29 Mar NumPy – Array Slicing
Slicing the array in a range from start to end is what we call Array Slicing. Slice (range) is passed in place of index i.e.
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n[1:3] |
The above will slice two elements from index 1 to index 3 because it includes the start index, but excludes the end index.
The following is the syntax to slice NumPy arrays:
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arr[start:end] |
Here, the start is the beginning index (include), and the end is the last index (excluded)
Slicing Examples
The following Array Slicing examples we will run:
- Slicing from index 1 to 3 (3 is excluded)
- Slicing from index 2 to 5 (5 is excluded)
- Slicing from index 5 to last
- Slicing from the beginning to index 5 (5 is excluded)
Example: Slicing from index 1 to 3 (3 is excluded)
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import numpy as np n = np.array([20, 25, 30, 35, 40, 45, 50, 55, 60, 65]) print(n[1:3]) |
Output
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[25 30] |
Example: Slicing from index 2 to 5 (5 is excluded)
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import numpy as np n = np.array([20, 25, 30, 35, 40, 45, 50, 55, 60, 65]) print(n[2:5]) |
Output
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[30 35 40] |
Example: Slicing from index 5 to last
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import numpy as np n = np.array([20, 25, 30, 35, 40, 45, 50, 55, 60, 65]) print(n[5:]) |
Output
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[45 50 55 60, 65] |
Example: Slicing from beginning to index 5 (5 is excluded)
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import numpy as np n = np.array([20, 25, 30, 35, 40, 45, 50, 55, 60, 65]) print(n[:5]) |
Output
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[20 25 30 35 40] |
Slice 1D arrays with STEP
We can also include steps while slicing. Step means a jump of elements. If the step is 2, that means 2 jumps for the next element.
Syntax
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arr[start:end:step} |
Example
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import numpy as np n = np.array([5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60]) print(n[1:10:2]) |
Output
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[10 20 30 40 50] |
Slicing 2D arrays with STEP
The following are the examples of slicing Two-Dimensional arrays with steps:
Example: Slicing from index 2 to 5 (excluding 5)
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import numpy as np n = np.array([[10,30,50,70,90,95],[4,8,12,14,16,18]]) print(n[0,2:5]) |
Output
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[50 70 90] |
Example: Slicing for both the dimensions with step
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import numpy as np n = np.array([[10, 30, 50, 70, 90, 95], [4, 8, 12, 14, 16, 18]]) print(n[0:2, 2:5]) |
Output
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[[50 70 90] [12 14 16]] |
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