使用日期时间作为 x 轴时，如何使散景忽略缺少的日期

Question

我正在查看散景文档中的烛台示例，可在此处找到：

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

我试图找出一种消除 x 轴中没有数据的“空格”的好方法。

具体来说，对于示例中使用的 MSFT 等财务数据，没有周末和节假日的数据。当没有日期数据时，有没有办法告诉散景不要在图表中留下空白？

为方便起见，这里粘贴了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：从 Bokeh 开始，0.12.6您可以为轴上的主要刻度标签指定覆盖。

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)

如果您有大量日期，这种方法可能会变得笨拙，并且可能需要自定义扩展。