numpy.asfarray() in Python Last Updated : 16 Nov, 2021 Comments Improve Suggest changes Like Article Like Report 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 form that can be converted to an float type array. This includes scalar, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. dtype : Float type code to coerce input array arr. If dtype is one of the ‘int’ dtypes, it is replaced with float64. Return : [ndarray] The input arr as a float ndarray. Code #1 : List to float type array Python # Python program explaining # numpy.asfarray() function import numpy as geek my_list = [1, 3, 5, 7, 9] print ("Input list : ", my_list) out_arr = geek.asfarray(my_list) print ("output float type array from input list : ", out_arr) Output : Input list : [1, 3, 5, 7, 9] output float type array from input list : [ 1. 3. 5. 7. 9.] Code #2 : Tuple to float type array Python # Python program explaining # numpy.asfarray() function import numpy as geek my_tuple = ([1, 3, 9], [8, 2, 6]) print ("Input tuple : ", my_tuple) out_arr = geek.asfarray(my_tuple, dtype ='int8') print ("output float type array from input tuple : ", out_arr) Output : Input tuple : ([1, 3, 9], [8, 2, 6]) output float type array from input tuple : [[ 1. 3. 9.] [ 8. 2. 6.]] Code #3 : Scalar to float type array Python # Python program explaining # numpy.asfarray() function import numpy as geek my_scalar = 15 print ("Input scalar : ", my_scalar) out_arr = geek.asfarray(my_scalar, dtype ='float') print ("output float type array from input scalar : ", out_arr) Output : InInput scalar : 15 output float type array from input scalar : 15.0 Comment More infoAdvertise with us Next Article numpy.asanyarray() in Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads numpy.asarray() in Python 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 a 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.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.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_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 Like