class_docstr: Represents a Pandas DataFrame for use with MLflow Tracking.
class_docstr_tok: ["Represents","a","Pandas","DataFrame","for","use","with","MLflow","Tracking","."]
docstr: An instance of :py:class:`mlflow.types.Schema` representing the tabular dataset. May be
  ``None`` if the schema cannot be inferred from the dataset.
docstr_tok: ["An","instance","of",":","py",":","class",":","`","mlflow.types.Schema","`","representing","the","tabular","dataset",".","May","be","``","None","``","if","the","schema","can","not","be","inferred","from","the","dataset","."]
code: def schema(self) -> Optional[Schema]:
      """
      An instance of :py:class:`mlflow.types.Schema` representing the tabular dataset. May be
      ``None`` if the schema cannot be inferred from the dataset.
      """
      try:
          return _infer_schema(self._df)
      except Exception as e:
          _logger.warning(
              "Failed to infer schema for Pandas dataset. Exception: %s",
              e,
          )
          return None
  
imports: import json
  import logging
  from functools import cached_property
  from typing import Any, Dict, Optional, Union
  import pandas
  from mlflow.data.dataset import Dataset
  from mlflow.data.dataset_source import DatasetSource
  from mlflow.data.digest_utils import compute_pandas_digest
  from mlflow.data.pyfunc_dataset_mixin import PyFuncConvertibleDatasetMixin, PyFuncInputsOutputs
  from mlflow.exceptions import MlflowException
  from mlflow.models.evaluation.base import EvaluationDataset
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.types import Schema
  from mlflow.types.utils import _infer_schema
  from mlflow.utils.annotations import experimental
label_desc: Use image node_id 9 for calling the PandasDataset obj's underlying member method code with example usage: obj.schema() and returns: _infer_schema, None