Numpy MaskedArray.masked_where() function | Python Last Updated : 27 Sep, 2019 Comments Improve Suggest changes Like Article Like Report In many circumstances, datasets can be incomplete or tainted by the presence of invalid data. For example, a sensor may have failed to record a data, or recorded an invalid value. The numpy.ma module provides a convenient way to address this issue, by introducing masked arrays.Masked arrays are arrays that may have missing or invalid entries. numpy.MaskedArray.masked_where() function is used to mask an array where a condition is met.It return arr as an array masked where condition is True. Any masked values of arr or condition are also masked in the output. Syntax : numpy.ma.masked_where(condition, arr, copy=True) Parameters: condition : [array_like] Masking condition. When condition tests floating point values for equality, consider using masked_values instead. arr : [ndarray] Input array which we want to mask. copy : [bool] If True (default) make a copy of arr in the result. If False modify arr in place and return a view. Return : [ MaskedArray] The result of masking arr where condition is True.. Code #1 : Python3 # Python program explaining # numpy.MaskedArray.masked_where() 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([1, 2, 3, -1, 2]) print ("Input array : ", in_arr) # applying MaskedArray.masked_where methods # to input array where value<= 1 mask_arr = ma.masked_where(in_arr<= 1, in_arr) print ("Masked array : ", mask_arr) Output: Input array : [ 1 2 3 -1 2] Masked array : [-- 2 3 -- 2] Code #2 : Python3 # Python program explaining # numpy.MaskedArray.masked_where() method # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma # creating input array in_arr1 in_arr1 = geek.arange(4) print ("1st Input array : ", in_arr1) # applying MaskedArray.masked_where methods # to input array in_arr1 where value = 1 mask_arr1 = ma.masked_where(in_arr1 == 1, in_arr1) print ("1st Masked array : ", mask_arr1) # creating input array in_arr2 in_arr2 = geek.arange(4) print ("2nd Input array : ", in_arr2) # applying MaskedArray.masked_where methods # to input array in_arr2 where value = 1 mask_arr2 = ma.masked_where(in_arr2 == 3, in_arr2) print ("2nd Masked array : ", mask_arr2) # applying MaskedArray.masked_where methods # to 1st masked array where second masked array # is used as condition res_arr = ma.masked_where(mask_arr1 == 3, mask_arr2) print("Resultant Masked array : ", res_arr) Output: 1st Input array : [0 1 2 3] 1st Masked array : [0 -- 2 3] 2nd Input array : [0 1 2 3] 2nd Masked array : [0 1 2 --] Resultant Masked array : [0 -- 2 --] Create Quiz Comment J jana_sayantan Follow 0 Improve J jana_sayantan Follow 0 Improve Article Tags : Python Python-numpy 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