如何在ipywidget输出小部件中显示matplotlib饼图？我正在使用Jupyter Notebook，目前没有任何显示

Question

My code result currently, but I want the Pie chart to show up under the Algo Tab

我的代码

Flexible

在上面的代码片段中，如果我不使用ipywidgets，则可以很好地生成饼图，但是如果我希望将此饼图放在ipywidget选项卡中，则看不到任何结果，您认为有解决这个问题的另一种方法？我正在使用Jupyter Notebook

Answer 1

基于this working code，建议您将绘图分配给变量my_plot，然后尝试plt.show(my_plot)或display(my_plot.figure)。

我使用笔记本here中的甜甜圈图概述了该方法。您需要运行笔记本才能看到它的渲染。为此，请转到here，然后按“在笔记本计算机上的选项卡小部件演示中以甜甜圈图开始”旁边的launch binder。在概述的过程中，我已经在笔记本的较早部分调用了绘图。因此，我提到了几种将其添加到上面的选项卡的方法。

从那里总结：
早先在笔记本中将甜甜圈图定义为donut_plot，以下代码将其添加到简单标签系统的第一个标签中：

%matplotlib inline
# based on https://stackoverflow.com/a/51060721/8508004
# and https://github.com/jupyter-widgets/ipywidgets/issues/1754
# combined with donut plot from 
# https://github.com/fomightez/donut_plots_with_subgroups/blob/master/demo_basics_from_df.ipynb
import matplotlib.pyplot as plt
import pandas as pd
import ipywidgets as widgets
import numpy as np

out1 = widgets.Output()
out2 = widgets.Output()
data1 = pd.DataFrame(np.random.normal(size = 50))
data2 = pd.DataFrame(np.random.normal(size = 100))

tab = widgets.Tab(children = [out1, out2])
tab.set_title(0, 'First')
tab.set_title(1, 'Second')
display(tab)

with out1:
    #fig1, axes1 = plt.subplots()
    #data1.hist(ax = axes1)
    #plt.show(fig1)
    display(donut_plot.figure)

with out2:
    fig2, axes2 = plt.subplots()
    data2.hist(ax = axes2)
    plt.show(fig2)

---

更新以下带有饼图的更多自包含示例：

为响应OP表达添加饼图的麻烦，我在上面链接的笔记本中添加了另一个示例。归结为以下。为了使代码块比上面更独立，我还包括了使用的数据框：

%matplotlib inline
# based on https://stackoverflow.com/a/51060721/8508004
# and https://github.com/jupyter-widgets/ipywidgets/issues/1754
# combined with donut plot from 
# https://github.com/fomightez/donut_plots_with_subgroups/blob/master/demo_basics_from_df.ipynb
import pandas as pd
obs = [('A', 1, "frizzled"), 
       ('A', 1, "lethargic"), 
       ('A', 1, "polythene"), 
       ('A', 1, "epic"),
       ('A', 2, "frizzled"), 
       ('A', 2, "lethargic"), 
       ('A', 2, "epic"),
       ('A', 3, "frizzled"), 
       ('A', 3, "lethargic"),
       ('A', 3, "polythene"),
       ('A', 3, "epic"),
       ('A', 3, "bedraggled"),
       ('B', 1, "frizzled"), 
       ('B', 1, "lethargic"),
       ('B', 1, "polythene"),
       ('B', 1, "epic"),
       ('B', 1, "bedraggled"),
       ('B', 1, "moombahcored"),
       ('B', 2, "frizzled"), 
       ('B', 2, "lethargic"),
       ('B', 2, "polythene"),
       ('B', 2, "epic"),
       ('B', 2, "bedraggled"),
       ('C', 1, "frizzled"), 
       ('C', 1, "lethargic"),
       ('C', 1, "polythene"),
       ('C', 1, "epic"),
       ('C', 1, "bedraggled"),
       ('C', 1, "moombahcored"),
       ('C', 1, "zoned"),
       ('C', 1, "erstaz"),
       ('C', 1, "mined"),
       ('C', 1, "liberated"),
       ('C', 2, "frizzled"), 
       ('C', 2, "lethargic"),
       ('C', 2, "polythene"),
       ('C', 2, "epic"),
       ('C', 2, "bedraggled"),
       ('C', 3, "frizzled"), 
       ('C', 3, "lethargic"),
       ('C', 3, "polythene"),
       ('C', 3, "epic"),
       ('C', 3, "bedraggled"),
       ('C', 4, "bedraggled"),
       ('C', 4, "frizzled"), 
       ('C', 4, "lethargic"),
       ('C', 4, "polythene"),
       ('C', 4, "epic"),
       ('C', 5, "frizzled"), 
       ('C', 5, "lethargic"),
       ('C', 5, "polythene"),
       ('C', 5, "epic"),
       ('C', 5, "bedraggled"),
       ('C', 5, "moombahcored")]
labels = ['group', 'subgroup', 'sub-subgroup']
df = pd.DataFrame.from_records(obs, columns=labels)
import matplotlib.pyplot as plt
import pandas as pd
import ipywidgets as widgets
import numpy as np

out1 = widgets.Output()
out2 = widgets.Output()
data1 = pd.DataFrame(np.random.normal(size = 50))
data2 = pd.DataFrame(np.random.normal(size = 100))

tab = widgets.Tab(children = [out1, out2])
tab.set_title(0, 'First')
tab.set_title(1, 'Second')
display(tab)

with out1:
    #fig1, axes1 = plt.subplots()
    #data1.hist(ax = axes1)
    #plt.show(fig1)
    grouped = df.groupby("group")
    grouped.size()
    group_names= grouped.size().index.tolist()
    group_size= grouped.size().tolist()
    my_plot  = plt.pie(group_size, labels=group_names,autopct="%0.f%%",radius=2.4)
    plt.show(my_plot)

with out2:
    fig2, axes2 = plt.subplots()
    data2.hist(ax = axes2)
    plt.show(fig2)

Answer 2

在节目单上显示

{p3}中上述答案中的

plt.show(fig)已被弃用：

In [1]: import matplotlib.pyplot as plt                                                                                                                                   

In [2]: fig = plt.figure()                                                                                                                                                

In [3]: plt.show(fig)                                                                                                                                                     
<ipython-input-3-d1fd62acb551>:1: MatplotlibDeprecationWarning: Passing the 
block parameter of show() positionally is deprecated since Matplotlib 3.1; the 
parameter will become keyword-only in 3.3.
    plt.show(fig)

plt.show(block=True)（或plt.show(block=False)）是仅关键字调用。

因此，display(fig)似乎是不久的将来唯一有效的选择。

---

在%matplotlib inline

人们可以看看在笔记本中嵌入的matplotlib图的其他选项：

• %matplotlib notebook

  注释：通常不需要显示或提供2个图形输出

• ％matplotlib小部件

  注释：要求ipympl，请参见Github上的Wayne