code: def get_elasticnet_coef_df(info_dict):
      """Gets the coefficients dataframe for Elastic Net regression models.
  
      Currently only returns the predictor names and their corresponding
      estimated coefficients.
  
      Parameters
      ----------
      info_dict : `dict`
          The information dictionary returned by
          `~greykite.algo.common.model_summary_utils.add_beta_var_lm`.
  
      Returns
      -------
      info_dict : `dict`
          The information dictionary with the following keys added:
  
              "coef_summary_df" : `pandas.DataFrame`
                  The summary df for estimated coefficients.
      """
      info_dict["coef_summary_df"] = pd.DataFrame(
          {
              "Pred_col": info_dict["pred_cols"],
              "Estimate": info_dict["beta"],
          }
      )
      return info_dict
  
imports: import numpy
  import pandas
  import statsmodels
  import statsmodels.api
  from scipy.stats import f
  from scipy.stats import norm
  from scipy.stats import t
  from sklearn.base import clone
  from sklearn.linear_model import Ridge
  from sklearn.model_selection import train_test_split
  from greykite.algo.common.col_name_utils import INTERCEPT
  from greykite.algo.common.col_name_utils import simplify_pred_cols
label_desc: Use image node_id 15 for calling a global function with example usage: get_elasticnet_coef_df(info_dict) and returns: info_dict