parameters: (self, i, columns=None, use_threads=True,
                         use_pandas_metadata=False)
return_statement: return self.reader.read_row_group(i, column_indices=column_indices,
                                            use_threads=use_threads)
docstring: Read a single row group from a Parquet file.
  
          Parameters
          ----------
          i : int
              Index of the individual row group that we want to read.
          columns : list
              If not None, only these columns will be read from the row group. A
              column name may be a prefix of a nested field, e.g. 'a' will select
              'a.b', 'a.c', and 'a.d.e'.
          use_threads : bool, default True
              Perform multi-threaded column reads.
          use_pandas_metadata : bool, default False
              If True and file has custom pandas schema metadata, ensure that
              index columns are also loaded.
  
          Returns
          -------
          pyarrow.table.Table
              Content of the row group as a table (of columns)
docstring_summary: Read a single row group from a Parquet file.
docstring_tokens: Read a single row group from a Parquet file .
function: def read_row_group(self, i, columns=None, use_threads=True,
                         use_pandas_metadata=False):
          """
          Read a single row group from a Parquet file.
  
          Parameters
          ----------
          i : int
              Index of the individual row group that we want to read.
          columns : list
              If not None, only these columns will be read from the row group. A
              column name may be a prefix of a nested field, e.g. 'a' will select
              'a.b', 'a.c', and 'a.d.e'.
          use_threads : bool, default True
              Perform multi-threaded column reads.
          use_pandas_metadata : bool, default False
              If True and file has custom pandas schema metadata, ensure that
              index columns are also loaded.
  
          Returns
          -------
          pyarrow.table.Table
              Content of the row group as a table (of columns)
          """
          column_indices = self._get_column_indices(
              columns, use_pandas_metadata=use_pandas_metadata)
          return self.reader.read_row_group(i, column_indices=column_indices,
                                            use_threads=use_threads)
function_tokens: def read_row_group ( self , i , columns = None , use_threads = True , use_pandas_metadata = False ) : column_indices = self . _get_column_indices ( columns , use_pandas_metadata = use_pandas_metadata ) return self . reader . read_row_group ( i , column_indices = column_indices , use_threads = use_threads )