Flatten in NumPy
Convert Multidimensional to 1D Array

What is flatten() in NumPy?

In NumPy, flatten() is a method used to transform a multi-dimensional array into a one-dimensional array. It's especially useful when you need a flat sequence of values from a matrix or tensor-like structure, such as when feeding data into machine learning models or simplifying output for reporting.

When should you use flatten()?

Use flatten() when you want to create a copy of your array data in one dimension. This is helpful when you’re doing operations that should not affect the original array or when reshaping is not an option due to inconsistent dimensions.

Basic Syntax

flattened_array = original_array.flatten()

The method returns a new 1D array with all the elements of the input array.

Example: Flattening a 2D Array

import numpy as np

matrix = np.array([[1, 2], [3, 4], [5, 6]])
flat = matrix.flatten()
print("Original:
", matrix)
print("Flattened:", flat)

Output Explanation

Original:
 [[1 2]
  [3 4]
  [5 6]]
Flattened: [1 2 3 4 5 6]

Here, the original array has a shape of (3, 2). After using flatten(), we get a 1D array with shape (6,). Importantly, flatten() returns a copy, not a view.

Check: Is the Result a View or a Copy?

flat[0] = 99
print("Modified Flattened:", flat)
print("Original After Modification:
", matrix)

Output

Modified Flattened: [99  2  3  4  5  6]
Original After Modification:
 [[1 2]
  [3 4]
  [5 6]]

As you can see, the original matrix remains unchanged. This confirms that flatten() creates a separate copy in memory.

Common Pitfall: Using flatten() When Memory Efficiency Matters

Since flatten() always returns a copy, it consumes extra memory. If your array is large and you don’t need to keep the original intact, consider using ravel() instead—it returns a view when possible.

Best Practice

• Use flatten() when you need an independent, one-dimensional copy of the array.
• Use ravel() when you are memory-conscious and can work with views.
• Double-check the shape before and after flattening to verify results, especially when chaining array transformations.

Summary

The flatten() method in NumPy is a straightforward yet powerful tool for transforming arrays into 1D formats. Whether you’re preprocessing data or simplifying structures for output, it provides a clean, safe way to flatten arrays without altering the source. Just remember—you're working with a copy, not a view.

Quick Recap

• Method: arr.flatten()
• Returns: 1D array (copy)
• Does it affect original? No
• Use Case: When you need a flat copy of array data