NumPy Tutorial

Python NumPy Tutorial numpy.empty() in Python numpy.empty_like() in Python numpy.eye() in Python numpy.identity() in Python numpy.ones() in Python numpy.ones_like() in Python numpy.zeros in Python numpy.zeros_like() in Python numpy.full() in Python numpy.full_like() in Python numpy.asarray() in Python numpy.frombuffer() in Python numpy.fromiter() in Python numpy.fromstring () in Python numpy.asanyarray() in Python with Example numpy.ascontiguousarray() in Python with Example Numpy.asmatrix() in Python with Example Numpy.copy() in Python with Example numpy.loadtxt() Python numpy.arrange() in Python numpy.linspace() in Python numpy.logspace() in Python numpy.geomspace() in Python numpy.meshgrid() in Python numpy.diag() in Python numpy.diagflat() in Python numpy.tri() in Python numpy.tril() in Python numpy.copyto() in Python numpy.reshape() in Python numpy.ravel() in Python numpy.ndarray.flat() in Python numpy.ndarray.flatten() in Python numpy.rollaxis() in Python numpy.swapaxes() in Python numpy.ndarray.T in Python numpy.transpose() in Python numpy.atleast_1d() in Python numpy.atleast_2d() in Python numpy.atleast_3d() in Python numpy.broadcast_to() in Python numpy.broadcast_arrays() in Python numpy.expand_dims() in Python numpy.squeeze() in Python numpy.asarray_chkfinite() in Python numpy.asscalar() in Python numpy.concatenate() in Python numpy.stack() in Python numpy.column_stack() in Python numpy.dstack() in Python numpy.hstack() in Python numpy.vstack() in Python numpy.split() in Python numpy.tile() in Python numpy.repeat() in Python numpy.delete() in Python numpy.append() in Python numpy.resize() in Python numpy.trim_zeros() in Python numpy.unique() in Python numpy.flip() in Python NumPy vs SciPy

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Numpy Attributes

numpy.frombuffer() in Python

numpy.frombuffer() in Python The frombuffer()  function of Python numpy class creates an array by using the given buffer. Syntax

numpy.frombuffer(buffer, dtype=float, count=-1, offset=0)
Parameter The numpy.frombuffer() method consists of four parameters, which are as follows:
  1. buffer: This parameter represents an object that depicts a buffer interface.
  2. dtype: It represents the data type of the returned data type array. It is an optional parameter, and by default,its value is 0.
  3. count: It represents the length of the returned ndarray. It is an optional parameter, and its default value is -1.
  4. offset: It represents the starting position to read from. It is also an optional parameter, and its default value is 0.
Return This function returns the array version of the buffer. Example 1
# Python Programming giving an example for 
# numpy.frombuffer() function
importnumpy as numpy
obj = b'This is my numpy program' 
print(type(obj)) 
n = numpy.frombuffer(obj, dtype = "S1") 
print(n) 
print(type(n))
Output
<class 'bytes'>
[b'T' b'h' b'i' b's' b' ' b'i' b's' b' ' b'm' b'y' b' ' b'n' b'u' b'm' b'p'
b'y' b' ' b'p' b'r' b'o' b'g' b'r' b'a' b'm']
<class 'numpy.ndarray'>