code: def stationarity_test(
      df,
      col,
      test="dickey-fuller",
      regression="c",
      compute_backend=None,
      **kwargs,
  ):
      """Perform stationarity tests to see if mean and variance are changing over time.
  
      Backend uses statsmodel's statsmodels.tsa.stattools.adfuller or statsmodels.tsa.stattools.kpss
  
      Args:
          df: The dataframe. Must contain a datetime index
          col: The feature of interest
          test: Choice of stationarity test. "kpss" or "dickey-fuller". Defaults to "dickey-fuller".
          regression: Constant and trend order to include in regression. Choose between 'c','ct','ctt', and 'nc'. Defaults to 'c'
          compute_backend: Select computing backend. Defaults to None (pandas).
          **kwargs: Keyword arguments
  
      Raises:
          ValueError: Invalid input data type.
          ValueError: `col` not found in dataframe.
  
      Returns:
          Pandas dataframe containing the statistics
      """
      if not _is_dataframe(df):
          raise ValueError("Unsupported input data type")
      if not isinstance(col, str):
          raise ValueError(f"{col} not found in dataframe")
  
      data = _get_compute_backend(
          compute_backend, df
      ).compute_stationarity_test(df[col], test, regression, **kwargs)
      return data
  
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 2 for calling a global function with example usage: stationarity_test(df, col, test, regression, compute_backend) and returns: data