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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 _adjust_returns(returns, adjustment_factor):
 """ Returns the returns series adjusted by adjustment_factor. Optimizes for the case of adjustment_factor being 0 by returning returns itself, not a copy! Parameters returns : pd.Series or np.ndarray adjustment_factor : pd.Series or np.ndarray or float or int Returns ------- adjusted_returns : array-like """

    if isinstance(adjustment_factor, (float, int)) and adjustment_factor == 0:
        return returns
    return returns - adjustment_factor