diff --git a/dev/CODE_OF_CONDUCT.html b/dev/CODE_OF_CONDUCT.html
index fc0fa097..8c5ff78f 100644
--- a/dev/CODE_OF_CONDUCT.html
+++ b/dev/CODE_OF_CONDUCT.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/LICENSE-text.html b/dev/LICENSE-text.html
index 2c09d398..1b1b4790 100644
--- a/dev/LICENSE-text.html
+++ b/dev/LICENSE-text.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/LICENSE.html b/dev/LICENSE.html
index b1842aeb..67ee8f3c 100644
--- a/dev/LICENSE.html
+++ b/dev/LICENSE.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/articles/index.html b/dev/articles/index.html
index d03fb7ec..9d577e9b 100644
--- a/dev/articles/index.html
+++ b/dev/articles/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/articles/syntax.html b/dev/articles/syntax.html
index 6332bf59..9bc697db 100644
--- a/dev/articles/syntax.html
+++ b/dev/articles/syntax.html
@@ -29,7 +29,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/articles/tidyselect.html b/dev/articles/tidyselect.html
index c0199ae6..cde46885 100644
--- a/dev/articles/tidyselect.html
+++ b/dev/articles/tidyselect.html
@@ -29,7 +29,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/authors.html b/dev/authors.html
index c7adb6bb..58efbd7c 100644
--- a/dev/authors.html
+++ b/dev/authors.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -75,13 +75,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Henry L, Wickham H (2024).
 <em>tidyselect: Select from a Set of Strings</em>.
-R package version 1.2.0.9000, https://github.com/r-lib/tidyselect, <a href="https://tidyselect.r-lib.org">https://tidyselect.r-lib.org</a>. 
+R package version 1.2.1.9000, https://github.com/r-lib/tidyselect, <a href="https://tidyselect.r-lib.org">https://tidyselect.r-lib.org</a>. 
 </p>
       <pre>@Manual{,
   title = {tidyselect: Select from a Set of Strings},
   author = {Lionel Henry and Hadley Wickham},
   year = {2024},
-  note = {R package version 1.2.0.9000, https://github.com/r-lib/tidyselect},
+  note = {R package version 1.2.1.9000, https://github.com/r-lib/tidyselect},
   url = {https://tidyselect.r-lib.org},
 }</pre>
     </div>
diff --git a/dev/deps/Source_Sans_Pro-0.4.8/font.css b/dev/deps/Source_Sans_Pro-0.4.8/font.css
index 81a445ae..41421abc 100644
--- a/dev/deps/Source_Sans_Pro-0.4.8/font.css
+++ b/dev/deps/Source_Sans_Pro-0.4.8/font.css
@@ -3,7 +3,7 @@
   font-style: italic;
   font-weight: 400;
   font-display: swap;
-  src: url(6xK1dSBYKcSV-LCoeQqfX1RYOo3qPa7j.woff) format('woff');
+  src: url(font?kit=6xK1dSBYKcSV-LCoeQqfX1RYOo3qPa7j&skey=28c775fa366622c1&v=v22) format('woff');
 }
 @font-face {
   font-family: 'Source Sans Pro';
diff --git a/dev/deps/Source_Sans_Pro-0.4.8/font?kit=6xK1dSBYKcSV-LCoeQqfX1RYOo3qPa7j&skey=28c775fa366622c1&v=v22 b/dev/deps/Source_Sans_Pro-0.4.8/font?kit=6xK1dSBYKcSV-LCoeQqfX1RYOo3qPa7j&skey=28c775fa366622c1&v=v22
new file mode 100644
index 00000000..5c513e7f
Binary files /dev/null and b/dev/deps/Source_Sans_Pro-0.4.8/font?kit=6xK1dSBYKcSV-LCoeQqfX1RYOo3qPa7j&skey=28c775fa366622c1&v=v22 differ
diff --git a/dev/index.html b/dev/index.html
index 33858adc..bf316455 100644
--- a/dev/index.html
+++ b/dev/index.html
@@ -35,7 +35,7 @@
     
     <a class="navbar-brand me-2" href="index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/news/index.html b/dev/news/index.html
index 6acd8a6f..add65582 100644
--- a/dev/news/index.html
+++ b/dev/news/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -55,6 +55,9 @@
 
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="development version" id="tidyselect-development-version">tidyselect (development version)<a class="anchor" aria-label="anchor" href="#tidyselect-development-version"></a></h2>
+</div>
+    <div class="section level2">
+<h2 class="pkg-version" data-toc-text="1.2.1" id="tidyselect-121">tidyselect 1.2.1<a class="anchor" aria-label="anchor" href="#tidyselect-121"></a></h2><p class="text-muted">CRAN release: 2024-03-11</p>
 <ul><li><p>Performance improvements (<a href="https://github.com/r-lib/tidyselect/issues/337" class="external-link">#337</a>, <a href="https://github.com/r-lib/tidyselect/issues/338" class="external-link">#338</a>, <a href="https://github.com/r-lib/tidyselect/issues/339" class="external-link">#339</a>, <a href="https://github.com/r-lib/tidyselect/issues/341" class="external-link">#341</a>)</p></li>
 <li><p><code><a href="../reference/eval_select.html">eval_select()</a></code> out-of-bounds errors now use the verb “select” rather than “subset” in the error message for consistency with <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">dplyr::select()</a></code> (<a href="https://github.com/r-lib/tidyselect/issues/271" class="external-link">#271</a>).</p></li>
 <li><p>Fix for CRAN checks.</p></li>
diff --git a/dev/pkgdown.yml b/dev/pkgdown.yml
index 47a13918..c2d814bd 100644
--- a/dev/pkgdown.yml
+++ b/dev/pkgdown.yml
@@ -4,7 +4,7 @@ pkgdown_sha: ~
 articles:
   syntax: syntax.html
   tidyselect: tidyselect.html
-last_built: 2024-03-11T11:16Z
+last_built: 2024-03-12T07:22Z
 urls:
   reference: https://tidyselect.r-lib.org/reference
   article: https://tidyselect.r-lib.org/articles
diff --git a/dev/reference/all_of.html b/dev/reference/all_of.html
index 7cfa7c97..2f88ec2b 100644
--- a/dev/reference/all_of.html
+++ b/dev/reference/all_of.html
@@ -32,7 +32,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/eval_relocate.html b/dev/reference/eval_relocate.html
index 050699f9..6a89f560 100644
--- a/dev/reference/eval_relocate.html
+++ b/dev/reference/eval_relocate.html
@@ -14,7 +14,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/eval_select.html b/dev/reference/eval_select.html
index 33a4cc53..6e96ed0f 100644
--- a/dev/reference/eval_select.html
+++ b/dev/reference/eval_select.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/everything.html b/dev/reference/everything.html
index 6414d53e..5985aaec 100644
--- a/dev/reference/everything.html
+++ b/dev/reference/everything.html
@@ -20,7 +20,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/faq-external-vector.html b/dev/reference/faq-external-vector.html
index d349377b..1ba87619 100644
--- a/dev/reference/faq-external-vector.html
+++ b/dev/reference/faq-external-vector.html
@@ -198,7 +198,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/faq-selection-context.html b/dev/reference/faq-selection-context.html
index ed105bb4..272b4fc9 100644
--- a/dev/reference/faq-selection-context.html
+++ b/dev/reference/faq-selection-context.html
@@ -108,7 +108,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/index.html b/dev/reference/index.html
index 0a869a56..b4764bbe 100644
--- a/dev/reference/index.html
+++ b/dev/reference/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/language.html b/dev/reference/language.html
index 762ec9f3..723d9221 100644
--- a/dev/reference/language.html
+++ b/dev/reference/language.html
@@ -76,7 +76,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/one_of.html b/dev/reference/one_of.html
index d667acf7..a0bb1018 100644
--- a/dev/reference/one_of.html
+++ b/dev/reference/one_of.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/peek_vars.html b/dev/reference/peek_vars.html
index 0ad8af5d..f28ed082 100644
--- a/dev/reference/peek_vars.html
+++ b/dev/reference/peek_vars.html
@@ -38,7 +38,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/poke_vars.html b/dev/reference/poke_vars.html
index 06b83c5f..d2057a0d 100644
--- a/dev/reference/poke_vars.html
+++ b/dev/reference/poke_vars.html
@@ -40,7 +40,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/reexports.html b/dev/reference/reexports.html
index 3a5f5aec..90d1a820 100644
--- a/dev/reference/reexports.html
+++ b/dev/reference/reexports.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/starts_with.html b/dev/reference/starts_with.html
index 8689cd0d..191ffa45 100644
--- a/dev/reference/starts_with.html
+++ b/dev/reference/starts_with.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/tidyselect-package.html b/dev/reference/tidyselect-package.html
index eb2b309e..d9789569 100644
--- a/dev/reference/tidyselect-package.html
+++ b/dev/reference/tidyselect-package.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/tidyselect_data_proxy.html b/dev/reference/tidyselect_data_proxy.html
index 8667cd1a..6d88ca17 100644
--- a/dev/reference/tidyselect_data_proxy.html
+++ b/dev/reference/tidyselect_data_proxy.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/vars_pull.html b/dev/reference/vars_pull.html
index c627b0a7..abb73c9c 100644
--- a/dev/reference/vars_pull.html
+++ b/dev/reference/vars_pull.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/vars_select.html b/dev/reference/vars_select.html
index fb87a667..c7f4432c 100644
--- a/dev/reference/vars_select.html
+++ b/dev/reference/vars_select.html
@@ -14,7 +14,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/vars_select_helpers.html b/dev/reference/vars_select_helpers.html
index d220652c..13460249 100644
--- a/dev/reference/vars_select_helpers.html
+++ b/dev/reference/vars_select_helpers.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/dev/reference/where.html b/dev/reference/where.html
index 5cd784c5..abbb45be 100644
--- a/dev/reference/where.html
+++ b/dev/reference/where.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">tidyselect</a>
 
-    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.0.9000</small>
+    <small class="nav-text text-danger me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.1.9000</small>
 
     
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diff --git a/dev/search.json b/dev/search.json
index 72509ca5..e1e0b87a 100644
--- a/dev/search.json
+++ b/dev/search.json
@@ -1 +1 @@
-[{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement codeofconduct@posit.co. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired [Mozilla’s code conduct enforcement ladder][https://github.com/mozilla/inclusion]. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://tidyselect.r-lib.org/dev/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2020 tidyselect authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"sets-of-variables","dir":"Articles","previous_headings":"","what":"Sets of variables","title":"Technical description of tidyselect","text":"tidyselect syntax sets variables, internally represented integer vectors locations. example, c(1L, 2L) represents set first second variables, c(1L, 2L, 1L). vector locations contains duplicates, normally treated element, since represent sets. exception occurs named elements whose names differ. names don’t match, treated different elements order allow renaming variable multiple names (see section Renaming variables). Today, syntax tidyselect generally designed around Boolean algebra, .e. recommend writing starts_with(\"\") & !ends_with(\"z\"). Earlier versions tidyselect flavour set operations, ’d write starts_with(\"\") - ends_with(\"b\"). set operations still supported, tidyselect represents variables internally, longer recommend Boolean algebra easy people understand.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"bare-names","dir":"Articles","previous_headings":"Sets of variables","what":"Bare names","title":"Technical description of tidyselect","text":"Within data-expressions (see Evaluation section), bare names represent locations, .e. set size 1. following expressions equivalent:","code":"mtcars %>% select_loc(mpg:hp, !cyl, vs) #>  mpg  cyl disp   hp drat   wt qsec   vs   am gear carb  #>    1    2    3    4    5    6    7    8    9   10   11  mtcars %>% select_loc(1:4, !2, 8) #>  mpg  cyl disp   hp drat   wt qsec   vs   am gear carb  #>    1    2    3    4    5    6    7    8    9   10   11"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"the-operator","dir":"Articles","previous_headings":"Sets of variables","what":"The : operator","title":"Technical description of tidyselect","text":": can used select consecutive variables two locations. returns corresponding sequence locations. bare names represent locations, easy select range variables:","code":"mtcars %>% select_loc(2:4) #>  cyl disp   hp  #>    2    3    4 mtcars %>% select_loc(cyl:hp) #>  cyl disp   hp  #>    2    3    4"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"boolean-operators","dir":"Articles","previous_headings":"Sets of variables","what":"Boolean operators","title":"Technical description of tidyselect","text":"| operator takes union two sets: & operator takes intersection two sets: ! operator takes complement set: Taking intersection complement produces set difference:","code":"iris %>% select_loc(starts_with(\"Sepal\") | ends_with(\"Width\")) #> Sepal.Length  Sepal.Width  Petal.Width  #>            1            2            4 iris %>% select_loc(starts_with(\"Sepal\") & ends_with(\"Width\")) #> Sepal.Width  #>           2 iris %>% select_loc(!ends_with(\"Width\")) #> Sepal.Length Petal.Length      Species  #>            1            3            5 iris %>% select_loc(starts_with(\"Sepal\") & !ends_with(\"Width\")) #> Sepal.Length  #>            1"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"dots-and-c","dir":"Articles","previous_headings":"Sets of variables","what":"Dots and c()","title":"Technical description of tidyselect","text":"tidyselect functions can take dots, like dplyr::select(), named argument, like tidyr::pivot_longer(). latter case, dots syntax accessible via c(). fact ... syntax implemented c(...) thus completely equivalent. c(x, y, z) equivalent x | y | z:","code":"mtcars %>% select_loc(mpg, disp:hp) #>  mpg disp   hp  #>    1    3    4  mtcars %>% select_loc(c(mpg, disp:hp)) #>  mpg disp   hp  #>    1    3    4 iris %>% select_loc(starts_with(\"Sepal\"), ends_with(\"Width\"), Species) #> Sepal.Length  Sepal.Width  Petal.Width      Species  #>            1            2            4            5  iris %>% select_loc(starts_with(\"Sepal\") | ends_with(\"Width\") | Species) #> Sepal.Length  Sepal.Width  Petal.Width      Species  #>            1            2            4            5"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"name-combination-and-propagation","dir":"Articles","previous_headings":"Sets of variables > Renaming variables","what":"Name combination and propagation","title":"Technical description of tidyselect","text":"named inputs provided ... c(), selection renamed. inputs already named, outer inner names combined ... separator: Otherwise outer names propagated selected elements according following rules: data frames, numeric suffix appended columns must uniquely named. normal vectors, name simply assigned selected inputs. Combination propagation can composed using nested c():","code":"mtcars %>% select_loc(foo = c(bar = mpg, baz = cyl)) #> foo...bar foo...baz  #>         1         2 mtcars %>% select_loc(foo = c(mpg, cyl)) #> foo1 foo2  #>    1    2 as.list(mtcars) %>% select_loc(foo = c(mpg, cyl)) #> foo foo  #>   1   2 mtcars %>% select_loc(foo = c(bar = c(mpg, cyl))) #> foo...bar1 foo...bar2  #>          1          2"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"set-combination-with-named-variables","dir":"Articles","previous_headings":"Sets of variables > Renaming variables","what":"Set combination with named variables","title":"Technical description of tidyselect","text":"Named elements special rules determine identities set. Unnamed elements match names: | c(foo = ) equivalent c(foo = ). & c(foo = ) equivalent c(foo = ). Named elements different names distinct: c(foo = ) & c(bar = ) equivalent c(). c(foo = ) | c(bar = ) equivalent c(foo = , bar = ). unnamed elements match named ones, possible select multiple elements rename one :","code":"iris %>% select_loc(!Species, foo = Sepal.Width) #> Sepal.Length          foo Petal.Length  Petal.Width  #>            1            2            3            4"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"predicate-functions","dir":"Articles","previous_headings":"Sets of variables","what":"Predicate functions","title":"Technical description of tidyselect","text":"Predicate function objects can supplied input env-expression, typically selection helper (). applied elements data, return TRUE FALSE indicate inclusion. Predicates env-expressions effectively expanded set variables represent:","code":"iris %>% select_loc(where(is.numeric)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width  #>            1            2            3            4  iris %>% select_loc(where(is.factor)) #> Species  #>       5  iris %>% select_loc(where(is.numeric) | where(is.factor)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species  #>            1            2            3            4            5  iris %>% select_loc(where(is.numeric) & where(is.factor)) #> named integer(0)"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"selection-helpers","dir":"Articles","previous_headings":"","what":"Selection helpers","title":"Technical description of tidyselect","text":"call selection helpers function inspects currently active variables peek_vars() returns selection. peek_vars() returns character vector names. returned selection can output conforming types described Data types section. Examples selection helpers all_of(), contains(), last_col(). selection helpers evaluated env-expressions (see Evaluation section).","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"supported-data-types","dir":"Articles","previous_headings":"","what":"Supported data types","title":"Technical description of tidyselect","text":"following data types can returned selection helpers forced via !! force() (latter works tidyselect treated env-expression, see Evaluation section): Vectors locations: Vectors names. matched transformed locations. Predicate functions. applied elements determine inclusion.","code":"iris %>% select_loc(force(c(1, 3))) #> Sepal.Length Petal.Length  #>            1            3 iris %>% select_loc(force(c(\"Sepal.Length\", \"Petal.Length\"))) #> Sepal.Length Petal.Length  #>            1            3 iris %>% select_loc(force(is.numeric)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width  #>            1            2            3            4"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"data-expressions-and-env-expressions","dir":"Articles","previous_headings":"Evaluation","what":"Data-expressions and env-expressions","title":"Technical description of tidyselect","text":"tidyselect typical tidy evaluation UI. main difference data masking. typical tidy eval function, expressions evaluated data-vars first scope, followed env-vars: possible bypass data frame variables forcing symbols looked environment !! .env: tidyselect, hierarchical data masking. Instead, expressions evaluated either context data frame user environment, without overlap. scope lookup depends kind expression: data-expressions evaluated data frame . includes bare symbols, boolean operators, -, :, c(). can’t refer environment-variables data-expression: env-expressions evaluated environment. includes calls mentioned , well symbols part calls. can’t refer data-variables data-expression: scoping unambiguous, can safely refer env-vars env-expression, without worry potential naming clashes data-vars: variable names character vector, safe refer env-var containing names all_of() env-expression: Note currently, env-vars still allowed data-expressions, compatibility. However process deprecated see note recommending use all_of() instead. note become deprecation warning future, error.","code":"mask <- function(data, expr) {   rlang::eval_tidy(rlang::enquo(expr), data) }  foo <- 10 cyl <- 200  # `cyl` represents the data frame column here: mtcars %>% mask(cyl * foo) #>  [1] 60 60 40 60 80 60 80 40 40 60 60 80 80 80 80 80 80 40 40 40 40 80 80 #> [24] 80 80 40 40 40 80 60 80 40 mtcars %>% mask(!!cyl * foo) #> [1] 2000 mtcars %>% mask(.env$cyl * foo) #> [1] 2000 cyl_pos <- 2 mtcars %>% select_loc(mpg | cyl_pos) #> Error in `select_loc()`: #> ! Can't select columns that don't exist. #> ✖ Column `cyl_pos` doesn't exist. mtcars %>% select_loc(all_of(mpg)) #> Error in `select_loc()`: #> ℹ In argument: `all_of(mpg)`. #> Caused by error: #> ! object 'mpg' not found x <- data.frame(x = 1:3, y = 4:6, z = 7:9)  # `ncol(x)` is an env-expression, so `x` represents the data frame in # the environment rather than the column in the data frame x %>% select_loc(2:ncol(x)) #> y z  #> 2 3 y <- c(\"y\", \"z\") x %>% select_loc(all_of(y)) #> y z  #> 2 3 mtcars %>% select_loc(cyl_pos) #> Warning: Using an external vector in selections was deprecated in tidyselect #> 1.1.0. #> ℹ Please use `all_of()` or `any_of()` instead. #>   # Was: #>   data %>% select(cyl_pos) #>  #>   # Now: #>   data %>% select(all_of(cyl_pos)) #>  #> See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated. #> cyl  #>   2"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"arithmetic-operators","dir":"Articles","previous_headings":"Evaluation","what":"Arithmetic operators","title":"Technical description of tidyselect","text":"Within data-expressions (see Evaluation section), +, * / overridden cause error. prevent confusion stemming normal data masking usage variables can transformed fly:","code":"mtcars %>% select_loc(cyl^2) #> Error in `select_loc()`: #> ! Can't use arithmetic operator `^` in selection context.  mtcars %>% select_loc(mpg * wt) #> Error in `select_loc()`: #> ! Can't use arithmetic operator `*` in selection context."},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"selecting-versus-renaming","dir":"Articles","previous_headings":"","what":"Selecting versus renaming","title":"Technical description of tidyselect","text":"select rename variants take types inputs type return value. important differences.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"all-renaming-inputs-must-be-named","dir":"Articles","previous_headings":"Selecting versus renaming","what":"All renaming inputs must be named","title":"Technical description of tidyselect","text":"Unlike eval_select() can select without renaming, eval_rename() expects fully named selection. one several names missing, error thrown.","code":"mtcars %>% select_loc(mpg) #> mpg  #>   1  mtcars %>% rename_loc(mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named."},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"renaming-to-an-existing-variable-name","dir":"Articles","previous_headings":"Selecting versus renaming","what":"Renaming to an existing variable name","title":"Technical description of tidyselect","text":"input data data frame, tidyselect generally throws error duplicate column names selected, order respect invariant unique column names. selection can rename variable existing name latter part selection: possible renaming. However, name conflict can solved renaming existing variable another name:","code":"# Lists can have duplicates as.list(mtcars) %>% select_loc(foo = mpg, foo = cyl) #> foo foo  #>   1   2  # Data frames cannot mtcars %>% select_loc(foo = mpg, foo = cyl) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"foo\" at locations 1 and 2. mtcars %>% select_loc(cyl, cyl = mpg) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"cyl\" at locations 1 and 2.  mtcars %>% select_loc(disp, cyl = mpg) #> disp  cyl  #>    3    1 mtcars %>% rename_loc(cyl, cyl = mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named.  mtcars %>% rename_loc(disp, cyl = mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named. mtcars %>% select_loc(foo = cyl, cyl = mpg) #> foo cyl  #>   2   1  mtcars %>% rename_loc(foo = cyl, cyl = mpg) #> foo cyl  #>   2   1"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"duplicate-columns-in-data-frames","dir":"Articles","previous_headings":"","what":"Duplicate columns in data frames","title":"Technical description of tidyselect","text":"Normally data frame shouldn’t duplicate names. However, real world messy duplicates happen wild. tidyselect tries permissive can duplicates users can restore unique names select() rename(). First let’s create data frame duplicate names: duplicates part selection, simply ignored: duplicates selected, error: duplicate names can repaired renaming chosen locations:","code":"dups <- vctrs::new_data_frame(list(x = 1, y = 2, x = 3)) dups %>% select_loc(y) #> y  #> 2 dups %>% select_loc(x) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"x\" at locations 1 and 2. dups %>% select_loc(x, foo = 3) #>   x foo  #>   1   3  dups %>% rename_loc(foo = 3) #> foo  #>   3"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"acknowledgements","dir":"Articles","previous_headings":"","what":"Acknowledgements","title":"Technical description of tidyselect","text":"tidyselect syntax inspired base::subset() function written Peter Dalgaard. select parameter subset.data.frame() evaluated data mask column names bound locations data frame. allows : create sequences variable locations. locations can combined c(). selection interface set tone development tidyselect syntax.","code":"mtcars %>% subset(select = c(cyl, hp:wt)) #> # A tibble: 32 × 4 #>     cyl    hp  drat    wt #>   <dbl> <dbl> <dbl> <dbl> #> 1     6   110  3.9   2.62 #> 2     6   110  3.9   2.88 #> 3     4    93  3.85  2.32 #> 4     6   110  3.08  3.22 #> # ℹ 28 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"selections-as-dots-or-as-named-arguments","dir":"Articles","previous_headings":"Before we start","what":"Selections as dots or as named arguments","title":"Implementing tidyselect interfaces","text":"two major ways designing function takes selections. Passing dots dplyr::select(). Interpolating named arguments tidyr::pivot_longer(). case, multiple inputs can provided inside c() using boolean operators: general recommendation take dots main purpose function create new data structure based selection. selection accessory main purpose function, take named argument. doubt, recommend using named arguments easier change named argument dots way around. advice , see Making data ... section tidyverse design book.","code":"mtcars %>% dplyr::select(mpg, cyl) mtcars %>% pivot_longer(c(mpg, cyl)) mtcars %>% pivot_longer(mpg | cyl)"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"do-you-need-tidyselect","dir":"Articles","previous_headings":"Before we start","what":"Do you need tidyselect?","title":"Implementing tidyselect interfaces","text":"tools described vignette rather low level. Depending use case, may easier wrap dplyr::select(). ’ll get data frame containing columns selected user, can handle various ways. following examples illustrate write function takes selection data returns corresponding data frame capitalised names: main advantage lower level tidyselect tools offer bit information flexibility. Instead returning selected data, return locations selected elements inside input data. don’t need selected locations can afford dependency, may consider wrapping dplyr instead.","code":"# Passing dots toupper_dots <- function(data, ...) {   sel <- dplyr::select(data, ...)   