code: def test_reformat_dataframes_for_plots():
      """Tests for _reformat_dataframes_for_plots"""
      df1 = pd.DataFrame({"a": [1, 2], "b": [3, 4], "c": [5, 6]})
      df2 = pd.DataFrame({"a": [1, 2], "b": [3, 4], "c": [5, 6]})
      input_dfs = [df1, df2]
      labels_suffix = ["original", "imputed"]
      expected_cols = [
          ["a (original)", "a (imputed)"],
          ["b (original)", "b (imputed)"],
          ["c (original)", "c (imputed)"],
      ]
  
      # 1. Correct Working ----
      output_dfs = _reformat_dataframes_for_plots(
          data=input_dfs, labels_suffix=labels_suffix
      )
  
      assert isinstance(output_dfs, List)
      for item, expected_cols in zip(output_dfs, expected_cols):
          assert isinstance(item, pd.DataFrame)
          assert item.columns.to_list() == expected_cols
  
      # Error raised ----
      with pytest.raises(ValueError) as errmsg:
          labels_suffix = ["original"]
          output_dfs = _reformat_dataframes_for_plots(
              data=input_dfs, labels_suffix=labels_suffix
          )
  
      # Capture Error message
      exceptionmsg = errmsg.value.args[0]
  
      # Check exact error received
      assert (
          "does not match the number of input dataframes"
          in exceptionmsg
      )
  
file_path: pycaret/tests/test_time_series_utils_plots.py
imports: from typing import List
  import pandas
  import pytest
  from plotly.subplots import make_subplots
  from time_series_test_utils import _ALL_PLOTS
  from pycaret.internal.plots.utils.time_series import ALLOWED_PLOT_DATA_TYPES, MULTIPLE_PLOT_TYPES_ALLOWED_AT_ONCE, _get_data_types_to_plot, _plot_fig_update, _reformat_dataframes_for_plots
label_desc: Use image node_id 2 for calling a global function with example usage: test_reformat_dataframes_for_plots() without return types