“To make Excel more user-friendly and powerful, Microsoft has joined hands with Anaconda, a programming language repository provider, to enable Python code to run in Excel without any additional setup.”
Artificial intelligence (AI) has empowered the global tech industry in many ways. The most popular one we hear about nowadays is the creation of ChatGPT, but AI is not just limited to strengthening modern-day software only, also it revitalizes yesteryear applications, such as MS Excel.
To make Excel more usable and powerful, Microsoft has joined hands with Anaconda, a programming language repository provider, to enable Python code to run in Excel without any additional setup. The step has been taken to enable data analysts to use data within the app for machine learning and data analytics.
Microsoft said, “With Python in Excel, you can type Python directly into a cell, the Python calculations run in the Microsoft Cloud, and your results are returned to the worksheet, including plots and visualizations,”.
Why has Microsoft taken this move?
The move signifies that a large amount of enterprise data globally is still archived in MS Excel and data analysts often find it troublesome to use Python inside Excel without additional setups.
Is it the first such move from Microsoft for adding Python code into Excel?
There have been a series of attempts to make it easier to use Python code in MS Excel before this. In 2014, Zoomer Analytic built Xlwings, a BSD-licensed Python library that couples with Excel and enables its spreadsheets and Python app to interact directly. Another attempt was made in 2017 by Continuum Analytics, creators of Anaconda. The company released Anaconda Fusion, a system for merging Anaconda’s enterprise-grade version to MS Excel 2016 and higher versions. These were paid add-ons to connect Python code to MS Excel sheets.
The company said, “However, with native Python integration with Excel, users will be able to use the new “PY” function to input Python code directly into Excel cells and perform tasks such as data cleaning, predictive analytics, and machine learning due to support from tools such as formulas, PivotTables, and Excel Charts”.