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Numpy Append

Numpy Append

Numpy is a fundamental package for scientific computing in Python. It provides a high-performance multidimensional array object, and tools for working with these arrays. One of the common operations when working with arrays is appending elements or arrays to an existing array. This article will provide a comprehensive guide on how to use the numpy.append() function, along with detailed examples.

Introduction to Numpy Append

The numpy.append() function is used to append values to the end of a given array. It returns a new array and does not modify the original array. The syntax of the numpy.append() function is as follows:

numpy.append(arr, values, axis=None)
  • arr: This is the array to which values are appended.
  • values: These are the values to be appended. This can be a scalar, list, or another array.
  • axis: This is the axis along which the values are appended. If axis is not specified, both arr and values are flattened before use.

Examples of Numpy Append

Example 1: Appending Scalars to a One-Dimensional Array

import numpy as np

arr = np.array([1, 2, 3])
values = 4
result = np.append(arr, values)
print(result)

Output:

Numpy Append

Example 2: Appending a List to a One-Dimensional Array

import numpy as np

arr = np.array([1, 2, 3])
values = [4, 5, 6]
result = np.append(arr, values)
print(result)

Output:

Numpy Append

Example 3: Appending an Array to Another Array

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
result = np.append(arr1, arr2)
print(result)

Output:

Numpy Append

Example 4: Appending with Axis Specified (2D Arrays)

import numpy as np

arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6]])
result = np.append(arr1, arr2, axis=0)
print(result)

Output:

Numpy Append

Example 5: Flattening and Appending Arrays

import numpy as np

arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6], [7, 8]])
result = np.append(arr1, arr2)
print(result)

Output:

Numpy Append

Example 6: Appending Arrays with Different Dimensions

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([[4, 5, 6], [7, 8, 9]])
result = np.append(arr1, arr2, axis=0)
print(result)

Example 7: Using Append in a Loop

import numpy as np

arr = np.array([1, 2, 3])
for i in range(4, 7):
    arr = np.append(arr, i)
print(arr)

Output:

Numpy Append

Example 8: Appending Multiple Arrays at Once

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
arr3 = np.array([7, 8, 9])
result = np.append(np.append(arr1, arr2), arr3)
print(result)

Output:

Numpy Append

Example 9: Appending Arrays with Different Shapes Using Axis

import numpy as np

arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([5, 6])
result = np.append(arr1, arr2.reshape(1, 2), axis=0)
print(result)

Output:

Numpy Append

Numpy Append Conclusion

The numpy.append() function is a versatile tool for adding elements to numpy arrays. Whether you’re working with one-dimensional or multi-dimensional arrays, understanding how to use numpy.append() effectively can help you manipulate array data more efficiently. The examples provided in this article illustrate various ways to use the numpy.append() function in different scenarios, making it easier to integrate into your data processing workflows.

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