code: def test_data():
      data = get_stallion_data()
      data["month"] = data.date.dt.month.astype(str)
      data["log_volume"] = np.log1p(data.volume)
      data["weight"] = 1 + np.sqrt(data.volume)
  
      data["time_idx"] = (
          data["date"].dt.year * 12 + data["date"].dt.month
      )
      data["time_idx"] -= data["time_idx"].min()
  
      special_days = [
          "easter_day",
          "good_friday",
          "new_year",
          "christmas",
          "labor_day",
          "independence_day",
          "revolution_day_memorial",
          "regional_games",
          "fifa_u_17_world_cup",
          "football_gold_cup",
          "beer_capital",
          "music_fest",
      ]
      data[special_days] = (
          data[special_days]
          .apply(lambda x: x.map({0: "", 1: x.name}))
          .astype("category")
      )
  
      data = data[lambda x: x.time_idx < 10]  # downsample
      return data
  
file_path: pytorch-forecasting/tests/conftest.py
imports: import os
  import sys
  import numpy
  import pytest
  from pytorch_forecasting import TimeSeriesDataSet
  from pytorch_forecasting.data.examples import get_stallion_data
label_desc: Use image node_id 1 for calling a global function with example usage: test_data() and returns: data