code: def make_time_series(
      start=start,
      target=target,
      feat_static_cat=fsc,
      feat_static_real=fsr,
      num_feat_dynamic_cat=1,
      num_feat_dynamic_real=1,
      num_past_feat_dynamic_real=1,
  ) -> DataEntry:
      feat_dynamic_cat = (
          make_dummy_dynamic_feat(target, num_feat_dynamic_cat).astype(
              "int64"
          )
          if num_feat_dynamic_cat > 0
          else None
      )
      feat_dynamic_real = (
          make_dummy_dynamic_feat(target, num_feat_dynamic_real).astype(
              "float"
          )
          if num_feat_dynamic_real > 0
          else None
      )
      past_feat_dynamic_real = (
          make_dummy_dynamic_feat(
              target, num_past_feat_dynamic_real
          ).astype("float")
          if num_past_feat_dynamic_real > 0
          else None
      )
      data = {
          "start": start,
          "target": target,
          "feat_static_cat": feat_static_cat,
          "feat_static_real": feat_static_real,
          "feat_dynamic_cat": feat_dynamic_cat,
          "feat_dynamic_real": feat_dynamic_real,
          "past_feat_dynamic_real": past_feat_dynamic_real,
      }
      return data
  
file_path: gluonts/test/dataset/test_stat.py
imports: import unittest
  from typing import cast
  import numpy
  import pandas
  from gluonts.dataset.common import DataEntry, Dataset
  from gluonts.dataset.stat import DatasetStatistics, ScaleHistogram, calculate_dataset_statistics
  from gluonts.exceptions import GluonTSDataError
label_desc: Use image node_id 2 for calling a global function with example usage: make_time_series(start, target, feat_static_cat, feat_static_real, num_feat_dynamic_cat, num_feat_dynamic_real, num_past_feat_dynamic_real) and returns: data