Numpy MaskedArray.maximum_fill_value() function | Python Last Updated : 29 Oct, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report numpy.MaskedArray.maximum_fill_value() function is used to return the minimum value that can be represented by the dtype of an object. Syntax : numpy.ma.maximum_fill_value(obj) Parameters: obj :[ ndarray, dtype or scalar ] The array data-type or scalar for which the minimum fill value is returned. Return : [ scalar ] The minimum fill value. Code #1 : Python3 # Python program explaining # numpy.MaskedArray.maximum_fill_value() 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, 3, 5, -3], dtype ='float') print ("Input array : ", in_arr) # Now we are creating a masked array. # by making entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[1, 0, 0, 0]) print ("Masked array : ", mask_arr) # applying MaskedArray.maximum_fill_value # methods to masked array out_val = ma.maximum_fill_value(mask_arr) print ("Minimum filled value : ", out_val) Output: Input array : [ 1. 3. 5. -3.] Masked array : [-- 3.0 5.0 -3.0] Minimum filled value : -inf Code #2 : Python3 # Python program explaining # numpy.MaskedArray.maximum_fill_value() 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, -3]]) print ("Input array : ", in_arr) # Now we are creating a masked array. # by making entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr) # applying MaskedArray.maximum_fill_value # methods to masked array out_val = ma.maximum_fill_value(mask_arr) print ("Minimum filled value : ", out_val) Output: Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] Minimum filled value : -2147483648 Comment More infoAdvertise with us Next Article Numpy MaskedArray.minimum_fill_value() function | Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads Numpy MaskedArray.minimum_fill_value() function | Python numpy.MaskedArray.minimum_fill_value() function is used to return the maximum value that can be represented by the dtype of an object. Syntax : numpy.ma.minimum_fill_value(obj) Parameters: obj :[ ndarray, dtype or scalar ] The array data-type or scalar for which the maximum fill value is returned. R 2 min read Numpy MaskedArray.default_fill_value() function | Python numpy.MaskedArray.default_fill_value() function is used to return the default fill value for the argument object.The default filling value depends on the datatype of the input array or the type of the input scalar.If datatype is bool then default filling value is True, for int it is 999999, 1.e20 fo 2 min read Numpy MaskedArray.common_fill_value() function | Python numpy.MaskedArray.common_fill_value() function is used to return the common filling value between two masked arrays.If arr1.fill_value == arr2.fill_value then it returns the fill value, otherwise return None. Syntax : numpy.ma.common_fill_value(arr1, arr2) Parameters: arr1, arr2 :[ MaskedArray ] The 3 min read Numpy MaskedArray.all() function | Python 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 arr 3 min read Numpy MaskedArray.var() function | Python numpy.MaskedArray.var() function is used to compute the variance along the specified axis. It returns the variance of the masked array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the specified axis. Syntax : numpy.m 3 min read Numpy MaskedArray.mean() function | Python numpy.MaskedArray.mean() function is used to return the average of the masked array elements along given axis.Here masked entries are ignored, and result elements which are not finite will be masked. Syntax : numpy.ma.mean(axis=None, dtype=None, out=None) Parameters: axis :[ int, optional] Axis alon 3 min read Like