code: def get_data():
      import os
  
      curdir = os.path.split(__file__)[0]
      dt = pandas.read_csv(
          os.path.join(curdir, "racd10data_with_transformed.csv")
      )
  
      # Transformations compared to original data
      ##dt3['income'] /= 10.
      ##dt3['aget'] = (dt3['age'] - dt3['age'].min()) / 5.
      ##dt3['aget2'] = dt3['aget']**2
  
      # How do we do this with pandas
      mask = ~((np.asarray(dt["private"]) == 1) & (dt["medicaid"] == 1))
      mask = mask & (dt["docvis"] <= 70)
      dt3 = dt[mask]
      dt3["const"] = 1  # add constant
      return dt3
  
imports: from statsmodels.compat.python import lmap
  import numpy
  import pandas
  from scipy import stats
  import pytest
  from statsmodels.regression.linear_model import OLS
  from statsmodels.sandbox.regression import gmm
  from numpy.testing import assert_allclose, assert_equal
label_desc: Use image node_id 1 for calling a global function with example usage: get_data() and returns: dt3