rlang::set_names(sel, toupper) } # Interpolating a named argument with {{ }} toupper_arg <- function(data, arg) {   sel <- dplyr::select(data, {{ arg }})   rlang::set_names(sel, toupper) }  mtcars %>% toupper_dots(mpg:disp, vs) #> # A tibble: 32 x 4 #>     MPG   CYL  DISP    VS #>   <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160     0 #> 2  21       6   160     0 #> 3  22.8     4   108     1 #> 4  21.4     6   258     1 #> # … with 28 more rows  mtcars %>% toupper_arg(c(mpg:disp, vs)) #> # A tibble: 32 x 4 #>     MPG   CYL  DISP    VS #>   <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160     0 #> 2  21       6   160     0 #> 3  22.8     4   108     1 #> 4  21.4     6   258     1 #> # … with 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"the-selection-evaluators","dir":"Articles","previous_headings":"","what":"The selection evaluators","title":"Implementing tidyselect interfaces","text":"tidyselect implemented non-standard evaluation (NSE). unique feature R language refers ability functions defuse (.e. delay execution) arguments, resume evaluation later on1. Crucially, evaluation can resumed different context according different rules, often domain-specific languages created R.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"defusing-and-resuming-evaluation-of-r-code","dir":"Articles","previous_headings":"The selection evaluators","what":"Defusing and resuming evaluation of R code","title":"Implementing tidyselect interfaces","text":"function argument defused, R halts evaluation code returns defused expression instead. expression contains code describes compute intended value. Defuse R code expr(): Defuse user’s R code enquo(): resume evaluation defused R code, use eval_tidy(): can resume evaluation data context passing data frame data argument: Resuming evaluation data context known data masking. data-vars inside data frame combined env-vars environment, making possible users refer data variables:","code":"own <- rlang::expr(1 + 2) own #> 1 + 2 fn <- function(arg) {   expr <- rlang::enquo(arg)   expr } user <- fn(1 + 2) user #> <quosure> #> expr: ^1 + 2 #> env:  global rlang::eval_tidy(own) #> [1] 3  rlang::eval_tidy(user) #> [1] 3 with_data <- function(data, x) {   expr <- rlang::enquo(x)   rlang::eval_tidy(expr, data = data) } NULL %>% with_data(mean(cyl) * 10) #> Error: object 'cyl' not found  mtcars %>% with_data(mean(cyl) * 10) #> [1] 61.875"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"resuming-defused-r-code-with-tidyselect-rules","dir":"Articles","previous_headings":"The selection evaluators","what":"Resuming defused R code with tidyselect rules","title":"Implementing tidyselect interfaces","text":"Taking tidyselect selections functions follows principles. First defuse expression, resume evaluation. Instead eval_tidy(), need special interpreters eval_select() eval_rename(). Like eval_tidy(), take defused expression data. return vector locations selected elements: user renamed selected elements, names vector locations reflect new names. eval_select() likely variant ’ll need implement tidyselect functions.","code":"eval_select(rlang::expr(mpg), mtcars) #> mpg  #>   1  eval_select(rlang::expr(c(mpg:disp, vs)), mtcars) #>  mpg  cyl disp   vs  #>    1    2    3    8 eval_select(rlang::expr(c(foo = mpg, bar = disp)), mtcars) #> foo bar  #>   1   3  eval_rename(rlang::expr(c(foo = mpg, bar = disp)), mtcars) #> foo bar  #>   1   3"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"simple-selections-with-dots","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Simple selections with dots","title":"Implementing tidyselect interfaces","text":"selecting function takes dots: Pass dots c() inside defused expression. Resume evaluation defused c() expression eval_select(). Use vector locations returned eval_select() subset rename input data. reimplement dplyr::select() 3 lines representing steps :","code":"select <- function(.data, ...) {   expr <- rlang::expr(c(...))   pos <- eval_select(expr, data = .data)   rlang::set_names(.data[pos], names(pos)) }  mtcars %>%   select(mpg, cyl) #> # A tibble: 32 × 2 #>     mpg   cyl #>   <dbl> <dbl> #> 1  21       6 #> 2  21       6 #> 3  22.8     4 #> 4  21.4     6 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"simple-selections-with-named-arguments","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Simple selections with named arguments","title":"Implementing tidyselect interfaces","text":"selecting function takes named arguments, defusing step bit different. need use enquo() defuse function argument .","code":"select <- function(.data, cols) {   expr <- rlang::enquo(cols)   pos <- eval_select(expr, data = .data)   rlang::set_names(.data[pos], names(pos)) }  mtcars %>%   select(c(mpg, cyl)) #> # A tibble: 32 × 2 #>     mpg   cyl #>   <dbl> <dbl> #> 1  21       6 #> 2  21       6 #> 3  22.8     4 #> 4  21.4     6 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"renaming-selections","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Renaming selections","title":"Implementing tidyselect interfaces","text":"eval_rename() variant rarely needed mentioned completeness. First note eval_select() eval_rename() allow renaming variables: eval_rename() similar eval_select() constraints meant renaming variables place. particular throws error selected inputs unnamed. practice, eval_rename() accepts c() expression expr argument, inputs inside outermost c() must named: constraint, doesn’t make much sense take named argument, time ’ll want pass dots defused c() expression. way user can easily pass names selections: example use vector locations returned eval_rename(), implement dplyr::rename():","code":"eval_select(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1  eval_rename(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1 eval_rename(rlang::expr(mpg), mtcars) #> Error: #> ! All renaming inputs must be named.  eval_rename(rlang::expr(c(mpg)), mtcars) #> Error: #> ! All renaming inputs must be named.  eval_rename(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1 wrapper <- function(data, ...) {   eval_rename(rlang::expr(c(...)), data) }  mtcars %>% wrapper(foo = mpg, bar = hp:wt) #>  foo bar1 bar2 bar3  #>    1    4    5    6 rename <- function(.data, ...) {   pos <- eval_rename(rlang::expr(c(...)), .data)   names(.data)[pos] <- names(pos)   .data }  mtcars %>%   rename(foo = mpg, bar = hp:wt) #> # A tibble: 32 × 11 #>     foo   cyl  disp  bar1  bar2  bar3  qsec    vs    am  gear  carb #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4 #> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4 #> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1 #> 4  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"creating-selection-helpers","dir":"Articles","previous_headings":"","what":"Creating selection helpers","title":"Implementing tidyselect interfaces","text":"Tools like starts_with() contains() called selection helpers. tools inspect variable names currently available selection peek_vars(). variable names registered automatically eval_select() duration evaluation: properties temporarily available calling function like peek_vars() called descriptors. Descriptors useful easy compose. instance, user combine starts_with() ends_with() without worry passing variables environment can found: create new selection helper: Inspect variables peek_vars(). convention done argument user can override. Return one supported data types: vector names locations (latter recommended, see section handling duplicate variables), predicate function. fn argument makes error message informative helper used wrong context: variables inspected default argument, easy override. mostly useful unit tests:","code":"x <- rlang::expr(print(peek_vars()))  invisible(eval_select(x, data = mtcars)) #>  [1] \"mpg\"  \"cyl\"  \"disp\" \"hp\"   \"drat\" \"wt\"   \"qsec\" \"vs\"   \"am\"   \"gear\" #> [11] \"carb\" my_selector <- function(prefix, suffix) {   intersect(     starts_with(prefix),     ends_with(suffix)   ) }  iris %>% select(my_selector(\"Sepal\", \"Length\")) #> # A tibble: 150 × 1 #>   Sepal.Length #>          <dbl> #> 1          5.1 #> 2          4.9 #> 3          4.7 #> 4          4.6 #> # ℹ 146 more rows if_width <- function(n, vars = peek_vars(fn = \"if_width\")) {   vars[nchar(vars) == n] }  mtcars %>% select(if_width(2)) #> # A tibble: 32 × 4 #>      hp    wt    vs    am #>   <dbl> <dbl> <dbl> <dbl> #> 1   110  2.62     0     1 #> 2   110  2.88     0     1 #> 3    93  2.32     1     1 #> 4   110  3.22     1     0 #> # ℹ 28 more rows mtcars[if_width(2)] #> Error: #> ! `if_width()` must be used within a *selecting* function. #> ℹ See <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details. if_width(2, vars = names(mtcars)) #> [1] \"hp\" \"wt\" \"vs\" \"am\""},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"handling-duplicate-variables","dir":"Articles","previous_headings":"Creating selection helpers","what":"Handling duplicate variables","title":"Implementing tidyselect interfaces","text":"However current implementation if_width() design flaw. doesn’t work properly input duplicate names: Supporting duplicates recommended data frames wild don’t always unique names. Also, tidyselect can used vectors don’t require unique names, might extended allow recoding character vectors future. cases, handling duplicates part normal usage selection helpers. support duplicates recommended return vectors locations selection helpers rather vector names. Fixing if_width() easy: input data frame, user now informed selection contain duplicates: duplicates selected input data frame, expected:","code":"dups <- vctrs::new_data_frame(list(foo = 1, quux = 2, foo = 3))  dups %>% select(if_width(3)) #>   foo #> 1   1 if_width <- function(n, vars = peek_vars(fn = \"if_width\")) {   which(nchar(vars) == n) } dups %>% select(if_width(3)) #> Error in `select()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"foo\" at locations 1 and 2. as.list(dups) %>% select(if_width(3)) #> $foo #> [1] 1 #>  #> $foo #> [1] 3"},{"path":"https://tidyselect.r-lib.org/dev/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Lionel Henry. Author, maintainer. Hadley Wickham. Author. . Copyright holder, funder.","code":""},{"path":"https://tidyselect.r-lib.org/dev/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Henry L, Wickham H (2024). tidyselect: Select Set Strings. R package version 1.2.0.9000, https://github.com/r-lib/tidyselect, https://tidyselect.r-lib.org.","code":"@Manual{,   title = {tidyselect: Select from a Set of Strings},   author = {Lionel Henry and Hadley Wickham},   year = {2024},   note = {R package version 1.2.0.9000, https://github.com/r-lib/tidyselect},   url = {https://tidyselect.r-lib.org}, }"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Select from a Set of Strings","text":"tidyselect package backend functions like dplyr::select() dplyr::pull() well several tidyr verbs. allows create selecting verbs consistent tidyverse packages. learn selection syntax user dplyr tidyr, read user-friendly ?language reference. learn implement tidyselect functions, read vignette(\"tidyselect\"). learn exactly tidyselect syntax interpreted, read technical description vignette(\"syntax\").","code":""},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Select from a Set of Strings","text":"Generally, tidyselect installed automatically packages need . need install manually reason, can get :","code":"install.packages(\"tidyselect\")"},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Select from a Set of Strings","text":"Please note tidyselect project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables from character vectors — all_of","title":"Select variables from character vectors — all_of","text":"selection helpers select variables contained character vector. especially useful programming selecting functions. all_of() strict selection. variables character vector missing, error thrown. any_of() check missing variables. especially useful negative selections, like make sure variable removed. order selected columns determined order vector.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables from character vectors — all_of","text":"","code":"all_of(x)  any_of(x, ..., vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables from character vectors — all_of","text":"x vector character names numeric locations. ... dots future extensions must empty. vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()).","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables from character vectors — all_of","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   common names variables vector.   refer variables selecting function, use all_of():   variable missing data frame, error:   Use any_of() allow missing variables:   any_of() especially useful remove variables data frame calling cause error:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) vars <- c(\"Sepal.Length\", \"Sepal.Width\")  iris[, vars] #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows iris %>% select(all_of(vars)) #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows  iris %>% pivot_longer(all_of(vars)) #> # A tibble: 300 x 5 #>   Petal.Length Petal.Width Species name         value #>          <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1          1.4         0.2 setosa  Sepal.Length   5.1 #> 2          1.4         0.2 setosa  Sepal.Width    3.5 #> 3          1.4         0.2 setosa  Sepal.Length   4.9 #> 4          1.4         0.2 setosa  Sepal.Width    3   #> # i 296 more rows starwars %>% select(all_of(vars)) #> Error: #> i In argument: `all_of(vars)`. #> Caused by error in `all_of()` at rlang/R/eval-tidy.R:121:3: #> ! Can't subset elements that don't exist. #> x Elements `Sepal.Length` and `Sepal.Width` don't exist. starwars %>% select(any_of(vars)) #> # A tibble: 87 x 0 iris %>% select(-any_of(vars)) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Species #>          <dbl>       <dbl> <fct>   #> 1          1.4         0.2 setosa  #> 2          1.4         0.2 setosa  #> 3          1.3         0.2 setosa  #> 4          1.5         0.2 setosa  #> # i 146 more rows  iris %>% select(-any_of(vars)) %>% select(-any_of(vars)) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Species #>          <dbl>       <dbl> <fct>   #> 1          1.4         0.2 setosa  #> 2          1.4         0.2 setosa  #> 3          1.3         0.2 setosa  #> 4          1.5         0.2 setosa  #> # i 146 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate an expression to relocate variables — eval_relocate","title":"Evaluate an expression to relocate variables — eval_relocate","text":"eval_relocate() variant eval_select() moves selection new location. Either can provided specify move selection . powers dplyr::relocate().","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate an expression to relocate variables — eval_relocate","text":"","code":"eval_relocate(   expr,   data,   ...,   before = NULL,   after = NULL,   strict = TRUE,   name_spec = NULL,   allow_rename = TRUE,   allow_empty = TRUE,   allow_predicates = TRUE,   before_arg = \"before\",   after_arg = \"after\",   env = caller_env(),   error_call = caller_env() )"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate an expression to relocate variables — eval_relocate","text":"expr Defused R code describing selection according tidyselect syntax. data named list, data frame, atomic vector. Technically, data can vector names() \"[[\" implementations. ... dots future extensions must empty. , Defused R code describing selection according tidyselect syntax. selection represents destination selection provided expr. Supplying neither move selection left-hand side. Supplying error. strict TRUE, --bounds errors thrown expr attempts select rename variable exist. FALSE, failed selections renamings ignored. name_spec name specification describing combine propagate names. used case nested c() expressions like c(foo = c(bar = starts_with(\"foo\"))). See name_spec argument vctrs::vec_c() description valid name specs. allow_rename TRUE (default), renaming syntax c(foo = bar) allowed. FALSE, causes error. useful implement purely selective behaviour. allow_empty TRUE (default), ok expr result empty selection. FALSE, error expr yields empty selection. allow_predicates TRUE (default), ok expr use predicates (.e. ()). FALSE, error expr uses predicate. automatically set FALSE data support predicates (determined tidyselect_data_has_predicates()). before_arg, after_arg Argument names . used error messages. env environment evaluate expr. Discarded expr quosure. error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate an expression to relocate variables — eval_relocate","text":"named vector numeric locations length equal length(data). position data represented exactly . names normally input data, except user supplied named selections c(). latter case, names reflect new names chosen user.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate an expression to relocate variables — eval_relocate","text":"","code":"library(rlang)  # Interpret defused code as a request to relocate x <- expr(c(mpg, disp)) after <- expr(wt) eval_relocate(x, mtcars, after = after) #>  cyl   hp drat   wt  mpg disp qsec   vs   am gear carb  #>    2    4    5    6    1    3    7    8    9   10   11   # Supplying neither `before` nor `after` will move the selection to the # left-hand side eval_relocate(x, mtcars) #>  mpg disp  cyl   hp drat   wt qsec   vs   am gear carb  #>    1    3    2    4    5    6    7    8    9   10   11   # Within a function, use `enquo()` to defuse a single argument. # Note that `before` and `after` must also be defused with `enquo()`. my_relocator <- function(x, expr, before = NULL, after = NULL) {   eval_relocate(enquo(expr), x, before = enquo(before), after = enquo(after)) }  my_relocator(mtcars, vs, before = hp) #>  mpg  cyl disp   vs   hp drat   wt qsec   am gear carb  #>    1    2    3    8    4    5    6    7    9   10   11   # Here is an example of using `eval_relocate()` to implement `relocate()`. # Note that the dots are passed on as a defused call to `c(...)`. relocate <- function(.x, ..., .before = NULL, .after = NULL) {   pos <- eval_relocate(     expr(c(...)),     .x,     before = enquo(.before),     after = enquo(.after)   )   set_names(.x[pos], names(pos)) }  relocate(mtcars, vs, .before = hp) #>                      mpg cyl  disp vs  hp drat    wt  qsec am gear carb #> Mazda RX4           21.0   6 160.0  0 110 3.90 2.620 16.46  1    4    4 #> Mazda RX4 Wag       21.0   6 160.0  0 110 3.90 2.875 17.02  1    4    4 #> Datsun 710          22.8   4 108.0  1  93 3.85 2.320 18.61  1    4    1 #> Hornet 4 Drive      21.4   6 258.0  1 110 3.08 3.215 19.44  0    3    1 #> Hornet Sportabout   18.7   8 360.0  0 175 3.15 3.440 17.02  0    3    2 #> Valiant             18.1   6 225.0  1 105 2.76 3.460 20.22  0    3    1 #> Duster 360          14.3   8 360.0  0 245 3.21 3.570 15.84  0    3    4 #> Merc 240D           24.4   4 146.7  1  62 3.69 3.190 20.00  0    4    2 #> Merc 230            22.8   4 140.8  1  95 3.92 3.150 22.90  0    4    2 #> Merc 280            19.2   6 167.6  1 123 3.92 3.440 18.30  0    4    4 #> Merc 280C           17.8   6 167.6  1 123 3.92 3.440 18.90  0    4    4 #> Merc 450SE          16.4   8 275.8  0 180 3.07 4.070 17.40  0    3    3 #> Merc 450SL          17.3   8 275.8  0 180 3.07 3.730 17.60  0    3    3 #> Merc 450SLC         15.2   8 275.8  0 180 3.07 3.780 18.00  0    3    3 #> Cadillac Fleetwood  10.4   8 472.0  0 205 2.93 5.250 17.98  0    3    4 #> Lincoln Continental 10.4   8 460.0  0 215 3.00 5.424 17.82  0    3    4 #> Chrysler Imperial   14.7   8 440.0  0 230 3.23 5.345 17.42  0    3    4 #> Fiat 128            32.4   4  78.7  1  66 4.08 2.200 19.47  1    4    1 #> Honda Civic         30.4   4  75.7  1  52 4.93 1.615 18.52  1    4    2 #> Toyota Corolla      33.9   4  71.1  1  65 4.22 1.835 19.90  1    4    1 #> Toyota Corona       21.5   4 120.1  1  97 3.70 2.465 20.01  0    3    1 #> Dodge Challenger    15.5   8 318.0  0 150 2.76 3.520 16.87  0    3    2 #> AMC Javelin         15.2   8 304.0  0 150 3.15 3.435 17.30  0    3    2 #> Camaro Z28          13.3   8 350.0  0 245 3.73 3.840 15.41  0    3    4 #> Pontiac Firebird    19.2   8 400.0  0 175 3.08 3.845 17.05  0    3    2 #> Fiat X1-9           27.3   4  79.0  1  66 4.08 1.935 18.90  1    4    1 #> Porsche 914-2       26.0   4 120.3  0  91 4.43 2.140 16.70  1    5    2 #> Lotus Europa        30.4   4  95.1  1 113 3.77 1.513 16.90  1    5    2 #> Ford Pantera L      15.8   8 351.0  0 264 4.22 3.170 14.50  1    5    4 #> Ferrari Dino        19.7   6 145.0  0 175 3.62 2.770 15.50  1    5    6 #> Maserati Bora       15.0   8 301.0  0 335 3.54 3.570 14.60  1    5    8 #> Volvo 142E          21.4   4 121.0  1 109 4.11 2.780 18.60  1    4    2 relocate(mtcars, starts_with(\"d\"), .after = last_col()) #>                      mpg cyl  hp    wt  qsec vs am gear carb  disp drat #> Mazda RX4           21.0   6 110 2.620 16.46  0  1    4    4 160.0 3.90 #> Mazda RX4 Wag       21.0   6 110 2.875 17.02  0  1    4    4 160.0 3.90 #> Datsun 710          22.8   4  93 2.320 18.61  1  1    4    1 108.0 3.85 #> Hornet 4 Drive      21.4   6 110 3.215 19.44  1  0    3    1 258.0 3.08 #> Hornet Sportabout   18.7   8 175 3.440 17.02  0  0    3    2 360.0 3.15 #> Valiant             18.1   6 105 3.460 20.22  1  0    3    1 225.0 2.76 #> Duster 360          14.3   8 245 3.570 15.84  0  0    3    4 360.0 3.21 #> Merc 240D           24.4   4  62 3.190 20.00  1  0    4    2 146.7 3.69 #> Merc 230            22.8   4  95 3.150 22.90  1  0    4    2 140.8 3.92 #> Merc 280            19.2   6 123 3.440 18.30  1  0    4    4 167.6 3.92 #> Merc 280C           17.8   6 123 3.440 18.90  1  0    4    4 167.6 3.92 #> Merc 450SE          16.4   8 180 4.070 17.40  0  0    3    3 275.8 3.07 #> Merc 450SL          17.3   8 180 3.730 17.60  0  0    3    3 275.8 3.07 #> Merc 450SLC         15.2   8 180 3.780 18.00  0  0    3    3 275.8 3.07 #> Cadillac Fleetwood  10.4   8 205 5.250 17.98  0  0    3    4 472.0 2.93 #> Lincoln Continental 10.4   8 215 5.424 17.82  0  0    3    4 460.0 3.00 #> Chrysler Imperial   14.7   8 230 5.345 17.42  0  0    3    4 440.0 3.23 #> Fiat 128            32.4   4  66 2.200 19.47  1  1    4    1  78.7 4.08 #> Honda Civic         30.4   4  52 1.615 18.52  1  1    4    2  75.7 4.93 #> Toyota Corolla      33.9   4  65 1.835 19.90  1  1    4    1  71.1 4.22 #> Toyota Corona       21.5   4  97 2.465 20.01  1  0    3    1 120.1 3.70 #> Dodge Challenger    15.5   8 150 3.520 16.87  0  0    3    2 318.0 2.76 #> AMC Javelin         15.2   8 150 3.435 17.30  0  0    3    2 304.0 3.15 #> Camaro Z28          13.3   8 245 3.840 15.41  0  0    3    4 350.0 3.73 #> Pontiac Firebird    19.2   8 175 3.845 17.05  0  0    3    2 400.0 3.08 #> Fiat X1-9           27.3   4  66 1.935 18.90  1  1    4    1  79.0 4.08 #> Porsche 914-2       26.0   4  91 2.140 16.70  0  1    5    2 120.3 4.43 #> Lotus Europa        30.4   4 113 1.513 16.90  1  1    5    2  95.1 3.77 #> Ford Pantera L      15.8   8 264 3.170 14.50  0  1    5    4 351.0 4.22 #> Ferrari Dino        19.7   6 175 2.770 15.50  0  1    5    6 145.0 3.62 #> Maserati Bora       15.0   8 335 3.570 14.60  0  1    5    8 301.0 3.54 #> Volvo 142E          21.4   4 109 2.780 18.60  1  1    4    2 121.0 4.11"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate an expression with tidyselect semantics — eval_rename","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"eval_select() eval_rename() evaluate defused R code (.e. quoted expressions) according special rules tidyselect syntax. power functions like dplyr::select(), dplyr::rename(), tidyr::pivot_longer(). See Get started vignette learn use eval_select() eval_rename() packages.