class_docstr: Determines the `n` most common elements.
  
  Description:
      Given a list of values, return the `n` values
      which appear the most frequently. If there are
      fewer than `n` unique values, the output will be
      filled with `NaN`.
  
  Args:
      n (int): defines "n" in "n most common." Defaults
          to 3.
  
  Examples:
      >>> n_most_common = NMostCommon(n=2)
      >>> x = ['orange', 'apple', 'orange', 'apple', 'orange', 'grapefruit']
      >>> n_most_common(x).tolist()
      ['orange', 'apple']
code: def __init__(self, n=3):
      self.n = n
      self.number_output_features = n
      self.description_template = [
          "the {} most common values of {{}}".format(n),
          "the most common value of {}",
          *["the {nth_slice} most common value of {}"] * (n - 1),
      ]
  
imports: import numpy
  from woodwork.column_schema import ColumnSchema
  from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
  from featuretools.utils.gen_utils import Library
label_desc: Use image node_id 1 to create a new NMostCommon object from inherited base classes: AggregationPrimitive with example: obj = NMostCommon(n)