Python NumPy Array Slicing | Part 83
Python NumPy Array Slicing @arvindprogramming
To slice a Numpy array, you can use the following syntax:
```python
new_array = array_name[start_index:end_index:step]
```
where:
`array_name` is the name of the Numpy array you want to slice.
`start_index` is the index at which the slicing will start (inclusive).
`end_index` is the index at which the slicing will end (exclusive).
`step` is the number of steps to take between the start and end indices (optional).
Here are a few examples to demonstrate how to slice a Numpy array:
1. Slicing the entire array:
```python
import Numpy as np
array = np.array([1, 2, 3, 4, 5])
new_array = array[:]
print(new_array) # Output: [1, 2, 3, 4, 5]
```
2. Slicing a specific range:
```python
import Numpy as np
array = np.array([1, 2, 3, 4, 5])
new_array = array[1:4]
print(new_array) # Output: [2, 3, 4]
```
3. Slicing with a step:
```python
import Numpy as np
array = np.array([1, 2, 3, 4, 5])
new_array = array[::2]
print(new_array) # Output: [1, 3, 5]
```
Note that slicing Numpy arrays does not create a new copy of the array; instead, it creates a view that shares the same underlying data. Any modifications made to the sliced array will also affect the original array.
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