method
ndarray.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)
Copy of the array, cast to a specified type.
Parameters:dtypestr or dtypeTypecode or data-type to which the array is cast.
order{‘C’, ‘F’, ‘A’, ‘K’}, optionalControls the memory layout order of the result. ‘C’ means C order, ‘F’ means Fortran order, ‘A’ means ‘F’ order if all the arrays are Fortran contiguous, ‘C’ order otherwise, and ‘K’ means as close to the order the array elements appear in memory as possible. Default is ‘K’.
casting{‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘same_value’, ‘unsafe’}, optionalControls what kind of data casting may occur. Defaults to ‘unsafe’ for backwards compatibility.
‘no’ means the data types should not be cast at all.
‘equiv’ means only byte-order changes are allowed.
‘safe’ means only casts which can preserve values are allowed.
‘same_kind’ means only safe casts or casts within a kind, like float64 to float32, are allowed.
‘unsafe’ means any data conversions may be done.
‘same_value’ means any data conversions may be done, but the values must not change, including rounding of floats or overflow of ints
Added in version 2.4: Support for 'same_value' was added.
subokbool, optionalIf True, then sub-classes will be passed-through (default), otherwise the returned array will be forced to be a base-class array.
copybool, optionalBy default, astype always returns a newly allocated array. If this is set to false, and the
, order, and subok requirements are satisfied, the input array is returned instead of a copy.
Returns:arr_tndarrayUnless
is False and the other conditions for returning the input array are satisfied (see description for
input parameter), arr_t is a new array of the same shape as the input array, with dtype, order given by
, order.
Raises:ComplexWarningWhen casting from complex to float or int. To avoid this, one should use a.real.astype(t).
ValueErrorWhen casting using 'same_value' and the values change or would overflow
Examples
>>> importnumpyasnp>>> x=np.array([1,2,2.5])>>> xarray([1. , 2. , 2.5])>>> x.astype(np.int_)array([1, 2, 2])>>> x.astype(np.int_,casting="same_value")Traceback (most recent call last):...ValueError: could not cast 'same_value' double to long>>> x[:2].astype(np.int_,casting="same_value")array([1, 2])