text: user9860: I'm performing correlation analysis using the corrr package in R, but I'm unable to extract the p values. Does anyone know how to get the p values in corrr package in R?
  
  user12844: Here is a suggested workaround:
  
  Generate a p-value table using one of these tools:
  
  RcmdrMisc::rcorr.adjust()
  psych::corr.test()
  
  
  
  Then use corrr:as_cordf() to generate the tidy dataframe with the same structure as a regular corrr correlation table.
  Personally, I have used the Hmisc::rcorr() package, and it works well:
  Hmisc::rcorr() %>% `[[`('P') %>% corrr::as_cordf()
  
  
  user2108: I would suggest looking at some of the documentation.
  As far as I can tell, the intention of the package is to visualize and organize correlation coefficient estimates. It does not seem that the author of the package has any interest in p-value estimation.
  If you are interested in computing p-values, I would suggest using a different tool, such as the builtin cor.test() function.
  
original_text: 9860: <p>I'm performing correlation analysis using the corrr package in R, but I'm unable to extract the p values. Does anyone know how to get the p values in corrr package in R?</p>
   12844: <p>Here is a <a href="https://github.com/tidymodels/corrr/issues/29" rel="nofollow noreferrer">suggested workaround</a>:</p>
  <ul>
  <li>Generate a p-value table using one of these tools:
  <ul>
  <li><code>RcmdrMisc::rcorr.adjust()</code></li>
  <li><code>psych::corr.test()</code></li>
  </ul>
  </li>
  </ul>
  <p>Then use <code>corrr:as_cordf()</code> to generate the tidy dataframe with the same structure as a regular corrr correlation table.</p>
  <p>Personally, I have used the <code>Hmisc::rcorr()</code> package, and it works well:</p>
  <pre><code>Hmisc::rcorr() %&gt;% `[[`('P') %&gt;% corrr::as_cordf()
  </code></pre>
   2108: <p>I would suggest looking at some of the <a href="https://cran.r-project.org/web/packages/corrr/index.html" rel="noreferrer">documentation</a>.</p>
  <p>As far as I can tell, the intention of the package is to visualize and organize correlation coefficient estimates. It does not seem that the author of the package has any interest in p-value estimation.</p>
  <p>If you are interested in computing p-values, I would suggest using a different tool, such as the builtin <code>cor.test()</code> function.</p>
  