code: def find_rare_class(series, verbose=0):
      ######### Print the % count of each class in a Target variable  #####
      """
      Works on Multi Class too. Prints class percentages count of target variable.
      It returns the name of the Rare class (the one with the minimum class member count).
      This can also be helpful in using it as pos_label in Binary and Multi Class problems.
      """
      return series.value_counts().index[-1]
  
imports: import pandas
  import numpy
  from itertools import combinations
  from sklearn.preprocessing import StandardScaler
  from category_encoders import HashingEncoder, SumEncoder, PolynomialEncoder, BackwardDifferenceEncoder
  from category_encoders import OneHotEncoder, HelmertEncoder, OrdinalEncoder, CountEncoder, BaseNEncoder
  from category_encoders import TargetEncoder, CatBoostEncoder, WOEEncoder, JamesSteinEncoder
  from category_encoders.glmm import GLMMEncoder
  from sklearn.preprocessing import LabelEncoder
  from category_encoders.wrapper import PolynomialWrapper
  from .encoders import FrequencyEncoder
  from .None import settings
  import pdb
  import copy
  import dask
  import dask.dataframe
label_desc: Use image node_id 1 for calling a global function with example usage: find_rare_class(series, verbose) and returns: series