Arrays in python (Array)

Arrays in python (Array)

In Python, an array (Array) is an ordered collection of data used to store a fixed number of elements of the same type. An array is a contiguous memory space where each element can be accessed and modified by index.

Features:

1. The elements in an array have the same data type, which can be numbers, strings, or other types.
2. The size of the array is fixed, once created, its length cannot be changed.
3. The elements in the array can be accessed and modified by index value.
4. The elements in the array are stored contiguously in memory.

Create an array:

In Python, you can use third-party libraries numpyto create and manipulate arrays. Numpy is a powerful mathematical and scientific computing library for Python, which provides a wealth of functions and methods for efficiently manipulating multidimensional arrays.

First you need to install numpythe library , you can use the following command to install:

pip install numpy

Once installed, you can use numpyto create arrays:

import numpy as np

arr = np.array([1, 2, 3, 4, 5])  # 创建一维数组
print(arr)  # 输出: [1 2 3 4 5]

matrix = np.array([[1, 2, 3], [4, 5, 6]])  # 创建二维数组
print(matrix)
# 输出:
# [[1 2 3]
#  [4 5 6]]

Access and modify array elements:

An index value can be used to access a specific element in an array. Index values ​​start at 0 and can be integers or slice objects. For multidimensional arrays, elements can be accessed and modified by indexing layer by layer.

import numpy as np

arr = np.array([1, 2, 3, 4, 5])

print(arr[0])  # 输出: 1，访问第一个元素

arr[2] = 10  # 修改第三个元素为10
print(arr)  # 输出: [ 1  2 10  4  5]

matrix = np.array([[1, 2, 3], [4, 5, 6]])

print(matrix[0, 1])  # 输出: 2，访问第一行第二列元素

matrix[1, 2] = 7  # 修改第二行第三列元素为7
print(matrix)
# 输出:
# [[1 2 3]
#  [4 5 7]]

Common operations:

• Array shape: You can use shapethe attribute to get the shape of the array, and return a tuple representing the size of each dimension.

import numpy as np

matrix = np.array([[1, 2, 3], [4, 5, 6]])

shape = matrix.shape
print(shape)  # 输出: (2, 3)，表示2行3列的二维数组

• Array operations: Numpy provides a wealth of functions and methods to manipulate arrays, such as calculating the maximum, minimum, average, and sorting.

import numpy as np

arr = np.array([5, 2, 1, 6, 4])

maximum = np.max(arr)  # 计算数组的最大值
print(maximum)  # 输出: 6

minimum = np.min(arr)  # 计算数组的最小值
print(minimum)  # 输出: 1

mean = np.mean(arr)  # 计算数组的平均值
print(mean)  # 输出: 3.6

sorted_arr = np.sort(arr)  # 对数组进行排序
print(sorted_arr)  # 输出: [1 2 4 5 6]

• Array slicing: A slice object can be used to obtain a subset of an array. A slice object consists of a start index, an end index, and a step size.

import numpy as np

arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

subset = arr[2:6]  # 获取索引2到5（不包括6）的子集
print(subset)  # 输出: [2 3 4 5]

reversed_arr = arr[::-1]  # 将数组逆序
print(reversed_arr)  # 输出: [9 8 7 6 5 4 3 2 1 0]

The above is a detailed explanation about arrays in Python. Arrays are a common data structure used to store and manipulate large amounts of data of the same type. With the help of third-party libraries numpy, we can efficiently create, access and manipulate arrays, so that we can conveniently perform numerical calculations and scientific operations.