importnumpyasnp# 创建一个 3x4 的数组data=np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]])print("原始数组:")print(data)# 选择要裁剪的列(例如第 1 列和第 3 列)columns_to_cut=[0,2]clipped_data=data[:,columns_to_cut]print("裁剪后的数组:")print(
row_indices = np.array([0, 2]) rows = matrix[row_indices, :] 使用布尔数组进行索引 column_mask = np.array([True, False, True]) columns = matrix[:, column_mask] 高级索引是更强大的工具,为用户在复杂数据集上提供了极大的灵活性。通过布尔索引,甚至可以基于数组中的真值来选择或排除数据。 四...
array[row, column] and use : to select a range of rows or columns 1r[2, 2]2r[3, 3:6]3r[:2, :-1]#selecting all the rows up to (and not including) row 2, and all the columns up to (and not including) the last column4r[-1, ::2]#selecting the last row, and only eve...
AXIS 1 IS THE DIRECTION ALONG THE COLUMNS In multidimensional arrays, if you omit later indices, the returned object will be a lower dimensional ndarray consisting of all the data along the higher dimensions. So in the 2 × 2 × 3 array arr3d: Similarly, arr3d[1, 1] gives you all of...
Numpy数组的切片slice 不是产生一个copy, 而是仅仅在原始数据的基础上生成一个新的view. 如果要生成copy,则明确使用copy( )方法. import numpy as npx=np.arange(10).reshape(2,5)x>>> array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]])x[0][2] # x[0][2] = x[0,2]>...
columns = [0, 2] print(columns) 1. 2. [0, 2] 1. x[np.ix_(rows, columns)] 1. array([[ 3, 5], [ 9, 11]]) 1. 2. 如果没有np.ix_调用,则只会选择对角线元素。 使用形状 (2, 3) 的二维布尔数组和四个 True 元素从形状 (2, 3, 5) 的三维数组中选择行,结果为形状 (4, 5...
Example: 2D NumPy Array Slicing importnumpyasnp# create a 2D arrayarray1 = np.array([[1,3,5,7], [9,11,13,15], [2,4,6,8]])# slice the array to get the first two rows and columnssubarray1 = array1[:2, :2]# slice the array to get the last two rows and columnssubarray2...
np.info(np.array) 基本使用 1)数组创建 import numpy as np # array函数创建一个一维数组 arr1 = np.array([1, 2, 3, 4, 5]) print("一维数组:", arr1) # 创建一个二维数组 arr2 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) ...
array([[1, 2, 3, 4], [5, 6, 7, 8]]) Use np.zeros to create an array with an initial value of 0: np.zeros(10) array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]) Create a 2-dimensional array: np.zeros((3, 6)) ...
arr1 = np.array([1, 2, 3, 4, 5]) 创建二维数组 arr2 = np.array([[1, 2, 3], [4, 5, 6]]) print(arr1) print(arr2) 数组的基本操作: import numpy as np 创建数组 arr = np.array([10, 20, 30, 40, 50]) 数组加法 ...