Lecture

Indexing and Slicing Arrays

After creating an array, you’ll often need to access individual elements or extract specific sections.

This process is called indexing and slicing.


Indexing

Indexing retrieves individual items based on their position.

Like Python lists, NumPy arrays use zero-based indexing — the first element is at position 0.

Indexing a 1D Array
arr = np.array([10, 20, 30, 40]) print(arr[1]) # Output: 20

For 2D arrays, use two indices: arr[row, column].

Indexing a 2D Array
matrix = np.array([[1, 2], [3, 4]]) print(matrix[1, 0]) # Output: 3

Slicing

Slicing allows you to select a range of elements using the : operator.

Slicing a 1D Array
arr = np.array([10, 20, 30, 40, 50]) print(arr[1:4]) # Output: [20 30 40]

You can also slice rows or columns in 2D arrays.

Slicing a 2D Array
matrix = np.array([[1, 2, 3], [4, 5, 6]]) print(matrix[:, 1]) # Output: [2 5]
Quiz
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How do you slice a 2D NumPy array to access a specific column?

To slice the second column of a 2D NumPy array, use the syntax: matrix[:, ]
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