numpy.asanyarray()function is used when we want to convert input to an array but it pass ndarray subclasses through. Input can be scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays.
Syntax : numpy.asanyarray(arr, dtype=None, order=None)
arr : [array_like] Input data, in any form that can be converted to an array. This includes scalars, 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 or an ndarray subclass] Array interpretation of arr. If arr is ndarray or a subclass of ndarray, it is returned as-is and no copy is performed.
Code #1 : List to array
Input list : [1, 3, 5, 7, 9] output array from input list : [1 3 5 7 9]
Code #2 : Tuple to array
Input touple : ([1, 3, 9], [8, 2, 6]) output array from input touple : [[1 3 9] [8 2 6]]
Code #3 : Scalar to array
Input scalar : 12 output array from input scalar : 12 class 'numpy.ndarray'
- Important differences between Python 2.x and Python 3.x with examples
- Python | Set 4 (Dictionary, Keywords in Python)
- Python | Sort Python Dictionaries by Key or Value
- chr() in Python
- gcd() in Python
- try and except in Python
- max() and min() in Python
- SHA in Python
- abs() in Python
- Any & All in Python
- pow() in Python
- SQL using Python | Set 1
- zip() in Python
- bin() in Python
- Python Set | pop()
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.