Free white paper: Five things Excel users should know about Python

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If you’ve visited my blog before you’ll know that I see Excel as a valuable slice of the data analytics stack. In fact, I think it’s the best way to learn analytics. Another slice of that stack is programming languages, including Python.

All signs point to Python becoming integrated with Excel, and there’s lots of interest about the language… and the possibilities.

To that end, I decided to publish this white paper on “five things Excel users should know about Python.” Perhaps before those five, know this — If you’re coming to Python from Excel, you’re in a position of power, not weakness. You’ve already done many of the same operations with data that you’ll do in Python. You’ve worked with functions.

The objective, then, is to transfer this knowledge as cleanly as possible, which is what I endeavor to do in this paper. I chose five general principles for Excel users to internalize. As an open source language, Python’s very philosophy is quite different from Excel’s, so I take some time providing some high-level perspective. But you’ll get plenty of time with your hands on the keyboard, too, learning some of the language’s fundamentals.

I hope this both demystifies Python for you and excites you to learn more.

Please enjoy the white paper and don’t hesitate to drop me a line or leave a comment with thoughts or questions.

When you sign up below, you’ll receive two emails: the first is a general orientation to my newsletter and resource library. A few minutes, a link to this paper will arrive. This email will also contain a link to a companion GitHub repo to run the code used in the paper, along with some other resources.

Download the white paper here 👇

If you are already subscribed to the newsletter… you can find this download in the white-papers subfolder of the resource library.

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Thanks for reading and be sure to peruse the other great content on the blog and in my resource library.

If you want to immerse yourself in Python, check out my book Advancing into Analytics: From Excel to Python and R. More information about the book including how to read for free is available here.

To leave a comment for the author, please follow the link and comment on their blog: Stringfest Analytics .

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