numpy is used to realize the simple code example of the concatenation of one and two dimensional arrays

1 d array

1.numpy initializes a 1-dimensional array

a = np.array([1,2,3]);
print a.shape

The output value should be (3,).

2 d array

numpy initializes a 2-dimensional array

a = np.array([[1,2,3]]);
b = np.array([[1],[2],[3]]);

print a.shape//(1 . 3 ) 
print b.shape// ( 3,1 ) 

Note that the arrays of (3,) and (3,1) are different. The former is a 1-dimensional array and the latter is a 2-dimensional array.

Joining together

3.numpy has many splicing functions. hstack and vstack, for example. Online and a lot of such summary posts. But the only way two arrays can be concatenated is if they have the same dimensions. So newaxis is used to convert a 1-dimensional array to a 2-dimensional array when concatenating 2-dimensional arrays and 1-dimensional arrays, that is, shape is converted from (3,) to (3,1).

a = np.array([1,2,3]);
b = np.array([[1],[2],[3]]);
# will 1 Dimensional array a into 2 Dimensional array 
a = a[:,np.newaxis];
c = np.concatenate((b,a),axis=1)
print c.shape// Output for ( 3,2 ) 

conclusion

That's the end of this article's simple code example of using numpy to splicing 1. 2 dimensional arrays. Those who are interested can continue to see other related topics on this site. If there is any deficiency, please let me know. Thank you for your support!