If len(groupby) > 1 and overlay > 1, cycle multiple sequential cmaps?

[ahuang11]

The first image is very noisy, the second image is much more understandable (although the legend labels are missing the names)

import pandas as pd
import xarray as xr
import hvplot.pandas

ds = xr.tutorial.open_dataset('air_temperature')

ds_sub = ds.sel(lat=[15, 40, 75], lon=272.5, time=ds['time.day'] == 15)
ds_sub = ds_sub.groupby(ds_sub['time'].dt.strftime('%m%d%H')).mean('time')
ds_sub.coords['label'] = ('lat', ['tropics', 'mid-latitude', 'arctic-circle'])
ds_sub['month'] = ds_sub['strftime'].str[:2]
ds_sub['hour'] = ds_sub['strftime'].str[-2:]


df = ds_sub.to_dataframe().reset_index()
df = df.drop(columns=['lat', 'lon', 'strftime'])

df.hvplot('month', 'air', groupby=['label', 'hour']).overlay(['label', 'hour']).opts(legend_position='right')

from pylab import *
def get_cmap(cmap):
    cmap = cm.get_cmap(cmap, 4)    # PiYG
    rgbs = [matplotlib.colors.rgb2hex(cmap(i)[:3]) for i in range(cmap.N)] # will return rgba, we take only first 3 so we get rgb
    return rgbs

ov = hv.NdOverlay()
for label, cmap in zip(df['label'].unique(), ['Reds', 'Greens', 'Blues'][::-1]):
    ov[label] =  df.loc[df['label'] == label].hvplot('month', 'air', groupby='hour', label=label, color=hv.Cycle(get_cmap(cmap)), dynamic=False).overlay()

ov

[philippjfr]

It's a good request I just don't know what the API would be so for now a slightly simpler way to achieve the same thing:

plot = df.hvplot('month', 'air', by=['label', 'hour'], legend='right').groupby('label')
for p, cmap in zip(plot, ('Reds', 'Greens', 'Blues')):
    p.opts('Curve', color=hv.Palette(cmap))
plot