code: def describe_categorical_1d_spark(
      config: Settings, df: DataFrame, summary: dict
  ) -> Tuple[Settings, DataFrame, dict]:
      """Describe a categorical series.
  
      Args:
          series: The Series to describe.
          summary: The dict containing the series description so far.
  
      Returns:
          A dict containing calculated series description values.
      """
  
      # FIXME: cat description
      redact = config.vars.cat.redact
      if not redact:
          summary["first_rows"] = (
              df.limit(5).toPandas().squeeze("columns")
          )
  
      return config, df, summary
  
imports: from typing import Tuple
  from pyspark.sql import DataFrame
  from ydata_profiling.config import Settings
  from ydata_profiling.model.summary_algorithms import describe_categorical_1d
label_desc: Use image node_id 1 for calling a global function with example usage: describe_categorical_1d_spark(config, df, summary) and returns: config,  df,  summary