Holoviews - Heatmap - Different color scale per each row of data

[vlaranjo]

I would like to have a different conditional formatting for each row shown in the heatmap - that is, colors should be the same but the scale should be applied independently for each row.

Picking up on the example in this link: Us Unemployment — HoloViews v1.15.1

from bokeh.sampledata.unemployment1948 import data

data = pd.melt(data.drop('Annual', 1), id_vars='Year', var_name='Month', value_name='Unemployment')
heatmap = hv.HeatMap(data, label="US Unemployment (1948 - 2013)")

colors = ["#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1", "#cc7878", "#933b41", "#550b1d"]
heatmap.opts(
    opts.HeatMap(width=900, height=400, xrotation=45, xaxis='top', labelled=[],
                 tools=['hover'], cmap=colors))

What I would like is for January’s row color scale to be independent of the other months in the y-axis. So that different values in December, for example, don’t affect the colors of January’s row.

Is it possible?

I provide a further example below:

[vlaranjo]

I could find an answer to the problem. I posted my code in here in case someone comes here in the future: Vasconomics_Materials/Articles/Stock Market Returns Seasonality/Code Conditional Formatting for Each Row HeatMap.ipynb at master · vlaranjo/Vasconomics_Materials · GitHub

The answer lies in running a loop of heatmaps and defining the label in a specific way:

heatmap = hv.HeatMap(data, label=f"Year {heatmap_row}")