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 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
# -----------------------------------------------------------------------------

    '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( "", parse_dates=['Date']) MSFT = pd.read_csv( "", parse_dates=['Date']) IBM = pd.read_csv( "", 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)