>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
[3, 4],
[5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
[3, 4, 6]])
import numpy as np
arr = np.array([1, 2, 1, 2, 3, 4, 5, 4, 6, 7])
arr = np.unique(arr)
print(arr)
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
arr = np.union1d(arr1, arr2)
print(arr)
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
arr = np.intersect1d(arr1, arr2, assume_unique=True)
print(arr)
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
arr = np.setdiff1d(arr1, arr2, assume_unique=True)
print(arr)
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
arr = np.setxor1d(arr1, arr2, assume_unique=True)
print(arr)