Why NumPy is so important?

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NumPy

One of the reasons NumPy is so important for numerical computations in Python is because it is designed for efficiency on large arrays of data.

There are a number of reasons for this:

• NumPy internally stores data in a contiguous block of memory, independent of other built-in Python objects. NumPy’s library of algorithms written in the C language can operate on this memory without any type checking or other overhead. NumPy arrays also use much less memory than built-in Python sequences.
• NumPy operations perform complex computations on entire arrays without the need for Python for loops.

e.g.

Conclusion

NumPy-based algorithms are generally 10 to 100 times faster (or more) than their pure Python counterparts and use significantly less memory.

Reference

Python for Data Analysis Second Edition

Why NumPy is so important?

原文：https://www.cnblogs.com/agilestyle/p/12243889.html