old_contents: import pandas
  import numpy as np
  
  from statsmodels.tools import data
  
  def test_missing_data_pandas():
      """
      Fixes GH: #144
      """
      X = np.random.random((10,5))
      X[1,2] = np.nan
      df = pandas.DataFrame(X)
      vals, cnames, rnames = data.interpret_data(df)
      np.testing.assert_equal(rnames, [0,2,3,4,5,6,7,8,9])
  
  def test_structarray():
      X = np.random.random((9,)).view([('var1', 'f8'),
                                          ('var2', 'f8'),
                                          ('var3', 'f8')])
      vals, cnames, rnames = data.interpret_data(X)
      np.testing.assert_equal(cnames, X.dtype.names)
      np.testing.assert_equal(vals, X.view((float,3)))
      np.testing.assert_equal(rnames, None)
  
  def test_recarray():
      X = np.random.random((9,)).view([('var1', 'f8'),
                                          ('var2', 'f8'),
                                          ('var3', 'f8')])
      vals, cnames, rnames = data.interpret_data(X.view(np.recarray))
      np.testing.assert_equal(cnames, X.dtype.names)
      np.testing.assert_equal(vals, X.view((float,3)))
      np.testing.assert_equal(rnames, None)
  
  
  def test_dataframe():
      X = np.random.random((10,5))
      df = pandas.DataFrame(X)
      vals, cnames, rnames = data.interpret_data(df)
      np.testing.assert_equal(vals, df.values)
      np.testing.assert_equal(rnames, df.index)
      np.testing.assert_equal(cnames, df.columns)
  
new_contents: import pandas
  import numpy as np
  
  from statsmodels.tools import data
  
  def test_missing_data_pandas():
      """
      Fixes GH: #144
      """
      X = np.random.random((10,5))
      X[1,2] = np.nan
      df = pandas.DataFrame(X)
      vals, cnames, rnames = data.interpret_data(df)
      np.testing.assert_equal(rnames.tolist(), [0,2,3,4,5,6,7,8,9])
  
  def test_structarray():
      X = np.random.random((9,)).view([('var1', 'f8'),
                                          ('var2', 'f8'),
                                          ('var3', 'f8')])
      vals, cnames, rnames = data.interpret_data(X)
      np.testing.assert_equal(cnames, X.dtype.names)
      np.testing.assert_equal(vals, X.view((float,3)))
      np.testing.assert_equal(rnames, None)
  
  def test_recarray():
      X = np.random.random((9,)).view([('var1', 'f8'),
                                          ('var2', 'f8'),
                                          ('var3', 'f8')])
      vals, cnames, rnames = data.interpret_data(X.view(np.recarray))
      np.testing.assert_equal(cnames, X.dtype.names)
      np.testing.assert_equal(vals, X.view((float,3)))
      np.testing.assert_equal(rnames, None)
  
  
  def test_dataframe():
      X = np.random.random((10,5))
      df = pandas.DataFrame(X)
      vals, cnames, rnames = data.interpret_data(df)
      np.testing.assert_equal(vals, df.values)
      np.testing.assert_equal(rnames.tolist(), df.index.tolist())
      np.testing.assert_equal(cnames, df.columns.tolist())
  
subject: Fix errors due to testing changes in np master