code: def marriage_transform(m_s_string):
      """Perform some simple manipulations."""
      result = "Low"
      if m_s_string.startswith("Married"):
          result = "Medium"
      elif m_s_string.startswith("Widowed"):
          result = "High"
      return result
  
file_path: fairlearn/examples/plot_new_metrics.py
imports: import functools
  import numpy
  import sklearn.metrics
  from sklearn.compose import ColumnTransformer
  from sklearn.compose import make_column_selector
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from fairlearn.datasets import fetch_adult
  from fairlearn.metrics import MetricFrame, count, selection_rate
label_desc: Use image node_id 2 for calling a global function with example usage: marriage_transform(m_s_string) and returns: result