code: def occupation_transform(occ_string):
      """Perform some simple manipulations."""
      result = "Small"
      # The isinstance check is to guard against 'missing'
      # data marked with NaN
      if not isinstance(occ_string, float) and occ_string.startswith(
          "Machine"
      ):
          result = "Large"
      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 3 for calling a global function with example usage: occupation_transform(occ_string) and returns: result