Great point Brian. For prototyping's sake monkey patching should be enough 
to test if the interaction is valuable or not.


On Monday, September 17, 2018 at 4:45:19 PM UTC-7, ellisonbg wrote:
>
> I think it could be regular python code that uses the Jupyter display 
> system to display the information. The challenge is to figure out how to 
> detect the pandas function calls and add the needed logic before and after. 
> A good starting point might be to just monkey patch the relevant pandas 
> calls and wrap them in the logic you need. That would allow you to get 
> started quickly and explore the problem space.
>
> On Mon, Sep 17, 2018 at 3:40 PM Adam Rule <[email protected] <javascript:>> 
> wrote:
>
>> I have noticed that a number of Jupyter users call df.head(), df.shape, 
>> df.describe(), or something similar almost every time they load or 
>> manipulate a dataframe to inspect what their manipulation did. I would like 
>> to develop an extension or kernel magic that prints useful information to a 
>> cell's output based on the pandas function called in that cell. For 
>> example, running pd.read_csv() might automatically print the shape and 
>> column names of the loaded dataframe and df.drop_duplicates() might 
>> automatically print how many duplicates were dropped and how many unique 
>> rows remain.
>>
>> How might I architect such an extension (e.g., a JupyterLab extension, an 
>> iPython kernel magic, or something else)? I think I would need to detect 
>> when certain pandas functions are about to be run by the kernel and gather 
>> information about the dataframe immediately before and after execution. 
>> Would that even be feasible?
>>
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>
>
> -- 
> Brian E. Granger
> Associate Professor of Physics and Data Science
> Cal Poly State University, San Luis Obispo
> @ellisonbg on Twitter and GitHub
> [email protected] <javascript:> and [email protected] <javascript:>
>

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