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 <acr...@gmail.com> 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
bgran...@calpoly.edu and elliso...@gmail.com

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