title: How to use a weighted mean estimator in seaborn factor plot (incl bootstrapping)?
body: <p>I have a dataframe where each of the rows has a certain weight which needs to be accounted for in the mean computations. I love seaborn factorplots and their bootstrapped 95% confidence intervals but haven't been able to get seaborn to accept a new weighted mean estimator.</p>
  
  <p>Here is an example of what I would like to do.</p>
  
  <pre><code>tips_all = sns.load_dataset("tips")
  tips_all["weight"] = 10 * np.random.rand(len(tips_all))
  sns.factorplot("size", "total_bill", 
                 data=tips_all, kind="point")
  # here I would like to have a mean estimator that computes a weighted mean
  # the bootstrapped confidence intervals should also use this weighted mean estimator
  # something like (tips_all["weight"] * tips_all["total_bill"]).sum() / tips_all["weight"].sum()
  # but on bootstrapped samples (for the confidence interval)
  </code></pre>