Numpy MaskedArray.default_fill_value() function | Python Last Updated : 29 Oct, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report 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 for float, for complex it is 1.e20+0.j, ‘?’ for object and ‘N/A’ for string. Syntax : numpy.ma.default_fill_value(obj) Parameters: obj :[ ndarray, dtype or scalar ] The array data-type or scalar for which the default fill value is returned. Return : [ scalar ] The default fill value. Code #1 : Python3 # Python program explaining # numpy.MaskedArray.default_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.default_fill_value # methods to masked array out_val = ma.default_fill_value(mask_arr) print ("Default filled value : ", out_val) Output: Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] Default filled value : 999999 Code #2 : Python3 # Python program explaining # numpy.MaskedArray.default_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 + 2j, 2 + 3j], [ 3-2j, -1 + 2j], [ 5-4j, -3-3j]]) print ("Input array : ", in_arr) # Now we are creating a masked array. # by making two entry as invalid. mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr) # applying MaskedArray.default_fill_value # methods to masked array out_val = ma.default_fill_value(mask_arr) print ("Default filled value : ", out_val) Output: Input array : [[ 1.+2.j 2.+3.j] [ 3.-2.j -1.+2.j] [ 5.-4.j -3.-3.j]] Masked array : [[-- (2+3j)] [-- (-1+2j)] [(5-4j) (-3-3j)]] Default filled value : (1e+20+0j) Comment More infoAdvertise with us Next Article Numpy MaskedArray.allequal() function | Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads 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.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.maximum_fill_value() function | Python 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. R 2 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.allequal() 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 arra 3 min read Numpy MaskedArray.dot() function | Python numpy.MaskedArray.dot() function is used to calculate the dot product of two mask arrays. Syntax : numpy.ma.dot(arr1, arr2, strict=False) Parameters: arr1, arr2:[ ndarray] Inputs arrays. strict : [bool, optional] Whether masked data are propagated (True) or set to 0 (False) for the computation. Defa 3 min read Like