importnumpyasnp# 创建随机浮点数数组random_array=np.random.rand(5)print(random_array) Python Copy Output: 示例代码 11:创建随机整数数组 importnumpyasnp# 创建随机整数数组random_int_array=np.random.randint(0,10,size=(5,))print(random_int_array) Python Copy Output: 8. 使用np.full创建常数填充的...
array_of_arrays#> array([array([0, 1, 2]), array([3, 4, 5, 6]), array([7, 8, 9])], dtype=object) 期望输出: #> array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) 51. 如何为 NumPy 数组生成 one-hot 编码? 难度:L4 问题:计算 one-hot 编码。 输入: np.random.seed(101) ...
numpy.random.randcreates an array of the given shape and populate it with random samples from auniformdistributionover[0,1). Parametersd0, d1, ..., dndefine dimentions of returned array. np.random.rand(2,3) Output: array([[0.20544659, 0.23520889, 0.11680902], [0.56246922, 0.60270525, 0.752...
np.random.random_integers(1, 10, size=(2, 5)) array([[ 3, 3, 8, 4, 5], [2, 7, 8, 10, 2]]) 5. numpy.random.random_sample(size=None) 6. numpy.random.random(size=None) 7. numpy.random.ranf(size=None) 8. numpy.random.sample(size=None) Return random floats in the half...
rand_arr = np.random.random((5,3)) 22. 如何通过禁用科学计数法(如 1e10)打印 NumPy 数组? 难度:L1 问题:通过禁用科学计数法(如 1e10)打印 NumPy 数组 rand_arr。 输入: # Create the random arraynp.random.seed(100)rand_arr = np.random.random([3,3])/1e3rand_arr#> array([[ 5.434049...
np.random.shuffle(arr) # 返回 array([[3, 4, 5], # [6, 7, 8], # [0, 1, 2]]) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. rand方法 Create an array of the given shape and populate it with random samplesfrom a uniform distribution over [0, 1)。
arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])` 期望输出: #> array([1, 3, 5, 7, 9]) 5. 如何将 NumPy 数组中满足给定条件的项替换成另一个数值? 难度:L1 问题:将 arr 中的所有奇数替换成 -1。 输入: arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) ...
In the above example, we have used thenp.random.rand()function to create an arrayarray1with5random numbers. This code generates a different output each time we run it. Create an Empty NumPy Array To create an empty NumPy array, we use thenp.empty()function. For example, ...
array_l =np.array(list_1) 1. 2. 3. 4. 运算如下 ② list创建 二维数组 用[ ] 框住list,“把list再作为list” import numpy as np #create from python list list_1=[1,2,3,4] list_2=[5,6,7,8] array_2=np.array([list_1,list_2]) ...
import numpy as np from timeit import timeit from numpy.lib.stride_tricks import as_strided # Adapted from Alex Rogozhnikov (linked below) # Generate array of (fake) closing prices prices = np.random.randn(100) # We want closing prices from the ten days prior window = 10 # Create arr...