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numpy.repeat () in Python

Parameters :

  array:  [array_like] Input array.  repetitions:  No. of repetitions of each array elements along the given axis.  axis:  Axis along which we want to repeat values. By default, it returns a flat output array. 

Return:

 An array with repetitions of array - arr elements as per repetitions, number of times we want to repeat arr 

Code 1:

# Python program illustrating
# numpy.repeat ()

 

import numpy as geek

 
# 1D

arr = geek.arange ( 5 )

print ( "arr:" , arr)

 

repetitions = 2

a = geek.repeat (arr, repetitions)

print ( "Repeating arr 2 times:" , a)

print ( "Shape:" , a.shape)

 

repetitions = 3

a = geek.repeat (arr, repetitions)

print ( "Repeating arr 3 times:" , a)

# [0 0 0 ..., 4 4 4] means [0 0 0 1 1 1 2 2 2 3 3 3 4 4 4]
# since it was long output, so it uses [...]

print ( "Shape:" , a.shape)

Output:

 arr: [0 1 2 3 4] Repeating arr 2 times: [0 0 1 1 2 2 3 3 4 4] Shape: (10,) Repeating arr 3 times: [0 0 0 ..., 4 4 4] Shape: (15,) 

Code 2:

# Python program illustrating
# numpy.repeat ()

 

import numpy as geek

 

arr = geek.arange ( 6 ). reshape ( 2 , 3 )

print ( " arr: " , arr)

  

repetitions = 2

print ( "Repeating arr:" , geek.repeat (arr, repetitions, 1 ))

print ( "arr Shape:" , geek. repeat (arr, repetitions) .shape)

  

 

repetitions = 2

print ( "Repeating arr:" , geek.repeat (arr, repetitions, 0 ))

print ( "arr Shape:" , geek.repeat (arr, repetitions) .shape)

 

repetitions = 3

print ( "Repeating arr: " , geek.repeat (arr, repetitions, 1 ))

print ( "arr Shape:" , geek.repeat (arr, repetitions) .shape)

Output:

 arr: [[0 1 2] [3 4 5]] Repeating arr: [[0 0 1 1 2 2] [3 3 4 4 5 5]] arr Shape: (12,) Repeating arr: [[ 0 1 2] [0 1 2] [3 4 5] [3 4 5]] arr Shape: (12,) Repeating arr: [[0 0 0 ..., 2 2 2] [3 3 3 ... , 5 5 5]] arr Shape: (18,) 

Links:
https://docs.scipy.org/doc/numpy/reference/generated/numpy.repeat.html

Notes:
These codes will not work for online IDs. Please run them on your systems to see how they work

This article is provided by Mohit Gupta_OMG

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