code: def plot_time_series(
      df,
      col,
      decompose=False,
      model="additive",
      compute_backend=None,
      viz_backend=None,
      **kwargs,
  ):
      """Plots time series given a dataframe with datetime index. Statistics are computed using the statsmodels API.
  
      Args:
          df: The dataframe with datetime index
          col (str or [str]): Column of interest. Column datatype must be numerical
          decompose: Set as True to decompose the timeseries with moving average. Defaults to False.
          model: Specify seasonal component when decompose is True. Defaults to "additive".
          compute_backend: Select computing backend. Defaults to None (pandas).
          viz_backend: Select visualization backend. Defaults to None (seaborn).
          **kwargs: Keyword arguments
  
      Raises:
          ValueError: Invalid input data type.
          ValueError: ```col``` not a list or string.
  
      Returns:
          The visualization
      """
      if not _is_dataframe(df):
          raise ValueError("Unsupported input data type")
      if not isinstance(col, (list, str)):
          raise ValueError(f"{col} must be list type or string type")
      if decompose:
          result = _get_compute_backend(
              compute_backend, df
          ).compute_decompose_timeseries(
              df, col=col, model=model, **kwargs
          )
          fig = _get_viz_backend(viz_backend).viz_plot_time_series(
              df, col=col, result=result, decompose=decompose, **kwargs
          )
      else:
          fig = _get_viz_backend(viz_backend).viz_plot_time_series(
              df, col, **kwargs
          )
      return fig
  
imports: import warnings
  from typing import Optional
  import matplotlib.pyplot
  import seaborn
  import pandas
  import numpy
  import plotly.graph_objs
  from plotly.subplots import make_subplots
  from plotly.offline import init_notebook_mode, iplot
  from data_describe.config._config import get_option
  from data_describe.backends import _get_viz_backend, _get_compute_backend
  from data_describe.compat import _is_dataframe, _compat, _requires, _in_notebook
label_desc: Use image node_id 1 for calling a global function with example usage: plot_time_series(df, col, decompose, model, compute_backend, viz_backend) and returns: fig