The Python in Excel environment is notably user-friendly, especially for those accustomed to Excel. It resonates with users familiar with writing formulas and functions in Excel cells, as this is precisely the approach Python in Excel adopts. However, Python workflows differ from those in Excel. Rather than relying on interdependent ...

I’ve long advocated for Excel users to enhance their skills by learning some Python. In fact, I’m so passionate about this idea that I authored a book on how Excel users can embrace Python. However, I recognize the hesitation. Python isn’t just another application where you can ...

The concept of objects significantly distinguishes Python from Excel, enhancing its importance in programming. Integrating Python objects into Excel introduces unique behaviors and functionalities, which will be the focal point of this blog post. Download the following to explore this intriguing intersection of Python and Excel.   We’ll begin the ...

Python in Excel provides a user-friendly and data analysis-optimized approach, especially suitable for general analysts beginning with Python. Notably, it defaults to loading all data inputs as Pandas DataFrames, a wise decision considering Excel users’ familiarity with tabular structures. Basic Python, on its own, isn’t inherently tailored for such ...

In an earlier post, I discussed typical challenges Excel users face when transitioning to Python: This article will explore the unique “gotchas” that arise specifically when integrating Python in Excel. Importing packages Python packages are crucial for streamlined and clear data analysis. Many standard data-related Python packages come pre-installed in ...

The availability of Python integration within Excel has made Python an accessible and valuable skill for many Excel users to consider adding to their toolkit. However, as an open-source programming language, Python operates differently from proprietary spreadsheet software like Excel. This post examines a significant distinction—the use of packages ...

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In a previous post I explored some “quick wins” for wrangling and analyzing data in Python that would be otherwise difficult to do in Excel. That post largely avoided data visualization, so this post will be on a similar topic — visualizations that would be difficult to build in regular Excel ...