code: def _parse_x_column(
      df: pd.DataFrame, x_from_user: str | None
  ) -> str | None:
      if x_from_user is None:
          return None
  
      elif isinstance(x_from_user, str):
          if x_from_user not in df.columns:
              raise StreamlitColumnNotFoundError(df, x_from_user)
  
          return x_from_user
  
      else:
          raise StreamlitAPIException(
              "x parameter should be a column name (str) or None to use the "
              f" dataframe's index. Value given: {x_from_user} "
              f"(type {type(x_from_user)})"
          )
  
imports: from __future__ import annotations
  from contextlib import nullcontext
  from datetime import date
  from enum import Enum
  from typing import TYPE_CHECKING, Any, Collection, Dict, List, Sequence, Tuple, cast
  import pandas
  from pandas.api.types import infer_dtype, is_integer_dtype
  from typing_extensions import Literal
  import streamlit.elements.arrow_vega_lite
  from streamlit import type_util
  from streamlit.color_util import Color, is_color_like, is_color_tuple_like, is_hex_color_like, to_css_color
  from streamlit.elements.altair_utils import AddRowsMetadata
  from streamlit.elements.arrow import Data
  from streamlit.elements.utils import last_index_for_melted_dataframes
  from streamlit.errors import Error, StreamlitAPIException
  from streamlit.proto.ArrowVegaLiteChart_pb2 import ArrowVegaLiteChart
  from streamlit.runtime.metrics_util import gather_metrics
label_desc: Use image node_id 10 for calling a global function with example usage: _parse_x_column(df, x_from_user) and returns: None, x_from_user