NumPy Array Slicing

The purpose of this article is to assist you in achieving your learning goals by introducing Numpy array slicing and presenting examples.

Table Of Content-

NumPy Array Slicing:

Slicing NumPy arrays

Numpy array slicing in Python is moving data from one index to another index.

In place of an index, we provide a slice: [start:end].

It is also possible to define the step as follows: [start:end:step].

In the absence of a start, it is assumed to be zero.

It is assumed the length of the array in that dimension if the limit is not specified.

It’s counted as 1 if we don’t complete step

From the below array, slice items from index 1 to index 6:

Numpy Array Slicing Example: 1

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[1:8])
print(type(prime_arr))
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Numpy array slicing examples

Numpy Array Slicing Example: 2

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[1:6])
print(type(silent_arr))
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Reminder: In the outcome, the beginning index is kept, but the last index is not kept.

From index 3 to the tail of the array, slice the items as follows:

Numpy Array Slicing Example: 3

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[3:])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Numpy Array Slicing Example: 4

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[3:])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

When slicing through a Numpy array, you can extract items from the start up to (but not including) index 6.

Numpy Array Slicing Example: 5

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[:6])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Numpy Array Slicing Example: 6

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[:6])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Numpy array slicing output

Negative Array Slice

In Numpy array slicing, utilizing a negative index indicates starting from the last:

Slice from index -7 to index -4.

NumPy Array Negative Slicing Example: 1

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[-7:-4])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

NumPy Array Negative Slicing Example: 2

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[-7:-4])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Python NumPy STEP

The step value is utilized to decide the interval of the slicing.

From index 1 to index 7, the following items have an increment of 2:

Python NumPy STEP Example: 1

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[1:7:2])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Python NumPy STEP Example: 2

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[1:7:2])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Provide all items with an increment of two from the whole array:

Python NumPy STEP Example: 3

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import numpy as npy
prime_arr = npy.array([2, 3, 5, 7, 11, 13, 17, 19])
print(prime_arr[::2])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Python NumPy STEP Example: 4

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import numpy as npy
silent_arr = npy.array(["align", "bridge", "design", "edge", "anchor", "muscle", "echo", "doubt"])
print(silent_arr[::2])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Slice 2-D Arrays

Take items index 2 to index 4 from the first array:

Example: 1

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import numpy as npy
mrx_arr = npy.array([[2,4,6,8,10], [1,3,5,7,9]])
print(mrx_arr[0, 2:5])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Example: 2

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import numpy as npy
mrx_arr = npy.array([["Major League Soccer","Premier League","La Liga","Serie A","Süper Lig"], ["Bundesliga","Ligue 1","Primeira Liga","Eredivise:","Scottish Premiership"]])
print(mrx_arr[0, 2:5])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Reminder: Keep in mind that the second item has an index of 1.

Display the 5th item from both arrays:

Example: 3

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import numpy as npy
mrx_arr = npy.array([[2,4,6,8,10], [1,3,5,7,9]])
print(mrx_arr[0:2, 4])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Example: 4

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import numpy as npy
mrx_arr = npy.array([["Major League Soccer","Premier League","La Liga","Serie A","Süper Lig"], ["Bundesliga","Ligue 1","Primeira Liga","Eredivise:","Scottish Premiership"]])
print(mrx_arr[0:2, 4])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Take items from index 2 to 4 of two arrays to obtain a two-dimensional array:

Example: 5

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import numpy as npy
mrx_arr = npy.array([[2,4,6,8,10], [1,3,5,7,9]])
print(mrx_arr[0:2, 2:5])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Example: 6

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import numpy as npy
mrx_arr = npy.array([["Major League Soccer","Premier League","La Liga","Serie A","Süper Lig"], ["Bundesliga","Ligue 1","Primeira Liga","Eredivise:","Scottish Premiership"]])
print(mrx_arr[0:2, 2:5])
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

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