class_docstr: A TFX ml-metadata store that provides read-only methods for notebooks.
class_docstr_tok: ["A","TFX","ml-metadata","store","that","provides","read-only","methods","for","notebooks","."]
docstr: Displays stats for `examples_id`.
  
  Args:
    examples_id: A `int` indicating the id of a `TFXArtifactTypes.EXAMPLES`
      artifact.
    split: A `string` specifying the split name, by default 'train' is used.
docstr_tok: ["Displays","stats","for","`","examples_id","`",".","Args",":","examples_id",":","A","`","int","`","indicating","the","id","of","a","`","TFXArtifactTypes.EXAMPLES","`","artifact",".","split",":","A","`","string","`","specifying","the","split","name",",","by","default","'train","'","is","used","."]
code: def display_stats_for_examples(self, examples_id, split="train"):
      """Displays stats for `examples_id`.
  
      Args:
        examples_id: A `int` indicating the id of a `TFXArtifactTypes.EXAMPLES`
          artifact.
        split: A `string` specifying the split name, by default 'train' is used.
      """
      stats_artifact = self.get_dest_artifact_of_type(
          examples_id, TFXArtifactTypes.EXAMPLE_STATS
      )
      if stats_artifact:
          tfdv.visualize_statistics(
              tfdv.load_stats_binary(
                  os.path.join(
                      stats_artifact.uri, split, "FeatureStats.pb"
                  )
              )
          )
  
imports: import os
  import time
  import papermill
  import tensorflow_data_validation
  import tensorflow_model_analysis
  import utils
  from ml_metadata.metadata_store import metadata_store
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 4 for calling the TFXReadonlyMetadataStore obj's underlying member method code with example usage: obj.display_stats_for_examples(examples_id, split) without return types