code: def test_tabstatistics():
      result, df, section = _test_block(
          kls=TabTSStatistics,
          sid=None,
          stitle=None,
          mappings={},
          plots=dict(),
          scope="tab",
      )
      result = result.result.series["Sales"]
      for loc, key in {
          "Mean": "mean",
          "Variance": "var",
          "Standard deviation": "std",
          "Median": "median",
          "Median absolute deviation": "mad",
          "Coefficient of variation": "cov",
          "Minimum": "minimum",
          "25%": "q25",
          "50%": "q50",
          "75%": "q75",
          "Maximum": "maximum",
          "Interquartile range": "iqr",
          "Kurtosis": "kurtosis",
          "Skewness": "skew",
      }.items():
          actual, expected = (
              section.stats.loc[loc, "Value"],
              result[key],
          )
          assert (
              actual == expected
          ), f"Expecting result[{key}]={expected}, got stats[{loc}]={actual}"
  
      assert isinstance(section.tests, pd.DataFrame)
      assert section.tests.columns.tolist() == [
          "Null Hypothesis",
          "Reject",
          "pvalue",
          "Confidence",
      ]
      assert section.tests.index.name == "Test"
      for test in [
          "levene_constant_variance",
          "ljungbox_autocorrelation",
          "jarque_bera_normality",
          "omnibus_normality",
          "adfuller_stationarity",
      ]:
          tr = result[test]
          assert tr.test in section.tests.index
          s = section.tests.loc[tr.test]
          assert s["Null Hypothesis"] == tr.null_hypothesis
          assert (
              s["Reject"] == "Yes"
              if tr.reject_null_hypothesis
              else "No"
          )
          assert float(s["pvalue"]) == round(tr.p_value, 3)
          assert float(s["Confidence"]) == round(tr.confidence_level, 2)
  
file_path: tslumen/tests/unit/report/html/test_sections.py
imports: import mock
  import pandas
  from tslumen.report.html.sections import SectionSummary, SectionTSFeatures, SectionRelations, SectionTimeSeries, SubTimeSeries, TabTSStatistics, TabTSDistribution, TabTSFeatures, TabTSAutoCorrelation, TabTSLagPlots, TabTSComponents, TabTSSeasonality, TabTSSmoothing, _FTS_MAIN, _FTS_STAT, _FTS_ACF, _PROFILERS_TSFEATURES
  from ..util import mkresult
label_desc: Use image node_id 9 for calling a global function with example usage: test_tabstatistics() without return types