code: def visualize_multiple_files(
      file_list: List[Union[str, Path]]
  ) -> FigureResampler:
      """Create FigureResampler where each subplot row represents all signals from a file.
  
      Parameters
      ----------
      file_list: List[Union[str, Path]]
  
      Returns
      -------
      FigureResampler
          Returns a view of the existing, global FigureResampler object.
  
      """
      fig = FigureResampler(
          make_subplots(rows=len(file_list), shared_xaxes=False),
          default_downsampler=MinMaxLTTB(parallel=True),
      )
      fig.update_layout(height=min(900, 350 * len(file_list)))
  
      for i, f in enumerate(file_list, 1):
          df = pd.read_parquet(
              f
          )  # TODO: replace with more generic data loading code
          if "timestamp" in df.columns:
              df = df.set_index("timestamp")
  
          for c in df.columns[::-1]:
              fig.add_trace(
                  go.Scattergl(name=c),
                  hf_x=df.index,
                  hf_y=df[c],
                  row=i,
                  col=1,
              )
      return fig
  
imports: from pathlib import Path
  from typing import List, Union
  import pandas
  import plotly.graph_objects
  from plotly.subplots import make_subplots
  from plotly_resampler import FigureResampler
  from plotly_resampler.aggregation import MinMaxLTTB
label_desc: Use image node_id 1 for calling a global function with example usage: visualize_multiple_files(file_list) and returns: fig