Python for Excel: A Modern Environment for Automation and Data Analysis

Python Meets the Spreadsheet 🐍📊

Excel is still where many teams model, forecast, and report. Python is where modern data work happens. Python for Excel: A Modern Environment for Automation and Data Analysis shows how the two fit together, and this second edition brings the discussion up to date with Python in Excel, Microsoft’s official integration.

Felix Zumstein writes for people who already know their way around a workbook and now want more powerful ways to automate, clean, analyze, and extend it. The book does not treat Python as a replacement for Excel. It treats Python as a way to reach the parts of a spreadsheet workflow that formulas and VBA handle awkwardly.

What the Second Edition Adds

The 2026 edition moves beyond the first edition’s open-source toolchain to cover Python in Excel directly. Readers learn how Python cells work, how the xl function connects Python to worksheet ranges, how pandas DataFrames behave inside Excel, and how plotting and execution order affect real workbooks. The book also updates the development environment with modern tools such as uv, Jupyter notebooks, Visual Studio Code, Ruff, and type hints.

Inside the Book

• Python core principles: the language features, data structures, control flow, functions, and style guidance that matter for practical scripting.
• Modern tooling: terminal basics, package management, Jupyter notebooks, VS Code, debugging, and code organization.
• pandas and NumPy: arrays, Series, DataFrames, indexing, missing data, grouping, pivot tables, time series, plotting, and CSV import or export.
• Python in Excel: Python cells, output types, the xl function, DataFrame roundtrips, initialization scripts, settings, shortcuts, and limitations.
• xlwings and xlwings Lite: using Excel as a data viewer, the Excel object model, automation, and custom functions.
• File manipulation: reading and writing Excel files with OpenPyXL and XlsxWriter.

Who This Book Is For

Analysts, engineers, data scientists, and advanced Excel users will find the most value here. The material assumes some comfort with spreadsheets and a willingness to write code, but it explains the Python side carefully enough that readers can build momentum as they go.

Why the Combination Matters

VBA served Excel well for decades, but it has not kept pace with the wider Python ecosystem. By connecting the two, Python for Excel helps readers bring data acquisition, statistical analysis, visualization, and repeatable automation into the same environment where many business decisions are already made. If your workbooks have outgrown manual formulas and you want a maintainable path forward, this is a practical guide to keep nearby.