B ÎYmã@sZdZddlmZddlmZddlmZmZddlm Z ee edœZ d d d efd d „Z d S) a.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. é)Úabsolute_importé)Úcreate_and_buildé)Ú LineBuilderÚPointSeriesBuilder)Ú StepBuilder)ÚlineÚstepZpointNcKs*t ||¡}||d<||d<t||f|ŽS)ab Create a timeseries chart using :class:`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 ` Examples: .. bokeh-plot:: :source-position: above import pandas as pd from bkcharts 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)) ÚxÚy)Ú BUILDER_TYPESÚgetr)Údatar r Z builder_typeZkws©rúClib/python3.7/site-packages/bkcharts/builders/timeseries_builder.pyÚ TimeSeries$sA r) Ú__doc__Z __future__rZbuilderrZ line_builderrrZ step_builderrr rrrrrÚs