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"","code":"eval_rename(   expr,   data,   env = caller_env(),   ...,   strict = TRUE,   name_spec = NULL,   allow_predicates = TRUE,   error_call = caller_env() )  eval_select(   expr,   data,   env = caller_env(),   ...,   include = NULL,   exclude = NULL,   strict = TRUE,   name_spec = NULL,   allow_rename = TRUE,   allow_empty = TRUE,   allow_predicates = TRUE,   error_call = caller_env() )"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"expr Defused R code describing selection according tidyselect syntax. data named list, data frame, atomic vector. Technically, data can vector names() \"[[\" implementations. env environment evaluate expr. Discarded expr quosure. ... dots future extensions must empty. strict TRUE, --bounds errors thrown expr attempts select rename variable exist. FALSE, failed selections renamings ignored. name_spec name specification describing combine propagate names. used case nested c() expressions like c(foo = c(bar = starts_with(\"foo\"))). See name_spec argument vctrs::vec_c() description valid name specs. allow_predicates TRUE (default), ok expr use predicates (.e. ()). FALSE, error expr uses predicate. automatically set FALSE data support predicates (determined tidyselect_data_has_predicates()). error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information. include, exclude Character vector column names always include exclude selection. allow_rename TRUE (default), renaming syntax c(foo = bar) allowed. FALSE, causes error. useful implement purely selective behaviour. allow_empty TRUE (default), ok expr result empty selection. FALSE, error expr yields empty selection.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"named vector numeric locations, one selected elements. names normally input data, except user supplied named selections c(). latter case, names reflect new names chosen user. given element may selected multiple times different names, case vector might contain duplicate locations.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"select rename variants take types inputs type return value. However eval_rename() extra constraints. requires named inputs, fail data frame column renamed another existing column name. See selecting versus renaming section syntax vignette description differences.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"","code":"library(rlang)  # Interpret defused code as selection: x <- expr(mpg:cyl) eval_select(x, mtcars) #> mpg cyl  #>   1   2   # Interpret defused code as a renaming selection. All inputs must # be named within `c()`: try(eval_rename(expr(mpg), mtcars)) #> Error in eval(expr, envir, enclos) :  #>   All renaming inputs must be named. eval_rename(expr(c(foo = mpg)), mtcars) #> foo  #>   1    # Within a function, use `enquo()` to defuse one argument: my_function <- function(x, expr) {   eval_select(enquo(expr), x) }  # If your function takes dots, evaluate a defused call to `c(...)` # with `expr(c(...))`: my_function <- function(.x, ...) {   eval_select(expr(c(...)), .x) }  # If your function takes dots and a named argument, use `{{ }}` # inside the defused expression to tunnel it inside the tidyselect DSL: my_function <- function(.x, .expr, ...) {   eval_select(expr(c({{ .expr }}, ...)), .x) }  # Note that the trick above works because `expr({{ arg }})` is the # same as `enquo(arg)`.   # The evaluators return a named vector of locations. Here are # examples of using these location vectors to implement `select()` # and `rename()`: select <- function(.x, ...) {   pos <- eval_select(expr(c(...)), .x)   set_names(.x[pos], names(pos)) } rename <- function(.x, ...) {   pos <- eval_rename(expr(c(...)), .x)   names(.x)[pos] <- names(pos)   .x }  select(mtcars, mpg:cyl) #>                      mpg cyl #> Mazda RX4           21.0   6 #> Mazda RX4 Wag       21.0   6 #> Datsun 710          22.8   4 #> Hornet 4 Drive      21.4   6 #> Hornet Sportabout   18.7   8 #> Valiant             18.1   6 #> Duster 360          14.3   8 #> Merc 240D           24.4   4 #> Merc 230            22.8   4 #> Merc 280            19.2   6 #> Merc 280C           17.8   6 #> Merc 450SE          16.4   8 #> Merc 450SL          17.3   8 #> Merc 450SLC         15.2   8 #> Cadillac Fleetwood  10.4   8 #> Lincoln Continental 10.4   8 #> Chrysler Imperial   14.7   8 #> Fiat 128            32.4   4 #> Honda Civic         30.4   4 #> Toyota Corolla      33.9   4 #> Toyota Corona       21.5   4 #> Dodge Challenger    15.5   8 #> AMC Javelin         15.2   8 #> Camaro Z28          13.3   8 #> Pontiac Firebird    19.2   8 #> Fiat X1-9           27.3   4 #> Porsche 914-2       26.0   4 #> Lotus Europa        30.4   4 #> Ford Pantera L      15.8   8 #> Ferrari Dino        19.7   6 #> Maserati Bora       15.0   8 #> Volvo 142E          21.4   4 rename(mtcars, foo = mpg) #>                      foo cyl  disp  hp drat    wt  qsec vs am gear carb #> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4 #> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4 #> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1 #> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1 #> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2 #> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1 #> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4 #> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2 #> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2 #> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4 #> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4 #> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3 #> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3 #> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3 #> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4 #> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 #> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4 #> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1 #> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2 #> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1 #> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1 #> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2 #> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2 #> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4 #> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2 #> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1 #> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2 #> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2 #> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4 #> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6 #> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8 #> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2"},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":null,"dir":"Reference","previous_headings":"","what":"Select all variables or the last variable — everything","title":"Select all variables or the last variable — everything","text":"functions selection helpers. everything() selects variable. also useful combination tidyselect operators. last_col() selects last variable.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select all variables or the last variable — everything","text":"","code":"everything(vars = NULL)  last_col(offset = 0L, vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select all variables or the last variable — everything","text":"vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()). offset Set n select nth var end.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select all variables or the last variable — everything","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   Use everything() select variables:   Use last_col() select last variable:   Supply offset n select variable located n positions end:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) mtcars <- as_tibble(mtcars) iris %>% select(everything()) #> # A tibble: 150 x 5 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species #>          <dbl>       <dbl>        <dbl>       <dbl> <fct>   #> 1          5.1         3.5          1.4         0.2 setosa  #> 2          4.9         3            1.4         0.2 setosa  #> 3          4.7         3.2          1.3         0.2 setosa  #> 4          4.6         3.1          1.5         0.2 setosa  #> # i 146 more rows  mtcars %>% pivot_longer(everything()) #> # A tibble: 352 x 2 #>   name  value #>   <chr> <dbl> #> 1 mpg      21 #> 2 cyl       6 #> 3 disp    160 #> 4 hp      110 #> # i 348 more rows iris %>% select(last_col()) #> # A tibble: 150 x 1 #>   Species #>   <fct>   #> 1 setosa  #> 2 setosa  #> 3 setosa  #> 4 setosa  #> # i 146 more rows  mtcars %>% pivot_longer(last_col()) #> # A tibble: 32 x 12 #>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear name  value #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> #> 1  21       6   160   110  3.9   2.62  16.5     0     1     4 carb      4 #> 2  21       6   160   110  3.9   2.88  17.0     0     1     4 carb      4 #> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4 carb      1 #> 4  21.4     6   258   110  3.08  3.22  19.4     1     0     3 carb      1 #> # i 28 more rows mtcars %>% select(1:last_col(5)) #> # A tibble: 32 x 6 #>     mpg   cyl  disp    hp  drat    wt #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160   110  3.9   2.62 #> 2  21       6   160   110  3.9   2.88 #> 3  22.8     4   108    93  3.85  2.32 #> 4  21.4     6   258   110  3.08  3.22 #> # i 28 more rows"},{"path":[]},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-external-vector.html","id":"ambiguity-between-columns-and-external-variables","dir":"Reference","previous_headings":"","what":"Ambiguity between columns and external variables","title":"FAQ - Note: Using an external vector in selections is ambiguous — faq-external-vector","text":"selecting functions like dplyr::select() tidyr::pivot_longer(), can refer variables name:   historical reasons, also possible refer external vector variable names. get correct result, warning informing selecting external variable ambiguous clear whether want data frame column external object.   decided deprecate particular approach using external vectors introduce ambiguity. Imagine data frame contains column name external variable.   different objects isn’t problem context forces specific find vars:   selection context however, column wins:","code":"mtcars %>% select(cyl, am, vs) #> # A tibble: 32 x 3 #>     cyl    am    vs #>   <dbl> <dbl> <dbl> #> 1     6     1     0 #> 2     6     1     0 #> 3     4     1     1 #> 4     6     0     1 #> # i 28 more rows  mtcars %>% select(mpg:disp) #> # A tibble: 32 x 3 #>     mpg   cyl  disp #>   <dbl> <dbl> <dbl> #> 1  21       6   160 #> 2  21       6   160 #> 3  22.8     4   108 #> 4  21.4     6   258 #> # i 28 more rows vars <- c(\"cyl\", \"am\", \"vs\") result <- mtcars %>% select(vars) #> Warning: Using an external vector in selections was deprecated in tidyselect #> 1.1.0. #> i Please use `all_of()` or `any_of()` instead. #>   # Was: #>   data %>% select(vars) #>  #>   # Now: #>   data %>% select(all_of(vars)) #>  #> See #> <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this #> warning was generated. some_df <- mtcars[1:4, ] some_df$vars <- 1:nrow(some_df) vars #> [1] \"cyl\" \"am\"  \"vs\"  some_df$vars #> [1] 1 2 3 4 some_df %>% select(vars) #> # A tibble: 4 x 1 #>    vars #>   <int> #> 1     1 #> 2     2 #> 3     3 #> 4     4"},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-external-vector.html","id":"fixing-the-ambiguity","dir":"Reference","previous_headings":"","what":"Fixing the ambiguity","title":"FAQ - Note: Using an external vector in selections is ambiguous — faq-external-vector","text":"make selection code robust silence message, use all_of() force external vector:   information comments , please see Github issue tracking deprecation process.","code":"some_df %>% select(all_of(vars)) #> # A tibble: 4 x 3 #>     cyl    am    vs #>   <dbl> <dbl> <dbl> #> 1     6     1     0 #> 2     6     1     0 #> 3     4     1     1 #> 4     6     0     1"},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-selection-context.html","id":null,"dir":"Reference","previous_headings":"","what":"FAQ - Error: Must be used within a selecting function — faq-selection-context","title":"FAQ - Error: Must be used within a selecting function — faq-selection-context","text":"Functions like starts_with(), contains() matches() selection helpers work selection context, e.g. dplyr::select() cols argument tidyr::pivot_longer(). Using selection helper anywhere else results error:   see error, may used selection helper wrong place, possibly result typo (e.g. misplaced comma wrong argument name). Alternatively, may deliberately trying reduce duplication code extracting selection variable:   make work ’ll need two things: Wrap whole thing function Use any_of() all_of() instead bare variable names","code":"starts_with(\"foo\") #> Error: #> ! `starts_with()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details.  mtcars[contains(\"foo\")] #> Error: #> ! `contains()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details.  subset(mtcars, select = matches(\"foo\")) #> Error: #> ! `matches()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details. my_vars <- c(name, species, ends_with(\"color\")) #> Error in eval(expr, envir, enclos): object 'name' not found my_vars <- function() {   c(any_of(c(\"name\", \"species\")), ends_with(\"color\")) } dplyr::select(starwars, my_vars()) #> # A tibble: 87 x 5 #>   name           species hair_color skin_color  eye_color #>   <chr>          <chr>   <chr>      <chr>       <chr>     #> 1 Luke Skywalker Human   blond      fair        blue      #> 2 C-3PO          Droid   <NA>       gold        yellow    #> 3 R2-D2          Droid   <NA>       white, blue red       #> 4 Darth Vader    Human   none       white       yellow    #> # i 83 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"overview-of-selection-features-","dir":"Reference","previous_headings":"","what":"Overview of selection features:","title":"Selection language — language","text":"tidyselect implements DSL selecting variables. provides helpers selecting variables: var1:var10: variables lying var1 left var10 right. starts_with(\"\"): names start \"\". ends_with(\"z\"): names end \"z\". contains(\"b\"): names contain \"b\". matches(\"x.y\"): names match regular expression x.y. num_range(x, 1:4): names following pattern, x1, x2, ..., x4. all_of(vars)/any_of(vars): matches names stored character vector vars. all_of(vars) error variables present; any_of(var) match just variables exist. everything(): variables. last_col(): furthest column right. (.numeric): variables .numeric() returns TRUE. well operators combining selections: !selection: variables match selection. selection1 & selection2: variables included selection1 selection2. selection1 | selection2: variables match either selection1 selection2. writing code inside packages can substitute \"var\" var avoid R CMD check notes.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"simple-examples","dir":"Reference","previous_headings":"","what":"Simple examples","title":"Selection language — language","text":"show usage basic selection operators. See specific help pages learn helpers like starts_with(). selection language can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   Select variables name:   Select multiple variables separating commas. Note order columns determined order inputs:   Functions like tidyr::pivot_longer() take variables dots. case use c() select multiple variables:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) starwars %>% select(height) #> # A tibble: 87 x 1 #>   height #>    <int> #> 1    172 #> 2    167 #> 3     96 #> 4    202 #> # i 83 more rows  iris %>% pivot_longer(Sepal.Length) #> # A tibble: 150 x 6 #>   Sepal.Width Petal.Length Petal.Width Species name         value #>         <dbl>        <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1         3.5          1.4         0.2 setosa  Sepal.Length   5.1 #> 2         3            1.4         0.2 setosa  Sepal.Length   4.9 #> 3         3.2          1.3         0.2 setosa  Sepal.Length   4.7 #> 4         3.1          1.5         0.2 setosa  Sepal.Length   4.6 #> # i 146 more rows starwars %>% select(homeworld, height, mass) #> # A tibble: 87 x 3 #>   homeworld height  mass #>   <chr>      <int> <dbl> #> 1 Tatooine     172    77 #> 2 Tatooine     167    75 #> 3 Naboo         96    32 #> 4 Tatooine     202   136 #> # i 83 more rows iris %>% pivot_longer(c(Sepal.Length, Petal.Length)) #> # A tibble: 300 x 5 #>   Sepal.Width Petal.Width Species name         value #>         <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1         3.5         0.2 setosa  Sepal.Length   5.1 #> 2         3.5         0.2 setosa  Petal.Length   1.4 #> 3         3           0.2 setosa  Sepal.Length   4.9 #> 4         3           0.2 setosa  Petal.Length   1.4 #> # i 296 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"operators-","dir":"Reference","previous_headings":"","what":"Operators:","title":"Selection language — language","text":": operator selects range consecutive variables:   ! operator negates selection:   & | take intersection union two selections:   take difference two selections, combine & ! operators:","code":"starwars %>% select(name:mass) #> # A tibble: 87 x 3 #>   name           height  mass #>   <chr>           <int> <dbl> #> 1 Luke Skywalker    172    77 #> 2 C-3PO             167    75 #> 3 R2-D2              96    32 #> 4 Darth Vader       202   136 #> # i 83 more rows starwars %>% select(!(name:mass)) #> # A tibble: 87 x 11 #>   hair_color skin_color  eye_color birth_year sex   gender    homeworld species #>   <chr>      <chr>       <chr>          <dbl> <chr> <chr>     <chr>     <chr>   #> 1 blond      fair        blue            19   male  masculine Tatooine  Human   #> 2 <NA>       gold        yellow         112   none  masculine Tatooine  Droid   #> 3 <NA>       white, blue red             33   none  masculine Naboo     Droid   #> 4 none       white       yellow          41.9 male  masculine Tatooine  Human   #> # i 83 more rows #> # i 3 more variables: films <list>, vehicles <list>, starships <list>  iris %>% select(!c(Sepal.Length, Petal.Length)) #> # A tibble: 150 x 3 #>   Sepal.Width Petal.Width Species #>         <dbl>       <dbl> <fct>   #> 1         3.5         0.2 setosa  #> 2         3           0.2 setosa  #> 3         3.2         0.2 setosa  #> 4         3.1         0.2 setosa  #> # i 146 more rows  iris %>% select(!ends_with(\"Width\")) #> # A tibble: 150 x 3 #>   Sepal.Length Petal.Length Species #>          <dbl>        <dbl> <fct>   #> 1          5.1          1.4 setosa  #> 2          4.9          1.4 setosa  #> 3          4.7          1.3 setosa  #> 4          4.6          1.5 setosa  #> # i 146 more rows iris %>% select(starts_with(\"Petal\") & ends_with(\"Width\")) #> # A tibble: 150 x 1 #>   Petal.Width #>         <dbl> #> 1         0.2 #> 2         0.2 #> 3         0.2 #> 4         0.2 #> # i 146 more rows  iris %>% select(starts_with(\"Petal\") | ends_with(\"Width\")) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Sepal.Width #>          <dbl>       <dbl>       <dbl> #> 1          1.4         0.2         3.5 #> 2          1.4         0.2         3   #> 3          1.3         0.2         3.2 #> 4          1.5         0.2         3.1 #> # i 146 more rows iris %>% select(starts_with(\"Petal\") & !ends_with(\"Width\")) #> # A tibble: 150 x 1 #>   Petal.Length #>          <dbl> #> 1          1.4 #> 2          1.4 #> 3          1.3 #> 4          1.5 #> # i 146 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Selection language — language","text":"order selected columns determined inputs. all_of(c(\"foo\", \"bar\")) selects \"foo\" first. c(starts_with(\"c\"), starts_with(\"d\")) selects columns starting \"c\" first, columns starting \"d\".","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Superseded selection helpers — one_of","title":"Superseded selection helpers — one_of","text":"one_of() superseded favour precise any_of() all_of() selectors.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Superseded selection helpers — one_of","text":"","code":"one_of(..., .vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Superseded selection helpers — one_of","text":"... One character vectors. .vars character vector variable names. called inside selecting functions like dplyr::select() automatically set names table.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":null,"dir":"Reference","previous_headings":"","what":"Peek at variables in the selection context — peek_vars","title":"Peek at variables in the selection context — peek_vars","text":"peek_vars() returns vector names variables currently available selection. peek_data() returns whole input vector (available eval_select()). Read Get started examples create selection helpers peek_vars(). variable names selection context registered automatically eval_select() eval_rename() duration evaluation. peek_vars() glue connects selection helpers current selection context.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Peek at variables in the selection context — peek_vars","text":"","code":"peek_vars(..., fn = NULL)  peek_data(..., fn = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Peek at variables in the selection context — peek_vars","text":"... dots future extensions must empty. fn name function use error messages helper used wrong context. supplied, generic error message used instead.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":null,"dir":"Reference","previous_headings":"","what":"Replace or get current variables — poke_vars","title":"Replace or get current variables — poke_vars","text":"Variables made available select helpers registering special placeholder. scoped_vars() changes current variables sets function exit hook automatically restores previous variables current function returns. with_vars() takes expression evaluated variable context. poke_vars() changes contents placeholder new set variables. returns previous variables invisibly responsibility restore done. expert use . peek_vars() returns variables currently registered. has_vars() returns TRUE variable context set, FALSE otherwise.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Replace or get current variables — poke_vars","text":"","code":"poke_vars(vars)  scoped_vars(vars, frame = caller_env())  with_vars(vars, expr)  has_vars()"},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Replace or get current variables — poke_vars","text":"vars character vector variable names. frame frame environment exit hook restoring old variables registered. expr expression evaluated within variable context.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Replace or get current variables — poke_vars","text":"poke_vars() scoped_vars(), old variables invisibly. peek_vars(), variables currently registered.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Replace or get current variables — poke_vars","text":"","code":"poke_vars(letters) peek_vars() #>  [1] \"a\" \"b\" \"c\" \"d\" \"e\" \"f\" \"g\" \"h\" \"i\" \"j\" \"k\" \"l\" \"m\" \"n\" \"o\" \"p\" \"q\" #> [18] \"r\" \"s\" \"t\" \"u\" \"v\" \"w\" \"x\" \"y\" \"z\"  # Now that the variables are registered, the helpers can figure out # the locations of elements within the variable vector: all_of(c(\"d\", \"z\")) #> [1]  4 26  # In a function be sure to restore the previous variables. An exit # hook is the best way to do it: fn <- function(vars) {   old <- poke_vars(vars)   on.exit(poke_vars(old))    all_of(\"d\") } fn(letters) #> [1] 4 fn(letters[3:5]) #> [1] 2  # The previous variables are still registered after fn() was # called: peek_vars() #>  [1] \"a\" \"b\" \"c\" \"d\" \"e\" \"f\" \"g\" \"h\" \"i\" \"j\" \"k\" \"l\" \"m\" \"n\" \"o\" \"p\" \"q\" #> [18] \"r\" \"s\" \"t\" \"u\" \"v\" \"w\" \"x\" \"y\" \"z\"   # It is recommended to use the scoped variant as it restores the # state automatically when the function returns: fn <- function(vars) {   scoped_vars(vars)   starts_with(\"r\") } fn(c(\"red\", \"blue\", \"rose\")) #> [1] 1 3  # The with_vars() helper makes it easy to pass an expression that # should be evaluated in a variable context. Thanks to lazy # evaluation, you can just pass the expression argument from your # wrapper to with_vars(): fn <- function(expr) {   vars <- c(\"red\", \"blue\", \"rose\")   with_vars(vars, expr) } fn(starts_with(\"r\")) #> [1] 1 3"},{"path":"https://tidyselect.r-lib.org/dev/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. rlang enquo, quo, quo_name, quos","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables that match a pattern — starts_with","title":"Select variables that match a pattern — starts_with","text":"selection helpers match variables according given pattern. starts_with(): Starts exact prefix. ends_with(): Ends exact suffix. contains(): Contains literal string. matches(): Matches regular expression. num_range(): Matches numerical range like x01, x02, x03.