Stacking together different NumPy arrays. The following shows how to stack together different NumPy Array of the Python NumPy module.
import numpy as np
from numpy import newaxis
In [2]:
a = np.floor(10*np.random.random((2,2)))
a
Out[2]:
array([[1., 1.],
[3., 0.]])
In [3]:
b = np.floor(10*np.random.random((2,2)))
b
Out[3]:
array([[2., 7.],
[5., 4.]])
In [4]:
np.vstack((a,b))
Out[4]:
array([[1., 1.],
[3., 0.],
[2., 7.],
[5., 4.]])
In [5]:
np.hstack((a,b))
Out[5]:
array([[1., 1., 2., 7.],
[3., 0., 5., 4.]])
In [6]:
np.column_stack((a,b))
Out[6]:
array([[1., 1., 2., 7.],
[3., 0., 5., 4.]])
In [7]:
a = np.array([4.,2.])
b = np.array([2.,8.])
a[:,newaxis]
Out[7]:
array([[4.],
[2.]])
In [8]:
np.column_stack((a[:,newaxis],b[:,newaxis]))
Out[8]:
array([[4., 2.],
[2., 8.]])
In [9]:
np.vstack((a[:,newaxis],b[:,newaxis]))
Out[9]:
array([[4.],
[2.],
[2.],
[8.]])
In [10]:
np.hstack((a[:,newaxis],b[:,newaxis]))
Out[10]:
array([[4., 2.],
[2., 8.]])
In [11]:
np.r_[1:4,0,4]
Out[11]:
array([1, 2, 3, 0, 4])