Numpy MaskedArray.anom() function | Python Last Updated : 30 Nov, 2022 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.anom() function Compute the anomalies (deviations from the arithmetic mean) along the given axis.It returns an array of anomalies, with the same shape as the input and where the arithmetic mean is computed along the given axis. Syntax : numpy.MaskedArray.anom(axis=None, dtype=None) Parameters: axis : [int or None] Axis over which the anomalies are taken. dtype : [ dtype, optional] Type to use in computing the variance. Return : [ndarray]an array of anomalies. Code #1 : Python3 # Python program explaining # numpy.MaskedArray.anom() 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, 5]) print ("Input array : ", in_arr) # Now we are creating a masked array # by making third entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[0, 0, 1, 0, 0]) print ("Masked array : ", mask_arr) # applying MaskedArray.anom methods to mask array out_arr = mask_arr.anom() print ("Output anomalies array : ", out_arr) Output: Input array : [ 1 2 3 -1 5] Masked array : [1 2 -- -1 5] Output anomalies array : [-0.75 0.25 -- -2.75 3.25] Code #2 : Python3 # Python program explaining # numpy.MaskedArray.anom() 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([10, 20, 30, 40, 50]) print ("Input array : ", in_arr) # Now we are creating a masked array by making # first and third entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[1, 0, 1, 0, 0]) print ("Masked array : ", mask_arr) # applying MaskedArray.anom methods to mask array out_arr = mask_arr.anom() print ("Output anomalies array : ", out_arr) Output: input array : [10 20 30 40 50] Masked array : [-- 20 -- 40 50] Output anomalies array : [-- -16.666666666666664 -- 3.3333333333333357 13.333333333333336] 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