class_docstr: Parameters for generating column of data
  
  Attributes
  ----------
  cardinality : int or None
      Size of a random set of values that generated data is sampled from.
      The values in the random set are derived from the given generator.
      If cardinality is None, the Iterable returned by the given generator
      is invoked for each value to be generated.
  null_frequency : 0.1
      Probability of a generated value being null
  generator : Callable
      Function for generating random data.
  is_sorted : bool
      Sort this column. Columns are sorted in same order as ColumnParameters
      instances stored in column_params of Parameters. If there are one or
      more columns marked as sorted, the generated PyArrow Table will be
      converted to a Pandas DataFrame to do the sorting. This may implicitly
      convert numbers to floats in the presence of nulls.
  dtype : optional
      a numpy dtype to control the format of the data
class_docstr_tok: ["Parameters","for","generating","column","of","data","Attributes","--","--","--","--","--","cardinality",":","int","or","None","Size","of","a","random","set","of","values","that","generated","data","is","sampled","from",".","The","values","in","the","random","set","are","derived","from","the","given","generator",".","If","cardinality","is","None",",","the","Iterable","returned","by","the","given","generator","is","invoked","for","each","value","to","be","generated",".","null_frequency",":","0.1","Probability","of","a","generated","value","being","null","generator",":","Callable","Function","for","generating","random","data",".","is_sorted",":","bool","Sort","this","column",".","Columns","are","sorted","in","same","order","as","ColumnParameters","instances","stored","in","column_params","of","Parameters",".","If","there","are","one","or","more","columns","marked","as","sorted",",","the","generated","PyArrow","Table","will","be","converted","to","a","Pandas","DataFrame","to","do","the","sorting",".","This","may","implicitly","convert","numbers","to","floats","in","the","presence","of","nulls",".","dtype",":","optional","a","numpy","dtype","to","control","the","format","of","the","data"]
code: def __init__(
      self,
      cardinality=100,
      null_frequency=0.1,
      generator=lambda: [
          _generate_string(string.ascii_letters, random.randint(4, 8))
          for _ in range(100)
      ],
      is_sorted=True,
      dtype=None,
  ):
      self.cardinality = cardinality
      self.null_frequency = null_frequency
      self.generator = generator
      self.is_sorted = is_sorted
      self.dtype = dtype
  
imports: import copy
  import random
  import string
  import uuid
  from multiprocessing import Pool
  import numpy
  import pandas
  import pyarrow
  from pyarrow import parquet
  import cudf
  from cudf.utils.dtypes import np_to_pa_dtype
label_desc: Use image node_id 1 to create a new ColumnParameters object  with example: obj = ColumnParameters(cardinality, null_frequency, generator, is_sorted, dtype)