code: def test_normal_quantiles_df():
      """Testing calculating normal quantiles for a sliced dataframe."""
      df = gen_sliced_df()
  
      model_dict = estimate_empirical_distribution(
          df=df,
          distribution_col="y",
          quantile_grid_size=None,
          quantiles=[0.025, 0.975],
          conditional_cols=["x"],
      )
  
      ecdf_df = model_dict["ecdf_df"]
  
      # check the case with regular mean
      quantiles_df = normal_quantiles_df(
          df=ecdf_df,
          mean_col="y_mean",
          std_col="y_std",
          quantiles=(0.025, 0.975),
      )
  
      quantiles_df = quantiles_df[["x", "normal_quantiles"]].copy()
      quantiles_df["normal_quantiles"] = quantiles_df[
          "normal_quantiles"
      ].apply(lambda x: tuple(e.round(2) for e in x))
      expected_df = pd.DataFrame()
      expected_df["x"] = ["a", "b", "c", "d", "e"]
      expected_df["normal_quantiles"] = [
          (89.94, 102.01),
          (190.2, 201.9),
          (290.25, 301.91),
          (479.37, 561.93),
          (-14.15, 6.43),
      ]
  
      assert expected_df.equals(
          quantiles_df
      ), "quantiles are not calculated correctly"
  
      # check the case with fixed_mean
      quantile_summary_col = "custom_quantiles"
      quantiles_df = normal_quantiles_df(
          df=ecdf_df,
          mean_col=None,
          std_col="y_std",
          fixed_mean=0,
          quantiles=(0.025, 0.975),
          quantile_summary_col=quantile_summary_col,
      )
  
      quantiles_df = quantiles_df[["x", quantile_summary_col]].copy()
      quantiles_df[quantile_summary_col] = quantiles_df[
          quantile_summary_col
      ].apply(lambda x: tuple(e.round(2) for e in x))
      expected_df = pd.DataFrame()
      expected_df["x"] = ["a", "b", "c", "d", "e"]
      expected_df[quantile_summary_col] = [
          (-6.04, 6.04),
          (-5.85, 5.85),
          (-5.83, 5.83),
          (-41.28, 41.28),
          (-10.29, 10.29),
      ]
  
      assert expected_df.equals(
          quantiles_df
      ), "quantiles are not calculated correctly"
  
imports: import pandas
  from greykite.algo.uncertainty.conditional.estimate_distribution import estimate_empirical_distribution
  from greykite.algo.uncertainty.conditional.normal_quantiles import normal_quantiles_df
  from greykite.common.testing_utils import gen_sliced_df
label_desc: Use image node_id 1 for calling a global function with example usage: test_normal_quantiles_df() without return types