numpy.byte_bounds() function – Python Last Updated : 08 Jul, 2020 Comments Improve Suggest changes Like Article Like Report numpy.byte_bounds() function returns pointers to the end-points of an array. Syntax : numpy.byte_bounds(arr) Parameters : arr : [ndarray] Input array. Return : [tuple of 2 integers] The first integer is the first byte of the array, the second integer is just past the last byte of the array. If arr is not contiguous it will not use every byte between the (low, high) values. Code #1 : Python3 # Python program explaining # numpy.byte_bounds() function # importing numpy as geek import numpy as geek arr = geek.eye(2, dtype = 'f') gfg = geek.byte_bounds(arr) print (gfg) Output : (37062512, 37062528) Code #2 : Python3 # Python program explaining # numpy.byte_bounds() function # importing numpy as geek import numpy as geek arr = geek.eye(2) gfg = geek.byte_bounds(arr) print (gfg) Output : (30421344, 30421376) Comment More infoAdvertise with us Next Article numpy.byte_bounds() function – Python sanjoy_62 Follow Improve Article Tags : Python Python-numpy Practice Tags : python Similar Reads numpy.finfo() function â Python numpy.finfo() function shows machine limits for floating point types. Syntax : numpy.finfo(dtype) Parameters : dtype : [float, dtype, or instance] Kind of floating point data-type about which to get information. Return : Machine parameters for floating point types. Code #1 : Python3 # Python program 1 min read numpy.frombuffer() function â Python numpy.frombuffer() function interpret a buffer as a 1-dimensional array. Syntax : numpy.frombuffer(buffer, dtype = float, count = -1, offset = 0) Parameters : buffer : [buffer_like] An object that exposes the buffer interface. dtype : [data-type, optional] Data-type of the returned array, default da 1 min read numpy.who function - Python numpy.who() function print the NumPy arrays in the given dictionary. Syntax : numpy.who(vardict = None) Parameters : vardict : [dict, optional] A dictionary possibly containing ndarrays. Return : Returns âNoneâ. If there is no dictionary passed in or vardict is None then returns NumPy arrays in the 1 min read Numpy size() function | Python numpy.size() function in Python is used to count the number of elements in a NumPy array. You can use it to get the total count of all elements, or to count elements along a specific axis, such as rows or columns in a multidimensional array. This makes it useful when quickly trying to understand the 2 min read numpy.iinfo() function â Python numpy.iinfo() function shows machine limits for integer types. Syntax : numpy.iinfo(dtype) Parameters : dtype : [integer type, dtype, or instance] The kind of integer data type to get information about. Return : Machine limits for integer types. Code #1 : Python3 # Python program explaining # numpy. 1 min read bytearray() function - Python The bytearray() function in Python creates a mutable sequence of bytes, which is essentially an array of integers in the range 0 to 255 (representing byte values). Unlike the immutable bytes type, bytearray allows us to modify its contents after creation, making it useful for tasks like binary data 5 min read numpy.base_repr() in Python numpy.base_repr(number, base=2, padding=0) function is used to return a string representation of a number in the given base system. For example, decimal number 10 is represented as 1010 in binary whereas it is represented as 12 in octal. Syntax : numpy.base_repr(number, base=2, padding=0) Parameters 3 min read numpy.mintypecode() function â Python numpy.mintypecode() function return the character for the minimum-size type to which given types can be safely cast. Syntax : numpy.mintypecode(typechars, typeset = 'GDFgdf', default = 'd') Parameters : typechars : [list of str or array_like] If a list of strings, each string should represent a dtyp 1 min read numpy.binary_repr() in Python numpy.binary_repr(number, width=None) function is used to represent binary form of the input number as a string. For negative numbers, if width is not given, a minus sign is added to the front. If width is given, the twoâs complement of the number is returned, with respect to that width. In a twoâs- 3 min read numpy.floor() in Python The numpy.floor() function returns the largest integer less than or equal to each element in the input array. It effectively rounds numbers down to the nearest whole number. Let's understand with an example:Pythonimport numpy as np a = [0.5, 1.5, 2.5, 3, 4.5, 10.1] res = np.floor(a) print("Floored:" 1 min read Like