- 1-D:
arr[0],arr[-1], slicearr[1:4], steparr[::2] - 2-D:
m[row, col], a whole rowm[0], a whole columnm[:, 1]
A slice is a view: changing it changes the original array. Use
.copy() for an independent copy.NumPy Indexing & Slicing
Access elements, rows and columns.
✍️ 3 exercises + code challenge in this lessonKey Takeaways: NumPy Indexing & Slicing
Mastering NumPy Indexing & Slicing helps you write clean and reliable NumPy code. Follow standard conventions, test edge cases, and keep logic simple. Try running the code example below and complete the exercises to build confidence.
NumPy Indexing & Slicing Code Example
NumPyimport numpy as np
arr = np.array([10, 20, 30, 40, 50])
print(arr[0], arr[-1])
print(arr[1:4])
print(arr[::2])
m = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(m[1, 2])
print(m[:, 0])Output
10 50 [20 30 40] [10 30 50] 6 [1 4 7]
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NumPy Indexing & Slicing Practice Exercises
Check what you learned in “NumPy Indexing & Slicing”.
/ 3 solved
Fill in the blank
Select the whole second column of a 2-D array.
col = m[:, ]
✓ Correct!
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Multiple choice
What is a NumPy slice?
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Code challenge
Print the last element of arr using a negative index.
Write the code in the live editor. Your answer is checked automatically.
✓ Solved
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