Numpy MaskedArray.resize() function | Python Last Updated : 03 Oct, 2019 Comments Improve Suggest changes Like Article Like Report numpy.MaskedArray.resize() function is used to a make a new masked array with the specified size and shape from the given array.The new array is filled with repeated copies of arr (in the order that the data are stored in memory). If arr is masked, the new array will be masked, and the new mask will be a repetition of the old one. Syntax : numpy.ma.resize(arr, new_shape) Parameters: arr: The input array which to be resized. new_shape:[ int or tuple of ints] The new shape of resized array. Return : [ resized_array] A new shape of the array. Code #1 : Python3 # Python program explaining # numpy.MaskedArray.resize() method # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma # creating input array of 2 * 2 in_arr = geek.array([[10, 20], [-10, 40]]) print ("Input array : ", in_arr) # Now we are creating a masked array. # by making one entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[[ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr) # applying MaskedArray.resize methods to make # it a 3 * 3 masked array out_arr = ma.resize(mask_arr, (3, 3)) print ("Output resized masked array : ", out_arr) Output: Input array : [[ 10 20] [-10 40]] Masked array : [[-- 20] [-10 40]] Output resized masked array : [[-- 20 -10] [40 -- 20] [-10 40 --]] Code #2 : Python3 # Python program explaining # numpy.MaskedArray.resize() method # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma # creating input array in_arr = geek.array([[[ 2e8, 3e-5]], [[ -4e-6, 2e5]]]) print ("Input array : ", in_arr) # Now we are creating a masked array. # by making one entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[[[ 1, 0]], [[ 0, 0]]]) print ("Masked array : ", mask_arr) # applying MaskedArray.resize methods to make # it a 1 * 6 masked array out_arr = ma.resize(mask_arr, (1, 6)) print ("Output resized masked array : ", out_arr) Output: Input array : [[[ 2.e+08 3.e-05]] [[-4.e-06 2.e+05]]] Masked array : [[[-- 3e-05]] [[-4e-06 200000.0]]] Output resized masked array : [[-- 3e-05 -4e-06 200000.0 -- 3e-05]] ? Create Quiz Comment J jana_sayantan Follow 0 Improve J jana_sayantan Follow 0 Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Explore Python FundamentalsPython Introduction 2 min read Input and Output in Python 4 min read Python Variables 4 min read Python Operators 4 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 5 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 3 min read Python MySQL 9 min read Python Packages 10 min read Python Modules 3 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 4 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 3 min read StatsModel Library - Tutorial 3 min read Learning Model Building in Scikit-learn 6 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 6 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 5 min read Build a REST API using Flask - Python 3 min read Building a Simple API with Django REST Framework 3 min read Python PracticePython Quiz 1 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like