code: def _col_params(
      result, float_format="%.4f", stars=True, include_r2=False
  ):
      """Stack coefficients and standard errors in single column"""
  
      # Extract parameters
      res = summary_params(result)
      # Format float
      for col in res.columns[:2]:
          res[col] = res[col].apply(lambda x: float_format % x)
      # Std.Errors in parentheses
      res.iloc[:, 1] = "(" + res.iloc[:, 1] + ")"
      # Significance stars
      if stars:
          idx = res.iloc[:, 3] < 0.1
          res.loc[idx, res.columns[0]] = (
              res.loc[idx, res.columns[0]] + "*"
          )
          idx = res.iloc[:, 3] < 0.05
          res.loc[idx, res.columns[0]] = (
              res.loc[idx, res.columns[0]] + "*"
          )
          idx = res.iloc[:, 3] < 0.01
          res.loc[idx, res.columns[0]] = (
              res.loc[idx, res.columns[0]] + "*"
          )
      # Stack Coefs and Std.Errors
      res = res.iloc[:, :2]
      res = res.stack(**FUTURE_STACK)
  
      # Add R-squared
      if include_r2:
          rsquared = getattr(result, "rsquared", np.nan)
          rsquared_adj = getattr(result, "rsquared_adj", np.nan)
          r2 = pd.Series(
              {
                  ("R-squared", ""): rsquared,
                  ("R-squared Adj.", ""): rsquared_adj,
              }
          )
  
          if r2.notnull().any():
              r2 = r2.apply(lambda x: float_format % x)
              res = pd.concat([res, r2], axis=0)
  
      res = pd.DataFrame(res)
      res.columns = [str(result.model.endog_names)]
      return res
  
imports: from statsmodels.compat.pandas import FUTURE_STACK
  from statsmodels.compat.python import lzip
  import datetime
  from functools import reduce
  import re
  import textwrap
  import numpy
  import pandas
  from .table import SimpleTable
  from .tableformatting import fmt_latex, fmt_txt
label_desc: Use image node_id 4 for calling a global function with example usage: _col_params(result, float_format, stars, include_r2) and returns: res