numpy.core.records.array#

core.records.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 the appropriate recarray creation function based on the inputs (see Notes).

Parameters:

objany: Input object. See Notes for details on how various input types are treated.
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 (strides define how many bytes each array element, row, column, etc. occupy in memory).
formats, names, titles, aligned, byteorder: If dtype is None, these arguments are passed to numpy.format_parser to construct a dtype. See that function for detailed 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

If obj is None, then call the recarray constructor. If obj is a string, then call the fromstring constructor. If obj is a list or a tuple, then if the first object is an ndarray, call fromarrays, otherwise call fromrecords. If obj is a recarray, then make a copy of the data in the recarray (if copy=True) and use the new formats, names, and titles. If obj is a file, then call fromfile. Finally, if obj is an ndarray, then return obj.view(recarray), making a copy of the data if copy=True.

Examples

>>> a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

>>> np.core.records.array(a)
rec.array([[1, 2, 3],
           [4, 5, 6],
           [7, 8, 9]],
    dtype=int32)

>>> b = [(1, 1), (2, 4), (3, 9)]
>>> c = np.core.records.array(b, formats = ['i2', 'f2'], names = ('x', 'y'))
>>> c
rec.array([(1, 1.0), (2, 4.0), (3, 9.0)],
          dtype=[('x', '<i2'), ('y', '<f2')])

>>> c.x
rec.array([1, 2, 3], dtype=int16)

>>> c.y
rec.array([ 1.0,  4.0,  9.0], dtype=float16)

>>> r = np.rec.array(['abc','def'], names=['col1','col2'])
>>> print(r.col1)
abc

>>> r.col1
array('abc', dtype='<U3')

>>> r.col2
array('def', dtype='<U3')