Experience Python in Excel Now

The Versatility of Excel +
The Power of Anaconda

The world’s most popular data application meets the world’s most trusted Python distribution.

Do More with Your Data

Use popular Python libraries within Excel for complex data analysis and modeling.

Create Custom Visualizations

Explore, manipulate, and present data like never before.

Streamline Your Data Preparation

Simplify complex data transformations and boost productivity while minimizing manual effort.

Share Work Effortlessly

Your work becomes more accessible, easier to understand, and easier to reproduce.

Experience Python in Excel Now
Which best describes you?

I’m an Excel Analyst

I’m a Python User

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Python in Excel

Discover how to leverage Python’s powerful libraries and scripting capabilities to supercharge your data manipulation, visualization, and analysis tasks within Excel.

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Machine Learning with Python in Excel

Explore the full potential of machine learning using Python and scikit-learn within Excel workbooks.

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Get Anaconda Certified: Data Analysis with Python in Excel

Enhance your data analysis skills with Python in Excel, boost your career, and unlock new opportunities.

By the end of this certification program, you’ll learn:

  • What are Python objects, and how they relate to Microsoft Excel
  • How pandas DataFrame and Series objects are fundamental to data analysis using Python
  • How Python provides a repeatable process for crafting the best data tables for your analyses
Register for This Certification
Experience Python in Excel Now

Discover Next-Level Capabilities with Toolbox

Unlock even more capabilities with the Anaconda add-in for Excel – for FREE while in Beta!

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Lean on our expertise
  • Anaconda Assistant: Your personal guide to write better code
  • Unlock the value of your data: streamline access, collaboration, and insights with our dynamic data catalog
  • Aids novice users to visualize information effectively
  • Seamlessly craft stunning visualizations that inspire and inform using Seaborn

Frequently Asked Questions

Why do I need Python in Excel?

Python in Excel lets you run Python code directly in the Excel formula bar. For Excel users, this enables new and powerful analysis and visualization capabilities. For Python users, this makes your Python code easier to share with your Excel-using colleagues, and you can avoid jumping back and forth between Excel and Jupyter notebooks.

Anaconda is integrating the Anaconda Distribution for Python within Excel. This provides not only the core Python functionality but also access to over 400 curated packages, enabling advanced data analysis and visualization directly within your Excel workbook.

Python is an ecosystem consisting of the core language and upwards of hundreds of thousands of third-party libraries, also referred to as packages, developed independently. A distribution, like the Anaconda Distribution for Python, is a subset of those third-party libraries collected into an installable software package.

In Python, the term ‘import’ is used to bring additional functionality into your code. It allows you to access methods and tools provided by third-party libraries or packages.

To get the most out of Python in Excel, start with these packages:

  • pandas for working with tables
  • Seaborn and Matplotlib for creating charts (Seaborn is more beginner friendly, while Matplotlib offers more customization)
  • statsmodels or SciPy for statistical analysis
  • scikit-learn for machine learning

These are a great starting point, with plenty of others to explore as you progress.

In the formula bar, you can click the Python button or type =PY( and start writing your Python code.

Python in Excel uses curated packages from the Anaconda Distribution, safeguarding against malicious packages that are commonly found in community-led repositories. Anaconda’s curation ensures that the packages are compatible and work seamlessly together, providing a trusted source for Python.

A DataFrame is a representation of tabular data organized by rows and columns. The pandas Python library reads tabular data in many formats like Excel or CSV and creates a DataFrame object. The DataFrame can then be used to perform exploratory analysis or data processing in Python.

See https://pandas.pydata.org/docs/getting_started/comparison/comparison_with_spreadsheets.html?highlight=excel for more information.

The VLOOKUP capability within Excel is used to merge two tables by at least one common column and under a specified condition in the pandas library you can perform similar operations using the merge() or join() methods.

The Anaconda Toolbox provides tools to supplement and assist your Python in Excel work. 

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