Ever needed to do the following in Excel or Power BI?
- Process and analyze text data (regular expressions, sentiment analysis, etc) ⌨️
- Load in very large or unusual datasets using parallel processing, API calls, web scraping, etc. 🔃
- Develop unique visualizations not available in the set menu of your tool’s offerings 📈
- Build statistical and machine learning models 🧮
- Add unit tests, CI/CD pipelines or other development best practices to your work 👷
A lot of this is difficult or even impossible to do with native Excel and Power BI capabilities.
That’s why Python is 🚨already officially available🚨 in Power BI and will ⏳likely be soon for Excel⏳(but there’s already opportunity to use it there).
It may feel like Python is a sideshow diversion to the awesome stack Microsoft has put together for data and BI… but 🏗️ Python is meant to be part of that stack 🏗️.
How have you been using Python to complement your work in Excel or Power BI? What obstacles have you faced? Let me know in comments. I’ll also share some resources below to get you started.
Resources
- Python for Excel by Felix Zumstein will not only teach you the basics of Python, but immediately get you augmenting and automating your Excel work with various Python tools.
- Extending Power BI with Python and R by Luca Zavarella will serve as a great handbook of ready-to-use code for the use cases I outlined earlier.
- How does Azure fit into all of this? Find out with Tobias Zwingmann’s AI-Powered Business Intelligence. You’ll learn how to add predictive analytics to your Power BI dashboard using Python, ML Studio and more.
- Honorable mention: If you’re an Excel user looking to pick up general Python and R knowledge, I must plug my own book Advancing into Analytics.
- I also gave a brief presentation on this topic to the RMB Bank Data Science Meetup. View the resources here. Drop me a line if you’re interested in a similar presentation to your group.
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