Excel is one of the most used and most empowering pieces of software out there, but that doesn't

make it a good fit for every data processing need. And when you outgrow Excel, a really good

option for that next step is Python and the data science tech stack, Pandas, Jupiter, and Friends.

Chris Moffat is back on Talk Python to give us concrete tips and tricks for moving from Excel to Python and Pandas.

This is Talk Python to me.

Episode 288 recorded September 15th, 2020. Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter where I'm at M. Kennedy. Keep up with the show and listen to

past episodes at talk python.fm. And follow the show on Twitter via at Talk Python. This episode is

sponsored by The Voyager video game, which is built on Python and Linode. Check out what they're both

offering during their segments. It really helps support the show. Talk Python to me is partially supported by our

training courses. I got a joke for you. What's the world's most popular IDE? Excel. Funny, right?

Except many companies really do run on Excel to the point where they would be much better off

using clean and simple programming tools. For many, Python's data science stack would be vastly better.

But moving from Excel to Python is a challenge.

Most data science courses don't focus specifically on the Excel use cases.

That's why we've teamed up with Chris Moffitt from Practical Business Python

to create a course tailor-made for helping people learn just enough pandas in Jupiter

to replace the problematic Excel usage with clean and scalable Python code.

If you or your coworkers are ready to move beyond Excel, visit TalkPython.fm slash Excel

or just click the link in the show notes to learn more about this online course at Talk Python

Training. Chris, welcome course at Talk Python Training.

Chris, welcome back to Talk Python to me.

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