Example #1
0
def _isnull_ndarraylike_old(obj):
    values = getattr(obj, 'values', obj)
    dtype = values.dtype

    if is_string_dtype(dtype):
        # Working around NumPy ticket 1542
        shape = values.shape

        if is_string_like_dtype(dtype):
            result = np.zeros(values.shape, dtype=bool)
        else:
            result = np.empty(shape, dtype=bool)
            vec = lib.isnullobj_old(values.ravel())
            result[:] = vec.reshape(shape)

    elif dtype in _DATELIKE_DTYPES:
        # this is the NaT pattern
        result = values.view('i8') == iNaT
    else:
        result = ~np.isfinite(values)

    # box
    if isinstance(obj, ABCSeries):
        from pandas import Series
        result = Series(result, index=obj.index, name=obj.name, copy=False)

    return result
Example #2
0
def _isnull_ndarraylike_old(obj):
    values = getattr(obj, 'values', obj)
    dtype = values.dtype

    if is_string_dtype(dtype):
        # Working around NumPy ticket 1542
        shape = values.shape

        if is_string_like_dtype(dtype):
            result = np.zeros(values.shape, dtype=bool)
        else:
            result = np.empty(shape, dtype=bool)
            vec = lib.isnullobj_old(values.ravel())
            result[:] = vec.reshape(shape)

    elif is_datetime64_dtype(dtype):
        # this is the NaT pattern
        result = values.view('i8') == iNaT
    else:
        result = ~np.isfinite(values)

    # box
    if isinstance(obj, ABCSeries):
        from pandas import Series
        result = Series(result, index=obj.index, name=obj.name, copy=False)

    return result
Example #3
0
def _isnull_ndarraylike_old(obj):
    from pandas import Series
    values = np.asarray(obj)

    if values.dtype.kind in ('O', 'S', 'U'):
        # Working around NumPy ticket 1542
        shape = values.shape

        if values.dtype.kind in ('S', 'U'):
            result = np.zeros(values.shape, dtype=bool)
        else:
            result = np.empty(shape, dtype=bool)
            vec = lib.isnullobj_old(values.ravel())
            result[:] = vec.reshape(shape)

        if isinstance(obj, Series):
            result = Series(result, index=obj.index, copy=False)
    elif values.dtype == np.dtype('M8[ns]'):
        # this is the NaT pattern
        result = values.view('i8') == tslib.iNaT
    else:
        result = -np.isfinite(obj)
    return result
Example #4
0
def _isnull_ndarraylike_old(obj):
    from pandas import Series
    values = np.asarray(obj)

    if values.dtype.kind in ('O', 'S', 'U'):
        # Working around NumPy ticket 1542
        shape = values.shape

        if values.dtype.kind in ('S', 'U'):
            result = np.zeros(values.shape, dtype=bool)
        else:
            result = np.empty(shape, dtype=bool)
            vec = lib.isnullobj_old(values.ravel())
            result[:] = vec.reshape(shape)

        if isinstance(obj, Series):
            result = Series(result, index=obj.index, copy=False)
    elif values.dtype == np.dtype('M8[ns]'):
        # this is the NaT pattern
        result = values.view('i8') == tslib.iNaT
    else:
        result = -np.isfinite(obj)
    return result