What is the difference between a numpy array (lets say X) that has a shape of (N,1) and (N,). Aren't both of them Nx1 matrices ? The reason I ask is because sometimes computations return either one or the other.
numpy array that is (n,1) and (n,)
Asked Answered
This is a 1D array:
>>> np.array([1, 2, 3]).shape
(3,)
This array is a 2D but there is only one element in the first dimension:
>>> np.array([[1, 2, 3]]).shape
(1, 3)
Transposing gives the shape you are asking for:
>>> np.array([[1, 2, 3]]).T.shape
(3, 1)
Now, look at the array. Only the first column of this 2D array is filled.
>>> np.array([[1, 2, 3]]).T
array([[1],
[2],
[3]])
Given these two arrays:
>>> a = np.array([[1, 2, 3]])
>>> b = np.array([[1, 2, 3]]).T
>>> a
array([[1, 2, 3]])
>>> b
array([[1],
[2],
[3]])
You can take advantage of broadcasting:
>>> a * b
array([[1, 2, 3],
[2, 4, 6],
[3, 6, 9]])
The missing numbers are filled in. Think for rows and columns in table or spreadsheet.
>>> a + b
array([[2, 3, 4],
[3, 4, 5],
[4, 5, 6]])
Doing this with higher dimensions gets tougher on your imagination.
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