code: def _partial_regression(endog, exog_i, exog_others):
      """Partial regression.
  
      regress endog on exog_i conditional on exog_others
  
      uses OLS
  
      Parameters
      ----------
      endog : array_like
      exog : array_like
      exog_others : array_like
  
      Returns
      -------
      res1c : OLS results instance
  
      (res1a, res1b) : tuple of OLS results instances
           results from regression of endog on exog_others and of exog_i on
           exog_others
      """
      # FIXME: This function does not appear to be used.
      res1a = OLS(endog, exog_others).fit()
      res1b = OLS(exog_i, exog_others).fit()
      res1c = OLS(res1a.resid, res1b.resid).fit()
  
      return res1c, (res1a, res1b)
  
imports: from statsmodels.compat.pandas import Appender
  from statsmodels.compat.python import lrange, lzip
  import numpy
  import pandas
  from patsy import dmatrix
  from statsmodels.genmod.generalized_estimating_equations import GEE
  from statsmodels.genmod.generalized_linear_model import GLM
  from statsmodels.graphics import utils
  from statsmodels.nonparametric.smoothers_lowess import lowess
  from statsmodels.regression.linear_model import GLS, OLS, WLS
  from statsmodels.sandbox.regression.predstd import wls_prediction_std
  from statsmodels.tools.tools import maybe_unwrap_results
  from ._regressionplots_doc import _plot_added_variable_doc, _plot_ceres_residuals_doc, _plot_influence_doc, _plot_leverage_resid2_doc, _plot_partial_residuals_doc
label_desc: Use image node_id 5 for calling a global function with example usage: _partial_regression(endog, exog_i, exog_others) and returns: res1c,  res1a,  res1b