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables that match a pattern — starts_with","text":"","code":"starts_with(match, ignore.case = TRUE, vars = NULL)  ends_with(match, ignore.case = TRUE, vars = NULL)  contains(match, ignore.case = TRUE, vars = NULL)  matches(match, ignore.case = TRUE, perl = FALSE, vars = NULL)  num_range(prefix, range, suffix = \"\", width = NULL, vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables that match a pattern — starts_with","text":"match character vector. length > 1, union matches taken. starts_with(), ends_with(), contains() exact match. matches() regular expression, can stringr pattern. ignore.case TRUE, default, ignores case matching names. vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()). perl Perl-compatible regexps used? prefix, suffix prefix/suffix added /numeric range. range sequence integers, like 1:5. width Optionally, \"width\" numeric range. example, range 2 gives \"01\", range three \"001\", etc.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables that match a pattern — starts_with","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   starts_with() selects variables matching prefix ends_with() matches suffix:   can supply multiple prefixes suffixes. Note order variables depends order suffixes prefixes:   contains() selects columns whose names contain word:   starts_with(), ends_with(), contains() use regular expressions. select regexp use matches():   starts_with() selects variables starting prefix. select range, use num_range(). Compare:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) iris %>% select(starts_with(\"Sepal\")) #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows  iris %>% select(ends_with(\"Width\")) #> # A tibble: 150 x 2 #>   Sepal.Width Petal.Width #>         <dbl>       <dbl> #> 1         3.5         0.2 #> 2         3           0.2 #> 3         3.2         0.2 #> 4         3.1         0.2 #> # i 146 more rows iris %>% select(starts_with(c(\"Petal\", \"Sepal\"))) #> # A tibble: 150 x 4 #>   Petal.Length Petal.Width Sepal.Length Sepal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          1.4         0.2          5.1         3.5 #> 2          1.4         0.2          4.9         3   #> 3          1.3         0.2          4.7         3.2 #> 4          1.5         0.2          4.6         3.1 #> # i 146 more rows  iris %>% select(ends_with(c(\"Width\", \"Length\"))) #> # A tibble: 150 x 4 #>   Sepal.Width Petal.Width Sepal.Length Petal.Length #>         <dbl>       <dbl>        <dbl>        <dbl> #> 1         3.5         0.2          5.1          1.4 #> 2         3           0.2          4.9          1.4 #> 3         3.2         0.2          4.7          1.3 #> 4         3.1         0.2          4.6          1.5 #> # i 146 more rows iris %>% select(contains(\"al\")) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows # [pt] is matched literally: iris %>% select(contains(\"[pt]al\")) #> # A tibble: 150 x 0  # [pt] is interpreted as a regular expression iris %>% select(matches(\"[pt]al\")) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows billboard %>% select(starts_with(\"wk\")) #> # A tibble: 317 x 76 #>     wk1   wk2   wk3   wk4   wk5   wk6   wk7   wk8   wk9  wk10  wk11  wk12  wk13 #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1    87    82    72    77    87    94    99    NA    NA    NA    NA    NA    NA #> 2    91    87    92    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA #> 3    81    70    68    67    66    57    54    53    51    51    51    51    47 #> 4    76    76    72    69    67    65    55    59    62    61    61    59    61 #> # i 313 more rows #> # i 63 more variables: wk14 <dbl>, wk15 <dbl>, wk16 <dbl>, wk17 <dbl>, #> #   wk18 <dbl>, wk19 <dbl>, wk20 <dbl>, wk21 <dbl>, ...  billboard %>% select(num_range(\"wk\", 10:15)) #> # A tibble: 317 x 6 #>    wk10  wk11  wk12  wk13  wk14  wk15 #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1    NA    NA    NA    NA    NA    NA #> 2    NA    NA    NA    NA    NA    NA #> 3    51    51    51    47    44    38 #> 4    61    61    59    61    66    72 #> # i 313 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect-package.html","id":null,"dir":"Reference","previous_headings":"","what":"tidyselect: Select from a Set of Strings — tidyselect-package","title":"tidyselect: Select from a Set of Strings — tidyselect-package","text":"backend selecting functions 'tidyverse'. makes easy implement select-like functions packages way consistent 'tidyverse' interfaces selection.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"tidyselect: Select from a Set of Strings — tidyselect-package","text":"Maintainer: Lionel Henry lionel@posit.co Authors: Hadley Wickham hadley@posit.co contributors: Posit Software, PBC [copyright holder, funder]","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":null,"dir":"Reference","previous_headings":"","what":"tidyselect methods for custom types — tidyselect_data_proxy","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"tidyselect_data_proxy() returns data frame. tidyselect_data_has_predicates() returns TRUE FALSE support predicate functions, return 0-row data frame tidyselect_data_proxy() FALSE tidyselect_data_has_predicates().","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"","code":"tidyselect_data_proxy(x)  tidyselect_data_has_predicates(x)"},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"x data-frame like object passed eval_select(), eval_rename(), friends.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variable — vars_pull","title":"Select variable — vars_pull","text":"function powers dplyr::pull() various functions tidyr package. similar vars_select() returns one column name slightly different semantics: allows negative numbers select columns end.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variable — vars_pull","text":"","code":"vars_pull(   vars,   var = -1,   error_call = caller_env(),   error_arg = caller_arg(var) )"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variable — vars_pull","text":"vars character vector existing column names. var variable specified : literal variable name positive integer, giving position counting left negative integer, giving position counting right. default returns last column (assumption column created recently). argument taken expression supports quasiquotation (can unquote column names column locations). error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information. error_arg argument name string. argument mentioned error messages input origin problem.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select variable — vars_pull","text":"selected column name unnamed string.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variable — vars_pull","text":"","code":"# It takes its argument by expression: vars_pull(letters, c) #> [1] \"c\"  # Negative numbers select from the end: vars_pull(letters, -3) #> [1] \"x\"  # You can unquote variables: var <- 10 vars_pull(letters, !!var) #> [1] \"j\""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Select or rename variables — vars_select","title":"Select or rename variables — vars_select","text":"Please use eval_select() eval_rename() instead. See vignette(\"tidyselect\") get started.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select or rename variables — vars_select","text":"","code":"vars_select(   .vars,   ...,   .include = character(),   .exclude = character(),   .strict = TRUE )  vars_rename(.vars, ..., .strict = TRUE)"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select or rename variables — vars_select","text":".vars character vector existing column names. ... Selection inputs. See help selection helpers. .include, .exclude Character vector column names always include/exclude. .strict TRUE, throw error attempt select rename variable exist.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select or rename variables — vars_select","text":"named character vector. Values existing column names, names new names.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":null,"dir":"Reference","previous_headings":"","what":"List of selection helpers — vars_select_helpers","title":"List of selection helpers — vars_select_helpers","text":"list contains selection helpers exported tidyselect. useful wanted embed helpers API without track addition new helpers tidyselect. However selection helpers now always embedded DSL.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List of selection helpers — vars_select_helpers","text":"","code":"vars_select_helpers"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"List of selection helpers — vars_select_helpers","text":"object class list length 11.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables with a function — where","title":"Select variables with a function — where","text":"selection helper selects variables function returns TRUE.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables with a function — where","text":"","code":"where(fn)"},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables with a function — where","text":"fn function returns TRUE FALSE (technically, predicate function). Can also purrr-like formula.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables with a function — where","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   () takes function returns variables function returns TRUE:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) is.factor(iris[[4]]) #> [1] FALSE  is.factor(iris[[5]]) #> [1] TRUE  iris %>% select(where(is.factor)) #> # A tibble: 150 x 1 #>   Species #>   <fct>   #> 1 setosa  #> 2 setosa  #> 3 setosa  #> 4 setosa  #> # i 146 more rows  is.numeric(iris[[4]]) #> [1] TRUE  is.numeric(iris[[5]]) #> [1] FALSE  iris %>% select(where(is.numeric)) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"the-formula-shorthand","dir":"Reference","previous_headings":"","what":"The formula shorthand","title":"Select variables with a function — where","text":"can use purrr-like formulas shortcut creating function spot. expressions equivalent:   shorthand useful adding logic inline. select numeric variables whose mean greater 3.5:","code":"iris %>% select(where(is.numeric)) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows  iris %>% select(where(function(x) is.numeric(x))) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows  iris %>% select(where(~ is.numeric(.x))) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows iris %>% select(where(~ is.numeric(.x) && mean(.x) > 3.5)) #> # A tibble: 150 x 2 #>   Sepal.Length Petal.Length #>          <dbl>        <dbl> #> 1          5.1          1.4 #> 2          4.9          1.4 #> 3          4.7          1.3 #> 4          4.6          1.5 #> # i 146 more rows"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-development-version","dir":"Changelog","previous_headings":"","what":"tidyselect (development version)","title":"tidyselect (development version)","text":"Performance improvements (#337, #338, #339, #341) eval_select() --bounds errors now use verb “select” rather “subset” error message consistency dplyr::select() (#271). Fix CRAN checks.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-120","dir":"Changelog","previous_headings":"","what":"tidyselect 1.2.0","title":"tidyselect 1.2.0","text":"CRAN release: 2022-10-10","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New features","title":"tidyselect 1.2.0","text":"New tidyselect_data_proxy() tidyselect_data_has_predicates() allows tidyselect work custom input types (#242). New eval_relocate() moving selection. powers dplyr::relocate() (#232).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"lifecycle-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Lifecycle changes","title":"tidyselect 1.2.0","text":"Using all_of() outside tidyselect context now deprecated (#269). future error consistent any_of(). Use .data tidyselect expressions now deprecated cleanly separate tidy-select data-masking. Replace .data$x \"x\" .data[[var]] all_of(var) (#169). Use bare predicates (wrapped ()) indirection (without using all_of()) formally deprecated (#317).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"minor-improvements-and-bug-fixes-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor improvements and bug fixes","title":"tidyselect 1.2.0","text":"Selection language: any_of() generates informative error supply many arguments (#241). all_of() (like any_of()) returns integer vector make easier combine functions (#270, #294). also fails can’t find variables even strict = FALSE. matches() recognises correctly uses stringr pattern objects (stringr::regex(), stringr::fixed(), etc) (#238). also now works named vectors (#250). num_range() gains suffix argument (#229). () now exported, like select helpers (#201), gives informative errors (#236). eval_select() include now preserves order variables ’re present selection (#224). eval_select() always returns named vector, even renaming permitted (#220). eval_select() eval_relocate() gain new allow_empty argument makes possible forbid empty selections allow_empty = FALSE (#252). eval_select(allow_rename = FALSE) longer fails empty selections (#221, @eutwt) predicate functions (#225). now properly fails partial renaming (#305). peek_var() error now generates hyperlink docs recent RStudio (#289). vars_pull() generates informative error messages (#234, #258, #318) gains error_call error_arg arguments. Errors produced tidyselect now informative. Evaluation errors now chained, child error call set error_call argument eval_select() eval_rename(). ’ve also improved backtraces base errors, done better propagating root error_call vctrs input checkers. tidyselect_verbosity longer used; deprecation messaging now controlled lifecycle_verbosity like packages (#317).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-112","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.2","title":"tidyselect 1.1.2","text":"CRAN release: 2022-02-21 Fix CRAN checks. Better compatibility rlang 1.0.0 errors. come soon.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-111","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.1","title":"tidyselect 1.1.1","text":"CRAN release: 2021-04-30 Fix CRAN checks. tidyselect re-licensed MIT (#217).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-110","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.0","title":"tidyselect 1.1.0","text":"CRAN release: 2020-05-11 Predicate functions must now wrapped (). {r} iris %>% select((.factor)) made change avoid puzzling error messages variable unexpectedly missing data frame corresponding function environment: {r} # Attempts invoke `data()` function data.frame(x = 1) %>% select(data) Now tidyselect correctly complain missing variable rather trying invoke function. compatibility support predicate functions starting 1 version. eval_select() gains allow_rename argument. set FALSE, renaming variables c(foo = bar) syntax error. useful implement purely selective behaviour (#178). Fixed issue preventing repeated deprecation messages tidyselect_verbosity set \"verbose\" (#184). any_of() now preserves order input variables (#186). return value eval_select() now always named, even inputs constant (#173).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-100","dir":"Changelog","previous_headings":"","what":"tidyselect 1.0.0","title":"tidyselect 1.0.0","text":"CRAN release: 2020-01-27 1.0.0 release tidyselect. features solidly defined implemented syntax, support predicate functions, new boolean operators, much .","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"documentation-1-0-0","dir":"Changelog","previous_headings":"","what":"Documentation","title":"tidyselect 1.0.0","text":"New Get started vignette client packages. Read vignette(\"tidyselect\") https://tidyselect.r-lib.org/articles/tidyselect.html. definition tidyselect language consolidated. technical description now available: https://tidyselect.r-lib.org/articles/syntax.html.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"tidyselect 1.0.0","text":"Selecting non-column variables bare names now triggers informative message suggesting use all_of() instead. Referring contextual objects bare name brittle might masked data frame column. Using all_of() safe (#76). tidyselect now uses vctrs validating inputs. changes may reveal programming errors previously silent. may also cause failures unit tests make faulty assumptions content error messages created tidyselect: --bounds errors thrown name doesn’t exist location large input. Logical vectors now fail properly. Selected variables now must unique. previously possible return duplicate selections circumstances. input names can longer contain NA values. Note recommend testthat::verify_output() monitoring error messages thrown packages don’t control. Unlike expect_error(), verify_output() cause CMD check failures error messages changed. See https://www.tidyverse.org/blog/2019/11/testthat-2-3-0/ information.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"syntax-1-0-0","dir":"Changelog","previous_headings":"","what":"Syntax","title":"tidyselect 1.0.0","text":"boolean operators can now used create selections (#106). ! negates selection. | takes union two selections. & takes intersection two selections. patterns can currently achieved using -, c() intersect() respectively. boolean operators intuitive use. Many thanks Irene Steves (@isteves) suggesting UI. can now use predicate functions selection contexts: feature available functions use legacy interface tidyselect. need updated use new eval_select() function instead vars_select(). Unary - inside nested c() now consistently syntax set difference (#130). Improved support named elements. now possible assign name multiple elements, input data structure doesn’t require unique names (.e. anything data frame). selection engine rewritten support clearer separation data-expressions (calls :, -, c) env-expressions (anything else). means can now safely use expressions type: Even data frame data contains column also named data, subexpression ncol(data) still correctly evaluated. data:ncol(data) expression equivalent 2:3 data looked relevant context without ambiguity: example bit contrived, many realistic cases changes make easier write safe code: {r} select_from <- function(data, var) {   data %>% dplyr::select({{ var }} : ncol(data)) } data %>% select_from(data) #> # tibble: 1 x 2 #>    data   bar #>   <dbl> <dbl> #> 1     2     3","code":"iris %>% select(is.factor) iris %>% select(is.factor | is.numeric) data %>% select(1:ncol(data)) data %>% pivot_longer(1:ncol(data)) data <- tibble(foo = 1, data = 2, bar = 3) data %>% dplyr::select(data:ncol(data)) #> # A tibble: 1 x 2 #>    data   bar #>   <dbl> <dbl> #> 1     2     3"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"user-facing-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"User-facing improvements","title":"tidyselect 1.0.0","text":"new selection helpers all_of() any_of() strict variants one_of(). former always fails variables unknown, latter . all_of() safer use expect selected variables exist. any_of() useful cases, instance ensure variables selected : Note all_of() any_of() bit conservative function signature one_of(): accept dots. equivalent one_of(\"\", \"b\") all_of(c(\"\", \"b\")). Selection helpers like all_of() starts_with() now available selection contexts, even haven’t attached search path. visible consequence change now easier use selection functions without attaching host package: still recommended export helpers package users can easily look documentation ?. starts_with(), ends_with(), contains(), matches() now accept vector inputs (#50). instance now equivalent ways selecting variables start either \"\" \"b\": {r} starts_with(c(\"\", \"b\")) starts_with(\"\") | starts_with(\"b\") matches() new argument perl allow Perl-like regular expressions (@fmichonneau, #71) Better support selecting S3 vectors. instance, factors treated characters.","code":"vars <- c(\"Species\", \"Genus\") iris %>% dplyr::select(-any_of(vars)) # Before dplyr::select(mtcars, dplyr::starts_with(\"c\"))  # After dplyr::select(mtcars, starts_with(\"c\"))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"api-1-0-0","dir":"Changelog","previous_headings":"","what":"API","title":"tidyselect 1.0.0","text":"New eval_select() eval_rename() functions client packages. replace vars_select() vars_rename(), now deprecated. functions: Take full data rather just names. makes possible use function predicates selection context. Return numeric vector locations rather vector names. makes possible use tidyselect inputs support duplicate names, like regular vectors.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"other-features-and-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Other features and fixes","title":"tidyselect 1.0.0","text":".strict argument vars_select() now works robustly consistently. Using arithmetic operators selection context now fails informatively (#84). now possible select columns data frames containing duplicate variables (#94). However, duplicates can’t part final selection. eval_rename() longer ignore names unquoted character vectors length 1 (#79). eval_rename() now fails variable renamed existing name (#70). eval_rename() better support existing duplicates (creating new duplicates error). eval_select(), eval_rename() vars_pull() now detect missing values uniformly (#72). vars_pull() now includes faulty expression error messages. performance issues eval_rename() many arguments fixed. make dplyr::rename_all() many columns much faster (@zkamvar, #92). tidyselect now much faster many columns, thanks performance fix rlang::env_bind() well internal fixes. vars_select() ignores vectors zeros (#82).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-025","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.5","title":"tidyselect 0.2.5","text":"CRAN release: 2018-10-11 maintenance release compatibility rlang 0.3.0.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-024","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.4","title":"tidyselect 0.2.4","text":"CRAN release: 2018-02-26 Fixed warning occurred vector column positions supplied vars_select() functions depending tidyr::gather() (#43 tidyverse/tidyr#374). Fixed compatibility issue rlang 0.2.0 (#51).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-023","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.3","title":"tidyselect 0.2.3","text":"CRAN release: 2017-11-06 Internal fixes prevision using tidyselect within dplyr. vars_select() vars_rename() now correctly support unquoting character vectors names. vars_select() now ignores missing variables.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-022","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.2","title":"tidyselect 0.2.2","text":"CRAN release: 2017-10-10 dplyr now correctly mentioned suggested package.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-021","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.1","title":"tidyselect 0.2.1","text":"CRAN release: 2017-10-09 - now supports character vectors addition strings. makes easy unquote column names exclude set: {r} vars <- c(\"cyl\", \"\", \"disp\", \"drat\") vars_select(names(mtcars), - !!vars) last_col() now issues error variable vector empty. last_col() now returns column positions rather column names consistency helpers. also makes compatible functions like seq(). c() now supports character vectors way - seq(). (#37 @gergness)","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-020","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.0","title":"tidyselect 0.2.0","text":"CRAN release: 2017-08-30 main point release revert troublesome behaviour introduced tidyselect 0.1.0. also includes features.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"evaluation-rules-0-2-0","dir":"Changelog","previous_headings":"","what":"Evaluation rules","title":"tidyselect 0.2.0","text":"special evaluation semantics selection changed back old behaviour new rules causing much trouble confusion. now data expressions (symbols calls : c()) can refer registered variables objects context. However semantics context expressions (calls : c()) remain . expressions evaluated context refer registered variables. ’re writing functions refer contextual objects, still good idea avoid data expressions. Since registered variables change function user input never know local objects might shadowed variable. Consider: select second element letters 14th? Since variables precedence data expression, select 14 first letters. can made robust turning data expression context expression: can also use quasiquotation since unquoted arguments guaranteed evaluated without user data scope. equivalent special rules context expressions, may clearer reader accustomed tidy eval: {r} vars_select(letters, seq(1, !! n)) Finally, may want explicit opposite direction. expect variable found data context, can use .data pronoun: {r} vars_select(names(mtcars), .data$cyl : .data$drat)","code":"n <- 2 vars_select(letters, 1:n) vars_select(letters, seq(1, n))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-features-0-2-0","dir":"Changelog","previous_headings":"","what":"New features","title":"tidyselect 0.2.0","text":"new select helper last_col() helpful select custom range: vars_select(vars, 3:last_col()). : - now handle strings well. makes easy unquote column name: (!!name) : last_col() - !!name. vars_select() gains .strict argument similar rename_vars(). set FALSE, errors unknown variables ignored. vars_select() now treats NULL empty inputs. follows trend tidyverse tools. vars_rename() now handles variable positions (integers round doubles) just like vars_select() (#20). vars_rename() now implemented tidy eval framework. Like vars_select(), expressions evaluated without user data scope. addition variable context now established can write rename helpers. return single round number string (variable position variable name). has_vars() predicate tests whether variable context set (#21). selection helpers now exported list vars_select_helpers. intended APIs embed helpers evaluation environment.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"fixes-0-2-0","dir":"Changelog","previous_headings":"","what":"Fixes","title":"tidyselect 0.2.0","text":"one_of() argument vars renamed .vars avoid spurious matching.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-011","dir":"Changelog","previous_headings":"","what":"tidyselect 0.1.1","title":"tidyselect 0.1.1","text":"CRAN release: 2017-07-24 tidyselect new home legacy functions dplyr::select_vars(), dplyr::rename_vars() dplyr::select_var().","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"api-changes-0-1-1","dir":"Changelog","previous_headings":"","what":"API changes","title":"tidyselect 0.1.1","text":"took opportunity make changes API: select_vars() rename_vars() now vars_select() vars_rename(). follows tidyverse convention prefix corresponds input type suffixes indicate output type. Similarly, select_var() now vars_pull(). arguments now prefixed dots limit argument matching issues. dots help, still good idea splice list captured quosures make sure dotted arguments never matched vars_select()’s named arguments: Error messages can now customised. consistency dplyr, error messages refer “columns” default. assumes variables selected come data frame. appropriate DSL, can now add attribute vars_type .vars vector specify alternative names. must character vector length 2 whose first component singular form second plural. example, c(\"variable\",   \"variables\").","code":"vars_select(vars, !!! quos(...))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"establishing-a-variable-context-0-1-1","dir":"Changelog","previous_headings":"","what":"Establishing a variable context","title":"tidyselect 0.1.1","text":"tidyselect provides ways establishing variable context: scoped_vars() sets variable context along exit hook automatically restores previous variables. preferred way changing variable context. with_vars() takes variables expression evaluates latter context former. poke_vars() establishes new variable context. returns previous context invisibly responsibility restore done. expert use . current_vars() renamed peek_vars(). naming reference peek poke legacy languages.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-evaluation-semantics-0-1-1","dir":"Changelog","previous_headings":"","what":"New evaluation semantics","title":"tidyselect 0.1.1","text":"evaluation semantics selecting verbs changed. Symbols now evaluated data-context isolated calling environment. means can longer refer local variables unless explicitly unquoting variables !!, mostly expert use. Note since dplyr 0.7, helper calls (like starts_with()) obey opposite behaviour evaluated calling context isolated data context. sum , symbols can refer data frame objects, helpers can refer contextual objects. differs usual R evaluation semantics data calling environment scope (former prevailing latter).","code":""}]
