如何在使用日期时间作为x轴时让bokeh忽略缺失日期

Question

我在看bokeh文档里的蜡烛图示例，链接在这里：

https://github.com/bokeh/bokeh/blob/master/examples/plotting/file/candlestick.py

我想找个好办法，去掉x轴上没有数据的“空白”部分。

具体来说，像示例中用到的MSFT这样的金融数据，在周末和节假日是没有数据的。那么，有没有办法让bokeh在没有数据的日期上不留空白呢？

为了方便，这里贴一下上面链接中的示例代码：

from math import pi
import pandas as pd

from bokeh.sampledata.stocks import MSFT
from bokeh.plotting import *

df = pd.DataFrame(MSFT)[:50]
df['date'] = 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 = 12*60*60*1000 # half day in ms

output_file("candlestick.html", title="candlestick.py example")

figure(x_axis_type = "datetime", tools="pan,wheel_zoom,box_zoom,reset,previewsave",
   width=1000, name="candlestick")

hold()

segment(df.date, df.high, df.date, df.low, color='black')
rect(df.date[inc], mids[inc], w, spans[inc], fill_color="#D5E1DD", line_color="black")
rect(df.date[dec], mids[dec], w, spans[dec], fill_color="#F2583E", line_color="black")

curplot().title = "MSFT Candlestick"
xaxis().major_label_orientation = pi/4
grid().grid_line_alpha=0.3

show()  # open a browser

Answer 1

更新于2016-05-26：

BokehJS接口的一些细节发生了变化。对于Bokeh 0.11及更新版本，__implementation__现在应该是：

__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
"""

预计以后不会再有变化。

2016-02-09

拉取请求3314是为了一个在2015-12-05有效的示例。原始代码在这里。关于蜡烛图示例的文档仍然显示着提问者在问题中使用的相同代码。

以下是供参考的内容。

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

---

由于代码使用了dataframe的索引，你的数据必须按日期升序排列。如果你的时间序列是按日期降序排列的，可以通过以下代码将其反转，以便与上面的代码一起使用：

df.sort_values(by='date', inplace=True)
df.reset_index(drop=True, inplace=True)

Answer 2

更新：从 Bokeh 0.12.6 版本开始，你可以为坐标轴上的主要刻度标签设置自定义选项。

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)

如果你有很多日期，这种方法可能会变得很麻烦，这时候可能需要使用一个自定义扩展。