code: def get_top_n(self, data):
      from pyspark.pandas import DataFrame, Series
  
      max_rows = get_option("plotting.max_rows")
      # Simply use the first 1k elements and make it into a pandas dataframe
      # For categorical variables, it is likely called from df.x.value_counts().plot.xxx().
      if isinstance(data, (Series, DataFrame)):
          data = data.head(max_rows + 1)._to_pandas()
      else:
          raise TypeError(
              "Only DataFrame and Series are supported for plotting."
          )
  
      self.partial = False
      if len(data) > max_rows:
          self.partial = True
          data = data.iloc[:max_rows]
      return data
  
imports: import importlib
  import pandas
  import numpy
  from pandas.core.base import PandasObject
  from pandas.core.dtypes.inference import is_integer
  from pyspark.ml.feature import Bucketizer
  from pyspark.mllib.stat import KernelDensity
  from pyspark.sql import functions
  from pyspark.pandas.missing import unsupported_function
  from pyspark.pandas.config import get_option
  from pyspark.pandas.utils import name_like_string
label_desc: Use image node_id 1 for calling the TopNPlotBase obj's underlying member method code with example usage: obj.get_top_n(data) and returns: data