Array Reshaping and Flattening

NumPy makes it easy to reshape arrays — changing the number of rows and columns without changing the data.

You can also flatten a multi-dimensional array into a 1D array.

Use .reshape(rows, columns) to change the array’s shape.
The total number of elements must stay the same.

Copy
arr = np.array([1, 2, 3, 4, 5, 6])
reshaped = arr.reshape(2, 3)

print(reshaped)
# [[1 2 3]
#  [4 5 6]]

Use .flatten() to turn any multi-dimensional array into a 1D array.

Copy
matrix = np.array([[1, 2, 3], [4, 5, 6]])
flat = matrix.flatten()

print(flat)  # [1 2 3 4 5 6]

• Use .reshape() to change an array’s shape (without changing its data)
• Use .flatten() to convert any array to 1D

You’ll now practice reshaping and flattening arrays using code in Jupyter.