How to Index a NumPy Array: Syntax and Examples

You can index a numpy array using square brackets [] with integers, slices, or boolean arrays. For example, arr[0] accesses the first element, and arr[1:4] accesses a slice from index 1 to 3.

Syntax

Indexing a NumPy array uses square brackets []. Inside the brackets, you can use:

• Integer index: Access a single element by its position.
• Slice: Access a range of elements using start:stop:step.
• Boolean array: Select elements where the condition is True.
• Multiple indices: Use commas to index multi-dimensional arrays.

python

import numpy as np

arr = np.array([10, 20, 30, 40, 50])

# Integer index
print(arr[0])  # First element

# Slice
print(arr[1:4])  # Elements from index 1 to 3

# Boolean indexing
print(arr[arr > 25])  # Elements greater than 25

# Multi-dimensional indexing
arr2d = np.array([[1, 2], [3, 4]])
print(arr2d[1, 0])  # Element at row 1, column 0

Output

10
[20 30 40]
[30 40 50]
3

Example

This example shows how to access elements in a 1D and 2D NumPy array using different indexing methods.

python

import numpy as np

# Create a 1D array
arr = np.array([5, 10, 15, 20, 25])

# Access single element
first = arr[0]

# Access slice
slice_part = arr[2:5]

# Boolean indexing
filtered = arr[arr >= 15]

# Create a 2D array
arr2d = np.array([[1, 2, 3], [4, 5, 6]])

# Access element at row 0, column 2
element_2d = arr2d[0, 2]

print("First element:", first)
print("Slice from index 2 to 4:", slice_part)
print("Elements >= 15:", filtered)
print("Element at row 0, col 2:", element_2d)

Output

First element: 5
Slice from index 2 to 4: [15 20 25]
Elements >= 15: [15 20 25]
Element at row 0, col 2: 3

Common Pitfalls

Common mistakes when indexing NumPy arrays include:

• Using parentheses () instead of square brackets [].
• Confusing Python list indexing with NumPy slicing (NumPy slices return views, not copies).
• Trying to use multiple indices without commas for multi-dimensional arrays.
• Using out-of-range indices causing IndexError.

python

import numpy as np

arr = np.array([1, 2, 3, 4, 5])

# Wrong: using parentheses
# print(arr(0))  # This raises TypeError

# Correct:
print(arr[0])  # Outputs 1

# Wrong: missing comma in 2D indexing
arr2d = np.array([[1, 2], [3, 4]])
# print(arr2d[1 0])  # SyntaxError

# Correct:
print(arr2d[1, 0])  # Outputs 3

Output

1
3

Quick Reference

Indexing Type	Syntax Example	Description
Integer	arr[2]	Access single element at index 2
Slice	arr[1:4]	Access elements from index 1 to 3
Boolean	arr[arr > 10]	Access elements where condition is True
Multi-dimensional	arr2d[0, 1]	Access element at row 0, column 1

Key Takeaways

Use square brackets [] with integers, slices, or boolean arrays to index NumPy arrays.

Multi-dimensional arrays require commas to separate indices for each dimension.

Slices return views, so modifying them changes the original array.

Avoid using parentheses () for indexing; it causes errors.

Check index ranges to prevent IndexError exceptions.