Given we want to make multiple scatter plots from a dataframe using a
groupby on a column like so:
perc_df.hvplot.scatter( x="donor", y="percentage", c="sex", rot=45, width=1400, groupby=["age_group"], ).layout( "age_group" ).cols( 1 )
the coloration of the markers by the
sex column will performed independently on each of the groupby’d dataframes. For example, if your color cycle is [blue, orange], and by chance, a row with
sex=='M' happens to be first in the given dataframe for a subplot of the layout, it will be assigned blue, and vice versa for ‘F’. In my case, I’m pre-sorting the data for visualization by
age, so either sex category could randomly be the first row for a subplot. I was wondering if it was possible to enforce somehow that a particular category’s label should always be given a certain color.