code: def test_x_dims(self):
      np.random.seed(3975)
      x_n = stats.norm.rvs(size=500)
  
      # 1d array
      data = x_n
      d_ks_norm, p_norm = lilliefors(
          data, dist="norm", pvalmethod="approx"
      )
      assert_almost_equal(d_ks_norm, 0.025957, decimal=3)
      assert_almost_equal(p_norm, 0.64175, decimal=3)
  
      # 2d array with size 1 second dimension
      data = x_n.reshape(-1, 1)
      d_ks_norm, p_norm = lilliefors(
          data, dist="norm", pvalmethod="approx"
      )
      assert_almost_equal(d_ks_norm, 0.025957, decimal=3)
      assert_almost_equal(p_norm, 0.64175, decimal=3)
  
      # 2d array with larger second dimension
      data = np.array([x_n, x_n]).T
      with pytest.raises(ValueError):
          lilliefors(data, dist="norm", pvalmethod="approx")
  
      # single-column DataFrame
      data = pd.DataFrame(data=x_n)
      d_ks_norm, p_norm = lilliefors(
          data, dist="norm", pvalmethod="approx"
      )
      assert_almost_equal(d_ks_norm, 0.025957, decimal=3)
      assert_almost_equal(p_norm, 0.64175, decimal=3)
  
      # two-column DataFrame
      data = pd.DataFrame(data=[x_n, x_n])
      with pytest.raises(ValueError):
          lilliefors(data, dist="norm", pvalmethod="approx")
  
      # DataFrame with observations in columns
      data = pd.DataFrame(data=x_n.reshape(-1, 1).T)
      with pytest.raises(ValueError):
          lilliefors(data, dist="norm", pvalmethod="approx")
  
file_path: statsmodels/statsmodels/stats/tests/test_lilliefors.py
imports: import numpy
  import pandas
  import pytest
  from numpy.testing import assert_almost_equal
  from scipy import stats
  from statsmodels.stats._lilliefors import lilliefors, get_lilliefors_table, kstest_fit, ksstat
label_desc: Use image node_id 7 for calling the TestLilliefors obj's underlying member method code with example usage: obj.test_x_dims() without return types