code: def test_pivot_mixed_case(connection):
      vf.runtime.set_connection(connection)
      source_0 = pd.DataFrame.from_records(
          [
              {"country": "Norway", "type": "gold", "count": 14},
              {"country": "Norway", "type": "silver", "count": 14},
              {"country": "Norway", "type": "Gold", "count": 11},
              {"country": "Germany", "type": "gold", "count": 14},
              {"country": "Germany", "type": "silver", "count": 10},
              {"country": "Germany", "type": "bronze", "count": 7},
              {"country": "Canada", "type": "gold", "count": 11},
              {"country": "Canada", "type": "silver", "count": 8},
              {"country": "Canada", "type": "bronze", "count": 10},
          ]
      )
      spec = json.loads(
          r"""
  {
    "$schema": "https://vega.github.io/schema/vega/v5.json",
    "data": [
      {
        "name": "source_0",
        "url": "table://source_0"
      },
      {
        "name": "data_0",
        "source": "source_0",
        "transform": [
          {
            "type": "pivot",
            "field": "type",
            "value": "count",
            "groupby": ["country"]
          }
        ]
      }
    ]
  }   
      """
      )
  
      datasets, warnings = vf.runtime.pre_transform_datasets(
          spec, ["data_0"], inline_datasets=dict(source_0=source_0)
      )
  
      assert set(datasets[0].columns.tolist()) == {
          "gold",
          "Gold",
          "silver",
          "bronze",
          "country",
      }
  
imports: import pandas
  import pytest
  from pandas import Timestamp, NaT
  import pyarrow
  import vegafusion
  import json
  import polars
  from datetime import date
  import decimal
  import base64
label_desc: Use image node_id 28 for calling a global function with example usage: test_pivot_mixed_case(connection) without return types