CODEWITHSUNDEEP
pythonpandasjupyter
Evgeny
Evgeny

Reputation: 4571

jupyter notebook/lab fails on imported function

I have a boolean subsetting function that works on a pandas dataframe:

def operational(df):
    return df[(df['cf'] != 0) & (df['ta'] > 0)]

it works well in a script and in a jupiter notebook, when entered in cell:

#df = ...
df2 = operational(df)

However, if I keep function definiton in pick.py and import in to jupyter, things go unexpected. It seems upon import of a module jupiter does not reconise the types of variables inside a function:

import pick

pick.operational(df).head()

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-16-374442fd7c0a> in <module>()
      1 import pick
----> 2 pick.operational(df).head()

C:\Users\Евгений\Documents\GitHub\sandbox\pick.py in operational(_df)
     11 
     12 def operational(df):
---> 13     return df[(df['cf'] != 0) & (df['ta'] > 0)]

     14 
     15 

TypeError: 'method' object is not subscriptable

Is importing something to notebook a generally bad idea? I use jupiter lab, if that matters.

Upvotes: 0

Views: 314

Answers (1)

tel
tel

Reputation: 13999

Okay, from the comments it sounds like you were expecting the notebook to automatically pick up changes in an imported script. By default, Python caches imports, so most of the time changes to imported modules won't get picked up until you restart Python.

Fortuitously, Jupyter notebooks run on IPython, which supplies a code reloading cell magic. All you need to do is run:

%autoreload 2

in any cell, and your notebook should, from then on, automatically pick up any changes in pick.py as you make them (you still have to save the changes to disk before the reload magic can see them, of course).

Upvotes: 2

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