How do I use custom labels for ticks in Bokeh?

Question

I understand how you specify specific ticks to show in Bokeh, but my question is if there is a way to assign a specific label to show versus the position. So for example

plot.xaxis[0].ticker=FixedTicker(ticks=[0,1])

will only show the x-axis labels at 0 and 1, but what if instead of showing 0 and 1 I wanted to show Apple and Orange. Something like

plot.xaxis[0].ticker=FixedTicker(ticks=[0,1], labels=['Apple', 'Orange'])

A histogram won't work for the data I am plotting. Is there anyway to use custom labels in Bokeh like this?

Answer 1

As of even more recent versions of Bokeh (0.12.14 or so) this is even simpler. Fixed ticks can just be passed directly as the "ticker" value, and major label overrides can be provided to explicitly supply custom labels for specific values:

from bokeh.io import output_file, show
from bokeh.plotting import figure

p = figure()
p.circle(x=[1,2,3], y=[4,6,5], size=20)

p.xaxis.ticker = [1, 2, 3]
p.xaxis.major_label_overrides = {1: 'A', 2: 'B', 3: 'C'}

output_file("test.html")

show(p)

---

NOTE: the old version of the answer below refers to the bokeh.charts API, which was since deprecated and removed

As of recent Bokeh releases (e.g. 0.12.4 or newer), this is now much simpler to accomplish using FuncTickFormatter:

import pandas as pd
from bokeh.charts import Bar, output_file, show
from bokeh.models import FuncTickFormatter

skills_list = ['cheese making', 'squanching', 'leaving harsh criticisms']
pct_counts = [25, 40, 1]
df = pd.DataFrame({'skill':skills_list, 'pct jobs with skill':pct_counts})
p = Bar(df, 'index', values='pct jobs with skill', title="Top skills for ___ jobs", legend=False)
label_dict = {}
for i, s in enumerate(skills_list):
    label_dict[i] = s

p.xaxis.formatter = FuncTickFormatter(code="""
    var labels = %s;
    return labels[tick];
""" % label_dict)

output_file("bar.html")
show(p)