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
some details of the BokehJS interface have changed. For Bokeh 0.11
and newer, the __implementation__
should now be:
__implementation__ = """
_ = require "underscore"
Model = require "model"
p = require "core/properties"
class DateGapTickFormatter extends Model
type: 'DateGapTickFormatter'
doFormat: (ticks) ->
date_labels = @get("date_labels")
return (date_labels[tick] ? "" for tick in ticks)
@define {
date_labels: [ p.Any ]
}
module.exports =
Model: DateGapTickFormatter
"""
This is not expected to change any further.
Pull request 3314 was made for an example that works on 2015-12-05. The original code is here. The documentation for the candlestick example is still showing the same code as the OP had in the question.
Included below for reference.
from math import pi
import pandas as pd
from bokeh.sampledata.stocks import MSFT
from bokeh.plotting import figure, show, output_file
from bokeh.models.formatters import TickFormatter, String, List
# In this custom TickFormatter, xaxis labels are taken from an array of date
# Strings (e.g. ['Sep 01', 'Sep 02', ...]) passed to the date_labels property.
class DateGapTickFormatter(TickFormatter):
date_labels = List(String)
__implementation__ = """
_ = require "underscore"
HasProperties = require "common/has_properties"
class DateGapTickFormatter extends HasProperties
type: 'DateGapTickFormatter'
format: (ticks) ->
date_labels = @get("date_labels")
return (date_labels[tick] ? "" for tick in ticks)
module.exports =
Model: DateGapTickFormatter
"""
df = pd.DataFrame(MSFT)[:50]
# xaxis date labels used in the custom TickFormatter
date_labels = [date.strftime('%b %d') for date in pd.to_datetime(df["date"])]
mids = (df.open + df.close)/2
spans = abs(df.close-df.open)
inc = df.close > df.open
dec = df.open > df.close
w = 0.5
output_file("custom_datetime_axis.html", title="custom_datetime_axis.py example")
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
p = figure(tools=TOOLS, plot_width=1000, toolbar_location="left")
# Using the custom TickFormatter. You must always define date_labels
p.xaxis[0].formatter = DateGapTickFormatter(date_labels = date_labels)
# x coordinates must be integers. If for example df.index are
# datetimes, you should replace them with a integer sequence
p.segment(df.index, df.high, df.index, df.low, color="black")
p.rect(df.index[inc], mids[inc], w, spans[inc], fill_color="#D5E1DD", line_color="black")
p.rect(df.index[dec], mids[dec], w, spans[dec], fill_color="#F2583E", line_color="black")
p.title = "MSFT Candlestick with custom x axis"
p.xaxis.major_label_orientation = pi/4
p.grid[0].ticker.desired_num_ticks = 6
show(p) # open a browser
Due to the code using the dataframe
index, your data must be sorted in ascending date order. If you have a time series in descending date order it can be reversed for use by the above code with:
df.sort_values(by='date', inplace=True)
df.reset_index(drop=True, inplace=True)