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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _nanmean_ddof_object(ddof, value, axis=None, **kwargs):
 """ In house nanmean. ddof argument will be used in _nanvar method """

    from .duck_array_ops import (count, fillna, _dask_or_eager_func,
                                 where_method)

    valid_count = count(value, axis=axis)
    value = fillna(value, 0)
    # As dtype inference is impossible for object dtype, we assume float
    # https://github.com/dask/dask/issues/3162
    dtype = kwargs.pop('dtype', None)
    if dtype is None and value.dtype.kind == 'O':
        dtype = value.dtype if value.dtype.kind in ['cf'] else float

    data = _dask_or_eager_func('sum')(value, axis=axis, dtype=dtype, **kwargs)
    data = data / (valid_count - ddof)
    return where_method(data, valid_count != 0)