Lecture

Array Reshaping and Flattening

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

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


Reshaping

Use .reshape(rows, columns) to change the shape of an array.

The total number of elements must remain the same.

Reshape Example
arr = np.array([1, 2, 3, 4, 5, 6]) reshaped = arr.reshape(2, 3) print(reshaped) # [[1 2 3] # [4 5 6]]

Flattening

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

Flatten Example
matrix = np.array([[1, 2, 3], [4, 5, 6]]) flat = matrix.flatten() print(flat) # [1 2 3 4 5 6]

Summary

  • Use .reshape() to change an array's shape without changing its data
  • Use .flatten() to reduce any array to 1D
Quiz
0 / 1

Using the reshape method in NumPy changes the actual data in the array.

True
False

Lecture

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