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

Misc

Numpy Attributes

Numpy.copy() in Python with Example

Numpy.copy() in Python The copy() function of Python numpy class returns an array copy for the given object. Syntax

numpy.copy(a, order='K')
Parameter a: It represent the array_like input data. order :  This parameter controls the memory layout of the copy. It is an optional parameter and supports C, F, A, k style where ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if ‘a’ is Fortran contiguous, ‘C’ otherwise and ‘K’ means match the layout of ‘a’ as closely as possible. Return This function returns the array interpretation of the specified array ‘a’. Example 1
# Python Programming giving an example for 
# numpy.ndarray.copy() function
importnumpy as numpy
n = numpy.array([[10, 11, 12, 13], [14, 15,16, 17]],
order ='F')
print("n is: \n", n)
# copying n to m
m = n.copy()
print("m is :\n", m)
print("\nn is successfully copied to m")
Output
n is:
 [[10 11 12 13]
 [14 15 16 17]]
m is :
 [[10 11 12 13]
 [14 15 16 17]]
n is successfully copied to m