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# numpy.ma.array

`numpy.ma.``array`(data, dtype=None, copy=False, order=False, mask=False, fill_value=None, keep_mask=True, hard_mask=False, shrink=True, subok=True, ndmin=0)

  Arrays with possibly masked values. Masked values of True exclude the corresponding element from any computation.

  Construction:
    x = MaskedArray(data, mask=nomask, dtype=None, copy=True, fill_value=None, keep_mask=True, hard_mask=False, shrink=True)

  Parameters: | data : {var} Input data. mask : {nomask, sequence}, optional Mask. Must be convertible to an array of booleans with the same shape as data: True indicates a masked (eg., invalid) data. dtype : {dtype}, optional Data type of the output. If dtype is None, the type of the data argument (data.dtype) is used. If dtype is not None and different from data.dtype, a copy is performed. copy : {False, True}, optional Whether to copy the input data (True), or to use a reference instead. Note: data are NOT copied by default. subok : {True, False}, optional Whether to return a subclass of MaskedArray (if possible) or a plain MaskedArray. ndmin : {0, int}, optional Minimum number of dimensions fill_value : {var}, optional Value used to fill in the masked values when necessary. If None, a default based on the datatype is used. keep_mask : {True, boolean}, optional Whether to combine mask with the mask of the input data, if any (True), or to use only mask for the output (False). hard_mask : {False, boolean}, optional Whether to use a hard mask or not. With a hard mask, masked values cannot be unmasked. shrink : {True, boolean}, optional Whether to force compression of an empty mask.

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