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NumPy vs Dataform: What are the differences?
NumPy: 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; Dataform: A framework for managing SQL based data operations. Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.
NumPy can be classified as a tool in the "Data Science Tools" category, while Dataform is grouped under "Business Intelligence".
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, Dataform provides the following key features:
- Version ontrol
- Scheduling
- Notifications and logging
NumPy and Dataform are both open source tools. NumPy with 12.3K GitHub stars and 4.03K forks on GitHub appears to be more popular than Dataform with 117 GitHub stars and 11 GitHub forks.
Pros of Dataform
Pros of NumPy
- Great for data analysis10
- Faster than list4
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What is Dataform?
What is NumPy?
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