numpy.rec.fromarrays#

rec.fromarrays(arrayList, dtype=None, shape=None, formats=None, names=None, titles=None, aligned=False, byteorder=None)[source]#

Create a record array from a (flat) list of arrays

Parameters:

arrayListlist or tuple: List of array-like objects (such as lists, tuples, and ndarrays).
dtypedata-type, optional: valid dtype for all arrays
shapeint or tuple of ints, optional: Shape of the resulting array. If not provided, inferred from arrayList[0].
formats, names, titles, aligned, byteorder: If dtype is None, these arguments are passed to numpy.rec.format_parser to construct a dtype. See that function for detailed documentation.

Returns:

np.recarray: Record array consisting of given arrayList columns.

Examples

>>> x1=np.array([1,2,3,4])
>>> x2=np.array(['a','dd','xyz','12'])
>>> x3=np.array([1.1,2,3,4])
>>> r = np.rec.fromarrays([x1,x2,x3],names='a,b,c')
>>> print(r[1])
(2, 'dd', 2.0) # may vary
>>> x1[1]=34
>>> r.a
array([1, 2, 3, 4])

>>> x1 = np.array([1, 2, 3, 4])
>>> x2 = np.array(['a', 'dd', 'xyz', '12'])
>>> x3 = np.array([1.1, 2, 3,4])
>>> r = np.rec.fromarrays(
...     [x1, x2, x3],
...     dtype=np.dtype([('a', np.int32), ('b', 'S3'), ('c', np.float32)]))
>>> r
rec.array([(1, b'a', 1.1), (2, b'dd', 2. ), (3, b'xyz', 3. ),
           (4, b'12', 4. )],
          dtype=[('a', '<i4'), ('b', 'S3'), ('c', '<f4')])