what is numpy

The NumPy system is an open source numerical computing extension for Python. This tool can be used to store and process large matrices. It is much more efficient than Python's own nested list structure (this structure can also be used to represent a matrix).

1: Numpy related introduction:

A scientific calculation implemented in python includes:

1. A powerful N-dimensional array Object Array;

2. A relatively mature (broadcast) function library;

3. A toolkit for integrating C/C and Fortran codes;

4. Practical Linear algebra, Fourier transforms, and random number generating functions. It is more convenient to use numpy with the sparse matrix operation package scipy.

2: The core of the NumPy package is the ndarray object. This encapsulates an n-dimensional array of homogeneous data types, with many operations performed in compiled code to improve performance. There are several important differences between NumPy arrays and standard Python sequences:

• NumPy arrays have a fixed size when they are created, unlike Python lists (which can grow dynamically). Changing the size of an ndarray will create a new array and delete the original array.

•The elements in a NumPy array need to be of the same data type and therefore the same size in memory. Exception: It is possible to have arrays of (Python, including NumPy) objects, allowing arrays of elements of different sizes.

•NumPy arrays facilitate advanced mathematical and other types of operations on large amounts of data. Generally, these operations can be performed more efficiently and with less code than using Python's built-in sequences.

• An increasing number of Python-based scientific and mathematical packages are using NumPy arrays; while these typically support Python sequence inputs, they convert these inputs to NumPy arrays before processing, and they typically output NumPy array. In other words, in order to effectively use a lot (or even most) of today's Python-based scientific/math software, it's not enough to know how to use Python's built-in sequence types - you also need to know how to use NumPy arrays.

The above is the detailed content of what is numpy. For more information, please follow other related articles on the PHP Chinese website!