numpy.place() in Python
Last Updated :
08 Mar, 2024
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
import numpy as geek
array = geek.arange( 12 ).reshape( 3 , 4 )
print ( "Original array : \n" , array)
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)
a = geek.place(array1, array1> 2 , [ 44 , 55 ])
print ( "\nPutting new elements to array1 : \n" , array1)
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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.
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