`numpy.rec:array`

source: /numpy/_core/records.py :941

Signature

   def     array (    obj    ,    dtype    =  None   ,    shape    =  None   ,    offset    =  0   ,    strides    =  None   ,    formats    =  None   ,    names    =  None   ,    titles    =  None   ,    aligned    =  False   ,    byteorder    =  None   ,    copy    =  True     )

Summary

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

Extended Summary

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

Parameters

obj : any: Input object. See Notes for details on how various input types are treated.
dtype : data-type, optional: Valid dtype for array.
shape : int or tuple of ints, optional: Shape of each array.
offset : int, optional: Position in the file or buffer to start reading from.
strides : tuple 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.
copy : bool, 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]])
a

✓

np.rec.array(a)

✓

b = [(1, 1), (2, 4), (3, 9)]
c = np.rec.array(b, formats = ['i2', 'f2'], names = ('x', 'y'))
c

✓

c.x

✓

c.y

✗

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

✓

r.col1

✓

r.col2

✓

Aliases

numpy.rec.array