Need advice about which tool to choose?Ask the StackShare community!
NumPy vs PyXLL: What are the differences?
Developers describe NumPy as "Fundamental package for scientific computing with Python". Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. On the other hand, PyXLL is detailed as "The Python Add-In for Microsoft Excel". Integrate Python into Microsoft Excel Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python.
Works with all 3rd party and open source Python packages. No need to write any VBA!.
NumPy and PyXLL can be primarily classified as "Data Science" tools.
Some of the features offered by NumPy are:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- tools for integrating C/C++ and Fortran code
On the other hand, PyXLL provides the following key features:
- User Defined Functions: Write Excel worksheet functions in Python - no VBA required
- Ribbon Customization: Give your users a rich Excel native experience
- Macros: No need for VBA, access to the full Excel Object Model in Python
NumPy is an open source tool with 11.4K GitHub stars and 3.76K GitHub forks. Here's a link to NumPy's open source repository on GitHub.
Pros of NumPy
- Great for data analysis10
- Faster than list4
Pros of PyXLL
- Fully replace VBA with Python5
- Excellent support2
- Very good performance1
Sign up to add or upvote prosMake informed product decisions
Cons of NumPy
Cons of PyXLL
- Cannot be deloyed to mac users1
Sign up to add or upvote consMake informed product decisions
What is NumPy?
What is PyXLL?
Need advice about which tool to choose?Ask the StackShare community!
What companies use PyXLL?
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with PyXLL?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+42