code: def getnist(filename):
      here = os.path.dirname(__file__)
      fname = os.path.abspath(os.path.join(here, "data", filename))
      with open(fname, encoding="utf-8") as fd:
          content = fd.read().split("\n")
  
      data = [line.split() for line in content[60:]]
      certified = [line.split() for line in content[40:48] if line]
      dataf = np.loadtxt(fname, skiprows=60)
      y, x = dataf.T
      y = y.astype(int)
      caty = np.unique(y)
      f = float(certified[0][-1])
      R2 = float(certified[2][-1])
      resstd = float(certified[4][-1])
      dfbn = int(certified[0][-4])
      dfwn = int(certified[1][-3])  # dfbn->dfwn is this correct
      prob = stats.f.sf(f, dfbn, dfwn)
      return y, x, np.array([f, prob, R2, resstd]), certified, caty
  
file_path: statsmodels/statsmodels/sandbox/regression/anova_nistcertified.py
imports: from statsmodels.compat.python import lmap
  import os
  import numpy
  from scipy import stats
  from statsmodels.tools.tools import add_constant
  from statsmodels.regression.linear_model import OLS
  from .try_ols_anova import data2dummy
label_desc: Use image node_id 1 for calling a global function with example usage: getnist(filename) and returns: y,  x,  np,  certified,  caty