>>> 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]])
a = np.array([1, 2, 3, 4])
b = np.array([5, 6, 7, 8])
np.concatenate((a, b))
import numpy as np
arr = np.array([1, 2, 1, 2, 3, 4, 5, 4, 6, 7])
# create a set array with no duplicates
arr = np.unique(arr)
print(arr)
# [1 2 3 4 5 6 7]
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
# create a 1d set array without from both arrays removing duplicates
arr = np.union1d(arr1, arr2)
print(arr)
# output [1 2 3 4 5 6]
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
# create a 1d set array where both numbers are found in both arrays
arr = np.intersect1d(arr1, arr2, assume_unique=True)
print(arr)
# output [3 4]
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
# create a 1d set array that contained only numbers found in the first array but not the second
arr = np.setdiff1d(arr1, arr2, assume_unique=True)
print(arr)
# output [1 2]
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
# create a 1d set array where numbers from both arrays are not in each other
arr = np.setxor1d(arr1, arr2, assume_unique=True)
print(arr)
# output [1 2 5 6]
#// required library
import numpy as npy
#// define 3 (1D) numpy arrays
arr1 = npy.array([10, 20, 30])
arr2 = npy.array([40, 50, 60])
arr3 = npy.array([70, 80, 90])
arrCon = npy.concatenate([arr1, arr2, arr3])
print(arrCon)
#// concatenation can also happen with 2D arrays
arr1_2d = npy.array([
[10, 20, 30],
[40, 50, 60]
])
arr2_2d = npy.array([
[11, 22, 33],
[44, 55, 66]
])
arr_2dCon = npy.concatenate([arr1_2d, arr2_2d])
print(arr_2dCon)
# Example 1: Use concatenate() to join two arrays
con = np.concatenate((arr, arr1))
print(con)
# Example 2: Use concatenate() with axis
con = np.concatenate((arr, arr1), axis=1)
print(con)
# Example 3: Use np.stack() function to Join Arrays
con = np.stack((arr, arr1), axis=1)
print(con)
# Example 4: Use np.hstack() function
con = np.hstack((arr, arr1))
print(con)
# Example 5: Use np.vstack() function
con = np.vstack((arr, arr1))
print(con)
# Example 6: Use np.dstack() function to Stacking Along Height (depth)
con = np.dstack((arr, arr1))
print(con)