code: def lower_case_validator(
      df: pd.DataFrame, column: Any
  ) -> Remediation | None:
      """
      This validator will suggest to lowercase the column values, if more than a third of letters are uppercase.
      """
  
      def lower_case(x: Any) -> Any:
          x[column] = x[column].str.lower()
          return x
  
      count_upper = (
          df[column]
          .apply(
              lambda x: sum(1 for c in x if c.isalpha() and c.isupper())
          )
          .sum()
      )
      count_lower = (
          df[column]
          .apply(
              lambda x: sum(1 for c in x if c.isalpha() and c.islower())
          )
          .sum()
      )
  
      if count_upper * 2 > count_lower:
          return Remediation(
              name="lower_case",
              immediate_msg=f"\n- More than a third of your `{column}` column/key is uppercase. Uppercase {column}s tends to perform worse than a mixture of case encountered in normal language. We recommend to lower case the data if that makes sense in your domain. See https://platform.openai.com/docs/guides/fine-tuning/preparing-your-dataset for more details",
              optional_msg=f"Lowercase all your data in column/key `{column}`",
              optional_fn=lower_case,
          )
      return None
  
imports: from __future__ import annotations
  import os
  import sys
  from typing import Any, TypeVar, Callable, Optional, NamedTuple
  from typing_extensions import TypeAlias
  from .._extras import pandas
label_desc: Use image node_id 12 for calling a global function with example usage: lower_case_validator(df, column) and returns: None, x, Remediation