code: def scoreatpercentile(
      data, per, limit=(), alphap=0.4, betap=0.4, axis=0, masknan=None
  ):
      """Calculate the score at the given 'per' percentile of the
      sequence a.  For example, the score at per=50 is the median.
  
      This function is a shortcut to mquantile
      """
      per = np.asarray(per, float)
      if (per < 0).any() or (per > 100.0).any():
          raise ValueError(
              "The percentile should be between 0. and 100. !"
              " (got %s)" % per
          )
      return quantiles(
          data,
          prob=[per / 100.0],
          alphap=alphap,
          betap=betap,
          limit=limit,
          axis=axis,
          masknan=masknan,
      ).squeeze()
  
file_path: statsmodels/statsmodels/sandbox/stats/stats_mstats_short.py
imports: import numpy
  from numpy import ma
  from scipy import stats
label_desc: Use image node_id 2 for calling a global function with example usage: scoreatpercentile(data, per, limit, alphap, betap, axis, masknan) and returns: quantiles