Customization - PFund-Plot's Documentation

If you want to customize the plot, you can set raw_figure to True to get the raw figure object, which is holoviews figure.

import pfeed as pe
import pfund_plot as plt
import holoviews as hv
import panel as pn
from docs.utils import display_html

feed = pe.YahooFinanceFeed()
df = feed.get_historical_data(product='AAPL_USD_STK', resolution='1d', rollback_period='1y')

holoviews_fig = plt.candlestick(df, display_mode='notebook', raw_figure=True)

# this is only needed in documentation
display_html(pn.pane.HoloViews(holoviews_fig))

Customized holoviews figure:¶

for more details, see hvplot and holoviews

customized_holoviews_fig = holoviews_fig.opts(bgcolor='gray')

# this is only needed in documentation
display_html(pn.pane.HoloViews(customized_holoviews_fig))

The plot above is actually using bokeh as the backend, so we can also obtain the bokeh figure and customize it if preferred.

Obtain bokeh figure:¶

bokeh_fig = hv.render(holoviews_fig, backend='bokeh')
type(bokeh_fig)

bokeh.plotting._figure.figure

Customized bokeh figure:¶

from bokeh.io import show

bokeh_fig.title.text = "Customized " + bokeh_fig.title.text
bokeh_fig.title.text_font_size = '20pt'
bokeh_fig.title.text_color = 'blue'

show(bokeh_fig)

PFund-Plot's Documentation

Layout

PFund-Plot's Documentation

Rendering