"""This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the Step class which lets you build your Step charts just
passing the arguments to the Chart class and calling the proper functions.
"""
# -----------------------------------------------------------------------------
# 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 .line_builder import LineBuilder
from ..glyphs import StepGlyph
# -----------------------------------------------------------------------------
# Classes and functions
# -----------------------------------------------------------------------------
[docs]def Step(data=None, x=None, y=None, **kws):
""" Create a step chart using :class:`StepBuilder
<bokeh.charts.builder.step_builder.StepBuilder>` to render the geometry
from the inputs.
.. note::
Only the x or y axis can display multiple variables, while the other is used
as an index.
Args:
data (list(list), numpy.ndarray, pandas.DataFrame, list(pd.Series)): a 2d data
source with columns of data for each stepped line.
x (str or list(str), optional): specifies variable(s) to use for x axis
y (str or list(str), optional): specifies variable(s) to use for y axis
In addition to the parameters specific to this chart,
:ref:`userguide_charts_defaults` are also accepted as keyword parameters.
.. note::
This chart type differs on input types as compared to other charts,
due to the way that series-type charts typically are plotting labeled series.
For example, a column for AAPL stock prices over time. Another way this could be
plotted is to have a DataFrame with a column of `stock_label` and columns of
`price`, which is the stacked format. Both should be supported, but the former
is the expected one. Internally, the latter format is being derived.
Returns:
:class:`Chart`: includes glyph renderers that generate the stepped lines
Examples:
.. bokeh-plot::
:source-position: above
from bokeh.charts import Step, show, output_file
# build a dataset where multiple columns measure the same thing
data = dict(
stamp=[.33, .33, .34, .37, .37, .37, .37, .39, .41, .42,
.44, .44, .44, .45, .46, .49, .49],
postcard=[.20, .20, .21, .23, .23, .23, .23, .24, .26, .27,
.28, .28, .29, .32, .33, .34, .35]
)
# create a step chart where each column of measures receives a unique color and dash style
step = Step(data, y=['stamp', 'postcard'],
dash=['stamp', 'postcard'],
color=['stamp', 'postcard'],
title="U.S. Postage Rates (1999-2015)",
ylabel='Rate per ounce', legend=True)
output_file("steps.html")
show(step)
"""
kws['x'] = x
kws['y'] = y
return create_and_build(StepBuilder, data, **kws)
[docs]class StepBuilder(LineBuilder):
"""This is the Step builder and it is in charge of plotting
Step 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 stepped lines taking the references from the source.
"""
[docs] def yield_renderers(self):
for group in self._data.groupby(**self.attributes):
glyph = StepGlyph(x=group.get_values(self.x.selection),
y=group.get_values(self.y.selection),
line_color=group['color'],
dash=group['dash'])
# save reference to composite glyph
self.add_glyph(group, glyph)
# yield each renderer produced by composite glyph
for renderer in glyph.renderers:
yield renderer
