code: def get_numeric_features_to_observed_range(examples):
    
    observed_features = collections.defaultdict(list)  # name -> [value, ]
    for example in examples:
      for feature_name in get_numeric_feature_names(example):
        original_feature = parse_original_feature_from_example(
            example, feature_name)
        observed_features[feature_name].extend(original_feature.original_value)
    return {
        feature_name: {
            'observedMin': min(feature_values),
            'observedMax': max(feature_values),
        }
        for feature_name, feature_values in iteritems(observed_features)
    }
docs: Returns numerical features and their observed ranges.
  
    Args:
      examples: Examples to read to get ranges.
  
    Returns:
      A dict mapping feature_name -> {'observedMin': 'observedMax': } dicts,
      with a key for each numerical feature.