Course Content
NumPy in a Nutshell
NumPy in a Nutshell
Negative Indexing
We discussed positive indexing, but there is also negative indexing. Negative indexing starts from the end, with index -1 referring to the last element, index -2 referring to the second-to-last element, and so on.
import numpy as np arr = np.array([[1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]) print(arr[-1 , -1])
This example illustrates how to retrieve a value of 10 from a given two-dimensional array using negative indexing.
The first index determines the row we choose (-1 refers to the last row), while the second index corresponds to the element we select within that row (-1 is the last one). As a result, we obtain a value of 10. Run the code above to verify it.
Swipe to show code editor
You have the following array:
[[-4, 3, 1], [2, 10, -4]]. Access the value 10.
Let's give it a try. Use only negative indices.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
Negative Indexing
We discussed positive indexing, but there is also negative indexing. Negative indexing starts from the end, with index -1 referring to the last element, index -2 referring to the second-to-last element, and so on.
import numpy as np arr = np.array([[1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]) print(arr[-1 , -1])
This example illustrates how to retrieve a value of 10 from a given two-dimensional array using negative indexing.
The first index determines the row we choose (-1 refers to the last row), while the second index corresponds to the element we select within that row (-1 is the last one). As a result, we obtain a value of 10. Run the code above to verify it.
Swipe to show code editor
You have the following array:
[[-4, 3, 1], [2, 10, -4]]. Access the value 10.
Let's give it a try. Use only negative indices.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
Negative Indexing
We discussed positive indexing, but there is also negative indexing. Negative indexing starts from the end, with index -1 referring to the last element, index -2 referring to the second-to-last element, and so on.
import numpy as np arr = np.array([[1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]) print(arr[-1 , -1])
This example illustrates how to retrieve a value of 10 from a given two-dimensional array using negative indexing.
The first index determines the row we choose (-1 refers to the last row), while the second index corresponds to the element we select within that row (-1 is the last one). As a result, we obtain a value of 10. Run the code above to verify it.
Swipe to show code editor
You have the following array:
[[-4, 3, 1], [2, 10, -4]]. Access the value 10.
Let's give it a try. Use only negative indices.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
We discussed positive indexing, but there is also negative indexing. Negative indexing starts from the end, with index -1 referring to the last element, index -2 referring to the second-to-last element, and so on.
import numpy as np arr = np.array([[1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]) print(arr[-1 , -1])
This example illustrates how to retrieve a value of 10 from a given two-dimensional array using negative indexing.
The first index determines the row we choose (-1 refers to the last row), while the second index corresponds to the element we select within that row (-1 is the last one). As a result, we obtain a value of 10. Run the code above to verify it.
Swipe to show code editor
You have the following array:
[[-4, 3, 1], [2, 10, -4]]. Access the value 10.
Let's give it a try. Use only negative indices.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowSwitch to desktop for real-world practiceContinue from where you are using one of the options below