Stocks Example

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URL: https://docs.bokeh.org/en/2.4.1/docs/gallery/stocks.html

Most examples work across multiple plotting backends, this example is also available for:

• Matplotlib - stocks example

import numpy as np
import pandas as pd
import holoviews as hv
from holoviews import opts
hv.extension('bokeh')

Defining the data

from holoviews.operation.timeseries import rolling
from bokeh.sampledata.stocks import AAPL, GOOG, IBM, MSFT

color_cycle = hv.Cycle(values=['#A6CEE3', '#B2DF8A','#33A02C', '#FB9A99'])

def get_curve(data, label=''):
    df = pd.DataFrame(data)
    df['date'] = df.date.astype('datetime64[ns]')
    return hv.Curve(df, ('date', 'Date'), ('adj_close', 'Price'), label=label)

hv.Dimension.type_formatters[np.datetime64] = '%Y'

aapl = get_curve(AAPL, label='AAPL')
goog = get_curve(GOOG, label='GOOG')
ibm  = get_curve(IBM, label='IBM')
msft = get_curve(MSFT, label='MSFT')

avg_curve = rolling(aapl, rolling_window=30).relabel('Average')
avg_scatter = hv.Scatter((np.array(AAPL['date'], dtype=np.datetime64), np.array(AAPL['adj_close'])), 
                         ('date', 'Date'), ('adj_close', 'Price'), label='close')

Plot

((aapl * goog * ibm * msft) + (avg_scatter * avg_curve)).opts(
    opts.Curve(color=color_cycle),
    opts.Curve('Curve.Average', color='navy'),
    opts.Scatter(alpha=0.2, size=4, color='darkgrey'),
    opts.Overlay(width=400, height=400, legend_position='top_left'))

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Download this notebook from GitHub (right-click to download).