class_docstr: Fetch trial component data and make them accessible for analytics.
docstr: Reshape trial component metrics to a pandas column.
  
  Args:
      metrics: trial component metrics
  Returns:
      dict: Key: Metric name, Value: Metric value
docstr_tok: ["Reshape","trial","component","metrics","to","a","pandas","column",".","Args",":","metrics",":","trial","component","metrics","Returns",":","dict",":","Key",":","Metric","name",",","Value",":","Metric","value"]
code: def _reshape_metrics(self, metrics):
      """Reshape trial component metrics to a pandas column.
  
      Args:
          metrics: trial component metrics
      Returns:
          dict: Key: Metric name, Value: Metric value
      """
      statistic_types = ["Min", "Max", "Avg", "StdDev", "Last", "Count"]
      out = OrderedDict()
      for metric_summary in metrics:
          metric_name = metric_summary["MetricName"]
          if (
              self._metric_names
              and metric_name not in self._metric_names
          ):
              continue
  
          for stat_type in statistic_types:
              stat_value = metric_summary.get(stat_type)
              if stat_value is not None:
                  out[
                      "{} - {}".format(metric_name, stat_type)
                  ] = stat_value
      return out
  
imports: from __future__ import print_function, absolute_import
  from abc import ABCMeta, abstractmethod
  from collections import defaultdict, OrderedDict
  import datetime
  import logging
  from six import with_metaclass
  from sagemaker.session import Session
  from sagemaker.utils import DeferredError
  from sagemaker.lineage import artifact
label_desc: Use image node_id 6 for calling the ExperimentAnalytics obj's underlying member method code with example usage: obj._reshape_metrics(metrics) and returns: out