title: seaborn's coefplot function throwing error
body: <p>I am trying to use seaborn's <code>coefplot</code> function but it is not showing an output. Instead I'm getting an error:</p>
  
  <blockquote>
    <p>AttributeError: module 'seaborn' has no attribute 'coefplot'.</p>
  </blockquote>
  
  <pre><code>myresultsmyresult .env_corr(env_vars)
  def env_corr(self, env_vars, coeff_plot=False, qq_plot=False):
      """
      Determine correlations with environmental/non-discretionary variables
      using a logit regression. Tobit will be implemented when available
      upstream in statsmodels.
  
      Takes:
          env_vars: A pandas dataframe of environmental variables
  
      Returns:
          corr_mod: the statsmodels' model instance containing the inputs
                    and results from the logit model.
  
      Note that there can be no spaces in the variables' names.
      """
  
      import matplotlib.pyplot as plt
      from statsmodels.regression.linear_model import OLS
      from statsmodels.graphics.gofplots import qqplot
      import seaborn as sns
  
      env_data = _to_dataframe(env_vars)
      corr_data = env_data.join(self['Efficiency'])
      corr_mod = OLS.from_formula(
          "Efficiency ~ " + " + ".join(env_vars.columns), corr_data)
      corr_res = corr_mod.fit()
  
      #plot coeffs
      if coeff_plot:
          coefplot("Efficiency ~ " + " + ".join(env_vars.columns),
                   data=corr_data)
          plt.xticks(rotation=45, ha='right')
          plt.title('Regression coefficients and standard errors')
  
      #plot qq of residuals
      if qq_plot:
          qqplot(corr_res.resid, line='s')
          plt.title('Distribution of residuals')
  
      print(corr_res.summary())
  
      return corr_res
  </code></pre>
  
  <p>Please help.</p>