numpy.place() in Python

The numpy.place() method makes changes in the array according the parameters - conditions and value(uses first N-values to put into array as per the mask being set by the user). It works opposite to numpy.extract(). 
 

Syntax:  

numpy.place(array, mask, vals) 

Parameters : 

array : [ndarray] Input array, we need to make changes into mask : [array_like]Boolean that must have same size as that of the input array value : Values to put into the array. Based on the mask condition it adds only N-elements to the array. If in case values in val are smaller than the mask, same values get repeated.

Return : 

Array with change elements i.e. new elements being put

# Python Program illustrating # numpy.place() method import numpy as geek array = geek.arange(12).reshape(3, 4) print("Original array : \n", array) # Putting new elements a = geek.place(array, array > 5, [15, 25, 35]) print("\nPutting up elements to array: \n", array) array1 = geek.arange(6).reshape(2, 3) print("\n\nOriginal array1 : \n", array) # Putting new elements a = geek.place(array1, array1>2, [44, 55]) print("\nPutting new elements to array1 : \n", array1) 

Output : 

Original array : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Putting up elements to array: [[ 0 1 2 3] [ 4 5 15 25] [35 15 25 35]] Original array1 : [[ 0 1 2 3] [ 4 5 15 25] [35 15 25 35]] Putting new elements to array1 : [[ 0 1 2] [44 55 44]]

Note : 
These codes won't run on online IDE's. So please, run them on your systems to explore the working.