code: def testLoadMetricsAsDataFrame_DoubleValueOnly(self):
      dfs = dataframe.metrics_as_dataframes(self.metrics_for_slices)
  
      expected = pd.DataFrame(
          {
              ("slices", "age"): [38.0, 38.0, None],
              ("slices", "sex"): [b"Female", b"Female", None],
              ("slices", "Overall"): [None, None, ""],
              ("metric_keys", "name"): [
                  "mean_absolute_error",
                  "mean_squared_logarithmic_error",
                  "mean_absolute_error",
              ],
              ("metric_keys", "model_name"): ["", "", ""],
              ("metric_keys", "output_name"): ["", "", ""],
              ("metric_keys", "example_weighted"): [False, False, None],
              ("metric_keys", "is_diff"): [False, False, False],
              ("metric_values", "double_value"): [0.1, 0.02, 0.3],
          }
      )
      pd.testing.assert_frame_equal(expected, dfs.double_value)
  
imports: import dataclasses
  import numpy
  import pandas
  import tensorflow
  from tensorflow_model_analysis.experimental import dataframe
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from google.protobuf import text_format
label_desc: Use image node_id 2 for calling the MetricsAsDataFrameTest obj's underlying member method code with example usage: obj.testLoadMetricsAsDataFrame_DoubleValueOnly() without return types