code: def tail_ratio(returns):
      
  
      if len(returns) < 1:
          return np.nan
  
      returns = np.asanyarray(returns)
      # Be tolerant of nan's
      returns = returns[~np.isnan(returns)]
      if len(returns) < 1:
          return np.nan
  
      return np.abs(np.percentile(returns, 95)) / \
          np.abs(np.percentile(returns, 5))
docs: Determines the ratio between the right (95%) and left tail (5%).
  
      For example, a ratio of 0.25 means that losses are four times
      as bad as profits.
  
      Parameters
      ----------
      returns : pd.Series or np.ndarray
          Daily returns of the strategy, noncumulative.
           - See full explanation in :func:`~empyrical.stats.cum_returns`.
  
      Returns
      -------
      tail_ratio : float