numpy.zeros — NumPy v2.6.dev0 Manual

numpy.zeros(shape, dtype=None, order='C', *, device=None, like=None)

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Return a new array of given shape and type, filled with zeros.

Parameters:shapeint or tuple of intsShape of the new array, e.g., (2,3) or 2.

dtypedata-type, optionalThe desired data-type for the array, e.g.,

numpy.int8

. Default is

numpy.float64

.

order{‘C’, ‘F’}, optional, default: ‘C’Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.

devicestr, optionalThe device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.

Added in version 2.0.0.

likearray_like, optionalReference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

Added in version 1.20.0.

Returns:outndarrayArray of zeros with the given shape, dtype, and order.

See also

zeros_like

Return an array of zeros with shape and type of input.

empty

Return a new uninitialized array.

ones

Return a new array setting values to one.

full

Return a new array of given shape filled with value.

Examples

>>> importnumpyasnp>>> np.zeros(5)array([ 0., 0., 0., 0., 0.])>>> np.zeros((5,),dtype=np.int_)array([0, 0, 0, 0, 0])>>> np.zeros((2,1))array([[ 0.], [ 0.]])>>> s=(2,2)>>> np.zeros(s)array([[ 0., 0.], [ 0., 0.]])>>> np.zeros((2,),dtype=[('x','i4'),('y','i4')])# custom dtypearray([(0, 0), (0, 0)], dtype=[('x', '<i4'), ('y', '<i4')])