Source code for

"""This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.

This is the BoxPlot class which lets you build your BoxPlot plots just passing
the arguments to the Chart class and calling the proper functions.
It also add a new chained stacked method.
# Copyright (c) 2012 - 2014, Anaconda, Inc. All rights reserved.
# Powered by the Bokeh Development Team.
# The full license is in the file LICENSE.txt, distributed with this software.

# Imports

from __future__ import absolute_import

from ..builder import create_and_build
from ...models import Range1d
from import Bool, String
from .bar_builder import BarBuilder
from ..glyphs import BoxGlyph
from ..utils import title_from_columns
from ..attributes import ColorAttr, CatAttr

# Classes and functions

[docs]def BoxPlot(data, label=None, values=None, color=None, group=None, xscale="categorical", yscale="linear", xgrid=False, ygrid=True, continuous_range=None, **kw): """Create a BoxPlot chart containing one or more boxes from table-like data. Create a boxplot chart using :class:`BoxPlotBuilder <>` to render the glyphs from input data and specification. This primary use case for the boxplot is to depict the distribution of a variable by providing summary statistics for it. This boxplot is particularly useful at comparing distributions between categorical variables. This chart implements functionality for segmenting and comparing the values of a variable by an associated categorical variable. Reference: `BoxPlot on Wikipedia <>`_ Args: data (:ref:`userguide_charts_data_types`): the data source for the chart values (str, optional): the values to use for producing the boxplot using table-like input data label (str or list(str), optional): the categorical variable to use for creating separate boxes color (str or list(str) or bokeh.charts._attributes.ColorAttr, optional): the categorical variable or color attribute specification to use for coloring the boxes. whisker_color (str or list(str) or bokeh.charts._attributes.ColorAttr, optional): the color of the "whiskers" that show the spread of values outside the .25 and .75 quartiles. marker (str or list(str) or bokeh.charts._attributes.MarkerAttr, optional): the marker glyph to use for the outliers outliers (bool, optional): whether to show outliers. Defaults to True. **kw: In addition to the parameters specific to this chart, :ref:`userguide_charts_defaults` are also accepted as keyword parameters. Returns: :class:`Chart`: includes glyph renderers that generate Boxes and Whiskers Examples: .. bokeh-plot:: :source-position: above from bokeh.charts import BoxPlot, output_file, show from bokeh.layouts import row from bokeh.sampledata.autompg import autompg as df box = BoxPlot(df, values='mpg', label='cyl', title="Auto MPG Box Plot", plot_width=400) box2 = BoxPlot(df, values='mpg', label='cyl', color='cyl', title="MPG Box Plot by Cylinder Count", plot_width=400) output_file('box.html') show(row(box, box2)) """ if continuous_range and not isinstance(continuous_range, Range1d): raise ValueError( "continuous_range must be an instance of bokeh.models.ranges.Range1d" ) # The continuous_range is the y_range (until we implement HBar charts) y_range = continuous_range kw['label'] = label kw['values'] = values kw['color'] = color kw['group'] = group kw['xscale'] = xscale kw['yscale'] = yscale kw['xgrid'] = xgrid kw['ygrid'] = ygrid kw['y_range'] = y_range return create_and_build(BoxPlotBuilder, data, **kw)
[docs]class BoxPlotBuilder(BarBuilder): """Produces Box Glyphs for groups of data. Handles box plot options to produce one to many boxes, which are used to describe the distribution of a variable. """ # ToDo: Support easier adding of one attr without reimplementation default_attributes = {'label': CatAttr(), 'color': ColorAttr(default='DimGrey'), 'outlier_fill_color': ColorAttr(default='red'), 'outlier_line_color': ColorAttr(default='red'), 'whisker_color': ColorAttr(default='black'), 'line_color': ColorAttr(default='black'), 'stack': CatAttr(), 'group': CatAttr()} # TODO: (bev) should be an enumeration marker = String(help=""" The marker type to use (e.g., ``circle``) if outliers=True. """) outliers = Bool(default=True, help=""" Whether to display markers for any outliers. """) glyph = BoxGlyph
[docs] def setup(self): if self.ylabel is None: self.ylabel = self.values.selected_title if self.xlabel is None: self.xlabel = title_from_columns(self.attributes['label'].columns)