Bar charts to hide categorical minor axis (subgroup)

Hello,

I am wrestling with this seemingly basic issue. I have a data that basically resembles the “Fruit counts by year” example from Bokeh documentation linked below.

I want to hide the minor xaxis (subgroup) from being visible. I intend to tackle this by giving each subgroup a color and then displaying a legend on what each color represents. So in the bokeh doc example, that would be hiding the ‘years’ and just leaving the ‘fruits’ labels for the x axis.

The following code is adapted from the example in the Grouping section of the user’s guide that you linked.

There are certainly alternative ways of achieving what you want, and probably several better ones, but the last two lines before the show() statement do the following (1) hide the years, and (2) set the font size of the hidden years labels to control how close the fruit labels appear.

Tested with bokeh 2.3.3.

Hope it helps

Screen Shot 2021-09-20 at 7.40.56 AM1334×584 10.4 KB

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
"""

from bokeh.io import output_file, show
from bokeh.models import ColumnDataSource, FactorRange
from bokeh.transform import factor_cmap
from bokeh.plotting import figure

output_file("bars.html")

fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']
years = ['2015', '2016', '2017']

data = {'fruits' : fruits,
        '2015'   : [2, 1, 4, 3, 2, 4],
        '2016'   : [5, 3, 3, 2, 4, 6],
        '2017'   : [3, 2, 4, 4, 5, 3]}

# this creates [ ("Apples", "2015"), ("Apples", "2016"), ("Apples", "2017"), ("Pears", "2015), ... ]
x = [ (fruit, year) for fruit in fruits for year in years ]
counts = sum(zip(data['2015'], data['2016'], data['2017']), ()) # like an hstack

source = ColumnDataSource(data=dict(x=x, counts=counts))

p = figure(x_range=FactorRange(*x), height=250, title="Fruit counts by year",
           toolbar_location=None, tools="")

palette = ["#c9d9d3", "#718dbf", "#e84d60"]
p.vbar(x='x', top='counts', width=0.9, source=source, line_color="white",
       # use the palette to colormap based on the the x[1:2] values
       fill_color=factor_cmap('x', palette=palette, factors=years, start=1, end=2))

p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xgrid.grid_line_color = None

p.xaxis.major_label_text_alpha = 0.0
p.xaxis.major_label_text_font_size = '1px'

show(p)

Thank you for your response and workaround. This did resolve my issue. I am so surprised such properties are not handled in a more traditional visibility toggle.

There is another way to accomplish this using a dodge (i.e. a visual offset) to position the bars, rather than nested categorical factors. That eliminates the “minor” ticks altogether. See

https://docs.bokeh.org/en/latest/docs/user_guide/categorical.html#visual-offset

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