numpy.place() in Python Last Updated : 08 Mar, 2024 Comments Improve Suggest changes Like Article Like Report 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 # 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. Comment More infoAdvertise with us Next Article numpy.place() in Python M Mohit Gupta Improve Article Tags : Python Python-numpy Python numpy-Indexing Practice Tags : python Similar Reads numpy.put() in Python The numpy.put() function replaces specific elements of an array with given values of p_array. Array indexed works on flattened array. Syntax: numpy.put(array, indices, p_array, mode = 'raise') Parameters : array : array_like, target array indices : index of the values to be fetched p_array : array_l 1 min read in_place module in Python Sometimes, while working with Python files, we can have utility in which we wish to alter files without using system context or sys stdout. Such situation require reading/writing files inplace, i.e without using process resources. This can be achieved using the ein_place module in Python. This modul 3 min read Python NumPy Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.Besides its obvious scientific uses, Numpy can also be used as an efficient m 6 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read Python | numpy.putmask() method With the help of numpy.putmask() method, we can change the elements in an array with the help of condition and given value by using numpy.putmask() method. Syntax : numpy.putmask(array, condition, value) Return : Return the array having new elements according to value. Example #1 : In this example w 1 min read Like