numpy.rec.array#

rec.array(obj,dtype=None,shape=None,offset=0,strides=None,formats=None,names=None,titles=None,aligned=False,byteorder=None,copy=True)[source]#

Construct a record array from a wide-variety of objects.

A general-purpose record array constructor that dispatches to theappropriaterecarray creation function based on the inputs (see Notes).

Parameters:
objany

Input object. See Notes for details on how various input types aretreated.

dtypedata-type, optional

Valid dtype for array.

shapeint or tuple of ints, optional

Shape of each array.

offsetint, optional

Position in the file or buffer to start reading from.

stridestuple of ints, optional

Buffer (buf) is interpreted according to these strides (stridesdefine how many bytes each array element, row, column, etc.occupy in memory).

formats, names, titles, aligned, byteorder

Ifdtype isNone, these arguments are passed tonumpy.format_parser to construct a dtype. See that function fordetailed documentation.

copybool, optional

Whether to copy the input object (True), or to use a reference instead.This option only applies when the input is an ndarray or recarray.Defaults to True.

Returns:
np.recarray

Record array created from the specified object.

Notes

Ifobj isNone, then call therecarray constructor. Ifobj is a string, then call thefromstring constructor. Ifobj is alist or a tuple, then if the first object is anndarray, callfromarrays, otherwise callfromrecords. Ifobj is arecarray, then make a copy of the data in the recarray(ifcopy=True) and use the new formats, names, and titles. Ifobjis a file, then callfromfile. Finally, if obj is anndarray, thenreturnobj.view(recarray), making a copy of the data ifcopy=True.

Examples

>>>a=np.array([[1,2,3],[4,5,6],[7,8,9]])>>>aarray([[1, 2, 3],       [4, 5, 6],       [7, 8, 9]])
>>>np.rec.array(a)rec.array([[1, 2, 3],           [4, 5, 6],           [7, 8, 9]],          dtype=int64)
>>>b=[(1,1),(2,4),(3,9)]>>>c=np.rec.array(b,formats=['i2','f2'],names=('x','y'))>>>crec.array([(1, 1.), (2, 4.), (3, 9.)],          dtype=[('x', '<i2'), ('y', '<f2')])
>>>c.xarray([1, 2, 3], dtype=int16)
>>>c.yarray([1.,  4.,  9.], dtype=float16)
>>>r=np.rec.array(['abc','def'],names=['col1','col2'])>>>print(r.col1)abc
>>>r.col1array('abc', dtype='<U3')
>>>r.col2array('def', dtype='<U3')
On this page