numpy.array¶

numpy.
array
(object, dtype=None, copy=True, order='K', subok=False, ndmin=0)¶ Create an array.
Parameters:  object : array_like
An array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence.
 dtype : datatype, optional
The desired datatype for the array. If not given, then the type will be determined as the minimum type required to hold the objects in the sequence.
 copy : bool, optional
If true (default), then the object is copied. Otherwise, a copy will only be made if __array__ returns a copy, if obj is a nested sequence, or if a copy is needed to satisfy any of the other requirements (
dtype
, order, etc.). order : {‘K’, ‘A’, ‘C’, ‘F’}, optional
Specify the memory layout of the array. If object is not an array, the newly created array will be in C order (row major) unless ‘F’ is specified, in which case it will be in Fortran order (column major). If object is an array the following holds.
order no copy copy=True ‘K’ unchanged F & C order preserved, otherwise most similar order ‘A’ unchanged F order if input is F and not C, otherwise C order ‘C’ C order C order ‘F’ F order F order When
copy=False
and a copy is made for other reasons, the result is the same as ifcopy=True
, with some exceptions for A, see the Notes section. The default order is ‘K’. subok : bool, optional
If True, then subclasses will be passedthrough, otherwise the returned array will be forced to be a baseclass array (default).
 ndmin : int, optional
Specifies the minimum number of dimensions that the resulting array should have. Ones will be prepended to the shape as needed to meet this requirement.
Returns:  out : ndarray
An array object satisfying the specified requirements.
See also
empty_like
 Return an empty array with shape and type of input.
ones_like
 Return an array of ones with shape and type of input.
zeros_like
 Return an array of zeros with shape and type of input.
full_like
 Return a new array with shape of input filled with value.
empty
 Return a new uninitialized array.
ones
 Return a new array setting values to one.
zeros
 Return a new array setting values to zero.
full
 Return a new array of given shape filled with value.
Notes
When order is ‘A’ and
object
is an array in neither ‘C’ nor ‘F’ order, and a copy is forced by a change in dtype, then the order of the result is not necessarily ‘C’ as expected. This is likely a bug.Examples
>>> np.array([1, 2, 3]) array([1, 2, 3])
Upcasting:
>>> np.array([1, 2, 3.0]) array([ 1., 2., 3.])
More than one dimension:
>>> np.array([[1, 2], [3, 4]]) array([[1, 2], [3, 4]])
Minimum dimensions 2:
>>> np.array([1, 2, 3], ndmin=2) array([[1, 2, 3]])
Type provided:
>>> np.array([1, 2, 3], dtype=complex) array([ 1.+0.j, 2.+0.j, 3.+0.j])
Datatype consisting of more than one element:
>>> x = np.array([(1,2),(3,4)],dtype=[('a','<i4'),('b','<i4')]) >>> x['a'] array([1, 3])
Creating an array from subclasses:
>>> np.array(np.mat('1 2; 3 4')) array([[1, 2], [3, 4]])
>>> np.array(np.mat('1 2; 3 4'), subok=True) matrix([[1, 2], [3, 4]])