Syntax : numpy.asarray(arr, dtype=None, order=None) Parameters : arr : [array_like] Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. 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 : [ndarray] Array interpretation of arr. No copy is performed if the input is already ndarray with matching dtype and order. If arr is a subclass of ndarray, a base class ndarray is returned.

# Python program explaining
# numpy.asarray() function

import numpy as geek
my_list = [1, 3, 5, 7, 9]

print ("Input  list : ", my_list)
 
  
out_arr = geek.asarray(my_list)
print ("output array from input list : ", out_arr) 

Input  list :  [1, 3, 5, 7, 9]
output array from input list :  [1 3 5 7 9]

# Python program explaining
# numpy.asarray() function

import numpy as geek

my_tuple = ([1, 3, 9], [8, 2, 6])
 
print ("Input  tuple : ", my_tuple)
  
out_arr = geek.asarray(my_tuple) 
print ("output array from input tuple : ", out_arr) 

Input  tuple :  ([1, 3, 9], [8, 2, 6])
output array from input tuple :  [[1 3 9]
 [8 2 6]]