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numpy.repeat() in Python

  • Last Updated : 23 Oct, 2020

The numpy.repeat() function repeats elements of the array – arr.
Syntax :

numpy.repeat(arr, repetitions, axis = None)

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
  
#Working on 1D
arr = geek.arange(5)
print("arr : \n", arr)
  
repetitions = 2
a = geek.repeat(arr, repetitions)
print("\nRepeating arr 2 times : \n", a)
print("Shape : ", a.shape)
  
repetitions = 3
a = geek.repeat(arr, repetitions)
print("\nRepeating arr 3 times : \n", 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 : \n", arr)
  
repetitions = 2
print("\nRepeating arr : \n", geek.repeat(arr, repetitions, 1))
print("arr Shape : \n", geek.repeat(arr, repetitions).shape)
  
  
repetitions = 2
print("\nRepeating arr : \n", geek.repeat(arr, repetitions, 0))
print("arr Shape : \n", geek.repeat(arr, repetitions).shape)
     
repetitions = 3
print("\nRepeating arr : \n", geek.repeat(arr, repetitions, 1))
print("arr Shape : \n", 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,)

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

Note :
These codes won’t run on online-ID. Please run them on your systems to explore the working
.
This article is contributed by Mohit Gupta_OMG πŸ˜€. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

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