code: def _drop(
      df_or_series,
      labels=None,
      axis=0,
      index=None,
      columns=None,
      level=None,
      inplace=False,
      errors="raise",
  ):
      axis = validate_axis(axis, df_or_series)
      if labels is not None:
          if axis == 0:
              index = labels
          else:
              columns = labels
  
      if index is not None and errors == "raise":
          warnings.warn(
              "Errors will not raise for non-existing indices"
          )
      if isinstance(columns, Entity):
          raise NotImplementedError("Columns cannot be Mars objects")
  
      op = DataFrameDrop(
          index=index, columns=columns, level=level, errors=errors
      )
      df = op(df_or_series)
      if inplace:
          df_or_series.data = df.data
      else:
          return df
  
imports: import warnings
  from collections import OrderedDict
  import numpy
  from ...None import opcodes
  from ...core import Entity, Chunk, CHUNK_TYPE, OutputType, recursive_tile
  from ...serialization.serializables import AnyField, StringField
  from ..core import IndexValue, DATAFRAME_TYPE, SERIES_TYPE, INDEX_CHUNK_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index, validate_axis
label_desc: Use image node_id 1 for calling a global function with example usage: _drop(df_or_series, labels, axis, index, columns, level, inplace, errors) and returns: df