Numpy MaskedArray asarray() method | Python
numpy.ma.asarray()
function is used when we want to convert input to a masked array of the given data-type.
No copy is performed if the input is already a ndarray. If arr is a subclass of MaskedArray, a base class MaskedArray is returned.
Syntax : numpy.ma.asarray(arr, dtype=None, order=None)
Parameters :
arr : [array_like] Input data, in any form that can be converted to a masked array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists, ndarrays and masked arrays.
dtype : [data-type, optional] By default, the data-type is inferred from the input data.
order : Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.
Return : [MaskedArray] Masked array interpretation of arr.
Code #1 :
import numpy as geek
my_list = [ 1 , 4 , 8 , 7 , 2 , 5 ]
print ( "Input list : " , my_list)
out_arr = geek.ma.asarray(my_list)
print ( "output array from input list : " , out_arr)
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Output :
Input list : [1, 4, 8, 7, 2, 5]
output array from input list : [1 4 8 7 2 5]
Code #2 :
import numpy as geek
my_tuple = ([ 1 , 4 , 8 ], [ 7 , 2 , 5 ])
print ( "Input tuple : " , my_tuple)
out_arr = geek.ma.asarray(my_tuple)
print ( "output array from input tuple : " , out_arr)
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Output :
Input tuple : ([1, 4, 8], [7, 2, 5])
output array from input tuple : [[1 4 8]
[7 2 5]]
Last Updated :
16 Nov, 2021
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