code: def identify_infotypes(
      df,
      engine_backend,
      sample_size=_SAMPLE_SIZE,
      score_threshold=_DEFAULT_SCORE_THRESHOLD,
  ):
      """Identify infotypes for each column in the dataframe.
  
      Args:
          df (DataFrame): The dataframe
          engine_backend: The backend analyzer engine. Default is presidio_analyzer.
          sample_size (int): Number of rows to sample from
          score_threshold (float): Minimum confidence value for detected entities to be returned
  
      Returns:
          Dictionary with columns as keys and values as infotypes detected
      """
      return {
          col: identify_column_infotypes(
              df[col],
              engine_backend=engine_backend,
              sample_size=sample_size,
              score_threshold=score_threshold,
          )
          for col in df.columns
      }
  
imports: import hashlib
  import logging
  from functools import reduce
  from typing import Optional, Union
  import warnings
  from data_describe.misc.logging import OutputLogger
  from data_describe.backends import _get_compute_backend
  from data_describe.compat import _is_dataframe, _compat, _requires
  from data_describe.config._config import get_option
  from data_describe._widget import BaseWidget
label_desc: Use image node_id 7 for calling a global function with example usage: identify_infotypes(df, engine_backend, sample_size, score_threshold) and returns: unknown