+[{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement codeofconduct@posit.co. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://tidyselect.r-lib.org/dev/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired [Mozilla’s code conduct enforcement ladder][https://github.com/mozilla/inclusion]. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://tidyselect.r-lib.org/dev/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2020 tidyselect authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"sets-of-variables","dir":"Articles","previous_headings":"","what":"Sets of variables","title":"Technical description of tidyselect","text":"tidyselect syntax sets variables, internally represented integer vectors locations. example, c(1L, 2L) represents set first second variables, c(1L, 2L, 1L). vector locations contains duplicates, normally treated element, since represent sets. exception occurs named elements whose names differ. names don’t match, treated different elements order allow renaming variable multiple names (see section Renaming variables). Today, syntax tidyselect generally designed around Boolean algebra, .e. recommend writing starts_with(\"\") & !ends_with(\"z\"). Earlier versions tidyselect flavour set operations, ’d write starts_with(\"\") - ends_with(\"b\"). set operations still supported, tidyselect represents variables internally, longer recommend Boolean algebra easy people understand.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"bare-names","dir":"Articles","previous_headings":"Sets of variables","what":"Bare names","title":"Technical description of tidyselect","text":"Within data-expressions (see Evaluation section), bare names represent locations, .e. set size 1. following expressions equivalent:","code":"mtcars %>% select_loc(mpg:hp, !cyl, vs) #>  mpg  cyl disp   hp drat   wt qsec   vs   am gear carb  #>    1    2    3    4    5    6    7    8    9   10   11  mtcars %>% select_loc(1:4, !2, 8) #>  mpg  cyl disp   hp drat   wt qsec   vs   am gear carb  #>    1    2    3    4    5    6    7    8    9   10   11"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"the-operator","dir":"Articles","previous_headings":"Sets of variables","what":"The : operator","title":"Technical description of tidyselect","text":": can used select consecutive variables two locations. returns corresponding sequence locations. bare names represent locations, easy select range variables:","code":"mtcars %>% select_loc(2:4) #>  cyl disp   hp  #>    2    3    4 mtcars %>% select_loc(cyl:hp) #>  cyl disp   hp  #>    2    3    4"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"boolean-operators","dir":"Articles","previous_headings":"Sets of variables","what":"Boolean operators","title":"Technical description of tidyselect","text":"| operator takes union two sets: & operator takes intersection two sets: ! operator takes complement set: Taking intersection complement produces set difference:","code":"iris %>% select_loc(starts_with(\"Sepal\") | ends_with(\"Width\")) #> Sepal.Length  Sepal.Width  Petal.Width  #>            1            2            4 iris %>% select_loc(starts_with(\"Sepal\") & ends_with(\"Width\")) #> Sepal.Width  #>           2 iris %>% select_loc(!ends_with(\"Width\")) #> Sepal.Length Petal.Length      Species  #>            1            3            5 iris %>% select_loc(starts_with(\"Sepal\") & !ends_with(\"Width\")) #> Sepal.Length  #>            1"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"dots-and-c","dir":"Articles","previous_headings":"Sets of variables","what":"Dots and c()","title":"Technical description of tidyselect","text":"tidyselect functions can take dots, like dplyr::select(), named argument, like tidyr::pivot_longer(). latter case, dots syntax accessible via c(). fact ... syntax implemented c(...) thus completely equivalent. c(x, y, z) equivalent x | y | z:","code":"mtcars %>% select_loc(mpg, disp:hp) #>  mpg disp   hp  #>    1    3    4  mtcars %>% select_loc(c(mpg, disp:hp)) #>  mpg disp   hp  #>    1    3    4 iris %>% select_loc(starts_with(\"Sepal\"), ends_with(\"Width\"), Species) #> Sepal.Length  Sepal.Width  Petal.Width      Species  #>            1            2            4            5  iris %>% select_loc(starts_with(\"Sepal\") | ends_with(\"Width\") | Species) #> Sepal.Length  Sepal.Width  Petal.Width      Species  #>            1            2            4            5"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"name-combination-and-propagation","dir":"Articles","previous_headings":"Sets of variables > Renaming variables","what":"Name combination and propagation","title":"Technical description of tidyselect","text":"named inputs provided ... c(), selection renamed. inputs already named, outer inner names combined ... separator: Otherwise outer names propagated selected elements according following rules: data frames, numeric suffix appended columns must uniquely named. normal vectors, name simply assigned selected inputs. Combination propagation can composed using nested c():","code":"mtcars %>% select_loc(foo = c(bar = mpg, baz = cyl)) #> foo...bar foo...baz  #>         1         2 mtcars %>% select_loc(foo = c(mpg, cyl)) #> foo1 foo2  #>    1    2 as.list(mtcars) %>% select_loc(foo = c(mpg, cyl)) #> foo foo  #>   1   2 mtcars %>% select_loc(foo = c(bar = c(mpg, cyl))) #> foo...bar1 foo...bar2  #>          1          2"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"set-combination-with-named-variables","dir":"Articles","previous_headings":"Sets of variables > Renaming variables","what":"Set combination with named variables","title":"Technical description of tidyselect","text":"Named elements special rules determine identities set. Unnamed elements match names: | c(foo = ) equivalent c(foo = ). & c(foo = ) equivalent c(foo = ). Named elements different names distinct: c(foo = ) & c(bar = ) equivalent c(). c(foo = ) | c(bar = ) equivalent c(foo = , bar = ). unnamed elements match named ones, possible select multiple elements rename one :","code":"iris %>% select_loc(!Species, foo = Sepal.Width) #> Sepal.Length          foo Petal.Length  Petal.Width  #>            1            2            3            4"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"predicate-functions","dir":"Articles","previous_headings":"Sets of variables","what":"Predicate functions","title":"Technical description of tidyselect","text":"Predicate function objects can supplied input env-expression, typically selection helper (). applied elements data, return TRUE FALSE indicate inclusion. Predicates env-expressions effectively expanded set variables represent:","code":"iris %>% select_loc(where(is.numeric)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width  #>            1            2            3            4  iris %>% select_loc(where(is.factor)) #> Species  #>       5  iris %>% select_loc(where(is.numeric) | where(is.factor)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species  #>            1            2            3            4            5  iris %>% select_loc(where(is.numeric) & where(is.factor)) #> named integer(0)"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"selection-helpers","dir":"Articles","previous_headings":"","what":"Selection helpers","title":"Technical description of tidyselect","text":"call selection helpers function inspects currently active variables peek_vars() returns selection. peek_vars() returns character vector names. returned selection can output conforming types described Data types section. Examples selection helpers all_of(), contains(), last_col(). selection helpers evaluated env-expressions (see Evaluation section).","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"supported-data-types","dir":"Articles","previous_headings":"","what":"Supported data types","title":"Technical description of tidyselect","text":"following data types can returned selection helpers forced via !! force() (latter works tidyselect treated env-expression, see Evaluation section): Vectors locations: Vectors names. matched transformed locations. Predicate functions. applied elements determine inclusion.","code":"iris %>% select_loc(force(c(1, 3))) #> Sepal.Length Petal.Length  #>            1            3 iris %>% select_loc(force(c(\"Sepal.Length\", \"Petal.Length\"))) #> Sepal.Length Petal.Length  #>            1            3 iris %>% select_loc(force(is.numeric)) #> Sepal.Length  Sepal.Width Petal.Length  Petal.Width  #>            1            2            3            4"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"data-expressions-and-env-expressions","dir":"Articles","previous_headings":"Evaluation","what":"Data-expressions and env-expressions","title":"Technical description of tidyselect","text":"tidyselect typical tidy evaluation UI. main difference data masking. typical tidy eval function, expressions evaluated data-vars first scope, followed env-vars: possible bypass data frame variables forcing symbols looked environment !! .env: tidyselect, hierarchical data masking. Instead, expressions evaluated either context data frame user environment, without overlap. scope lookup depends kind expression: data-expressions evaluated data frame . includes bare symbols, boolean operators, -, :, c(). can’t refer environment-variables data-expression: env-expressions evaluated environment. includes calls mentioned , well symbols part calls. can’t refer data-variables data-expression: scoping unambiguous, can safely refer env-vars env-expression, without worry potential naming clashes data-vars: variable names character vector, safe refer env-var containing names all_of() env-expression: Note currently, env-vars still allowed data-expressions, compatibility. However process deprecated see note recommending use all_of() instead. note become deprecation warning future, error.","code":"mask <- function(data, expr) {   rlang::eval_tidy(rlang::enquo(expr), data) }  foo <- 10 cyl <- 200  # `cyl` represents the data frame column here: mtcars %>% mask(cyl * foo) #>  [1] 60 60 40 60 80 60 80 40 40 60 60 80 80 80 80 80 80 40 40 40 40 80 80 #> [24] 80 80 40 40 40 80 60 80 40 mtcars %>% mask(!!cyl * foo) #> [1] 2000 mtcars %>% mask(.env$cyl * foo) #> [1] 2000 cyl_pos <- 2 mtcars %>% select_loc(mpg | cyl_pos) #> Error in `select_loc()`: #> ! Can't select columns that don't exist. #> ✖ Column `cyl_pos` doesn't exist. mtcars %>% select_loc(all_of(mpg)) #> Error in `select_loc()`: #> ℹ In argument: `all_of(mpg)`. #> Caused by error: #> ! object 'mpg' not found x <- data.frame(x = 1:3, y = 4:6, z = 7:9)  # `ncol(x)` is an env-expression, so `x` represents the data frame in # the environment rather than the column in the data frame x %>% select_loc(2:ncol(x)) #> y z  #> 2 3 y <- c(\"y\", \"z\") x %>% select_loc(all_of(y)) #> y z  #> 2 3 mtcars %>% select_loc(cyl_pos) #> Warning: Using an external vector in selections was deprecated in tidyselect #> 1.1.0. #> ℹ Please use `all_of()` or `any_of()` instead. #>   # Was: #>   data %>% select(cyl_pos) #>  #>   # Now: #>   data %>% select(all_of(cyl_pos)) #>  #> See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated. #> cyl  #>   2"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"arithmetic-operators","dir":"Articles","previous_headings":"Evaluation","what":"Arithmetic operators","title":"Technical description of tidyselect","text":"Within data-expressions (see Evaluation section), +, * / overridden cause error. prevent confusion stemming normal data masking usage variables can transformed fly:","code":"mtcars %>% select_loc(cyl^2) #> Error in `select_loc()`: #> ! Can't use arithmetic operator `^` in selection context.  mtcars %>% select_loc(mpg * wt) #> Error in `select_loc()`: #> ! Can't use arithmetic operator `*` in selection context."},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"selecting-versus-renaming","dir":"Articles","previous_headings":"","what":"Selecting versus renaming","title":"Technical description of tidyselect","text":"select rename variants take types inputs type return value. important differences.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"all-renaming-inputs-must-be-named","dir":"Articles","previous_headings":"Selecting versus renaming","what":"All renaming inputs must be named","title":"Technical description of tidyselect","text":"Unlike eval_select() can select without renaming, eval_rename() expects fully named selection. one several names missing, error thrown.","code":"mtcars %>% select_loc(mpg) #> mpg  #>   1  mtcars %>% rename_loc(mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named."},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"renaming-to-an-existing-variable-name","dir":"Articles","previous_headings":"Selecting versus renaming","what":"Renaming to an existing variable name","title":"Technical description of tidyselect","text":"input data data frame, tidyselect generally throws error duplicate column names selected, order respect invariant unique column names. selection can rename variable existing name latter part selection: possible renaming. However, name conflict can solved renaming existing variable another name:","code":"# Lists can have duplicates as.list(mtcars) %>% select_loc(foo = mpg, foo = cyl) #> foo foo  #>   1   2  # Data frames cannot mtcars %>% select_loc(foo = mpg, foo = cyl) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"foo\" at locations 1 and 2. mtcars %>% select_loc(cyl, cyl = mpg) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"cyl\" at locations 1 and 2.  mtcars %>% select_loc(disp, cyl = mpg) #> disp  cyl  #>    3    1 mtcars %>% rename_loc(cyl, cyl = mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named.  mtcars %>% rename_loc(disp, cyl = mpg) #> Error in `rename_loc()`: #> ! All renaming inputs must be named. mtcars %>% select_loc(foo = cyl, cyl = mpg) #> foo cyl  #>   2   1  mtcars %>% rename_loc(foo = cyl, cyl = mpg) #> foo cyl  #>   2   1"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"duplicate-columns-in-data-frames","dir":"Articles","previous_headings":"","what":"Duplicate columns in data frames","title":"Technical description of tidyselect","text":"Normally data frame shouldn’t duplicate names. However, real world messy duplicates happen wild. tidyselect tries permissive can duplicates users can restore unique names select() rename(). First let’s create data frame duplicate names: duplicates part selection, simply ignored: duplicates selected, error: duplicate names can repaired renaming chosen locations:","code":"dups <- vctrs::new_data_frame(list(x = 1, y = 2, x = 3)) dups %>% select_loc(y) #> y  #> 2 dups %>% select_loc(x) #> Error in `select_loc()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"x\" at locations 1 and 2. dups %>% select_loc(x, foo = 3) #>   x foo  #>   1   3  dups %>% rename_loc(foo = 3) #> foo  #>   3"},{"path":"https://tidyselect.r-lib.org/dev/articles/syntax.html","id":"acknowledgements","dir":"Articles","previous_headings":"","what":"Acknowledgements","title":"Technical description of tidyselect","text":"tidyselect syntax inspired base::subset() function written Peter Dalgaard. select parameter subset.data.frame() evaluated data mask column names bound locations data frame. allows : create sequences variable locations. locations can combined c(). selection interface set tone development tidyselect syntax.","code":"mtcars %>% subset(select = c(cyl, hp:wt)) #> # A tibble: 32 × 4 #>     cyl    hp  drat    wt #>   <dbl> <dbl> <dbl> <dbl> #> 1     6   110  3.9   2.62 #> 2     6   110  3.9   2.88 #> 3     4    93  3.85  2.32 #> 4     6   110  3.08  3.22 #> # ℹ 28 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"selections-as-dots-or-as-named-arguments","dir":"Articles","previous_headings":"Before we start","what":"Selections as dots or as named arguments","title":"Implementing tidyselect interfaces","text":"two major ways designing function takes selections. Passing dots dplyr::select(). Interpolating named arguments tidyr::pivot_longer(). case, multiple inputs can provided inside c() using boolean operators: general recommendation take dots main purpose function create new data structure based selection. selection accessory main purpose function, take named argument. doubt, recommend using named arguments easier change named argument dots way around. advice , see Making data ... section tidyverse design book.","code":"mtcars %>% dplyr::select(mpg, cyl) mtcars %>% pivot_longer(c(mpg, cyl)) mtcars %>% pivot_longer(mpg | cyl)"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"do-you-need-tidyselect","dir":"Articles","previous_headings":"Before we start","what":"Do you need tidyselect?","title":"Implementing tidyselect interfaces","text":"tools described vignette rather low level. Depending use case, may easier wrap dplyr::select(). ’ll get data frame containing columns selected user, can handle various ways. following examples illustrate write function takes selection data returns corresponding data frame capitalised names: main advantage lower level tidyselect tools offer bit information flexibility. Instead returning selected data, return locations selected elements inside input data. don’t need selected locations can afford dependency, may consider wrapping dplyr instead.","code":"# Passing dots toupper_dots <- function(data, ...) {   sel <- dplyr::select(data, ...)   rlang::set_names(sel, toupper) } # Interpolating a named argument with {{ }} toupper_arg <- function(data, arg) {   sel <- dplyr::select(data, {{ arg }})   rlang::set_names(sel, toupper) }  mtcars %>% toupper_dots(mpg:disp, vs) #> # A tibble: 32 x 4 #>     MPG   CYL  DISP    VS #>   <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160     0 #> 2  21       6   160     0 #> 3  22.8     4   108     1 #> 4  21.4     6   258     1 #> # … with 28 more rows  mtcars %>% toupper_arg(c(mpg:disp, vs)) #> # A tibble: 32 x 4 #>     MPG   CYL  DISP    VS #>   <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160     0 #> 2  21       6   160     0 #> 3  22.8     4   108     1 #> 4  21.4     6   258     1 #> # … with 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"the-selection-evaluators","dir":"Articles","previous_headings":"","what":"The selection evaluators","title":"Implementing tidyselect interfaces","text":"tidyselect implemented non-standard evaluation (NSE). unique feature R language refers ability functions defuse (.e. delay execution) arguments, resume evaluation later on1. Crucially, evaluation can resumed different context according different rules, often domain-specific languages created R.","code":""},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"defusing-and-resuming-evaluation-of-r-code","dir":"Articles","previous_headings":"The selection evaluators","what":"Defusing and resuming evaluation of R code","title":"Implementing tidyselect interfaces","text":"function argument defused, R halts evaluation code returns defused expression instead. expression contains code describes compute intended value. Defuse R code expr(): Defuse user’s R code enquo(): resume evaluation defused R code, use eval_tidy(): can resume evaluation data context passing data frame data argument: Resuming evaluation data context known data masking. data-vars inside data frame combined env-vars environment, making possible users refer data variables:","code":"own <- rlang::expr(1 + 2) own #> 1 + 2 fn <- function(arg) {   expr <- rlang::enquo(arg)   expr } user <- fn(1 + 2) user #> <quosure> #> expr: ^1 + 2 #> env:  global rlang::eval_tidy(own) #> [1] 3  rlang::eval_tidy(user) #> [1] 3 with_data <- function(data, x) {   expr <- rlang::enquo(x)   rlang::eval_tidy(expr, data = data) } NULL %>% with_data(mean(cyl) * 10) #> Error: object 'cyl' not found  mtcars %>% with_data(mean(cyl) * 10) #> [1] 61.875"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"resuming-defused-r-code-with-tidyselect-rules","dir":"Articles","previous_headings":"The selection evaluators","what":"Resuming defused R code with tidyselect rules","title":"Implementing tidyselect interfaces","text":"Taking tidyselect selections functions follows principles. First defuse expression, resume evaluation. Instead eval_tidy(), need special interpreters eval_select() eval_rename(). Like eval_tidy(), take defused expression data. return vector locations selected elements: user renamed selected elements, names vector locations reflect new names. eval_select() likely variant ’ll need implement tidyselect functions.","code":"eval_select(rlang::expr(mpg), mtcars) #> mpg  #>   1  eval_select(rlang::expr(c(mpg:disp, vs)), mtcars) #>  mpg  cyl disp   vs  #>    1    2    3    8 eval_select(rlang::expr(c(foo = mpg, bar = disp)), mtcars) #> foo bar  #>   1   3  eval_rename(rlang::expr(c(foo = mpg, bar = disp)), mtcars) #> foo bar  #>   1   3"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"simple-selections-with-dots","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Simple selections with dots","title":"Implementing tidyselect interfaces","text":"selecting function takes dots: Pass dots c() inside defused expression. Resume evaluation defused c() expression eval_select(). Use vector locations returned eval_select() subset rename input data. reimplement dplyr::select() 3 lines representing steps :","code":"select <- function(.data, ...) {   expr <- rlang::expr(c(...))   