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# Python | Flatten a 2d numpy array into 1d array

Given a 2d numpy array, the task is to flatten a 2d numpy array into a 1d array. Below are a few methods to solve the task.

Method #1 : Using np.flatten()

## Python3

 `# Python code to demonstrate` `# flattening a 2d numpy array` `# into 1d array`   `import` `numpy as np`   `ini_array1 ``=` `np.array([[``1``, ``2``, ``3``], [``2``, ``4``, ``5``], [``1``, ``2``, ``3``]])`   `# printing initial arrays` `print``("initial array", ``str``(ini_array1))`   `# Multiplying arrays` `result ``=` `ini_array1.flatten()`   `# printing result` `print``("New resulting array: ", result)`

Output:

```initial array [[1 2 3]
[2 4 5]
[1 2 3]]
New resulting array:  [1 2 3 2 4 5 1 2 3]```

Time complexity: O(n), where n is the total number of elements in the 2D numpy array.
Auxiliary space: O(n), as the result array is also of size n. The flatten function returns a flattened 1D array, which is stored in the “result” variable.

Method #2: Using np.ravel()

## Python3

 `# Python code to demonstrate` `# flattening a 2d numpy array` `# into 1d array`   `import` `numpy as np`   `ini_array1 ``=` `np.array([[``1``, ``2``, ``3``], [``2``, ``4``, ``5``], [``1``, ``2``, ``3``]])`   `# printing initial arrays` `print``("initial array", ``str``(ini_array1))`   `# Multiplying arrays` `result ``=` `ini_array1.ravel()`   `# printing result` `print``("New resulting array: ", result)`

Output:

```initial array [[1 2 3]
[2 4 5]
[1 2 3]]
New resulting array:  [1 2 3 2 4 5 1 2 3]```

Method #3: Using np.reshape()

## Python3

 `# Python code to demonstrate` `# flattening a 2d numpy array` `# into 1d array`   `import` `numpy as np`   `ini_array1 ``=` `np.array([[``1``, ``2``, ``3``], [``2``, ``4``, ``5``], [``1``, ``2``, ``3``]])`   `# printing initial arrays` `print``("initial array", ``str``(ini_array1))`   `# Multiplying arrays` `result ``=` `ini_array1.reshape([``1``, ``9``])`   `# printing result` `print``("New resulting array: ", result)`

Output:

```initial array [[1 2 3]
[2 4 5]
[1 2 3]]
New resulting array:  [[1 2 3 2 4 5 1 2 3]]```

Time Complexity: O(n), where n is the total number of elements in the 2D numpy array.
Auxiliary Space: O(n), as the program creates a new 1D list with the same number of elements as the original 2D array.

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