core.records.
array
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).
recarray
Input object. See Notes for details on how various input types are treated.
Valid dtype for array.
Shape of each array.
Position in the file or buffer to start reading from.
Buffer (buf) is interpreted according to these strides (strides define how many bytes each array element, row, column, etc. occupy in memory).
If dtype is None, these arguments are passed to numpy.format_parser to construct a dtype. See that function for detailed documentation.
dtype
None
numpy.format_parser
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.
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.
fromstring
ndarray
fromarrays
fromrecords
copy=True
fromfile
obj.view(recarray)
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')