pos <- eval_select(expr, data = .data)   rlang::set_names(.data[pos], names(pos)) }  mtcars %>%   select(mpg, cyl) #> # A tibble: 32 × 2 #>     mpg   cyl #>   <dbl> <dbl> #> 1  21       6 #> 2  21       6 #> 3  22.8     4 #> 4  21.4     6 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"simple-selections-with-named-arguments","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Simple selections with named arguments","title":"Implementing tidyselect interfaces","text":"selecting function takes named arguments, defusing step bit different. need use enquo() defuse function argument .","code":"select <- function(.data, cols) {   expr <- rlang::enquo(cols)   pos <- eval_select(expr, data = .data)   rlang::set_names(.data[pos], names(pos)) }  mtcars %>%   select(c(mpg, cyl)) #> # A tibble: 32 × 2 #>     mpg   cyl #>   <dbl> <dbl> #> 1  21       6 #> 2  21       6 #> 3  22.8     4 #> 4  21.4     6 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"renaming-selections","dir":"Articles","previous_headings":"The selection evaluators > Resuming defused R code with tidyselect rules","what":"Renaming selections","title":"Implementing tidyselect interfaces","text":"eval_rename() variant rarely needed mentioned completeness. First note eval_select() eval_rename() allow renaming variables: eval_rename() similar eval_select() constraints meant renaming variables place. particular throws error selected inputs unnamed. practice, eval_rename() accepts c() expression expr argument, inputs inside outermost c() must named: constraint, doesn’t make much sense take named argument, time ’ll want pass dots defused c() expression. way user can easily pass names selections: example use vector locations returned eval_rename(), implement dplyr::rename():","code":"eval_select(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1  eval_rename(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1 eval_rename(rlang::expr(mpg), mtcars) #> Error: #> ! All renaming inputs must be named.  eval_rename(rlang::expr(c(mpg)), mtcars) #> Error: #> ! All renaming inputs must be named.  eval_rename(rlang::expr(c(foo = mpg)), mtcars) #> foo  #>   1 wrapper <- function(data, ...) {   eval_rename(rlang::expr(c(...)), data) }  mtcars %>% wrapper(foo = mpg, bar = hp:wt) #>  foo bar1 bar2 bar3  #>    1    4    5    6 rename <- function(.data, ...) {   pos <- eval_rename(rlang::expr(c(...)), .data)   names(.data)[pos] <- names(pos)   .data }  mtcars %>%   rename(foo = mpg, bar = hp:wt) #> # A tibble: 32 × 11 #>     foo   cyl  disp  bar1  bar2  bar3  qsec    vs    am  gear  carb #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4 #> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4 #> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1 #> 4  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1 #> # ℹ 28 more rows"},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"creating-selection-helpers","dir":"Articles","previous_headings":"","what":"Creating selection helpers","title":"Implementing tidyselect interfaces","text":"Tools like starts_with() contains() called selection helpers. tools inspect variable names currently available selection peek_vars(). variable names registered automatically eval_select() duration evaluation: properties temporarily available calling function like peek_vars() called descriptors. Descriptors useful easy compose. instance, user combine starts_with() ends_with() without worry passing variables environment can found: create new selection helper: Inspect variables peek_vars(). convention done argument user can override. Return one supported data types: vector names locations (latter recommended, see section handling duplicate variables), predicate function. fn argument makes error message informative helper used wrong context: variables inspected default argument, easy override. mostly useful unit tests:","code":"x <- rlang::expr(print(peek_vars()))  invisible(eval_select(x, data = mtcars)) #>  [1] \"mpg\"  \"cyl\"  \"disp\" \"hp\"   \"drat\" \"wt\"   \"qsec\" \"vs\"   \"am\"   \"gear\" #> [11] \"carb\" my_selector <- function(prefix, suffix) {   intersect(     starts_with(prefix),     ends_with(suffix)   ) }  iris %>% select(my_selector(\"Sepal\", \"Length\")) #> # A tibble: 150 × 1 #>   Sepal.Length #>          <dbl> #> 1          5.1 #> 2          4.9 #> 3          4.7 #> 4          4.6 #> # ℹ 146 more rows if_width <- function(n, vars = peek_vars(fn = \"if_width\")) {   vars[nchar(vars) == n] }  mtcars %>% select(if_width(2)) #> # A tibble: 32 × 4 #>      hp    wt    vs    am #>   <dbl> <dbl> <dbl> <dbl> #> 1   110  2.62     0     1 #> 2   110  2.88     0     1 #> 3    93  2.32     1     1 #> 4   110  3.22     1     0 #> # ℹ 28 more rows mtcars[if_width(2)] #> Error: #> ! `if_width()` must be used within a *selecting* function. #> ℹ See <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details. if_width(2, vars = names(mtcars)) #> [1] \"hp\" \"wt\" \"vs\" \"am\""},{"path":"https://tidyselect.r-lib.org/dev/articles/tidyselect.html","id":"handling-duplicate-variables","dir":"Articles","previous_headings":"Creating selection helpers","what":"Handling duplicate variables","title":"Implementing tidyselect interfaces","text":"However current implementation if_width() design flaw. doesn’t work properly input duplicate names: Supporting duplicates recommended data frames wild don’t always unique names. Also, tidyselect can used vectors don’t require unique names, might extended allow recoding character vectors future. cases, handling duplicates part normal usage selection helpers. support duplicates recommended return vectors locations selection helpers rather vector names. Fixing if_width() easy: input data frame, user now informed selection contain duplicates: duplicates selected input data frame, expected:","code":"dups <- vctrs::new_data_frame(list(foo = 1, quux = 2, foo = 3))  dups %>% select(if_width(3)) #>   foo #> 1   1 if_width <- function(n, vars = peek_vars(fn = \"if_width\")) {   which(nchar(vars) == n) } dups %>% select(if_width(3)) #> Error in `select()`: #> ! Names must be unique. #> ✖ These names are duplicated: #>   * \"foo\" at locations 1 and 2. as.list(dups) %>% select(if_width(3)) #> $foo #> [1] 1 #>  #> $foo #> [1] 3"},{"path":"https://tidyselect.r-lib.org/dev/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Lionel Henry. Author, maintainer. Hadley Wickham. Author. . Copyright holder, funder.","code":""},{"path":"https://tidyselect.r-lib.org/dev/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Henry L, Wickham H (2024). tidyselect: Select Set Strings. R package version 1.2.1.9000, https://github.com/r-lib/tidyselect, https://tidyselect.r-lib.org.","code":"@Manual{,   title = {tidyselect: Select from a Set of Strings},   author = {Lionel Henry and Hadley Wickham},   year = {2024},   note = {R package version 1.2.1.9000, https://github.com/r-lib/tidyselect},   url = {https://tidyselect.r-lib.org}, }"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Select from a Set of Strings","text":"tidyselect package backend functions like dplyr::select() dplyr::pull() well several tidyr verbs. allows create selecting verbs consistent tidyverse packages. learn selection syntax user dplyr tidyr, read user-friendly ?language reference. learn implement tidyselect functions, read vignette(\"tidyselect\"). learn exactly tidyselect syntax interpreted, read technical description vignette(\"syntax\").","code":""},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Select from a Set of Strings","text":"Generally, tidyselect installed automatically packages need . need install manually reason, can get :","code":"install.packages(\"tidyselect\")"},{"path":"https://tidyselect.r-lib.org/dev/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Select from a Set of Strings","text":"Please note tidyselect project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables from character vectors — all_of","title":"Select variables from character vectors — all_of","text":"selection helpers select variables contained character vector. especially useful programming selecting functions. all_of() strict selection. variables character vector missing, error thrown. any_of() check missing variables. especially useful negative selections, like make sure variable removed. order selected columns determined order vector.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables from character vectors — all_of","text":"","code":"all_of(x)  any_of(x, ..., vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables from character vectors — all_of","text":"x vector character names numeric locations. ... dots future extensions must empty. vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()).","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/all_of.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables from character vectors — all_of","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   common names variables vector.   refer variables selecting function, use all_of():   variable missing data frame, error:   Use any_of() allow missing variables:   any_of() especially useful remove variables data frame calling cause error:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) vars <- c(\"Sepal.Length\", \"Sepal.Width\")  iris[, vars] #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows iris %>% select(all_of(vars)) #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows  iris %>% pivot_longer(all_of(vars)) #> # A tibble: 300 x 5 #>   Petal.Length Petal.Width Species name         value #>          <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1          1.4         0.2 setosa  Sepal.Length   5.1 #> 2          1.4         0.2 setosa  Sepal.Width    3.5 #> 3          1.4         0.2 setosa  Sepal.Length   4.9 #> 4          1.4         0.2 setosa  Sepal.Width    3   #> # i 296 more rows starwars %>% select(all_of(vars)) #> Error: #> i In argument: `all_of(vars)`. #> Caused by error in `all_of()` at rlang/R/eval-tidy.R:121:3: #> ! Can't subset elements that don't exist. #> x Elements `Sepal.Length` and `Sepal.Width` don't exist. starwars %>% select(any_of(vars)) #> # A tibble: 87 x 0 iris %>% select(-any_of(vars)) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Species #>          <dbl>       <dbl> <fct>   #> 1          1.4         0.2 setosa  #> 2          1.4         0.2 setosa  #> 3          1.3         0.2 setosa  #> 4          1.5         0.2 setosa  #> # i 146 more rows  iris %>% select(-any_of(vars)) %>% select(-any_of(vars)) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Species #>          <dbl>       <dbl> <fct>   #> 1          1.4         0.2 setosa  #> 2          1.4         0.2 setosa  #> 3          1.3         0.2 setosa  #> 4          1.5         0.2 setosa  #> # i 146 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate an expression to relocate variables — eval_relocate","title":"Evaluate an expression to relocate variables — eval_relocate","text":"eval_relocate() variant eval_select() moves selection new location. Either can provided specify move selection . powers dplyr::relocate().","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate an expression to relocate variables — eval_relocate","text":"","code":"eval_relocate(   expr,   data,   ...,   before = NULL,   after = NULL,   strict = TRUE,   name_spec = NULL,   allow_rename = TRUE,   allow_empty = TRUE,   allow_predicates = TRUE,   before_arg = \"before\",   after_arg = \"after\",   env = caller_env(),   error_call = caller_env() )"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate an expression to relocate variables — eval_relocate","text":"expr Defused R code describing selection according tidyselect syntax. data named list, data frame, atomic vector. Technically, data can vector names() \"[[\" implementations. ... dots future extensions must empty. , Defused R code describing selection according tidyselect syntax. selection represents destination selection provided expr. Supplying neither move selection left-hand side. Supplying error. strict TRUE, --bounds errors thrown expr attempts select rename variable exist. FALSE, failed selections renamings ignored. name_spec name specification describing combine propagate names. used case nested c() expressions like c(foo = c(bar = starts_with(\"foo\"))). See name_spec argument vctrs::vec_c() description valid name specs. allow_rename TRUE (default), renaming syntax c(foo = bar) allowed. FALSE, causes error. useful implement purely selective behaviour. allow_empty TRUE (default), ok expr result empty selection. FALSE, error expr yields empty selection. allow_predicates TRUE (default), ok expr use predicates (.e. ()). FALSE, error expr uses predicate. automatically set FALSE data support predicates (determined tidyselect_data_has_predicates()). before_arg, after_arg Argument names . used error messages. env environment evaluate expr. Discarded expr quosure. error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate an expression to relocate variables — eval_relocate","text":"named vector numeric locations length equal length(data). position data represented exactly . names normally input data, except user supplied named selections c(). latter case, names reflect new names chosen user.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_relocate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate an expression to relocate variables — eval_relocate","text":"","code":"library(rlang)  # Interpret defused code as a request to relocate x <- expr(c(mpg, disp)) after <- expr(wt) eval_relocate(x, mtcars, after = after) #>  cyl   hp drat   wt  mpg disp qsec   vs   am gear carb  #>    2    4    5    6    1    3    7    8    9   10   11   # Supplying neither `before` nor `after` will move the selection to the # left-hand side eval_relocate(x, mtcars) #>  mpg disp  cyl   hp drat   wt qsec   vs   am gear carb  #>    1    3    2    4    5    6    7    8    9   10   11   # Within a function, use `enquo()` to defuse a single argument. # Note that `before` and `after` must also be defused with `enquo()`. my_relocator <- function(x, expr, before = NULL, after = NULL) {   eval_relocate(enquo(expr), x, before = enquo(before), after = enquo(after)) }  my_relocator(mtcars, vs, before = hp) #>  mpg  cyl disp   vs   hp drat   wt qsec   am gear carb  #>    1    2    3    8    4    5    6    7    9   10   11   # Here is an example of using `eval_relocate()` to implement `relocate()`. # Note that the dots are passed on as a defused call to `c(...)`. relocate <- function(.x, ..., .before = NULL, .after = NULL) {   pos <- eval_relocate(     expr(c(...)),     .x,     before = enquo(.before),     after = enquo(.after)   )   set_names(.x[pos], names(pos)) }  relocate(mtcars, vs, .before = hp) #>                      mpg cyl  disp vs  hp drat    wt  qsec am gear carb #> Mazda RX4           21.0   6 160.0  0 110 3.90 2.620 16.46  1    4    4 #> Mazda RX4 Wag       21.0   6 160.0  0 110 3.90 2.875 17.02  1    4    4 #> Datsun 710          22.8   4 108.0  1  93 3.85 2.320 18.61  1    4    1 #> Hornet 4 Drive      21.4   6 258.0  1 110 3.08 3.215 19.44  0    3    1 #> Hornet Sportabout   18.7   8 360.0  0 175 3.15 3.440 17.02  0    3    2 #> Valiant             18.1   6 225.0  1 105 2.76 3.460 20.22  0    3    1 #> Duster 360          14.3   8 360.0  0 245 3.21 3.570 15.84  0    3    4 #> Merc 240D           24.4   4 146.7  1  62 3.69 3.190 20.00  0    4    2 #> Merc 230            22.8   4 140.8  1  95 3.92 3.150 22.90  0    4    2 #> Merc 280            19.2   6 167.6  1 123 3.92 3.440 18.30  0    4    4 #> Merc 280C           17.8   6 167.6  1 123 3.92 3.440 18.90  0    4    4 #> Merc 450SE          16.4   8 275.8  0 180 3.07 4.070 17.40  0    3    3 #> Merc 450SL          17.3   8 275.8  0 180 3.07 3.730 17.60  0    3    3 #> Merc 450SLC         15.2   8 275.8  0 180 3.07 3.780 18.00  0    3    3 #> Cadillac Fleetwood  10.4   8 472.0  0 205 2.93 5.250 17.98  0    3    4 #> Lincoln Continental 10.4   8 460.0  0 215 3.00 5.424 17.82  0    3    4 #> Chrysler Imperial   14.7   8 440.0  0 230 3.23 5.345 17.42  0    3    4 #> Fiat 128            32.4   4  78.7  1  66 4.08 2.200 19.47  1    4    1 #> Honda Civic         30.4   4  75.7  1  52 4.93 1.615 18.52  1    4    2 #> Toyota Corolla      33.9   4  71.1  1  65 4.22 1.835 19.90  1    4    1 #> Toyota Corona       21.5   4 120.1  1  97 3.70 2.465 20.01  0    3    1 #> Dodge Challenger    15.5   8 318.0  0 150 2.76 3.520 16.87  0    3    2 #> AMC Javelin         15.2   8 304.0  0 150 3.15 3.435 17.30  0    3    2 #> Camaro Z28          13.3   8 350.0  0 245 3.73 3.840 15.41  0    3    4 #> Pontiac Firebird    19.2   8 400.0  0 175 3.08 3.845 17.05  0    3    2 #> Fiat X1-9           27.3   4  79.0  1  66 4.08 1.935 18.90  1    4    1 #> Porsche 914-2       26.0   4 120.3  0  91 4.43 2.140 16.70  1    5    2 #> Lotus Europa        30.4   4  95.1  1 113 3.77 1.513 16.90  1    5    2 #> Ford Pantera L      15.8   8 351.0  0 264 4.22 3.170 14.50  1    5    4 #> Ferrari Dino        19.7   6 145.0  0 175 3.62 2.770 15.50  1    5    6 #> Maserati Bora       15.0   8 301.0  0 335 3.54 3.570 14.60  1    5    8 #> Volvo 142E          21.4   4 121.0  1 109 4.11 2.780 18.60  1    4    2 relocate(mtcars, starts_with(\"d\"), .after = last_col()) #>                      mpg cyl  hp    wt  qsec vs am gear carb  disp drat #> Mazda RX4           21.0   6 110 2.620 16.46  0  1    4    4 160.0 3.90 #> Mazda RX4 Wag       21.0   6 110 2.875 17.02  0  1    4    4 160.0 3.90 #> Datsun 710          22.8   4  93 2.320 18.61  1  1    4    1 108.0 3.85 #> Hornet 4 Drive      21.4   6 110 3.215 19.44  1  0    3    1 258.0 3.08 #> Hornet Sportabout   18.7   8 175 3.440 17.02  0  0    3    2 360.0 3.15 #> Valiant             18.1   6 105 3.460 20.22  1  0    3    1 225.0 2.76 #> Duster 360          14.3   8 245 3.570 15.84  0  0    3    4 360.0 3.21 #> Merc 240D           24.4   4  62 3.190 20.00  1  0    4    2 146.7 3.69 #> Merc 230            22.8   4  95 3.150 22.90  1  0    4    2 140.8 3.92 #> Merc 280            19.2   6 123 3.440 18.30  1  0    4    4 167.6 3.92 #> Merc 280C           17.8   6 123 3.440 18.90  1  0    4    4 167.6 3.92 #> Merc 450SE          16.4   8 180 4.070 17.40  0  0    3    3 275.8 3.07 #> Merc 450SL          17.3   8 180 3.730 17.60  0  0    3    3 275.8 3.07 #> Merc 450SLC         15.2   8 180 3.780 18.00  0  0    3    3 275.8 3.07 #> Cadillac Fleetwood  10.4   8 205 5.250 17.98  0  0    3    4 472.0 2.93 #> Lincoln Continental 10.4   8 215 5.424 17.82  0  0    3    4 460.0 3.00 #> Chrysler Imperial   14.7   8 230 5.345 17.42  0  0    3    4 440.0 3.23 #> Fiat 128            32.4   4  66 2.200 19.47  1  1    4    1  78.7 4.08 #> Honda Civic         30.4   4  52 1.615 18.52  1  1    4    2  75.7 4.93 #> Toyota Corolla      33.9   4  65 1.835 19.90  1  1    4    1  71.1 4.22 #> Toyota Corona       21.5   4  97 2.465 20.01  1  0    3    1 120.1 3.70 #> Dodge Challenger    15.5   8 150 3.520 16.87  0  0    3    2 318.0 2.76 #> AMC Javelin         15.2   8 150 3.435 17.30  0  0    3    2 304.0 3.15 #> Camaro Z28          13.3   8 245 3.840 15.41  0  0    3    4 350.0 3.73 #> Pontiac Firebird    19.2   8 175 3.845 17.05  0  0    3    2 400.0 3.08 #> Fiat X1-9           27.3   4  66 1.935 18.90  1  1    4    1  79.0 4.08 #> Porsche 914-2       26.0   4  91 2.140 16.70  0  1    5    2 120.3 4.43 #> Lotus Europa        30.4   4 113 1.513 16.90  1  1    5    2  95.1 3.77 #> Ford Pantera L      15.8   8 264 3.170 14.50  0  1    5    4 351.0 4.22 #> Ferrari Dino        19.7   6 175 2.770 15.50  0  1    5    6 145.0 3.62 #> Maserati Bora       15.0   8 335 3.570 14.60  0  1    5    8 301.0 3.54 #> Volvo 142E          21.4   4 109 2.780 18.60  1  1    4    2 121.0 4.11"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate an expression with tidyselect semantics — eval_rename","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"eval_select() eval_rename() evaluate defused R code (.e. quoted expressions) according special rules tidyselect syntax. power functions like dplyr::select(), dplyr::rename(), tidyr::pivot_longer(). See Get started vignette learn use eval_select() eval_rename() packages.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"","code":"eval_rename(   expr,   data,   env = caller_env(),   ...,   strict = TRUE,   name_spec = NULL,   allow_predicates = TRUE,   error_call = caller_env() )  eval_select(   expr,   data,   env = caller_env(),   ...,   include = NULL,   exclude = NULL,   strict = TRUE,   name_spec = NULL,   allow_rename = TRUE,   allow_empty = TRUE,   allow_predicates = TRUE,   error_call = caller_env() )"},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"expr Defused R code describing selection according tidyselect syntax. data named list, data frame, atomic vector. Technically, data can vector names() \"[[\" implementations. env environment evaluate expr. Discarded expr quosure. ... dots future extensions must empty. strict TRUE, --bounds errors thrown expr attempts select rename variable exist. FALSE, failed selections renamings ignored. name_spec name specification describing combine propagate names. used case nested c() expressions like c(foo = c(bar = starts_with(\"foo\"))). See name_spec argument vctrs::vec_c() description valid name specs. allow_predicates TRUE (default), ok expr use predicates (.e. ()). FALSE, error expr uses predicate. automatically set FALSE data support predicates (determined tidyselect_data_has_predicates()). error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information. include, exclude Character vector column names always include exclude selection. allow_rename TRUE (default), renaming syntax c(foo = bar) allowed. FALSE, causes error. useful implement purely selective behaviour. allow_empty TRUE (default), ok expr result empty selection. FALSE, error expr yields empty selection.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"named vector numeric locations, one selected elements. names normally input data, except user supplied named selections c(). latter case, names reflect new names chosen user. given element may selected multiple times different names, case vector might contain duplicate locations.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"select rename variants take types inputs type return value. However eval_rename() extra constraints. requires named inputs, fail data frame column renamed another existing column name. See selecting versus renaming section syntax vignette description differences.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/eval_select.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate an expression with tidyselect semantics — eval_rename","text":"","code":"library(rlang)  # Interpret defused code as selection: x <- expr(mpg:cyl) eval_select(x, mtcars) #> mpg cyl  #>   1   2   # Interpret defused code as a renaming selection. All inputs must # be named within `c()`: try(eval_rename(expr(mpg), mtcars)) #> Error in eval(expr, envir, enclos) :  #>   All renaming inputs must be named. eval_rename(expr(c(foo = mpg)), mtcars) #> foo  #>   1    # Within a function, use `enquo()` to defuse one argument: my_function <- function(x, expr) {   eval_select(enquo(expr), x) }  # If your function takes dots, evaluate a defused call to `c(...)` # with `expr(c(...))`: my_function <- function(.x, ...) {   eval_select(expr(c(...)), .x) }  # If your function takes dots and a named argument, use `{{ }}` # inside the defused expression to tunnel it inside the tidyselect DSL: my_function <- function(.x, .expr, ...) {   eval_select(expr(c({{ .expr }}, ...)), .x) }  # Note that the trick above works because `expr({{ arg }})` is the # same as `enquo(arg)`.   # The evaluators return a named vector of locations. Here are # examples of using these location vectors to implement `select()` # and `rename()`: select <- function(.x, ...) {   pos <- eval_select(expr(c(...)), .x)   set_names(.x[pos], names(pos)) } rename <- function(.x, ...) {   pos <- eval_rename(expr(c(...)), .x)   names(.x)[pos] <- names(pos)   .x }  select(mtcars, mpg:cyl) #>                      mpg cyl #> Mazda RX4           21.0   6 #> Mazda RX4 Wag       21.0   6 #> Datsun 710          22.8   4 #> Hornet 4 Drive      21.4   6 #> Hornet Sportabout   18.7   8 #> Valiant             18.1   6 #> Duster 360          14.3   8 #> Merc 240D           24.4   4 #> Merc 230            22.8   4 #> Merc 280            19.2   6 #> Merc 280C           17.8   6 #> Merc 450SE          16.4   8 #> Merc 450SL          17.3   8 #> Merc 450SLC         15.2   8 #> Cadillac Fleetwood  10.4   8 #> Lincoln Continental 10.4   8 #> Chrysler Imperial   14.7   8 #> Fiat 128            32.4   4 #> Honda Civic         30.4   4 #> Toyota Corolla      33.9   4 #> Toyota Corona       21.5   4 #> Dodge Challenger    15.5   8 #> AMC Javelin         15.2   8 #> Camaro Z28          13.3   8 #> Pontiac Firebird    19.2   8 #> Fiat X1-9           27.3   4 #> Porsche 914-2       26.0   4 #> Lotus Europa        30.4   4 #> Ford Pantera L      15.8   8 #> Ferrari Dino        19.7   6 #> Maserati Bora       15.0   8 #> Volvo 142E          21.4   4 rename(mtcars, foo = mpg) #>                      foo cyl  disp  hp drat    wt  qsec vs am gear carb #> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4 #> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4 #> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1 #> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1 #> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2 #> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1 #> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4 #> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2 #> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2 #> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4 #> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4 #> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3 #> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3 #> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3 #> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4 #> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 #> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4 #> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1 #> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2 #> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1 #> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1 #> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2 #> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2 #> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4 #> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2 #> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1 #> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2 #> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2 #> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4 #> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6 #> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8 #> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2"},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":null,"dir":"Reference","previous_headings":"","what":"Select all variables or the last variable — everything","title":"Select all variables or the last variable — everything","text":"functions selection helpers. everything() selects variable. also useful combination tidyselect operators. last_col() selects last variable.