title: Tabulate responses for multiple columns by grouping variable with dplyr
body: <p>Hi:I'm new to the plyr/dplyr family but enjoying it. I can see it's massive utility for my own work, but I'm stil trying to get my head around it.<br>
  I have a data frame that looks like below. </p>
  
  <p>1) How do I produce a table for each non-grouping variable that shows the distribution of responses within each value of the grouping variable? </p>
  
  <p>2) Note: I do have some missing values and I would like to exclude them from the tabulation.  I realize the summarize_each command will apply the function to each column, but I don't know how to handle the missing values issue in a simple way. I have seen some codes that suggest you have to filter out missing values, but what if the missing values are scattered randomly through the non-grouping variables? </p>
  
  <p>3) Fundamentally, is it best to just use complete cases with dplyr?</p>
  
  <pre><code>#library
  library(dplyr)
  #sample data
  group&lt;-sample(c('A', 'B', 'C'), 100, replace=TRUE)
  var1&lt;-sample(c(1,2,3,4,5,NA), 100, replace=TRUE,     prob=c(0.15,0.15,0.15,0.15,0.15,0.25))
  var2&lt;-sample(c(1,2,3,4,5,NA), 100, replace=TRUE, prob=c(0.15,0.15,0.15,0.15,0.15,0.25))
  var3&lt;-sample(c(1,2,3,4,5,NA), 100, replace=TRUE, prob=c(0.15,0.15,0.15,0.15,0.15,0.25))
  df&lt;-data.frame(group, var1, var2, var3)
  #my code
  out_df&lt;-df %&gt;%group_by(group)
  out_df %&gt;% summarise_each(funs(table))
  </code></pre>