code: def test_encoder():
      df = pd.DataFrame(
          {
              "car": [
                  "Honda",
                  "Benze",
                  "Ford",
                  "Honda",
                  "Benze",
                  "Ford",
                  np.nan,
              ]
          }
      )
      data_id, column_type = "1", "encoder"
      build_data_inst({data_id: df})
  
      cfg = {"col": "car", "algo": "one_hot"}
      builder = ColumnBuilder(data_id, column_type, "Col1", cfg)
      verify_builder(
          builder,
          lambda col: all(
              [
                  col[c].isnull().sum() == 0
                  for c in ["car_Ford", "car_Honda"]
              ]
          ),
      )
  
      if parse_version(skl.__version__) >= parse_version("0.20.0"):
          cfg = {"col": "car", "algo": "ordinal"}
          builder = ColumnBuilder(data_id, column_type, "Col1", cfg)
          verify_builder(builder, lambda col: col.isnull().sum() == 0)
  
      if parse_version(skl.__version__) >= parse_version("0.12.0"):
          cfg = {"col": "car", "algo": "label"}
          builder = ColumnBuilder(data_id, column_type, "Col1", cfg)
          verify_builder(builder, lambda col: col.isnull().sum() == 0)
  
      if parse_version(skl.__version__) >= parse_version("0.13.0"):
          cfg = {"col": "car", "algo": "feature_hasher", "n": 1}
          builder = ColumnBuilder(data_id, column_type, "Col1", cfg)
          verify_builder(
              builder, lambda col: col["car_0"].isnull().sum() == 0
          )
  
imports: import numpy
  import pandas
  import pytest
  import sklearn
  from numpy.random import randn
  from pkg_resources import parse_version
  from six import PY3
  import dtale.pandas_util
  from dtale.column_builders import ColumnBuilder, ZERO_STD_ERROR
  from tests.dtale import build_data_inst
label_desc: Use image node_id 13 for calling a global function with example usage: test_encoder() without return types