
withpalette (seq[color]) – a list of colors to use for colormapping
low (float) – a minimum value of the range to map into the palette. Values below this are clamped to
low
.high (float) – a maximum value of the range to map into the palette. Values above this are clamped to
high
.low_color (color, optional) – color to be used if data is lower than
low
value. If None, values lower thanlow
are mapped to the first color in the palette. (default: None)high_color (color, optional) – color to be used if data is higher than
high
value. If None, values higher thanhigh
are mapped to the last color in the palette. (default: None)nan_color (color, optional) – a default color to use when mapping data from a column does not succeed (default: “gray”)
- log_cmap(field_name: str, palette: Sequence[ColorLike], low: float, high: float, low_color: ColorLike | None = None, high_color: ColorLike | None = None, nan_color: ColorLike = 'gray') Field [source]¶
Create a
DataSpec
dict that applies a client-sideLogColorMapper
transformation to aColumnDataSource
column.- Parameters
field_name (str) – a field name to configure
DataSpec
withpalette (seq[color]) – a list of colors to use for colormapping
low (float) – a minimum value of the range to map into the palette. Values below this are clamped to
low
.high (float) – a maximum value of the range to map into the palette. Values above this are clamped to
high
.low_color (color, optional) – color to be used if data is lower than
low
value. If None, values lower thanlow
are mapped to the first color in the palette. (default: None)high_color (color, optional) – color to be used if data is higher than
high
value. If None, values higher thanhigh
are mapped to the last color in the palette. (default: None)nan_color (color, optional) – a default color to use when mapping data from a column does not succeed (default: “gray”)
- stack(*fields: str) Expr [source]¶
Create a Create a
DataSpec
dict to generate aStack
expression for aColumnDataSource
.Examples
p.vbar(bottom=stack("sales", "marketing"), ...
will generate a
Stack
that sums the"sales"
and"marketing"
columns of a data source, and use those values as thetop
coordinate for aVBar
.