【Python | NumPy】基础

1. 创建一个NumPy数组

x = np.array([list])

2. 访问数组属性

x.ndim # the number of dimensions of the array

x.size # the total number of elements of the array

x.shape # returns a tuple of integers that indicate the number of elements stored along each dimension of the array.

x.dtype # type of the ndarray

3. 基本数组操作

# 为NumPy数组添加元素4

x = np.append(x, 4)

# 删除NumPy数组中第一个元素

x = np.delete(x, 0)

# 将NumPy数组中元素排序

x = np.sort(x)

# 创建一个数组（注意"arange"只有一个"r"）

x = np.arange(2, 10, 3)

4. Changing the shape

# 将数组变为3行，2列的二维数组

x = np.reshape(3, 2)

# 将数组变为一维数组

x = np.reshape(7)

5. Indexing and slicing

NumPy arrays can be indexed and sliced the same way that Python lists are.

import numpy as np

x = np.arange(1, 10)

print(x)

print(x[0:2])

print(x[5:])

print(x[:2])

print(x[-3:])

#打印特定条件下的数组

print(x[x<4])

print(x[(x > 5) & (x%2 == 0)])

6. 数组计算

# The sum of all elements

x.sum()

# Get the smallest / largest element

x.min()

x.max()

# Multiply all elements by 2

y = x * 2

7. Statistics

print(np.mean(x))

print(np.median(x))

print(np.var(x))

print(np.std(x))