code: def read_partitioned_to_pandas(
      self,
      f,
      partitions: Dict,
      partition_keys: Dict,
      columns=None,
      nrows=None,
      use_arrow_dtype=None,
      **kwargs,
  ):
      raw_df = self.read_to_pandas(
          f,
          columns=columns,
          nrows=nrows,
          use_arrow_dtype=use_arrow_dtype,
          **kwargs,
      )
      for col, value in partition_keys.items():
          dictionary = partitions[col]
          raw_df[col] = pd.Series(
              value,
              dtype=pd.CategoricalDtype(categories=dictionary.tolist()),
              index=raw_df.index,
          )
      return raw_df
  
imports: import os
  from typing import Dict
  from urllib.parse import urlparse
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...lib.filesystem import file_size, get_fs, glob, open_file, FileSystem
  from ...serialization.serializables import AnyField, BoolField, DictField, ListField, StringField, Int32Field, Int64Field
  from ...utils import is_object_dtype, lazy_import
  from ..arrays import ArrowStringDtype
  from ..operands import OutputType
  from ..utils import parse_index, to_arrow_dtypes, contain_arrow_dtype
  from .core import IncrementalIndexDatasource, ColumnPruneSupportedDataSourceMixin, IncrementalIndexDataSourceMixin, merge_small_files
label_desc: Use image node_id 5 for calling the ParquetEngine obj's underlying member method code with example usage: obj.read_partitioned_to_pandas(f, partitions, partition_keys, columns, nrows, use_arrow_dtype) and returns: raw_df