input: Write a Python function to create a customer profile from a dataset based on feature frequency.
  assert create_customer_profile(pd.DataFrame({'A': [1, 2, 1, 1], 'B': [1, 1, 2, 2]})) == {1: 'High', 2: 'Medium'}
  assert create_customer_profile(pd.DataFrame({'A': [3, 3, 3, 4], 'B': [4, 4, 3, 3]})) == {3: 'High', 4: 'Medium'}
  assert create_customer_profile(pd.DataFrame({'A': [5, 6, 5, 6], 'B': [6, 5, 6, 5]})) == {5: 'High', 6: 'High'}
output: import pandas as pd
  
  def create_customer_profile(df):
      frequency = df.apply(pd.Series.value_counts).sum(axis=1)
      max_freq = frequency.max()
      
      profile = {}
      for feature, count in frequency.items():
          if count == max_freq:
              profile[feature] = 'High'
          else:
              profile[feature] = 'Medium'
      
      return profile