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How to Expose a Plot Generated Using a Pandas Dataframe as a Jupyter Notebook as an App t

Current Workflow
As an ML engineer, I am using a jupyter notebook to plot some pandas dataframes. Basically, inside the jupyter notebook, I am setting some hard-coded configurations like


```
k_1:float=2.3
date_to_analyse:str='2024-06-17' # 17th June
region_to_analyse:str='montana'
...
```
Based on the hardcoded parameters like above, the notebook (along with some helper functions) runs a query to my company's data warehouse in Google Big Query, crunches a few numbers, applies some business logic and generates a pandas dataframe for transaction numbers minute by minute throughout the day.

The plot of the pandas dataframe is what's important to the business user, which I show to them as part of our model evaluation metric.

The logic is straightforward enough.

Objective
I am tasked with making this into a self-service application directly usable by the business team, where a user can
* input the above values via a simple UI
* the plot appears on the screen.

I don't have a dedicated frontend guy, neither do I have frontend experience myself. So was just wondering whether there is a simple enough solution (best if serverless, and part of the GCP eco-system) that can accomplish this?

I know about Google colab notebooks (basically, jupyter notebook, right?), but have not tried them. Can they provide a simple way to expose the notebook's functionality (generate the plots from user provided configs)

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1 REPLY 1

Hello ,

Thank you for contacting Google Cloud Community!

I'd be glad to assist you in creating a self-service application for your business team using Google Cloud Platform (GCP) services.You can try the following options:

Option 1: If you prefer the familiar Jupyter Notebook environment, consider creating a notebook with your existing code and uploading it to Cloud Storage.
Option 2: Alternatively, for a cleaner separation of concerns, write a Python script replicating the logic from your notebook. This script would be executed by the Cloud Function.

Regards,
Jai Ade

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