class_docstr: Merging dictionaries of features containing dataframes with statistics as its values.
code: def transform(self, dicts: list):
      merged_stats = {}
      for dict_ in dicts:
          for feature, values in dict_.items():
              if isinstance(values, pd.DataFrame):
                  # we add statistics dataframe to the final output for specific feature however
                  # if the feature already exists - we concatenate its dataframe with the existing one
                  if feature in merged_stats:
                      merged_stats[feature] = merged_stats[
                          feature
                      ].combine_first(values)
                  else:
                      merged_stats[feature] = values
      return merged_stats
  
imports: from __future__ import annotations
  import pandas
  from popmon.base import Module
label_desc: Use image node_id 2 for calling the MergeStatistics obj's underlying member method code with example usage: obj.transform(dicts) and returns: merged_stats