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Anaconda vs NumPy: What are the differences?
Developers describe Anaconda as "The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders". A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda. On the other hand, NumPy is detailed 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.
Anaconda and NumPy can be primarily classified as "Data Science" tools.
NumPy is an open source tool with 11.1K GitHub stars and 3.67K GitHub forks. Here's a link to NumPy's open source repository on GitHub.
Instacart, Suggestic, and Twilio SendGrid are some of the popular companies that use NumPy, whereas Anaconda is used by ADEXT, Luuna, and DLabs. NumPy has a broader approval, being mentioned in 63 company stacks & 34 developers stacks; compared to Anaconda, which is listed in 4 company stacks and 5 developer stacks.
Pros of Anaconda
Pros of NumPy
- Great for data analysis8
- Faster than list2
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What is Anaconda?
What is NumPy?
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What companies use Anaconda?
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What tools integrate with Anaconda?
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