code: def display_anomalies(anomalies: anomalies_pb2.Anomalies) -> None:
      """Displays the input anomalies (for use in a Jupyter notebook).
  
      Args:
        anomalies: An Anomalies protocol buffer.
      """
      anomalies_df = get_anomalies_dataframe(anomalies)
      if anomalies_df.empty:
          display(
              HTML('<h4 style="color:green;">No anomalies found.</h4>')
          )
      else:
          display(anomalies_df)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import base64
  import collections
  import sys
  from typing import Dict, Iterable, List, Optional, Text, Tuple, Union
  import pandas
  from tensorflow_data_validation import types
  from tensorflow_data_validation.skew.protos import feature_skew_results_pb2
  from tensorflow_data_validation.utils import stats_util
  from tensorflow_metadata.proto.v0 import anomalies_pb2
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 6 for calling a global function with example usage: display_anomalies(anomalies) without return types