code: def test_from_float():
      df = conversion_data()
      data_id, column_type = "1", "type_conversion"
      i = 0
      build_data_inst({data_id: df})
  
      cfg = {"col": "float", "to": "int", "from": "float"}
      builder = ColumnBuilder(
          data_id, column_type, "Col{}".format(++i), cfg
      )
      verify_builder(builder, lambda col: col.values[0] == 1)
  
      cfg = {"col": "float", "to": "str", "from": "float"}
      builder = ColumnBuilder(
          data_id, column_type, "Col{}".format(++i), cfg
      )
      verify_builder(builder, lambda col: col.values[0] == "1.5")
  
      cfg = {"col": "float", "to": "hex", "from": "float"}
      builder = ColumnBuilder(
          data_id, column_type, "Col{}".format(++i), cfg
      )
      verify_builder(
          builder, lambda col: col.values[0] == "0x1.8000000000000p+0"
      )
  
file_path: dtale/tests/dtale/column_builders/test_type_conversion.py
imports: import numpy
  import pandas
  import pytest
  from dtale.column_builders import ColumnBuilder
  from tests.dtale.column_builders.test_column_builders import verify_builder
  from tests.dtale import build_data_inst
label_desc: Use image node_id 5 for calling a global function with example usage: test_from_float() without return types