Image by Tumisu from Pixabay

A few months ago I came across an awesome online Jupyter notebook tool called Deepnote. And I also came across an awesome tool called Datapane for publishing reports with Python charts. These two products have had terrific developments in the last few weeks, and I combined them to publish an online report that updates every day! Check it out here.

Summary

  • In a Deepnote notebook, I wrote Python code that pulls holdings data from the SSGA website for ETFs that track the S&P 500 and the S&P 500 ESG indices.


Photo by Hello I’m Nik 🎞 on Unsplash

In September 2020, after a lot of head-scratching, I managed to create a data visualisation app with Python and Streamlit and publish it on the web using Heroku. And I did all this on a cheap old Chromebook, which is not even a ‘proper’ PC!

I thought I’d write about the whole process so that others who wish to try programming and creating data apps won’t be put off by technical jargon and the lack of powerful computing devices.

The Hardware

As I said above, the only computing device I used for the entire process is a 4GB RAM, 32GB local storage…

Shantala Mukherjee

Senior Investment Analyst for multi-asset portfolios. Data, finance, technology and history are some of my favourite things.

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