在散景中一张带有两个不同y轴范围的图表? [英] One chart with two different y axis ranges in Bokeh?

问题描述

我想要一个在左侧y轴上带有数量"信息的条形图，然后在右侧的收益率％"上覆盖一个散点图/折线图.我可以分别创建每个图表，但是不知道如何将它们组合成一个图.

I would like a Bar chart with Quantity information on the left y-axis, and then overlay a Scatter/Line plot with Yield % on the right. I can create each of these charts separately, but do not know how to combine them into a single plot.

在matplotlib中，我们将使用twinx()创建第二个图形，然后在各个图形上使用yaxis.tick_left()和yaxis.tick_right().

In matplotlib, we would create a second figure using twinx(), and then use yaxis.tick_left() and yaxis.tick_right() on the respective figures.

是否有一种方法可以与Bokeh做类似的事情?

Is there a method for doing something similar with Bokeh?

推荐答案

是的，现在在散景图中可以有两个y轴. 下面的代码显示了对设置第二个y轴重要的脚本部分 到通常的图形绘制脚本.

Yes, now it is possible to have two y axes in Bokeh plots. The code below shows script parts significant in setting up the second y axis to the usual figure plotting script.

# Modules needed from Bokeh.
from bokeh.io import output_file, show
from bokeh.plotting import figure
from bokeh.models import LinearAxis, Range1d

# Seting the params for the first figure.
s1 = figure(x_axis_type="datetime", tools=TOOLS, plot_width=1000,
           plot_height=600)

# Setting the second y axis range name and range
s1.extra_y_ranges = {"foo": Range1d(start=-100, end=200)}

# Adding the second axis to the plot.  
s1.add_layout(LinearAxis(y_range_name="foo"), 'right')

# Setting the rect glyph params for the first graph. 
# Using the default y range and y axis here.           
s1.rect(df_j.timestamp, mids, w, spans, fill_color="#D5E1DD", line_color="black")

# Setting the rect glyph params for the second graph. 
# Using the aditional y range named "foo" and "right" y axis here. 
s1.rect(df_j.timestamp, ad_bar_coord, w, bar_span,
         fill_color="#D5E1DD", color="green", y_range_name="foo")

# Show the combined graphs with twin y axes.
show(s1)

我们得到的情节看起来像这样:

And the plot we get looks like this:

如果您想在第二个轴上添加标签，则可以通过编辑对如下:

If you want to add a label to the second axis, this can be accomplished by editing the call to LinearAxis as follows:

s1.add_layout(LinearAxis(y_range_name="foo", axis_label='foo label'), 'right')

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