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Numpy ndarray.flatten() function | Python

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In this article, we will explore the syntax, definition, and usage of the NumPy `ndarray.flatten()` function. We will provide a comprehensive explanation along with an illustrative example to enhance understanding.

numpy.ndarray.flatten() Function Syntax

numpy.ndarray.flatten() function returns a copy of the array collapsed into one dimension.

Syntax : numpy.ndarray.flatten(order=’C’)

Parameters :

  • order : [{‘C’, ‘F’, ‘A’, ‘K’}, optional] ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.

Return : [ndarray] A copy of the input array, flattened to one dimension.

What is numpy.ndarray.flatten() Function in Python?

The numpy.ndarray.flatten() function in Python is a method provided by the NumPy library, which is widely used for numerical and array operations. This function is specifically designed for NumPy arrays (ndarrays) and serves the purpose of returning a flattened copy of the input array. The term “flattened” implies that the resulting array is a one-dimensional representation of the original, unraveling any nested dimensions.

numpy.ndarray.flatten() Function Examples

There are various examples of numpy.ndarray.flatten() function, here we are discussing some generally used examples of numpy.ndarray.flatten() Function those are following.

  • Numpy Flatten Function
  • numpy.ndarray.flatten() in Fortran Order
  • Concatenate Flattened Arrays
  • Initialize a Flattened Array with Zeros
  • Find Maximum Value in Flattened Array

Numpy Flatten Function

In this example code uses the numpy library to create a 2D array ‘arr’. The `flatten()` function is then applied to ‘arr’, converting it into a 1D array ‘gfg’, which is printed. The result is a flattened version of the original 2D array.

Python3




# importing numpy as geek
import numpy as geek
 
arr = geek.array([[5, 6], [7, 8]])
 
gfg = arr.flatten()
 
print( gfg )


Output :

[5 6 7 8]

numpy.ndarray.flatten() in Fortran Order

In this example This code uses the NumPy library to create a 2×2 array ‘arr’. The `flatten(‘F’)` function is then applied to flatten the array in column-major order (‘F’) and the result is printed.

Python3




# importing numpy as geek
import numpy as geek
 
arr = geek.array([[5, 6], [7, 8]])
 
gfg = arr.flatten('F')
 
print( gfg )


Output :

[5 6 7 8]

Concatenate Flattened Arrays

In this example code uses NumPy to create two 2D arrays, `array1` and `array2`. It then flattens both arrays and concatenates them into a single 1D array named `concatenated_array`. Finally, it prints the original arrays and the concatenated result.

Python3




import numpy as np
 
# Create two 2D arrays
array1 = np.array([[1, 2, 3], [4, 5, 6]])
array2 = np.array([[7, 8, 9], [10, 11, 12]])
 
# Flatten the arrays and concatenate them
concatenated_array = np.concatenate((array1.flatten(), array2.flatten()))
 
print("Array 1:")
print(array1)
print("\nArray 2:")
print(array2)
print("\nConcatenated Array:")
print(concatenated_array)


Output :

Array 1:
[[1 2 3]
[4 5 6]]
Array 2:
[[ 7 8 9]
[10 11 12]]
Concatenated Array:
[ 1 2 3 4 5 6 7 8 9 10 11 12]

Initialize a Flattened Array with Zeros

In this example code uses the NumPy library to create a 2D array named `original_array`. It then flattens this array and creates a new flattened array called `flattened_zeros` with the same shape, initialized with zeros. Finally, it prints both the original 2D array and the flattened array filled with zeros.

Python3




import numpy as np
 
# Create a 2D array
original_array = np.array([[1, 2, 3],
                           [4, 5, 6]])
 
# Flatten the array and initialize a new flattened array with zeros
flattened_zeros = np.zeros_like(original_array.flatten())
 
print("Original Array:")
print(original_array)
print("\nFlattened Zeros Array:")
print(flattened_zeros)


Output :

Original Array:
[[1 2 3]
[4 5 6]]
Flattened Zeros Array:
[0 0 0 0 0 0]

Find Maximum Value in Flattened Array

In this example The code uses NumPy to create a 3×3 array named `original_array`. It then flattens the array, finds the maximum value in the flattened version, and prints the original array along with the maximum value.

Python3




import numpy as np
 
# Create a 3x3 array
original_array = np.array([[4, 12, 8],
                           [5, 9, 10],
                           [7, 6, 11]])
 
# Flatten the array and find the maximum value
max_value = original_array.flatten().max()
 
print("Original Array:")
print(original_array)
print("\nMaximum Value in Flattened Array:", max_value)


Output:

Original Array:
[[ 4 12 8]
[ 5 9 10]
[ 7 6 11]]
Maximum Value in Flattened Array: 12


Last Updated : 29 Dec, 2023
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