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select all variables or the last variable — everything","text":"","code":"everything(vars = NULL)  last_col(offset = 0L, vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select all variables or the last variable — everything","text":"vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()). offset Set n select nth var end.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/everything.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select all variables or the last variable — everything","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   Use everything() select variables:   Use last_col() select last variable:   Supply offset n select variable located n positions end:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) mtcars <- as_tibble(mtcars) iris %>% select(everything()) #> # A tibble: 150 x 5 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species #>          <dbl>       <dbl>        <dbl>       <dbl> <fct>   #> 1          5.1         3.5          1.4         0.2 setosa  #> 2          4.9         3            1.4         0.2 setosa  #> 3          4.7         3.2          1.3         0.2 setosa  #> 4          4.6         3.1          1.5         0.2 setosa  #> # i 146 more rows  mtcars %>% pivot_longer(everything()) #> # A tibble: 352 x 2 #>   name  value #>   <chr> <dbl> #> 1 mpg      21 #> 2 cyl       6 #> 3 disp    160 #> 4 hp      110 #> # i 348 more rows iris %>% select(last_col()) #> # A tibble: 150 x 1 #>   Species #>   <fct>   #> 1 setosa  #> 2 setosa  #> 3 setosa  #> 4 setosa  #> # i 146 more rows  mtcars %>% pivot_longer(last_col()) #> # A tibble: 32 x 12 #>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear name  value #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> #> 1  21       6   160   110  3.9   2.62  16.5     0     1     4 carb      4 #> 2  21       6   160   110  3.9   2.88  17.0     0     1     4 carb      4 #> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4 carb      1 #> 4  21.4     6   258   110  3.08  3.22  19.4     1     0     3 carb      1 #> # i 28 more rows mtcars %>% select(1:last_col(5)) #> # A tibble: 32 x 6 #>     mpg   cyl  disp    hp  drat    wt #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1  21       6   160   110  3.9   2.62 #> 2  21       6   160   110  3.9   2.88 #> 3  22.8     4   108    93  3.85  2.32 #> 4  21.4     6   258   110  3.08  3.22 #> # i 28 more rows"},{"path":[]},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-external-vector.html","id":"ambiguity-between-columns-and-external-variables","dir":"Reference","previous_headings":"","what":"Ambiguity between columns and external variables","title":"FAQ - Note: Using an external vector in selections is ambiguous — faq-external-vector","text":"selecting functions like dplyr::select() tidyr::pivot_longer(), can refer variables name:   historical reasons, also possible refer external vector variable names. get correct result, warning informing selecting external variable ambiguous clear whether want data frame column external object.   decided deprecate particular approach using external vectors introduce ambiguity. Imagine data frame contains column name external variable.   different objects isn’t problem context forces specific find vars:   selection context however, column wins:","code":"mtcars %>% select(cyl, am, vs) #> # A tibble: 32 x 3 #>     cyl    am    vs #>   <dbl> <dbl> <dbl> #> 1     6     1     0 #> 2     6     1     0 #> 3     4     1     1 #> 4     6     0     1 #> # i 28 more rows  mtcars %>% select(mpg:disp) #> # A tibble: 32 x 3 #>     mpg   cyl  disp #>   <dbl> <dbl> <dbl> #> 1  21       6   160 #> 2  21       6   160 #> 3  22.8     4   108 #> 4  21.4     6   258 #> # i 28 more rows vars <- c(\"cyl\", \"am\", \"vs\") result <- mtcars %>% select(vars) #> Warning: Using an external vector in selections was deprecated in tidyselect #> 1.1.0. #> i Please use `all_of()` or `any_of()` instead. #>   # Was: #>   data %>% select(vars) #>  #>   # Now: #>   data %>% select(all_of(vars)) #>  #> See #> <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this #> warning was generated. some_df <- mtcars[1:4, ] some_df$vars <- 1:nrow(some_df) vars #> [1] \"cyl\" \"am\"  \"vs\"  some_df$vars #> [1] 1 2 3 4 some_df %>% select(vars) #> # A tibble: 4 x 1 #>    vars #>   <int> #> 1     1 #> 2     2 #> 3     3 #> 4     4"},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-external-vector.html","id":"fixing-the-ambiguity","dir":"Reference","previous_headings":"","what":"Fixing the ambiguity","title":"FAQ - Note: Using an external vector in selections is ambiguous — faq-external-vector","text":"make selection code robust silence message, use all_of() force external vector:   information comments , please see Github issue tracking deprecation process.","code":"some_df %>% select(all_of(vars)) #> # A tibble: 4 x 3 #>     cyl    am    vs #>   <dbl> <dbl> <dbl> #> 1     6     1     0 #> 2     6     1     0 #> 3     4     1     1 #> 4     6     0     1"},{"path":"https://tidyselect.r-lib.org/dev/reference/faq-selection-context.html","id":null,"dir":"Reference","previous_headings":"","what":"FAQ - Error: Must be used within a selecting function — faq-selection-context","title":"FAQ - Error: Must be used within a selecting function — faq-selection-context","text":"Functions like starts_with(), contains() matches() selection helpers work selection context, e.g. dplyr::select() cols argument tidyr::pivot_longer(). Using selection helper anywhere else results error:   see error, may used selection helper wrong place, possibly result typo (e.g. misplaced comma wrong argument name). Alternatively, may deliberately trying reduce duplication code extracting selection variable:   make work ’ll need two things: Wrap whole thing function Use any_of() all_of() instead bare variable names","code":"starts_with(\"foo\") #> Error: #> ! `starts_with()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details.  mtcars[contains(\"foo\")] #> Error: #> ! `contains()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details.  subset(mtcars, select = matches(\"foo\")) #> Error: #> ! `matches()` must be used within a *selecting* function. #> i See #>   <https://tidyselect.r-lib.org/reference/faq-selection-context.html> #>   for details. my_vars <- c(name, species, ends_with(\"color\")) #> Error in eval(expr, envir, enclos): object 'name' not found my_vars <- function() {   c(any_of(c(\"name\", \"species\")), ends_with(\"color\")) } dplyr::select(starwars, my_vars()) #> # A tibble: 87 x 5 #>   name           species hair_color skin_color  eye_color #>   <chr>          <chr>   <chr>      <chr>       <chr>     #> 1 Luke Skywalker Human   blond      fair        blue      #> 2 C-3PO          Droid   <NA>       gold        yellow    #> 3 R2-D2          Droid   <NA>       white, blue red       #> 4 Darth Vader    Human   none       white       yellow    #> # i 83 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"overview-of-selection-features-","dir":"Reference","previous_headings":"","what":"Overview of selection features:","title":"Selection language — language","text":"tidyselect implements DSL selecting variables. provides helpers selecting variables: var1:var10: variables lying var1 left var10 right. starts_with(\"\"): names start \"\". ends_with(\"z\"): names end \"z\". contains(\"b\"): names contain \"b\". matches(\"x.y\"): names match regular expression x.y. num_range(x, 1:4): names following pattern, x1, x2, ..., x4. all_of(vars)/any_of(vars): matches names stored character vector vars. all_of(vars) error variables present; any_of(var) match just variables exist. everything(): variables. last_col(): furthest column right. (.numeric): variables .numeric() returns TRUE. well operators combining selections: !selection: variables match selection. selection1 & selection2: variables included selection1 selection2. selection1 | selection2: variables match either selection1 selection2. writing code inside packages can substitute \"var\" var avoid R CMD check notes.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"simple-examples","dir":"Reference","previous_headings":"","what":"Simple examples","title":"Selection language — language","text":"show usage basic selection operators. See specific help pages learn helpers like starts_with(). selection language can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   Select variables name:   Select multiple variables separating commas. Note order columns determined order inputs:   Functions like tidyr::pivot_longer() take variables dots. case use c() select multiple variables:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) starwars %>% select(height) #> # A tibble: 87 x 1 #>   height #>    <int> #> 1    172 #> 2    167 #> 3     96 #> 4    202 #> # i 83 more rows  iris %>% pivot_longer(Sepal.Length) #> # A tibble: 150 x 6 #>   Sepal.Width Petal.Length Petal.Width Species name         value #>         <dbl>        <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1         3.5          1.4         0.2 setosa  Sepal.Length   5.1 #> 2         3            1.4         0.2 setosa  Sepal.Length   4.9 #> 3         3.2          1.3         0.2 setosa  Sepal.Length   4.7 #> 4         3.1          1.5         0.2 setosa  Sepal.Length   4.6 #> # i 146 more rows starwars %>% select(homeworld, height, mass) #> # A tibble: 87 x 3 #>   homeworld height  mass #>   <chr>      <int> <dbl> #> 1 Tatooine     172    77 #> 2 Tatooine     167    75 #> 3 Naboo         96    32 #> 4 Tatooine     202   136 #> # i 83 more rows iris %>% pivot_longer(c(Sepal.Length, Petal.Length)) #> # A tibble: 300 x 5 #>   Sepal.Width Petal.Width Species name         value #>         <dbl>       <dbl> <fct>   <chr>        <dbl> #> 1         3.5         0.2 setosa  Sepal.Length   5.1 #> 2         3.5         0.2 setosa  Petal.Length   1.4 #> 3         3           0.2 setosa  Sepal.Length   4.9 #> 4         3           0.2 setosa  Petal.Length   1.4 #> # i 296 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"operators-","dir":"Reference","previous_headings":"","what":"Operators:","title":"Selection language — language","text":": operator selects range consecutive variables:   ! operator negates selection:   & | take intersection union two selections:   take difference two selections, combine & ! operators:","code":"starwars %>% select(name:mass) #> # A tibble: 87 x 3 #>   name           height  mass #>   <chr>           <int> <dbl> #> 1 Luke Skywalker    172    77 #> 2 C-3PO             167    75 #> 3 R2-D2              96    32 #> 4 Darth Vader       202   136 #> # i 83 more rows starwars %>% select(!(name:mass)) #> # A tibble: 87 x 11 #>   hair_color skin_color  eye_color birth_year sex   gender    homeworld species #>   <chr>      <chr>       <chr>          <dbl> <chr> <chr>     <chr>     <chr>   #> 1 blond      fair        blue            19   male  masculine Tatooine  Human   #> 2 <NA>       gold        yellow         112   none  masculine Tatooine  Droid   #> 3 <NA>       white, blue red             33   none  masculine Naboo     Droid   #> 4 none       white       yellow          41.9 male  masculine Tatooine  Human   #> # i 83 more rows #> # i 3 more variables: films <list>, vehicles <list>, starships <list>  iris %>% select(!c(Sepal.Length, Petal.Length)) #> # A tibble: 150 x 3 #>   Sepal.Width Petal.Width Species #>         <dbl>       <dbl> <fct>   #> 1         3.5         0.2 setosa  #> 2         3           0.2 setosa  #> 3         3.2         0.2 setosa  #> 4         3.1         0.2 setosa  #> # i 146 more rows  iris %>% select(!ends_with(\"Width\")) #> # A tibble: 150 x 3 #>   Sepal.Length Petal.Length Species #>          <dbl>        <dbl> <fct>   #> 1          5.1          1.4 setosa  #> 2          4.9          1.4 setosa  #> 3          4.7          1.3 setosa  #> 4          4.6          1.5 setosa  #> # i 146 more rows iris %>% select(starts_with(\"Petal\") & ends_with(\"Width\")) #> # A tibble: 150 x 1 #>   Petal.Width #>         <dbl> #> 1         0.2 #> 2         0.2 #> 3         0.2 #> 4         0.2 #> # i 146 more rows  iris %>% select(starts_with(\"Petal\") | ends_with(\"Width\")) #> # A tibble: 150 x 3 #>   Petal.Length Petal.Width Sepal.Width #>          <dbl>       <dbl>       <dbl> #> 1          1.4         0.2         3.5 #> 2          1.4         0.2         3   #> 3          1.3         0.2         3.2 #> 4          1.5         0.2         3.1 #> # i 146 more rows iris %>% select(starts_with(\"Petal\") & !ends_with(\"Width\")) #> # A tibble: 150 x 1 #>   Petal.Length #>          <dbl> #> 1          1.4 #> 2          1.4 #> 3          1.3 #> 4          1.5 #> # i 146 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/language.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Selection language — language","text":"order selected columns determined inputs. all_of(c(\"foo\", \"bar\")) selects \"foo\" first. c(starts_with(\"c\"), starts_with(\"d\")) selects columns starting \"c\" first, columns starting \"d\".","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Superseded selection helpers — one_of","title":"Superseded selection helpers — one_of","text":"one_of() superseded favour precise any_of() all_of() selectors.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Superseded selection helpers — one_of","text":"","code":"one_of(..., .vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/one_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Superseded selection helpers — one_of","text":"... One character vectors. .vars character vector variable names. called inside selecting functions like dplyr::select() automatically set names table.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":null,"dir":"Reference","previous_headings":"","what":"Peek at variables in the selection context — peek_vars","title":"Peek at variables in the selection context — peek_vars","text":"peek_vars() returns vector names variables currently available selection. peek_data() returns whole input vector (available eval_select()). Read Get started examples create selection helpers peek_vars(). variable names selection context registered automatically eval_select() eval_rename() duration evaluation. peek_vars() glue connects selection helpers current selection context.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Peek at variables in the selection context — peek_vars","text":"","code":"peek_vars(..., fn = NULL)  peek_data(..., fn = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/peek_vars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Peek at variables in the selection context — peek_vars","text":"... dots future extensions must empty. fn name function use error messages helper used wrong context. supplied, generic error message used instead.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":null,"dir":"Reference","previous_headings":"","what":"Replace or get current variables — poke_vars","title":"Replace or get current variables — poke_vars","text":"Variables made available select helpers registering special placeholder. scoped_vars() changes current variables sets function exit hook automatically restores previous variables current function returns. with_vars() takes expression evaluated variable context. poke_vars() changes contents placeholder new set variables. returns previous variables invisibly responsibility restore done. expert use . peek_vars() returns variables currently registered. has_vars() returns TRUE variable context set, FALSE otherwise.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Replace or get current variables — poke_vars","text":"","code":"poke_vars(vars)  scoped_vars(vars, frame = caller_env())  with_vars(vars, expr)  has_vars()"},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Replace or get current variables — poke_vars","text":"vars character vector variable names. frame frame environment exit hook restoring old variables registered. expr expression evaluated within variable context.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Replace or get current variables — poke_vars","text":"poke_vars() scoped_vars(), old variables invisibly. peek_vars(), variables currently registered.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/poke_vars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Replace or get current variables — poke_vars","text":"","code":"poke_vars(letters) peek_vars() #>  [1] \"a\" \"b\" \"c\" \"d\" \"e\" \"f\" \"g\" \"h\" \"i\" \"j\" \"k\" \"l\" \"m\" \"n\" \"o\" \"p\" \"q\" #> [18] \"r\" \"s\" \"t\" \"u\" \"v\" \"w\" \"x\" \"y\" \"z\"  # Now that the variables are registered, the helpers can figure out # the locations of elements within the variable vector: all_of(c(\"d\", \"z\")) #> [1]  4 26  # In a function be sure to restore the previous variables. An exit # hook is the best way to do it: fn <- function(vars) {   old <- poke_vars(vars)   on.exit(poke_vars(old))    all_of(\"d\") } fn(letters) #> [1] 4 fn(letters[3:5]) #> [1] 2  # The previous variables are still registered after fn() was # called: peek_vars() #>  [1] \"a\" \"b\" \"c\" \"d\" \"e\" \"f\" \"g\" \"h\" \"i\" \"j\" \"k\" \"l\" \"m\" \"n\" \"o\" \"p\" \"q\" #> [18] \"r\" \"s\" \"t\" \"u\" \"v\" \"w\" \"x\" \"y\" \"z\"   # It is recommended to use the scoped variant as it restores the # state automatically when the function returns: fn <- function(vars) {   scoped_vars(vars)   starts_with(\"r\") } fn(c(\"red\", \"blue\", \"rose\")) #> [1] 1 3  # The with_vars() helper makes it easy to pass an expression that # should be evaluated in a variable context. Thanks to lazy # evaluation, you can just pass the expression argument from your # wrapper to with_vars(): fn <- function(expr) {   vars <- c(\"red\", \"blue\", \"rose\")   with_vars(vars, expr) } fn(starts_with(\"r\")) #> [1] 1 3"},{"path":"https://tidyselect.r-lib.org/dev/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. rlang enquo, quo, quo_name, quos","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables that match a pattern — starts_with","title":"Select variables that match a pattern — starts_with","text":"selection helpers match variables according given pattern. starts_with(): Starts exact prefix. ends_with(): Ends exact suffix. contains(): Contains literal string. matches(): Matches regular expression. num_range(): Matches numerical range like x01, x02, x03.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables that match a pattern — starts_with","text":"","code":"starts_with(match, ignore.case = TRUE, vars = NULL)  ends_with(match, ignore.case = TRUE, vars = NULL)  contains(match, ignore.case = TRUE, vars = NULL)  matches(match, ignore.case = TRUE, perl = FALSE, vars = NULL)  num_range(prefix, range, suffix = \"\", width = NULL, vars = NULL)"},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables that match a pattern — starts_with","text":"match character vector. length > 1, union matches taken. starts_with(), ends_with(), contains() exact match. matches() regular expression, can stringr pattern. ignore.case TRUE, default, ignores case matching names. vars character vector variable names. supplied, variables taken current selection context (established functions like select() pivot_longer()). perl Perl-compatible regexps used? prefix, suffix prefix/suffix added /numeric range. range sequence integers, like 1:5. width Optionally, \"width\" numeric range. example, range 2 gives \"01\", range three \"001\", etc.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/starts_with.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables that match a pattern — starts_with","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   starts_with() selects variables matching prefix ends_with() matches suffix:   can supply multiple prefixes suffixes. Note order variables depends order suffixes prefixes:   contains() selects columns whose names contain word:   starts_with(), ends_with(), contains() use regular expressions. select regexp use matches():   starts_with() selects variables starting prefix. select range, use num_range(). Compare:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) iris %>% select(starts_with(\"Sepal\")) #> # A tibble: 150 x 2 #>   Sepal.Length Sepal.Width #>          <dbl>       <dbl> #> 1          5.1         3.5 #> 2          4.9         3   #> 3          4.7         3.2 #> 4          4.6         3.1 #> # i 146 more rows  iris %>% select(ends_with(\"Width\")) #> # A tibble: 150 x 2 #>   Sepal.Width Petal.Width #>         <dbl>       <dbl> #> 1         3.5         0.2 #> 2         3           0.2 #> 3         3.2         0.2 #> 4         3.1         0.2 #> # i 146 more rows iris %>% select(starts_with(c(\"Petal\", \"Sepal\"))) #> # A tibble: 150 x 4 #>   Petal.Length Petal.Width Sepal.Length Sepal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          1.4         0.2          5.1         3.5 #> 2          1.4         0.2          4.9         3   #> 3          1.3         0.2          4.7         3.2 #> 4          1.5         0.2          4.6         3.1 #> # i 146 more rows  iris %>% select(ends_with(c(\"Width\", \"Length\"))) #> # A tibble: 150 x 4 #>   Sepal.Width Petal.Width Sepal.Length Petal.Length #>         <dbl>       <dbl>        <dbl>        <dbl> #> 1         3.5         0.2          5.1          1.4 #> 2         3           0.2          4.9          1.4 #> 3         3.2         0.2          4.7          1.3 #> 4         3.1         0.2          4.6          1.5 #> # i 146 more rows iris %>% select(contains(\"al\")) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows # [pt] is matched literally: iris %>% select(contains(\"[pt]al\")) #> # A tibble: 150 x 0  # [pt] is interpreted as a regular expression iris %>% select(matches(\"[pt]al\")) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows billboard %>% select(starts_with(\"wk\")) #> # A tibble: 317 x 76 #>     wk1   wk2   wk3   wk4   wk5   wk6   wk7   wk8   wk9  wk10  wk11  wk12  wk13 #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1    87    82    72    77    87    94    99    NA    NA    NA    NA    NA    NA #> 2    91    87    92    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA #> 3    81    70    68    67    66    57    54    53    51    51    51    51    47 #> 4    76    76    72    69    67    65    55    59    62    61    61    59    61 #> # i 313 more rows #> # i 63 more variables: wk14 <dbl>, wk15 <dbl>, wk16 <dbl>, wk17 <dbl>, #> #   wk18 <dbl>, wk19 <dbl>, wk20 <dbl>, wk21 <dbl>, ...  billboard %>% select(num_range(\"wk\", 10:15)) #> # A tibble: 317 x 6 #>    wk10  wk11  wk12  wk13  wk14  wk15 #>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1    NA    NA    NA    NA    NA    NA #> 2    NA    NA    NA    NA    NA    NA #> 3    51    51    51    47    44    38 #> 4    61    61    59    61    66    72 #> # i 313 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect-package.html","id":null,"dir":"Reference","previous_headings":"","what":"tidyselect: Select from a Set of Strings — tidyselect-package","title":"tidyselect: Select from a Set of Strings — tidyselect-package","text":"backend selecting functions 'tidyverse'. makes easy implement select-like functions packages way consistent 'tidyverse' interfaces selection.