numpy.asarray() in Python Last Updated : 12 Nov, 2021 Comments Improve Suggest changes Like Article Like Report 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 āCā. 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 Python # 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) Output : Input list : [1, 3, 5, 7, 9] output array from input list : [1 3 5 7 9] Code #2 : Tuple to array Python # 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) Output : Input tuple : ([1, 3, 9], [8, 2, 6]) output array from input tuple : [[1 3 9] [8 2 6]] Comment More infoAdvertise with us Next Article numpy.asarray() in Python jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-arrayCreation Practice Tags : python Similar Reads numpy.asfarray() in Python numpy.asfarray()function is used when we want to convert input to a float type array. Input includes scalar, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asfarray(arr, dtype=type 'numpy.float64') Parameters : arr : [array_like] Input data, in any for 2 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read numpy.asanyarray() in Python 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) Parameters : arr : [array_ 2 min read numpy.array_str() in Python numpy.array_str()function is used to represent the data of an array as a string. The data in the array is returned as a single string. This function is similar to array_repr, the difference being that array_repr also returns information on the kind of array and its data type. Syntax : numpy.array_st 2 min read numpy.asfortranarray() in Python numpy.asfortranarray() function is used when we want to convert input to a array which is laid out in Fortran order in memory. Input includes scalar, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asfortranarray(arr, dtype=None)Â Parameters :Â arr : [ar 2 min read numpy.array_repr() in Python numpy.array_repr()function is used to convert an array to a string. Syntax : numpy.array_repr(arr, max_line_width=None, precision=None, suppress_small=None) Parameters : arr : [array_like] Input array. max_line_width : [int, optional] The maximum number of columns the string should span. Newline cha 2 min read numpy.asscalar() in Python numpy.asscalar() function is used when we want to convert an array of size 1 to its scalar equivalent. Syntax : numpy.asscalar(arr) Parameters : arr : [ndarray] Input array of size 1. Return : Scalar representation of arr. The output data type is the same type returned by the inputâs item method. Co 1 min read numpy.arange() in Python numpy.arange() function creates an array of evenly spaced values within a given interval. It is similar to Python's built-in range() function but returns a NumPy array instead of a list. Let's understand with a simple example:Pythonimport numpy as np #create an array arr= np.arange(5 , 10) print(arr 2 min read numpy.ascontiguousarray() in Python numpy.ascontiguousarray()function is used when we want to return a contiguous array in memory (C order). Syntax : numpy.ascontiguousarray(arr, dtype=None) Parameters : arr : [array_like] Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, 2 min read numpy.asarray_chkfinite() in Python numpy.asarray_chkfinite() function is used when we want to convert the input to an array, checking for NaNs (Not A Number) or Infs(Infinities). Input includes scalar, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asarray_chkfinite(arr, dtype=None, ord 2 min read Like