code: def plot_result(dataframe):
      """
      The function draws a graph based on the dataframe
  
      :param dataframe: dataframe with columns 'date','temperature','ridge','composite',
      'with_gap'
      """
  
      gap_array = np.array(dataframe["with_gap"])
      masked_array = np.ma.masked_where(gap_array == -100.0, gap_array)
  
      plt.plot(
          dataframe["date"],
          dataframe["temperature"],
          c="blue",
          alpha=0.5,
          label="Actual values",
          linewidth=1,
      )
      plt.plot(
          dataframe["date"],
          dataframe["ridge"],
          c="orange",
          alpha=0.8,
          label="Bi-directional ridge gap-filling",
          linewidth=1,
      )
      plt.plot(
          dataframe["date"],
          dataframe["composite"],
          c="red",
          alpha=0.8,
          label="Composite gap-filling",
          linewidth=1,
      )
      plt.plot(dataframe["date"], masked_array, c="blue")
      plt.grid()
      plt.legend()
      plt.show()
  
file_path: FEDOT/cases/time_series_gapfilling_case.py
imports: import os
  import matplotlib.pyplot
  import numpy
  import pandas
  from sklearn.metrics import mean_absolute_error, mean_squared_error, median_absolute_error
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.utils import fedot_project_root
  from fedot.utilities.ts_gapfilling import ModelGapFiller
label_desc: Use image node_id 2 for calling a global function with example usage: plot_result(dataframe) without return types