How do I add an extra column to a NumPy array using `np.c_[...]`?

Adding an Extra Column to a NumPy Array

NumPy, a powerful library for scientific computing in Python, provides a range of methods to manipulate multidimensional data. Among these is the task of adding an extra column to an array. Let's explore how to achieve this using specialized NumPy functions that offer a convenient and efficient way to extend the dimensions of your arrays.

Using np.r_[...] and np.c_[...]

For adding an extra column to a 2D array, two useful NumPy functions are np.r_[...] (for adding rows) and np.c_[...] (for adding columns). Unlike np.vstack and np.hstack, these functions use square brackets [] instead of parentheses ().

Consider the following 2D array:

<code class="python">import numpy as np

a = np.array([
    [1, 2, 3],
    [2, 3, 4],
])</code>

To add a column of zeros along the second axis, using np.c_[...]:

<code class="python">b = np.c_[a, np.zeros(a.shape[0])]</code>

This results in the desired output:

<code class="python">b = np.array([
    [1, 2, 3, 0],
    [2, 3, 4, 0],
])</code>

Additional Examples

np.r_[...] and np.c_[...] offer versatility in adding rows/columns to arrays. Here are some further examples:

<code class="python">N = 3
A = np.eye(N)

# Add a column
np.c_[A, np.ones(N)]

# Add two columns
np.c_[np.ones(N), A, np.ones(N)]

# Add a row
np.r_[A, [A[1]]]

# Mix vectors and scalars
np.r_[A[0], 1, 2, 3, A[1]]

# Use lists or tuples
np.r_[A[0], [1, 2, 3], A[1]]
np.r_[A[0], (1, 2, 3), A[1]]

# Use Python slice syntax
np.r_[A[0], 1:4, A[1]]</code>

Understanding Square Brackets vs. Round Parentheses

It's important to note that np.r_[...] and np.c_[...] use square brackets, while np.vstack and np.hstack use round parentheses. This is because Python interprets 1:4 as a slice object when used within square brackets. This slice object represents the values 1, 2, and 3, which are then added to the array.

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