class_docstr: The config analyzer evaluates a single model configuration by obtaining its
  performance from a tracker across datasets and compiling it into a
  dataframe.
docstr: Args:
      tracker: The tracker which is used to obtain performances.
docstr_tok: ["Args",":","tracker",":","The","tracker","which","is","used","to","obtain","performances","."]
code: def __init__(self, tracker: ModelTracker):
      """
      Args:
          tracker: The tracker which is used to obtain performances.
      """
      self.tracker = tracker
      self.datasets = {
          c.dataset
          for c in self.tracker.get_evaluations().configurations
      }
  
imports: from typing import Dict, Union
  import pandas
  from tsbench.config import Config, ModelConfig
  from tsbench.evaluations.metrics import Performance
  from tsbench.evaluations.tracking import ModelTracker
label_desc: Use image node_id 1 to create a new ConfigAnalyzer object  with example: obj = ConfigAnalyzer(tracker)