I am looking at the candlestick example in the bokeh docs, found here:
https://github.com/bokeh/bokeh/blob/master/examples/plotting/file/candlestick.py
and I
UPDATE: As of Bokeh 0.12.6 you can specify overrides for major tick labels on axes.
import pandas as pd
from bokeh.io import show, output_file
from bokeh.plotting import figure
from bokeh.sampledata.stocks import MSFT
df = pd.DataFrame(MSFT)[:50]
inc = df.close > df.open
dec = df.open > df.close
p = figure(plot_width=1000, title="MSFT Candlestick with Custom X-Axis")
# map dataframe indices to date strings and use as label overrides
p.xaxis.major_label_overrides = {
i: date.strftime('%b %d') for i, date in enumerate(pd.to_datetime(df["date"]))
}
# use the *indices* for x-axis coordinates, overrides will print better labels
p.segment(df.index, df.high, df.index, df.low, color="black")
p.vbar(df.index[inc], 0.5, df.open[inc], df.close[inc], fill_color="#D5E1DD", line_color="black")
p.vbar(df.index[dec], 0.5, df.open[dec], df.close[dec], fill_color="#F2583E", line_color="black")
output_file("custom_datetime_axis.html", title="custom_datetime_axis.py example")
show(p)
If you have a very large number of dates, this approach might become unwieldy, and a Custom Extension might become necessary.