Array Indexing
Accessing individual elements and rows/columns by position
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Explanation
NumPy indexing works like Python lists for 1D, and extends naturally to multiple dimensions.
1D indexing:
python a = np.array([10, 20, 30, 40, 50]) a[0] # 10 (first) a[-1] # 50 (last) a[-2] # 40 (second to last)
2D indexing — [row, col]:
```python m = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
m[0, 0] # 1 (top-left) m[1, 2] # 6 (row 1, col 2) m[-1, -1] # 9 (bottom-right)
m[0] # [1, 2, 3] (entire first row) m[:, 1] # [2, 5, 8] (entire second column) ```
Examples
Row and column access
The colon : means "all" for that dimension
import numpy as np
m = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(m[1, 2]) # 6
print(m[2]) # [7 8 9] — row 2
print(m[:, 0]) # [1 4 7] — col 0
print(m[-1, -1]) # 9Next in NumPy
Array Slicing