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 Scatter class which lets you build your Scatter charts
just passing the arguments to the Chart class and calling the proper
# 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 bokeh.charts.builder import create_and_build, XYBuilder
from bokeh.charts.glyphs import PointGlyph
from bokeh.charts.attributes import MarkerAttr, ColorAttr
from bokeh.charts.utils import add_tooltips_columns

# Classes and functions

[docs]def Scatter(data=None, x=None, y=None, **kws): """ Create a scatter chart using :class:`ScatterBuilder <>` to render the geometry from values. Args: data (:ref:`userguide_charts_data_types`): table-like data x (str or list(str), optional): the column label to use for the x dimension y (str or list(str), optional): the column label to use for the y dimension 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 the scatter points Examples: .. bokeh-plot:: :source-position: above from bokeh.sampledata.autompg import autompg as df from bokeh.charts import Scatter, output_file, show scatter = Scatter(df, x='mpg', y='hp', color='cyl', marker='origin', title="Auto MPG", xlabel="Miles Per Gallon", ylabel="Horsepower") output_file('scatter.html') show(scatter) """ kws['x'] = x kws['y'] = y return create_and_build(ScatterBuilder, data, **kws)
[docs]class ScatterBuilder(XYBuilder): """This is the Scatter class and it is in charge of plotting Scatter charts in an easy and intuitive way. Essentially, we provide a way to ingest the data, make the proper calculations and push the references into a source object. We additionally make calculations for the ranges. And finally add the needed glyphs (markers) taking the references from the source. """ default_attributes = {'color': ColorAttr(), 'marker': MarkerAttr()}
[docs] def yield_renderers(self): """Use the marker glyphs to display the points. Takes reference points from data loaded at the ColumnDataSource. """ for group in self._data.groupby(**self.attributes): glyph = PointGlyph(label=group.label, x=group.get_values(self.x.selection), y=group.get_values(self.y.selection), line_color=group['color'], fill_color=group['color'], marker=group['marker']) self.add_glyph(group, glyph) for renderer in glyph.renderers: if self.tooltips: renderer = add_tooltips_columns(renderer, self.tooltips, group) yield renderer