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numpy.full_like() in Python

Last Updated : 9 Mar, 2022

The numpy.full_like() function return a new array with the same shape and type as a given array.
Syntax : 
 

numpy.full_like(a, fill_value, dtype = None, order = 'K', subok = True)


Parameters : 

shape : Number of rows
order : C_contiguous or F_contiguous
dtype : [optional, float(by Default )] Data type of returned array. 
subok : [bool, optional] to make subclass of a or not


Returns : 

ndarray


 

Output : 
 

x before full_like : 
 [[0 1 2 3 4]
 [5 6 7 8 9]]

x after full_like : 
 [[10 10 10 10 10]
 [10 10 10 10 10]]


y before full_like : 
 [[0 1 2 3 4]
 [5 6 7 8 9]]

y after full_like : 
 [[ 0.01 0.01 0.01 0.01 0.01]
 [ 0.01 0.01 0.01 0.01 0.01]]


References : 
https://numpy.org/doc/stable/reference/generated/numpy.full_like.html#numpy.full_like 
Note : 
These codes won’t run on online IDE's. So please, run them on your systems to explore the working.
 

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