"""This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the TimeSeries chart, which provides a convenient interface for
generating different charts using series-like data by transforming the data
to a consistent format and producing renderers.
"""
# -----------------------------------------------------------------------------
# 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, PointSeriesBuilder
from .step_builder import StepBuilder
# -----------------------------------------------------------------------------
# Classes and functions
# -----------------------------------------------------------------------------
BUILDER_TYPES = {
'line': LineBuilder,
'step': StepBuilder,
'point': PointSeriesBuilder
}
[docs]def TimeSeries(data=None, x=None, y=None, builder_type=LineBuilder, **kws):
""" Create a timeseries chart using :class:`LineBuilder
<bokeh.charts.builder.line_builder.LineBuilder>` to produce the renderers from
the inputs. The timeseries chart acts as a switchboard to produce charts
for timeseries data with different glyph representations.
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
builder_type (str or `Builder`, optional): the type of builder to use to produce
the renderers. Supported options are 'line', 'step', or 'point'.
In addition to the parameters specific to this chart,
:ref:`userguide_charts_defaults` are also accepted as keyword parameters.
Returns:
a new :class:`Chart <bokeh.charts.Chart>`
Examples:
.. bokeh-plot::
:source-position: above
import pandas as pd
from bokeh.charts import TimeSeries, show, output_file
from bokeh.layouts import column
# read in some stock data from the Yahoo Finance API
AAPL = pd.read_csv(
"http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000&d=0&e=1&f=2010",
parse_dates=['Date'])
MSFT = pd.read_csv(
"http://ichart.yahoo.com/table.csv?s=MSFT&a=0&b=1&c=2000&d=0&e=1&f=2010",
parse_dates=['Date'])
IBM = pd.read_csv(
"http://ichart.yahoo.com/table.csv?s=IBM&a=0&b=1&c=2000&d=0&e=1&f=2010",
parse_dates=['Date'])
data = dict(
AAPL=AAPL['Adj Close'],
Date=AAPL['Date'],
MSFT=MSFT['Adj Close'],
IBM=IBM['Adj Close'],
)
tsline = TimeSeries(data,
x='Date', y=['IBM', 'MSFT', 'AAPL'],
color=['IBM', 'MSFT', 'AAPL'], dash=['IBM', 'MSFT', 'AAPL'],
title="Timeseries", ylabel='Stock Prices', legend=True)
tspoint = TimeSeries(data,
x='Date', y=['IBM', 'MSFT', 'AAPL'],
color=['IBM', 'MSFT', 'AAPL'], dash=['IBM', 'MSFT', 'AAPL'],
builder_type='point', title="Timeseries Points",
ylabel='Stock Prices', legend=True)
output_file("timeseries.html")
show(column(tsline, tspoint))
"""
builder_type = BUILDER_TYPES.get(builder_type, builder_type)
kws['x'] = x
kws['y'] = y
return create_and_build(builder_type, data, **kws)
