code: def get_column_type(
      column: pd.Series,
  ) -> Literal["float", "int", "string", "time", "other"]:
      """Get the type of column."""
      if is_float_dtype(column):
          return "float"
      elif is_numeric_dtype(column):
          return "int"
      elif is_datetime64_any_dtype(column):
          return "time"
  
      try:
          column: pd.Series = pd.to_numeric(column)
          if is_float_dtype(column):
              return "float"
          else:
              return "int"
      except ValueError:
          return "string"
      # Non-string objects like pd.Timestamp results in TypeError
      except TypeError:
          return "other"
  
file_path: deepchecks/deepchecks/utils/type_inference.py
imports: import typing
  import numpy
  import pandas
  from pandas.core.dtypes.common import is_datetime64_any_dtype, is_float_dtype, is_numeric_dtype
  from typing_extensions import Literal
  from deepchecks.utils.logger import get_logger
  from deepchecks.utils.typing import Hashable
  from deepchecks.utils.validation import ensure_hashable_or_mutable_sequence
label_desc: Use image node_id 4 for calling a global function with example usage: get_column_type(column) and returns: str, str, str, str, str, str, str