Description
If you want to add value labels to your data you have to overlay holoviews hv.Label() on your plot:
# import libraries
import numpy as np
import pandas as pd
import holoviews as hv
import hvplot.pandas
# create some sample data
df = pd.DataFrame({
'col1': ['bar1', 'bar2', 'bar3'],
'col2': np.random.rand(3)
})
# create your plot
plot = df.hvplot(kind='bar', x='col1', y='col2', ylim=(0, 1.2))
# create your labels separately
# kdims specifies the x and y position of your value label
# vdims specifies the column to use for the value text of your label
labels = hv.Labels(data=df, kdims=['col1', 'col2'], vdims='col2')
# use the * symbol to overlay your labels on your plot
plot * labels
It would be nice if you could just use something like parameter
value_labels=True
to do this automagically right away with hvplot:
plot = df.hvplot(kind='bar', x='col1', y='col2', ylim=(0, 1.2), value_labels=True)
See also: https://stackoverflow.com/questions/58900736/adding-value-labels-to-hvplot-bar
If possible the default offset should also be a bit smart:
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