在 Jupyter/Python 中使用散景绘制交互式饼图 [英] Using bokeh to plot interactive pie chart in Jupyter/Python

问题描述

我是 Bokeh 的新手，如果能帮助我了解如何使用 Bokeh 在 Jupyer/Python 中绘制简单的交互式饼图，我将不胜感激.我计划在 Bokeh 中使用CustomJS with a Python function"，如页面底部所述

比Donut版本略显冗长，但是python端和JS端的数据结构关系更清晰直接.

I am new to Bokeh and I would really appreciate some help in figuring out how to use Bokeh to plot a simple interactive pie chart in Jupyer/Python. I am planning to use 'CustomJS with a Python function' in Bokeh as explained at the bottom of the page here. The pie chart consists of two entries with a slider that can change the shape of one pie 'v2' inside the circle shape of (v1+v2). I have tried to follow the example in bokeh website that shows the interactivity with a sine plot, but I just cannot get it to work with my pie chart. Any help would be greatly appreciated. Below is the code block I am using inside a Jupyter notebook.

import numpy as np
import matplotlib.pyplot as plt
from bokeh.layouts import column
from bokeh.models import CustomJS, ColumnDataSource, Slider
from bokeh.plotting import Figure, output_file, show, output_notebook
from bokeh.charts import Donut, show

#output_file('donut.html')
output_notebook()

v1=1
v2=.2
import pandas as pd
data = pd.Series([v1,v2], index = list('ab')) 
plot = Figure(plot_width=400, plot_height=400)
plot = Donut(data) 
    
    
def pie_chart(source=data,window=None,deltav=None):
    data = source.data
    v2 = deltav.value
    #v2 = data['v2']
    source.trigger('change')
    
slider = Slider(start=.1, end=1., value=.2, step=.1, title="delta-V", callback=CustomJS.from_py_func(pie_chart))
callback.args["deltav"] = slider
    
l = column(slider, plot)
show(l)

解决方案

If you want to interactively update things, then you will be better off using the bokeh.plotting API. For some fairly uninteresting technical reasons, the bokeh.charts API (including Donut) is not well-suited for use cases that require updating things in place.

With bokeh.plotting there is a wedge glyph method that you can use to draw pie charts. Here is a complete example written (using Bokeh 0.12.5) that updates a pie chart with a slider:

from math import pi

from bokeh.io import output_file, show
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, CustomJS, Slider
from bokeh.plotting import figure

output_file("pie.html")

source = ColumnDataSource(data=dict(
    start=[0, 0.2], end=[0.2, 2*pi], color=['firebrick', 'navy']
))

plot = figure()
plot.wedge(x=0, y=0, start_angle='start', end_angle='end', radius=1,
        color='color', alpha=0.6, source=source)

slider = Slider(start=.1, end=1., value=.2, step=.1, title="delta-V")

def update(source=source, slider=slider, window=None):
    data = source.data
    data['end'][0] = slider.value
    source.trigger('change')

slider.js_on_change('value', CustomJS.from_py_func(update))

show(column(slider, plot))

It's slightly more verbose than the Donut version, but the relationship between the data structures on the python side and on the JS side are much more clear and direct.

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