class_docstr: An ml-metadata store that provides read-only methods for notebooks.
class_docstr_tok: ["An","ml-metadata","store","that","provides","read-only","methods","for","notebooks","."]
docstr: Returns a `pd.DataFrame` for an artifact with `artifact_id`.
  
  Args:
    artifact_id: An `int` indicating the id of an artifact in the store.
  
  Returns:
    A `pd.DataFrame` to display the properties of the artifact corresponding
    to `artifact_id` or None if no such artifact exists in the store.
docstr_tok: ["Returns","a","`","pd.DataFrame","`","for","an","artifact","with","`","artifact_id","`",".","Args",":","artifact_id",":","An","`","int","`","indicating","the","id","of","an","artifact","in","the","store",".","Returns",":","A","`","pd.DataFrame","`","to","display","the","properties","of","the","artifact","corresponding","to","`","artifact_id","`","or","None","if","no","such","artifact","exists","in","the","store","."]
code: def get_artifact_df(self, artifact_id):
      """Returns a `pd.DataFrame` for an artifact with `artifact_id`.
  
      Args:
        artifact_id: An `int` indicating the id of an artifact in the store.
  
      Returns:
        A `pd.DataFrame` to display the properties of the artifact corresponding
        to `artifact_id` or None if no such artifact exists in the store.
      """
      artifacts = self.metadata_store.get_artifacts_by_id([artifact_id])
      return (
          self.get_df_from_single_artifact_or_execution(artifacts[0])
          if artifacts
          else None
      )
  
imports: import re
  from IPython.display import display_html
  import matplotlib.pyplot
  import networkx
  import pandas
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 4 for calling the ReadonlyMetadataStore obj's underlying member method code with example usage: obj.get_artifact_df(artifact_id) and returns: unknown