NumPy array basicsnp.array([1,2,3])
| Creates a 1D array with values 1, 2, 3. (shape 1x3) | np.array([(1,2,3), (4,5,6)])
| Creates 2D array of shape 2x3 with values 1,2,3,4,5,6 | np.array([[(1,2,3), (4,5,6)], [(7,8,9), (10,11,12)]])
| Creates a 3D array with shape 2x2x3 | np.zeros(3,4)
| Creates a 3x4 array of zeros | np.arrange(1,60,5)
| Creates a 1D array of values 1 through 60 at steps of 5 | a.reshape(2,3,4)
| Reshapes array a into an array of shape 2x3x4 | a.shape
| To get the shape of the array a |
Subsettinga[0]
| Gets the 0th element in 1D array a | b[0,0]
| Gets the 0th element in 2D array b | c[0,0,0]
| Gets the 0th element in 3D array c | c[9,0,0]
| Gets the element which is the 0th element in the 0th row in the 9th depth |
Slicing arrays1D arrays | a[:]
| Selects everything | a[2:5]
| Selects the 2nd through the 4th rows (does not include the 5th row) | 2D arrays | b[:,:]
| Selects all rows and all columns | b[:,0]
| Selects all rows, and the zeroth column | b[0,:]
| Selects the zeroth row, and all columns in that row | b[0:2,:]
| Selects the zeroth and first row, but NOT the second. It includes all the columns in that row | b[0:2,0:2]
| Selects the zeroth and first row, and the zeroth and first column | 3D arrays | c[:,:,:]
| Selects all rows and columns on all depths | c[0,:,:]
| Selects the everything in the first depth | c[:,0,:]
| Selects the first row of each depth | c[:,:,0]
| Selects the first column of each depth |
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Its very helpful
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