Write a NumPy program to replace all the nan (missing values) of a given array with the mean of another array. Sample Solution: Python Code: # Importing the NumPy library import numpy as np # Creating NumPy arrays: array_nums1 from 0 to 19 reshaped into a 4x5 array and array_nums2 ...
The second and the third arguments to np.where don't need to be arrays; one or both of them can be scalar. A typical use of where in data analysis is to produce a new array of values base on another array(通过一个多维数组,对其进行判断, 产生新数组, 通过三元表达式的写法). Suppose yo...
Indexing NumPy array with another NumPy array By indexingarr2with another array, thearr2must return the corresponding values. Also,arr1must contain all the values less than or equal to the length of values ofarr2. This can be simply done by converting thearr1into atupleand then indexing the...
padding with spaces; prints " hello"prints.center(7)# Center a string, padding with spaces; prints " hello "prints.replace('l','(ell)')# Replace all instances of one substring with another;# prints
://codingpy.com/article/getting-started-with-jupyter-notebook-part-1/1.array定义一个矩阵2.shape,dim,size的意义及使用shape表矩阵格式例如array.shape(2,3)即表示一2*3矩阵; dim表示维度 size表示内存大小(个人理解为元素个数)3.定义数据类型 dtype!4.定义一个全为零的矩阵(同理全为一 ...
20. 考虑一个 (6,7,8) 形状的数组,其第100个元素的索引(x,y,z)是什么? print(np.unravel_index(100,(6,7,8))) 复制 21. 用tile函数去创建一个 8x8的棋盘样式矩阵(★☆☆) Z=np.tile(np.array([[0,1],[1,0]]),(4,4))print(Z) ...
array=np.ma.masked_array(data,mask=mask)# Compute the mean of the unmasked elementsmean_value=masked_array.mean()# Replace all masked values with the mean of the unmasked elementsfilled_array=masked_array.filled(mean_value)# Print the original array, the masked array, and the filled array...
Z = np.tile( np.array([[0,1],[1,0]]), (4,4))print(Z) 1. 22.归一化一个5x5随机矩阵(★☆☆) Z = np.random.random((5,5))Z = (Z - np.mean (Z)) / (np.std (Z))print(Z) 1. 23.创建一个自定义dtype,将颜色描述为四个unsigned bytes(RGBA)(★☆☆) ...
(array([0,1,4]),) 11. 创建3x3单位矩阵 (★☆☆) Z=np.eye(3)print(Z) [[1.0.0.][0.1.0.][0.0.1.]] 12. 使用随机值创建3x3x3数组 (★☆☆) Z=np.random.random((3,3,3))print(Z) [[[0.189401890.244014180.78815012][0.588396570.107912250.13944297][0.038460020.516909790.1773832]][[0.10936...
(提示: array1:-1, 1:-1) Z = np.ones((10,10)) Z1:\-1,1:\-1= 0 print(Z) 16. 对于一个存在在数组,如何添加一个用0填充的边界? (★☆☆) (提示: np.pad) Z = np.ones((5,5)) Z = np.pad(Z, pad_width=1, mode='constant', constant_values=0) ...