NumPy ndarray.flatten() function in Python
The ndarray.flatten() function in NumPy is used to return a one-dimensional copy of the array. This method is useful when you want to convert a multi-dimensional array into a single dimension.
Syntax:
ndarray.flatten(order='C')
Parameters
- order (optional): It specifies the order in which the array elements should be read. The default is ‘C’, which means to read and write the elements using C-like index order, with the last axis index changing fastest, back to the first axis index changing slowest. Other options are:
'F': Fortran-like index order, with the first index changing fastest, and the last index changing slowest.'A': ‘F’ order if the array is Fortran contiguous, ‘C’ order otherwise.'K': Keep the order of the array as much as possible.
Returns
- flattened_array: A one-dimensional array.
Example Usage
Code:
import numpy as np # Creating a 2D array arr = np.array([[1, 2], [3, 4]]) # Flattening the array using default C order flattened_arr = arr.flatten() print(flattened_arr) # Output: [1 2 3 4] # Flattening the array using Fortran order flattened_arr_f = arr.flatten(order='F') print(flattened_arr_f) # Output: [1 3 2 4] # Creating a 3D array arr_3d = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) # Flattening the 3D array flattened_arr_3d = arr_3d.flatten() print(flattened_arr_3d)
output:
[1 2 3 4 5 6 7 8]
Key Points
flatten()always returns a copy of the array.- It is different from
ravel(), which returns a flattened array but returns a view whenever possible. Useravel()if you need a flattened view of the array. - Choosing the correct order (
'C','F','A','K') can be important depending on the structure of your data and performance considerations.
Using ndarray.flatten() can be very useful in situations where you need to process or analyze data in a single-dimensional format, regardless of its original shape.