numpy.repeat() in Python

About :
numpy.repeat(arr, repetitions, axis = None) : repeat elements of the array – arr.

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 :

filter_none

edit
close

play_arrow

link
brightness_4
code

# 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)

chevron_right


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 :

filter_none

edit
close

play_arrow

link
brightness_4
code

# 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)

chevron_right


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 😀. 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.

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.



My Personal Notes arrow_drop_up