import numpy as np
import holoviews as hv
from holoviews import opts

hv.extension('matplotlib')

np.random.seed(9)
data = np.random.rand(10, 2)
points = hv.Points(data)
labels = hv.Labels({('x', 'y'): data, 'text': [chr(65+i) for i in range(10)]}, ['x', 'y'], 'text')

(points* labels).opts(
    opts.Labels(color='text', cmap='Category20', xoffset=0.05, yoffset=0.05, size=14, padding=0.2),
    opts.Points(color='black', s=25))

value_dimension = hv.Dimension('Values', value_format=lambda x: '%.1f' % x)
xs = ys = np.linspace(-2.5, 2.5, 25)
zs = np.sin(xs**2)*np.sin(ys**2)[:, np.newaxis]

hv.Labels((xs, ys, zs), vdims=value_dimension).opts(
    opts.Labels(bgcolor='black', cmap='viridis', color='Values', fig_size=200, padding=0.05, size=8))