import hvplot.pandas
import panel as pn
import holoviews as hv
from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature
pn.extension()
This example demonstrates how to put widgets together to build a simple UI for exploring the distribution of sea surface temperatures, as follows:
pn.depends
to express the dependencies on the widget valuesbins = pn.widgets.IntSlider(name='Number of bins', start=5, end=25, step=5, value=10)
kde = pn.widgets.Checkbox(name='Show density estimate')
observations = pn.widgets.Checkbox(name='Show individual observations')
bandwidth = pn.widgets.FloatSlider(name='KDE Bandwidth', start=0.1, end=1)
@pn.depends(bins.param.value, kde.param.value,
observations.param.value, bandwidth.param.value)
def get_plot(bins, kde, obs, bw):
plot = sea_surface_temperature.hvplot.hist(bins=bins, normed=True, xlabel='Temperature (C)', padding=0.1)
if kde:
plot *= sea_surface_temperature.hvplot.kde().opts(bandwidth=bw)
if obs:
plot *= hv.Spikes(sea_surface_temperature, 'temperature').opts(
line_width=0.1, alpha=0.1, spike_length=-0.01)
return plot
widgets = pn.WidgetBox('## Sea surface temperatures', bins, observations, kde)
def add_bandwidth(event):
if event.new:
widgets.append(bandwidth)
else:
widgets.remove(bandwidth)
kde.param.watch(add_bandwidth, 'value')
pn.Row(widgets, get_plot).servable()