Python Data Science NumPy Array Slicing

Slicing Arrays: slicing in python means taking elements from one given index to another given index.

We pass slice instead of index like this: [start:end].

We can also define the step, like this: [start:end:step].

If we don't pass start its considered 0.

If we don't pass end its considered length of array in that dimension.

If we don't pass step its considered 1.

Example 1: Slice elements from index 1 to index 5 from the following array.

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[1:5])

the output will be

[12 13 14 15]

Note: The result includes the start index, but excludes the end index.

Example 2: Slice elements from index 4 to the end of the array.

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[4:])

the output will be

[15 16 17]

Example 3: Slice elements from the beginning to index 4 (not included).

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[:4])

the output will be

[11 12 13 14]

Negative Slicing

In negative slicing the minus operator is used to refer to an index from the end.

Example 4: Slice from the index 3 from the end to index 1 from the end.

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[-3:-1])

the output will be

[15 16]

STEP: Use the step value to determine the step of the slicing.

Example 5: Return every other element from index 1 to index 5.

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[1:5:2])

the output will be

[12 14]

Example 6: Return every other element from the entire array.

Code

import numpy as np

arr = np.array([11, 12, 13, 14, 15, 16, 17])

print(arr[::2])

the output will be

[11 13 15 17]

Slicing 2-D Arrays

Example 7: From the second element, slice elements from index 1 to index 4 (not included).

Code

import numpy as np

arr = np.array([[11, 12, 13, 14, 15], [16, 17, 18, 19, 20]])

print(arr[1, 1:4])

the output will be

[17 18 19]

Note: Remember that second element has index 1.

Example 8: From both elements, return index 2.

Code

import numpy as np

arr = np.array([[11, 12, 13, 14, 15], [16, 17, 18, 19, 20]])

print(arr[0:2, 2])

the output will be

[13 18]

Example 9: From both elements, slice index 1 to index 4 (not included), this will return a 2-D array.

Code

import numpy as np

arr = np.array([[11, 12, 13, 14, 15], [16, 17, 18, 19, 20]])

print(arr[0:2, 1:4])

the output will be

   [[12 13 14]
 [17 18 19]]