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# NumPy Creating Arrays from Existing Data In this section, we will learn how to create arrays from existing arrays. ### numpy.asarray numpy.asarray is similar to numpy.array, but numpy.asarray has only three parameters, two fewer than numpy.array. numpy.asarray(a, dtype = None, order = None) Parameter Description: | Parameter | Description | | --- | --- | | a | Input data in any form, such as list, tuple of lists, tuple, tuple of tuples, list of tuples, multidimensional array. | | dtype | Data type, optional. | | order | Optional. Can be "C" or "F", representing row-major (C-style) or column-major (Fortran-style) order in memory. | ### Example Convert a list to an ndarray: ## Example import numpy as np x = [1,2,3]a = np.asarray(x)print(a) Output: Convert a tuple to an ndarray: ## Example import numpy as np x = (1,2,3)a = np.asarray(x)print(a) Output: Convert a list of tuples to an ndarray: ## Example import numpy as np x = [(1,2,3),(4,5)]a = np.asarray(x)print(a) Output: [(1, 2, 3) (4, 5)] Setting the dtype parameter: ## Example import numpy as np x = [1,2,3]a = np.asarray(x, dtype = float)print(a) Output: [ 1. 2. 3.] ### numpy.frombuffer numpy.frombuffer is used to create a dynamic array. numpy.frombuffer takes a buffer input parameter and reads it as a stream to convert it into an ndarray object. numpy.frombuffer(buffer, dtype = float, count = -1, offset = 0) > **Note:** When the buffer is a string, Python3 defaults to Unicode strings, so you need to convert it to a bytestring by adding a `b` before the original string. Parameter Description: | Parameter | Description | | --- | --- | | buffer | Any object that can be read as a stream. | | dtype | Data type of the returned array, optional. | | count | Number of data items to read. Default is -1, which reads all data. | | offset | Starting position for reading. Default is 0. | ## Python3.x Example import numpy as np s = b'Hello World'a = np.frombuffer(s, dtype = 'S1')print(a) Output: [b'H' b'e' b'l' b'l' b'o' b' ' b'W' b'o' b'r' b'l' b'd'] ## Python2.x Example import numpy as np s = 'Hello World'a = np.frombuffer(s, dtype = 'S1')print(a) Output: ['H' 'e' 'l' 'l' 'o' ' ' 'W' 'o' 'r' 'l' 'd'] ### numpy.fromiter The numpy.fromiter method creates an ndarray object from an iterable object, returning a one-dimensional array. numpy.fromiter(iterable, dtype, count=-1) | Parameter | Description | | --- | --- | | iterable | An iterable object. | | dtype | Data type of the returned array. | | count | Number of data items to read. Default is -1, which reads all data. | ## Example import numpy as np# Create a list object using the range function list=range(5)it=iter(list)# Create an ndarray using the iterator x=np.fromiter(it, dtype=float)print(x) Output: [0. 1. 2. 3. 4.]