Helper functions for applying client-side computations such as transformations to data fields or ColumnDataSource expressions.
ColumnDataSource
cumsum
Create a Create a DataSpec dict to generate a CumSum expression for a ColumnDataSource.
DataSpec
CumSum
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 the start_angle value, the cumulative sums will start with a zero value. For start_angle, no initial zero will be added (i.e. the sums will start with the first angle value, and include the last).
"angle"
start_angle
dodge
Create a DataSpec dict that applies a client-side Dodge transformation to a ColumnDataSource column.
Dodge
field_name (str) – a field name to configure DataSpec with
value (float) – the fixed offset to add to column data
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)
FactorRange
dict
factor_cmap
Create a DataSpec dict that applies a client-side CategoricalColorMapper transformation to a ColumnDataSource column.
CategoricalColorMapper
palette (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”)
factor_hatch
Create a DataSpec dict that applies a client-side CategoricalPatternMapper transformation to a ColumnDataSource column.
CategoricalPatternMapper
patterns (seq[string]) – a list of hatch patterns to use to map to
Added in version 1.1.1
factor_mark
Create a DataSpec dict that applies a client-side CategoricalMarkerMapper transformation to a ColumnDataSource column.
CategoricalMarkerMapper
Note
This transform is primarily only useful with scatter, which can be parameterized by glyph type.
scatter
markers (seq[string]) – a list of markers to use to map to
jitter
Create a DataSpec dict that applies a client-side Jitter transformation to a ColumnDataSource column.
Jitter
width (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")
"uniform"
"normal"
linear_cmap
Create a DataSpec dict that applyies a client-side LinearColorMapper transformation to a ColumnDataSource column.
LinearColorMapper
low (float) – a minimum value of the range to map into the palette. Values below this are clamped to low.
low
high (float) – a maximum value of the range to map into the palette. Values above this are clamped to high.
high
low_color (color, optional) – color to be used if data is lower than low value. If None, values lower than low 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 than high are mapped to the last color in the palette. (default: None)
log_cmap
Create a DataSpec dict that applies a client-side LogColorMapper transformation to a ColumnDataSource column.
LogColorMapper
stack
Create a Create a DataSpec dict to generate a Stack expression for a ColumnDataSource.
Stack
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 the top coordinate for a VBar.
"sales"
"marketing"
top
VBar
transform
Create a DataSpec dict that applies an arbitrary client-side Transform to a ColumnDataSource column.
Transform
field_name (str) – A field name to configure DataSpec with
transform (Transform) – A transforms to apply to that field