numpy.asarray() in Python
Last Updated :
12 Nov, 2021
numpy.asarray()function is used when we want to convert input to an array. Input can be lists, lists of tuples, tuples, tuples of tuples, tuples of lists and arrays.
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.
Code #1 : List to array
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)
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Output :
Input list : [1, 3, 5, 7, 9]
output array from input list : [1 3 5 7 9]
Code #2 : Tuple to array
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)
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Output :
Input tuple : ([1, 3, 9], [8, 2, 6])
output array from input tuple : [[1 3 9]
[8 2 6]]