numpy.place() in Python

numpy.place(array, mask, vals) : make 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().

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

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]]

References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.place.html#numpy.place

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.