code: def decomp_subplot(
      fig: go.Figure,
      data: pd.Series,
      col: int,
      plot: str,
      classical_decomp_type: str,
      period: int,
  ) -> go.Figure:
      """Function to add decomposition to a Plotly subplot
  
      Parameters
      ----------
      fig : go.Figure
          Plotly figure to which the decomposition plots need to be added
      data : pd.Series
          Data whose decomposition must be added
      col : int
          Column of the figure where the plot needs to be inserted. Starts from 1.
          Note that rows do not need to be specified since there will be 4 rows
          per column. Must be enforced from outside when creating the figure.
      plot : str
          Options are
            - "decomp": for Classical Decomposition
            - "decomp_stl": for STL Decomposition
      classical_decomp_type : str
          The classical decomposition type. Options are: ["additive", "multiplicative"]
      period : int
          The seasonal period to use for decomposition
  
      Returns
      -------
      go.Figure
          Returns back the plotly figure with the decomposition results inserted.
      """
  
      data_ = (
          data.to_timestamp()
          if isinstance(data.index, pd.PeriodIndex)
          else data
      )
  
      x = (
          data.index.to_timestamp()
          if isinstance(data.index, pd.PeriodIndex)
          else data.index
      )
  
      # Plot Original data ----
      row = 1
      fig.add_trace(
          go.Scattergl(
              x=x,
              y=data_,
              line=dict(color=DEFAULT_PLOTLY_COLORS[row - 1], width=2),
              mode="lines+markers",
              name="Actual",
              marker=dict(size=2),
          ),
          row=row,
          col=col,
      )
  
      if plot == "decomp":
          try:
              decomp_result = seasonal_decompose(
                  data_, period=period, model=classical_decomp_type
              )
          except ValueError as exception:
              logger.warning(exception)
              logger.warning(
                  "Seasonal Decompose plot failed most likely due to missing data"
              )
              return fig, None
      elif plot == "decomp_stl":
          decomp_result = STL(data_, period=period).fit()
  
      row = 2
      fig.add_trace(
          go.Scattergl(
              x=x,
              y=decomp_result.seasonal,
              line=dict(color=DEFAULT_PLOTLY_COLORS[row - 1], width=2),
              mode="lines+markers",
              name="Seasonal",
              marker=dict(size=2),
          ),
          row=row,
          col=col,
      )
  
      row = 3
      fig.add_trace(
          go.Scattergl(
              x=x,
              y=decomp_result.trend,
              line=dict(color=DEFAULT_PLOTLY_COLORS[row - 1], width=2),
              mode="lines+markers",
              name="Trend",
              marker=dict(size=2),
          ),
          row=row,
          col=col,
      )
  
      row = 4
      fig.add_trace(
          go.Scattergl(
              x=x,
              y=decomp_result.resid,
              line=dict(color=DEFAULT_PLOTLY_COLORS[row - 1], width=2),
              mode="markers",
              name="Residuals",
              marker=dict(
                  size=4,
              ),
          ),
          row=row,
          col=col,
      )
  
      return fig, decomp_result
  
imports: from math import ceil
  from typing import Any, Dict, List, Optional, Tuple, Union
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import plotly.express
  import plotly.graph_objects
  import plotly.io
  from plotly.colors import DEFAULT_PLOTLY_COLORS
  from plotly.subplots import make_subplots
  from scipy.fft import fft, fftfreq
  from scipy.signal import periodogram
  from statsmodels.graphics.gofplots import qqplot
  from statsmodels.tsa.seasonal import STL, seasonal_decompose
  from statsmodels.tsa.stattools import acf, ccf, pacf
  from pycaret.internal.logging import get_logger
  from pycaret.utils.generic import _resolve_dict_keys
  from pycaret.utils.time_series import TSAllowedPlotDataTypes
label_desc: Use image node_id 7 for calling a global function with example usage: decomp_subplot(fig, data, col, plot, classical_decomp_type, period) and returns: fig,  decomp_result, fig,  None