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

Answer 1

EDIT: Updated for Bokeh 0.12.5 but also see simpler method in the other answer.

This worked for me:

import pandas as pd
from bokeh.charts import Bar, output_file, show
from bokeh.models import TickFormatter
from bokeh.core.properties import Dict, Int, String

class FixedTickFormatter(TickFormatter):
    """
    Class used to allow custom axis tick labels on a bokeh chart
    Extends bokeh.model.formatters.TickFormatte
    """

    JS_CODE =  """
        import {Model} from "model"
        import * as p from "core/properties"

        export class FixedTickFormatter extends Model
          type: 'FixedTickFormatter'
          doFormat: (ticks) ->
            labels = @get("labels")
            return (labels[tick] ? "" for tick in ticks)
          @define {
            labels: [ p.Any ]
          }
    """

    labels = Dict(Int, String, help="""
    A mapping of integer ticks values to their labels.
    """)

    __implementation__ = JS_CODE

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[0].formatter = FixedTickFormatter(labels=label_dict)
output_file("bar.html")
show(p)

Answer 2

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)