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"tidyselect: Select from a Set of Strings — tidyselect-package","text":"Maintainer: Lionel Henry lionel@posit.co Authors: Hadley Wickham hadley@posit.co contributors: Posit Software, PBC [copyright holder, funder]","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":null,"dir":"Reference","previous_headings":"","what":"tidyselect methods for custom types — tidyselect_data_proxy","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"tidyselect_data_proxy() returns data frame. tidyselect_data_has_predicates() returns TRUE FALSE support predicate functions, return 0-row data frame tidyselect_data_proxy() FALSE tidyselect_data_has_predicates().","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"","code":"tidyselect_data_proxy(x)  tidyselect_data_has_predicates(x)"},{"path":"https://tidyselect.r-lib.org/dev/reference/tidyselect_data_proxy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"tidyselect methods for custom types — tidyselect_data_proxy","text":"x data-frame like object passed eval_select(), eval_rename(), friends.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variable — vars_pull","title":"Select variable — vars_pull","text":"function powers dplyr::pull() various functions tidyr package. similar vars_select() returns one column name slightly different semantics: allows negative numbers select columns end.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variable — vars_pull","text":"","code":"vars_pull(   vars,   var = -1,   error_call = caller_env(),   error_arg = caller_arg(var) )"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variable — vars_pull","text":"vars character vector existing column names. var variable specified : literal variable name positive integer, giving position counting left negative integer, giving position counting right. default returns last column (assumption column created recently). argument taken expression supports quasiquotation (can unquote column names column locations). error_call execution environment currently running function, e.g. caller_env(). function mentioned error messages source error. See call argument abort() information. error_arg argument name string. argument mentioned error messages input origin problem.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select variable — vars_pull","text":"selected column name unnamed string.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_pull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variable — vars_pull","text":"","code":"# It takes its argument by expression: vars_pull(letters, c) #> [1] \"c\"  # Negative numbers select from the end: vars_pull(letters, -3) #> [1] \"x\"  # You can unquote variables: var <- 10 vars_pull(letters, !!var) #> [1] \"j\""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Select or rename variables — vars_select","title":"Select or rename variables — vars_select","text":"Please use eval_select() eval_rename() instead. See vignette(\"tidyselect\") get started.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select or rename variables — vars_select","text":"","code":"vars_select(   .vars,   ...,   .include = character(),   .exclude = character(),   .strict = TRUE )  vars_rename(.vars, ..., .strict = TRUE)"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select or rename variables — vars_select","text":".vars character vector existing column names. ... Selection inputs. See help selection helpers. .include, .exclude Character vector column names always include/exclude. .strict TRUE, throw error attempt select rename variable exist.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select or rename variables — vars_select","text":"named character vector. Values existing column names, names new names.","code":""},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":null,"dir":"Reference","previous_headings":"","what":"List of selection helpers — vars_select_helpers","title":"List of selection helpers — vars_select_helpers","text":"list contains selection helpers exported tidyselect. useful wanted embed helpers API without track addition new helpers tidyselect. However selection helpers now always embedded DSL.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List of selection helpers — vars_select_helpers","text":"","code":"vars_select_helpers"},{"path":"https://tidyselect.r-lib.org/dev/reference/vars_select_helpers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"List of selection helpers — vars_select_helpers","text":"object class list length 11.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":null,"dir":"Reference","previous_headings":"","what":"Select variables with a function — where","title":"Select variables with a function — where","text":"selection helper selects variables function returns TRUE.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select variables with a function — where","text":"","code":"where(fn)"},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select variables with a function — where","text":"fn function returns TRUE FALSE (technically, predicate function). Can also purrr-like formula.","code":""},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select variables with a function — where","text":"Selection helpers can used functions like dplyr::select() tidyr::pivot_longer(). first attach tidyverse:   () takes function returns variables function returns TRUE:","code":"library(tidyverse)  # For better printing iris <- as_tibble(iris) is.factor(iris[[4]]) #> [1] FALSE  is.factor(iris[[5]]) #> [1] TRUE  iris %>% select(where(is.factor)) #> # A tibble: 150 x 1 #>   Species #>   <fct>   #> 1 setosa  #> 2 setosa  #> 3 setosa  #> 4 setosa  #> # i 146 more rows  is.numeric(iris[[4]]) #> [1] TRUE  is.numeric(iris[[5]]) #> [1] FALSE  iris %>% select(where(is.numeric)) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows"},{"path":"https://tidyselect.r-lib.org/dev/reference/where.html","id":"the-formula-shorthand","dir":"Reference","previous_headings":"","what":"The formula shorthand","title":"Select variables with a function — where","text":"can use purrr-like formulas shortcut creating function spot. expressions equivalent:   shorthand useful adding logic inline. select numeric variables whose mean greater 3.5:","code":"iris %>% select(where(is.numeric)) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows  iris %>% select(where(function(x) is.numeric(x))) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows  iris %>% select(where(~ is.numeric(.x))) #> # A tibble: 150 x 4 #>   Sepal.Length Sepal.Width Petal.Length Petal.Width #>          <dbl>       <dbl>        <dbl>       <dbl> #> 1          5.1         3.5          1.4         0.2 #> 2          4.9         3            1.4         0.2 #> 3          4.7         3.2          1.3         0.2 #> 4          4.6         3.1          1.5         0.2 #> # i 146 more rows iris %>% select(where(~ is.numeric(.x) && mean(.x) > 3.5)) #> # A tibble: 150 x 2 #>   Sepal.Length Petal.Length #>          <dbl>        <dbl> #> 1          5.1          1.4 #> 2          4.9          1.4 #> 3          4.7          1.3 #> 4          4.6          1.5 #> # i 146 more rows"},{"path":[]},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-121","dir":"Changelog","previous_headings":"","what":"tidyselect 1.2.1","title":"tidyselect 1.2.1","text":"CRAN release: 2024-03-11 Performance improvements (#337, #338, #339, #341) eval_select() --bounds errors now use verb “select” rather “subset” error message consistency dplyr::select() (#271). Fix CRAN checks.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-120","dir":"Changelog","previous_headings":"","what":"tidyselect 1.2.0","title":"tidyselect 1.2.0","text":"CRAN release: 2022-10-10","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New features","title":"tidyselect 1.2.0","text":"New tidyselect_data_proxy() tidyselect_data_has_predicates() allows tidyselect work custom input types (#242). New eval_relocate() moving selection. powers dplyr::relocate() (#232).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"lifecycle-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Lifecycle changes","title":"tidyselect 1.2.0","text":"Using all_of() outside tidyselect context now deprecated (#269). future error consistent any_of(). Use .data tidyselect expressions now deprecated cleanly separate tidy-select data-masking. Replace .data$x \"x\" .data[[var]] all_of(var) (#169). Use bare predicates (wrapped ()) indirection (without using all_of()) formally deprecated (#317).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"minor-improvements-and-bug-fixes-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor improvements and bug fixes","title":"tidyselect 1.2.0","text":"Selection language: any_of() generates informative error supply many arguments (#241). all_of() (like any_of()) returns integer vector make easier combine functions (#270, #294). also fails can’t find variables even strict = FALSE. matches() recognises correctly uses stringr pattern objects (stringr::regex(), stringr::fixed(), etc) (#238). also now works named vectors (#250). num_range() gains suffix argument (#229). () now exported, like select helpers (#201), gives informative errors (#236). eval_select() include now preserves order variables ’re present selection (#224). eval_select() always returns named vector, even renaming permitted (#220). eval_select() eval_relocate() gain new allow_empty argument makes possible forbid empty selections allow_empty = FALSE (#252). eval_select(allow_rename = FALSE) longer fails empty selections (#221, @eutwt) predicate functions (#225). now properly fails partial renaming (#305). peek_var() error now generates hyperlink docs recent RStudio (#289). vars_pull() generates informative error messages (#234, #258, #318) gains error_call error_arg arguments. Errors produced tidyselect now informative. Evaluation errors now chained, child error call set error_call argument eval_select() eval_rename(). ’ve also improved backtraces base errors, done better propagating root error_call vctrs input checkers. tidyselect_verbosity longer used; deprecation messaging now controlled lifecycle_verbosity like packages (#317).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-112","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.2","title":"tidyselect 1.1.2","text":"CRAN release: 2022-02-21 Fix CRAN checks. Better compatibility rlang 1.0.0 errors. come soon.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-111","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.1","title":"tidyselect 1.1.1","text":"CRAN release: 2021-04-30 Fix CRAN checks. tidyselect re-licensed MIT (#217).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-110","dir":"Changelog","previous_headings":"","what":"tidyselect 1.1.0","title":"tidyselect 1.1.0","text":"CRAN release: 2020-05-11 Predicate functions must now wrapped (). {r} iris %>% select((.factor)) made change avoid puzzling error messages variable unexpectedly missing data frame corresponding function environment: {r} # Attempts invoke `data()` function data.frame(x = 1) %>% select(data) Now tidyselect correctly complain missing variable rather trying invoke function. compatibility support predicate functions starting 1 version. eval_select() gains allow_rename argument. set FALSE, renaming variables c(foo = bar) syntax error. useful implement purely selective behaviour (#178). Fixed issue preventing repeated deprecation messages tidyselect_verbosity set \"verbose\" (#184). any_of() now preserves order input variables (#186). return value eval_select() now always named, even inputs constant (#173).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-100","dir":"Changelog","previous_headings":"","what":"tidyselect 1.0.0","title":"tidyselect 1.0.0","text":"CRAN release: 2020-01-27 1.0.0 release tidyselect. features solidly defined implemented syntax, support predicate functions, new boolean operators, much .","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"documentation-1-0-0","dir":"Changelog","previous_headings":"","what":"Documentation","title":"tidyselect 1.0.0","text":"New Get started vignette client packages. Read vignette(\"tidyselect\") https://tidyselect.r-lib.org/articles/tidyselect.html. definition tidyselect language consolidated. technical description now available: https://tidyselect.r-lib.org/articles/syntax.html.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"tidyselect 1.0.0","text":"Selecting non-column variables bare names now triggers informative message suggesting use all_of() instead. Referring contextual objects bare name brittle might masked data frame column. Using all_of() safe (#76). tidyselect now uses vctrs validating inputs. changes may reveal programming errors previously silent. may also cause failures unit tests make faulty assumptions content error messages created tidyselect: --bounds errors thrown name doesn’t exist location large input. Logical vectors now fail properly. Selected variables now must unique. previously possible return duplicate selections circumstances. input names can longer contain NA values. Note recommend testthat::verify_output() monitoring error messages thrown packages don’t control. Unlike expect_error(), verify_output() cause CMD check failures error messages changed. See https://www.tidyverse.org/blog/2019/11/testthat-2-3-0/ information.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"syntax-1-0-0","dir":"Changelog","previous_headings":"","what":"Syntax","title":"tidyselect 1.0.0","text":"boolean operators can now used create selections (#106). ! negates selection. | takes union two selections. & takes intersection two selections. patterns can currently achieved using -, c() intersect() respectively. boolean operators intuitive use. Many thanks Irene Steves (@isteves) suggesting UI. can now use predicate functions selection contexts: feature available functions use legacy interface tidyselect. need updated use new eval_select() function instead vars_select(). Unary - inside nested c() now consistently syntax set difference (#130). Improved support named elements. now possible assign name multiple elements, input data structure doesn’t require unique names (.e. anything data frame). selection engine rewritten support clearer separation data-expressions (calls :, -, c) env-expressions (anything else). means can now safely use expressions type: Even data frame data contains column also named data, subexpression ncol(data) still correctly evaluated. data:ncol(data) expression equivalent 2:3 data looked relevant context without ambiguity: example bit contrived, many realistic cases changes make easier write safe code: {r} select_from <- function(data, var) {   data %>% dplyr::select({{ var }} : ncol(data)) } data %>% select_from(data) #> # tibble: 1 x 2 #>    data   bar #>   <dbl> <dbl> #> 1     2     3","code":"iris %>% select(is.factor) iris %>% select(is.factor | is.numeric) data %>% select(1:ncol(data)) data %>% pivot_longer(1:ncol(data)) data <- tibble(foo = 1, data = 2, bar = 3) data %>% dplyr::select(data:ncol(data)) #> # A tibble: 1 x 2 #>    data   bar #>   <dbl> <dbl> #> 1     2     3"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"user-facing-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"User-facing improvements","title":"tidyselect 1.0.0","text":"new selection helpers all_of() any_of() strict variants one_of(). former always fails variables unknown, latter . all_of() safer use expect selected variables exist. any_of() useful cases, instance ensure variables selected : Note all_of() any_of() bit conservative function signature one_of(): accept dots. equivalent one_of(\"\", \"b\") all_of(c(\"\", \"b\")). Selection helpers like all_of() starts_with() now available selection contexts, even haven’t attached search path. visible consequence change now easier use selection functions without attaching host package: still recommended export helpers package users can easily look documentation ?. starts_with(), ends_with(), contains(), matches() now accept vector inputs (#50). instance now equivalent ways selecting variables start either \"\" \"b\": {r} starts_with(c(\"\", \"b\")) starts_with(\"\") | starts_with(\"b\") matches() new argument perl allow Perl-like regular expressions (@fmichonneau, #71) Better support selecting S3 vectors. instance, factors treated characters.","code":"vars <- c(\"Species\", \"Genus\") iris %>% dplyr::select(-any_of(vars)) # Before dplyr::select(mtcars, dplyr::starts_with(\"c\"))  # After dplyr::select(mtcars, starts_with(\"c\"))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"api-1-0-0","dir":"Changelog","previous_headings":"","what":"API","title":"tidyselect 1.0.0","text":"New eval_select() eval_rename() functions client packages. replace vars_select() vars_rename(), now deprecated. functions: Take full data rather just names. makes possible use function predicates selection context. Return numeric vector locations rather vector names. makes possible use tidyselect inputs support duplicate names, like regular vectors.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"other-features-and-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Other features and fixes","title":"tidyselect 1.0.0","text":".strict argument vars_select() now works robustly consistently. Using arithmetic operators selection context now fails informatively (#84). now possible select columns data frames containing duplicate variables (#94). However, duplicates can’t part final selection. eval_rename() longer ignore names unquoted character vectors length 1 (#79). eval_rename() now fails variable renamed existing name (#70). eval_rename() better support existing duplicates (creating new duplicates error). eval_select(), eval_rename() vars_pull() now detect missing values uniformly (#72). vars_pull() now includes faulty expression error messages. performance issues eval_rename() many arguments fixed. make dplyr::rename_all() many columns much faster (@zkamvar, #92). tidyselect now much faster many columns, thanks performance fix rlang::env_bind() well internal fixes. vars_select() ignores vectors zeros (#82).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-025","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.5","title":"tidyselect 0.2.5","text":"CRAN release: 2018-10-11 maintenance release compatibility rlang 0.3.0.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-024","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.4","title":"tidyselect 0.2.4","text":"CRAN release: 2018-02-26 Fixed warning occurred vector column positions supplied vars_select() functions depending tidyr::gather() (#43 tidyverse/tidyr#374). Fixed compatibility issue rlang 0.2.0 (#51).","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-023","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.3","title":"tidyselect 0.2.3","text":"CRAN release: 2017-11-06 Internal fixes prevision using tidyselect within dplyr. vars_select() vars_rename() now correctly support unquoting character vectors names. vars_select() now ignores missing variables.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-022","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.2","title":"tidyselect 0.2.2","text":"CRAN release: 2017-10-10 dplyr now correctly mentioned suggested package.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-021","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.1","title":"tidyselect 0.2.1","text":"CRAN release: 2017-10-09 - now supports character vectors addition strings. makes easy unquote column names exclude set: {r} vars <- c(\"cyl\", \"\", \"disp\", \"drat\") vars_select(names(mtcars), - !!vars) last_col() now issues error variable vector empty. last_col() now returns column positions rather column names consistency helpers. also makes compatible functions like seq(). c() now supports character vectors way - seq(). (#37 @gergness)","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-020","dir":"Changelog","previous_headings":"","what":"tidyselect 0.2.0","title":"tidyselect 0.2.0","text":"CRAN release: 2017-08-30 main point release revert troublesome behaviour introduced tidyselect 0.1.0. also includes features.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"evaluation-rules-0-2-0","dir":"Changelog","previous_headings":"","what":"Evaluation rules","title":"tidyselect 0.2.0","text":"special evaluation semantics selection changed back old behaviour new rules causing much trouble confusion. now data expressions (symbols calls : c()) can refer registered variables objects context. However semantics context expressions (calls : c()) remain . expressions evaluated context refer registered variables. ’re writing functions refer contextual objects, still good idea avoid data expressions. Since registered variables change function user input never know local objects might shadowed variable. Consider: select second element letters 14th? Since variables precedence data expression, select 14 first letters. can made robust turning data expression context expression: can also use quasiquotation since unquoted arguments guaranteed evaluated without user data scope. equivalent special rules context expressions, may clearer reader accustomed tidy eval: {r} vars_select(letters, seq(1, !! n)) Finally, may want explicit opposite direction. expect variable found data context, can use .data pronoun: {r} vars_select(names(mtcars), .data$cyl : .data$drat)","code":"n <- 2 vars_select(letters, 1:n) vars_select(letters, seq(1, n))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-features-0-2-0","dir":"Changelog","previous_headings":"","what":"New features","title":"tidyselect 0.2.0","text":"new select helper last_col() helpful select custom range: vars_select(vars, 3:last_col()). : - now handle strings well. makes easy unquote column name: (!!name) : last_col() - !!name. vars_select() gains .strict argument similar rename_vars(). set FALSE, errors unknown variables ignored. vars_select() now treats NULL empty inputs. follows trend tidyverse tools. vars_rename() now handles variable positions (integers round doubles) just like vars_select() (#20). vars_rename() now implemented tidy eval framework. Like vars_select(), expressions evaluated without user data scope. addition variable context now established can write rename helpers. return single round number string (variable position variable name). has_vars() predicate tests whether variable context set (#21). selection helpers now exported list vars_select_helpers. intended APIs embed helpers evaluation environment.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"fixes-0-2-0","dir":"Changelog","previous_headings":"","what":"Fixes","title":"tidyselect 0.2.0","text":"one_of() argument vars renamed .vars avoid spurious matching.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"tidyselect-011","dir":"Changelog","previous_headings":"","what":"tidyselect 0.1.1","title":"tidyselect 0.1.1","text":"CRAN release: 2017-07-24 tidyselect new home legacy functions dplyr::select_vars(), dplyr::rename_vars() dplyr::select_var().","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"api-changes-0-1-1","dir":"Changelog","previous_headings":"","what":"API changes","title":"tidyselect 0.1.1","text":"took opportunity make changes API: select_vars() rename_vars() now vars_select() vars_rename(). follows tidyverse convention prefix corresponds input type suffixes indicate output type. Similarly, select_var() now vars_pull(). arguments now prefixed dots limit argument matching issues. dots help, still good idea splice list captured quosures make sure dotted arguments never matched vars_select()’s named arguments: Error messages can now customised. consistency dplyr, error messages refer “columns” default. assumes variables selected come data frame. appropriate DSL, can now add attribute vars_type .vars vector specify alternative names. must character vector length 2 whose first component singular form second plural. example, c(\"variable\",   \"variables\").","code":"vars_select(vars, !!! quos(...))"},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"establishing-a-variable-context-0-1-1","dir":"Changelog","previous_headings":"","what":"Establishing a variable context","title":"tidyselect 0.1.1","text":"tidyselect provides ways establishing variable context: scoped_vars() sets variable context along exit hook automatically restores previous variables. preferred way changing variable context. with_vars() takes variables expression evaluates latter context former. poke_vars() establishes new variable context. returns previous context invisibly responsibility restore done. expert use . current_vars() renamed peek_vars(). naming reference peek poke legacy languages.","code":""},{"path":"https://tidyselect.r-lib.org/dev/news/index.html","id":"new-evaluation-semantics-0-1-1","dir":"Changelog","previous_headings":"","what":"New evaluation semantics","title":"tidyselect 0.1.1","text":"evaluation semantics selecting verbs changed. Symbols now evaluated data-context isolated calling environment. means can longer refer local variables unless explicitly unquoting variables !!, mostly expert use. Note since dplyr 0.7, helper calls (like starts_with()) obey opposite behaviour evaluated calling context isolated data context. sum , symbols can refer data frame objects, helpers can refer contextual objects. differs usual R evaluation semantics data calling environment scope (former prevailing latter).","code":""}]