如何使用变量浏览器连接到现有的Jupyter Notebook内核并检查变量?

问题描述

如果我有一个通过Jupyter Notebook运行的内核，则可以使用Options > Connect to an exisisting kernel > Browse从Spyder轻松连接到它.现在，只需运行df，即可访问Jupyter内核并查看数据框或任何其他变量:

If I've got a kernel running through a Jupyter Notebook, I can easily connect to it from Spyder using Options > Connect to an exisisting kernel > Browse. Now I can get access to the Jupyter kernel and view the dataframe or any other variable by just running df:

Jupyter代码段:

#imports
import numpy as np
import pandas as pd

# Some sample data
np.random.seed(1234)
df = pd.DataFrame({'A1':np.random.normal(10, 1, 8),
                   'B1':np.random.normal(20, 2, 8)})

Spyder代码段:

df

# output:
          A1         B1
0  10.471435  20.031393
1   8.809024  15.514630
2  11.432707  22.300071
3   9.687348  21.983892
4   9.279411  21.906648
5  10.887163  15.957490
6  10.859588  19.331845
7   9.363476  20.004237

但是为什么Spyder的Variable Explorer中的数据框不可用?

But why is the dataframe not available in the Variable Explorer in Spyder?

推荐答案

(此处为[Spyder维护程序] )，这是因为笔记本计算机创建的内核不具备显示其内核所需的功能.变量浏览器中的命名空间.

(Spyder maintainer here) This happens because the kernels that are created by the notebook doesn't have the functionality necessary to display its namespace in our Variable Explorer.

很抱歉，目前没有简单的解决方法.

And there's no easy workaround for that at the moment, sorry.

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