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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 _nan_minmax_object(func, fill_value, value, axis=None, **kwargs):
 """ In house nanmin and nanmax for object array """

    valid_count = count(value, axis=axis)
    filled_value = fillna(value, fill_value)
    data = getattr(np, func)(filled_value, axis=axis, **kwargs)
    if not hasattr(data, 'dtype'):  # scalar case
        data = dtypes.fill_value(value.dtype) if valid_count == 0 else data
        return np.array(data, dtype=value.dtype)
    return where_method(data, valid_count != 0)