Thinning of CategoricalAxes tick labels

Hello,

I have a plot that has some ordered sequence of strings (say, serial numbers of experiments) at x-axis. The sequence can be mapped to a (continuous?) integer series.

As far as I understand, CategoricalAxes are usually used for this.

Unfortunately, when there are a lot of such categories, visual overlap occurs.

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Is there any “idiomatic way” for visual thinning of xticklabels for CategoricalAxes at current scale (like for DateTimeAxis or LinearAxis) so that recalculation to a new scale occurs when zooming?

Moreover I think the LinearAxis is more suitable if the mapping like {int xvalue : str view} is possible.

@dinya Have you tested major_label_overrides? (link). Maybe that can be used.

The example below use idx field in the CDS as x values (integers) for placing the data, but uses the x field for the axis label.

import numpy as np
from bokeh.io import output_file, save
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource

output_file('page.html')

alpha = list('abcdefghijklmnopqrstuvwxyz')
data = {
    'x': alpha,
    'idx': list(range(len(alpha))),
    'y': np.random.rand(len(alpha))
}

src = ColumnDataSource(data = data)

p = figure(width = 300)
p.circle(x = 'idx', y = 'y', alpha = 0.7, source = src)

p.xaxis.major_label_overrides = {
    i: a for i, a in zip(data['idx'], data['x'])
}
p.xaxis.minor_tick_line_color = None

save(p)

@Jonas_Grave_Kristens Thanks a lot.

But how to hide floats between idx-ticks and outside the idx range?

@dinya You can use bounds to limit axis labels to just a certain range (link, link). And you can use min_interval on an axis ticker to control interval between ticks (link).

p.xaxis.bounds = (min(data['idx']), max(data['idx']))
p.xaxis.ticker.min_interval = 1

@Jonas_Grave_Kristens Your recipes are exactly what I need . Thank you!

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Just circling back to note that the next version 3.6 will add a CustomJSTicker that can be used to adjust categorical ticks

Bokeh 3.6. is released and CustomJSTicker is now available to use.