code: def _render_distribution_fit_information_if_available(
      state, label
  ) -> Optional[AnalysisState]:
      if state.distributions_fit is not None:  # type: ignore # state is always present
          dist_fit_state = state.distributions_fit.train_data  # type: ignore
          dist_info = ["### Distribution fits for target variable"]
          if (label in dist_fit_state) and (
              len(dist_fit_state[label]) > 0
          ):
              for d, p in state.distributions_fit.train_data[label].items():  # type: ignore
                  dist_info.append(
                      f" - [{d}](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.{d}.html)"
                  )
                  if p.param is not None and len(p.param) > 0:
                      params = ", ".join(
                          [
                              f"{shape}: {param}"
                              for shape, param in zip(p.shapes, p.param)
                          ]
                      )
                      dist_info.append(
                          f'   - p-value: {p["pvalue"]:.3f}'
                      )
                      dist_info.append(f"   - Parameters: ({params})")
          else:
              dist_info.append(
                  f" - ⚠️ none of the [attempted](https://docs.scipy.org/doc/scipy/reference/stats.html#continuous-distributions) "  # type: ignore
                  f"distribution fits satisfy specified minimum p-value threshold: `{state.distributions_fit_pvalue_min}`"
              )
          analyze(
              viz_facets=[
                  MarkdownSectionComponent("\n".join(dist_info))
              ]
          )
      return state
  
imports: import logging
  from typing import Any, Dict, List, Optional, Tuple, Union
  import pandas
  from autogluon.common.utils.log_utils import verbosity2loglevel
  from autogluon.features import CategoryFeatureGenerator
  from autogluon.tabular import TabularPredictor
  from ..None import AnalysisState
  from ..analysis import AnomalyDetectorAnalysis, ApplyFeatureGenerator, AutoGluonModelEvaluator, AutoGluonModelQuickFit, Correlation, DistributionFit, FeatureInteraction, MissingValuesAnalysis, ProblemTypeControl, ShapAnalysis, TrainValidationSplit, XShiftDetector
  from ..analysis.base import AbstractAnalysis, BaseAnalysis, SaveArgsToState
  from ..analysis.dataset import DatasetSummary, LabelInsightsAnalysis, RawTypesAnalysis, Sampler, SpecialTypesAnalysis, VariableTypeAnalysis
  from ..analysis.interaction import FeatureDistanceAnalysis
  from ..state import is_key_present_in_state
  from ..utils.common import expand_nested_args_into_nested_maps, get_empty_dict_if_none
  from ..utils.defaults import QuickFitDefaults
  from ..visualization import AnomalyScoresVisualization, ConfusionMatrix, CorrelationVisualization, DatasetStatistics, DatasetTypeMismatch, ExplainForcePlot, ExplainWaterfallPlot, FeatureImportance, FeatureInteractionVisualization, LabelInsightsVisualization, MarkdownSectionComponent, MissingValues, ModelLeaderboard, PropertyRendererComponent, RegressionEvaluation, XShiftSummary
  from ..visualization.base import AbstractVisualization
  from ..visualization.interaction import FeatureDistanceAnalysisVisualization, PDPInteractions
  from ..visualization.layouts import SimpleVerticalLinearLayout
label_desc: Use image node_id 12 for calling a global function with example usage: _render_distribution_fit_information_if_available(state, label) and returns: state