numpy.dtype.base() function - Python Last Updated : 11 Jun, 2020 Summarize Comments Improve Suggest changes Share Like Article Like Report numpy.dtype.base() function returns dtype for the base element of the subarrays, regardless of their dimension or shape. Syntax : numpy.dtype.base() Return : Returns data type of the base element. Code #1 : Python3 # Python program explaining # numpy.dtype.base() function # importing numpy as geek import numpy as geek x = geek.dtype('i2') gfg = x.base print (gfg) Output : int16 Code #2 : Python3 # Python program explaining # numpy.dtype.base() function # importing numpy as geek import numpy as geek x = geek.dtype('8f') gfg = x.base print (gfg) Output : float32 Comment More infoAdvertise with us Next Article numpy.dtype.base() function - Python S sanjoy_62 Follow Improve Article Tags : Python Python-numpy Python numpy-DataType Practice Tags : python Similar Reads numpy.dtype.kind() function – Python numpy.dtype.kind() function determine the character code by identifying the general kind of data. Syntax : numpy.dtype.kind(type) Parameters : type : [dtype] The input data-type. Return : Return the character code by identifying the general kind of data. Code #1 : Python3 # Python program explaining 1 min read numpy.dtype.subdtype() function – Python numpy.dtype.subdtype() function returns Tuple(item_dtype, shape) if this dtype describes a sub-array, and None otherwise. Syntax : numpy.dtype.subdtype(type) type : [dtype] The input data-type. Return : Return Tuple(item_dtype, shape) if this dtype describes a sub-array, and None otherwise. Code #1 1 min read numpy.fromstring() function – Python numpy.fromstring() function create a new one-dimensional array initialized from text data in a string. Syntax : numpy.fromstring(string, dtype = float, count = -1, sep = ' ') Parameters : string : [str] A string that contained the data. dtype : [data-type, optional] Data-type of the array. Default d 1 min read numpy.frombuffer() function – 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 ‘None’. If there is no dictionary passed in or vardict is None then returns NumPy arrays in the 1 min read Like