Numpy MaskedArray asarray() method | Python

Last Updated : 16 Nov, 2021
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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 : Python3 
# Python program explaining
# numpy.ma.asarray() function
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)
Output : 
Input list :  [1, 4, 8, 7, 2, 5]
output array from input list :  [1 4 8 7 2 5]
  Code #2 : Python3 
# Python program explaining
# numpy.ma.asarray() function

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)
Output : 
Input tuple :  ([1, 4, 8], [7, 2, 5])
output array from input tuple :  [[1 4 8]
 [7 2 5]]

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