title: How to use dplyr across to filter NA in multiple columns
body: <p>I am trying to filter out rows with NA values across multiple columns. A row should only be dropped if all columns of interest are NA.</p>
  <p>The scenario is the same as in this question (but I don't have enough reputation to make a comment): <a href="https://stackoverflow.com/questions/33520854/filtering-data-frame-based-on-na-on-multiple-columns">filtering data frame based on NA on multiple columns</a></p>
  <p>One of the solutions is to use:</p>
  <pre><code>library(dplyr)
  df_non_na &lt;- df %&gt;% filter_at(vars(type,company),all_vars(!is.na(.)))
  </code></pre>
  <p>Since &quot;filter_at&quot; is being depreciated in dplyr, how can I use &quot;filter&quot; and &quot;across&quot; to achieve a similar outcome?</p>