code: def test_explicit_scalar_cat(fill_df):
      """
      Test output if fill_value is a scalar, explicit is False,
      and one of the columns is of category dtype.
      """
      fill_df = fill_df.astype({"value1": "category"})
      result = fill_df.complete(
          "group",
          ("item_id", "item_name"),
          fill_value=0,
          explicit=False,
      ).astype({"value2": int})
      columns = ["group", "item_id", "item_name"]
      fill_df["value1"] = fill_df["value1"].cat.add_categories([0])
      expected = (
          fill_df.set_index(columns)
          .unstack("group", fill_value=0)
          .stack(dropna=False)
          .reset_index()
          .reindex(columns=fill_df.columns)
          .sort_values(columns, ignore_index=True)
          .astype(
              {
                  "value1": pd.CategoricalDtype(
                      categories=[1.0, 3.0, 4.0, 0.0], ordered=False
                  )
              }
          )
      )
      assert_frame_equal(result, expected, check_dtype=False)
  
imports: from string import ascii_lowercase
  import numpy
  import pandas
  import pytest
  from hypothesis import given, settings
  from pandas.testing import assert_frame_equal
  from janitor.testing_utils.strategies import categoricaldf_strategy
label_desc: Use image node_id 34 for calling a global function with example usage: test_explicit_scalar_cat(fill_df) without return types