code: def _test_all(
      data: pd.Series,
      data_name: Optional[str] = None,
      alpha: float = 0.05,
      data_kwargs: Optional[Dict] = None,
  ) -> pd.DataFrame:
      """Performs several tests on on the time series data
  
      - Summary Statistics
      - Ljung-Box Test for white noise
      - ADF test for difference stationarity
      - KPSS test for trend stationarity
      - Shapiro Test for Normality
  
      Parameters
      ----------
      data : pd.Series
          Time Series data on which the test needs to be performed
      alpha : float, optional
          Significance Level, by default 0.05
      data_kwargs : Optional[Dict], optional
          Users can specify `lags list` or `order_list` to run the test for the
          data as well as for its lagged versions, by default None
  
          >>> _test_all(data=data, data_kwargs={"order_list": [1, 2]})
          >>> _test_all(data=data, data_kwargs={"lags_list": [1, [1, 12]]})
  
      Returns
      -------
      pd.DataFrame
          Detailed results dataframe
      """
      result_summary_stats = _summary_stats(
          data=data, data_name=data_name, data_kwargs=data_kwargs
      )
      result_wn = _is_white_noise(
          data,
          data_name=data_name,
          alpha=alpha,
          verbose=True,
          data_kwargs=data_kwargs,
      )
      result_adf = _is_stationary_adf(
          data,
          data_name=data_name,
          alpha=alpha,
          verbose=True,
          data_kwargs=data_kwargs,
      )
      result_kpss = _is_stationary_kpss(
          data,
          data_name=data_name,
          alpha=alpha,
          verbose=True,
          data_kwargs=data_kwargs,
      )
      result_normality = _is_gaussian(
          data,
          data_name=data_name,
          alpha=alpha,
          verbose=True,
          data_kwargs=data_kwargs,
      )
  
      all_dfs = [
          result_summary_stats,
          result_wn[1],
          result_adf[1],
          result_kpss[1],
          result_normality[1],
      ]
      final = pd.concat(all_dfs)
      return final
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import numpy
  import pandas
  import statsmodels.api
  from pmdarima.arima.utils import ndiffs, nsdiffs
  from statsmodels.tools.sm_exceptions import MissingDataError
  from statsmodels.tsa.api import kpss
  from statsmodels.tsa.stattools import adfuller
  from pycaret.internal.logging import get_logger
  from pycaret.internal.tests import _format_test_results
  from pycaret.internal.tests.stats import _is_gaussian, _summary_stats
  from pycaret.utils.time_series import _get_diff_name_list
  from pycaret.utils.time_series.exceptions import MissingDataError
label_desc: Use image node_id 2 for calling a global function with example usage: _test_all(data, data_name, alpha, data_kwargs) and returns: final