code: def test_check_time_series2():
      """Checks value column stats"""
      ts = UnivariateTimeSeries()
      df = pd.DataFrame(
          {
              TIME_COL: [
                  dt(2018, 1, 1, 0, 0, 1),
                  dt(2018, 1, 1, 0, 0, 2),
                  dt(2018, 1, 1, 0, 0, 3),
              ],
              VALUE_COL: [1, 2, 3],
          }
      )
      ts.load_data(df, TIME_COL, VALUE_COL)
      assert ts.value_stats["mean"] == 2.0
      assert ts.value_stats["std"] == 1.0
      assert ts.value_stats["min"] == 1.0
      assert ts.value_stats["25%"] == 1.5
      assert ts.value_stats["50%"] == 2.0
      assert ts.value_stats["75%"] == 2.5
      assert ts.value_stats["max"] == 3.0
      assert ts.df[VALUE_COL].equals(ts.y)
  
imports: import datetime
  from datetime import datetime
  import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from greykite.common.constants import ADJUSTMENT_DELTA_COL
  from greykite.common.constants import END_TIME_COL
  from greykite.common.constants import METRIC_COL
  from greykite.common.constants import START_TIME_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.python_utils import assert_equal
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.common.testing_utils import generate_df_with_reg_for_tests
  from greykite.common.time_properties import get_canonical_data
  from greykite.common.viz.timeseries_plotting import add_groupby_column
  from greykite.framework.benchmark.data_loader_ts import DataLoaderTS
  from greykite.framework.constants import MEAN_COL_GROUP
  from greykite.framework.constants import OVERLAY_COL_GROUP
  from greykite.framework.constants import QUANTILE_COL_GROUP
  from greykite.framework.input.univariate_time_series import UnivariateTimeSeries
label_desc: Use image node_id 2 for calling a global function with example usage: test_check_time_series2() without return types