diff --git a/docs/r/news/index.html b/docs/r/news/index.html
index 367d1f307ee..b46408c957d 100644
--- a/docs/r/news/index.html
+++ b/docs/r/news/index.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en-US"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • Arrow R Package</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.8/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.8/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Changelog"><meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png"><meta property="og:image:alt" content="Apache Arrow logo, displaying the triple chevron image adjacent to the text"><!-- Matomo --><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en-US"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • Arrow R Package</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Changelog"><meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png"><meta property="og:image:alt" content="Apache Arrow logo, displaying the triple chevron image adjacent to the text"><!-- Matomo --><script>
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@@ -73,13 +73,42 @@ <h1>Changelog</h1>
     </div>
 
     <div class="section level2">
-<h2 class="pkg-version" data-toc-text="25.0.0" id="arrow-2500">arrow 25.0.0<a class="anchor" aria-label="anchor" href="#arrow-2500"></a></h2>
+<h2 class="pkg-version" data-toc-text="25.0.0" id="arrow-2500">arrow 25.0.0<a class="anchor" aria-label="anchor" href="#arrow-2500"></a></h2><p class="text-muted">CRAN release: 2026-07-16</p>
+<div class="section level3">
+<h3 id="breaking-changes-25-0-0">Breaking changes<a class="anchor" aria-label="anchor" href="#breaking-changes-25-0-0"></a></h3>
+<ul><li>Arrow <code>uint64</code> types are now always converted to R <code>double</code> (numeric) vectors, regardless of the values. Previously, small <code>uint64</code> values were converted to R <code>integer</code>, which could cause inconsistent types within list columns when different list elements had different value ranges (<a href="https://github.com/apache/arrow/issues/50339" class="external-link">#50339</a>).</li>
+</ul></div>
+<div class="section level3">
+<h3 id="new-features-25-0-0">New features<a class="anchor" aria-label="anchor" href="#new-features-25-0-0"></a></h3>
+<ul><li>
+<code>Field</code> objects now support field-level metadata via <code>$metadata</code> and <code>$with_metadata()</code> (<a href="https://github.com/max-romagnoli" class="external-link">@max-romagnoli</a>, <a href="https://github.com/apache/arrow/issues/33390" class="external-link">#33390</a>).</li>
+<li>Parquet files now support list-columns of ordered factors (ordered dictionaries) (<a href="https://github.com/apache/arrow/issues/49689" class="external-link">#49689</a>).</li>
+</ul></div>
+<div class="section level3">
+<h3 id="minor-improvements-and-fixes-25-0-0">Minor improvements and fixes<a class="anchor" aria-label="anchor" href="#minor-improvements-and-fixes-25-0-0"></a></h3>
+<ul><li>
+<code>Array$create()</code> now gives a clearer error message when given a <code>POSIXct</code> object with an invalid timezone (<a href="https://github.com/apache/arrow/issues/40886" class="external-link">#40886</a>).</li>
+<li>Dictionary arrays with <code>large_string</code> value types now convert correctly to R factors (<a href="https://github.com/apache/arrow/issues/39603" class="external-link">#39603</a>).</li>
+<li>
+<code><a href="../reference/open_dataset.html">open_dataset()</a></code> now gives a clearer error message when providing a mix of readr and Arrow options (<a href="https://github.com/Rich-T-kid" class="external-link">@Rich-T-kid</a>, <a href="https://github.com/apache/arrow/issues/33420" class="external-link">#33420</a>).</li>
+<li>
+<code><a href="../reference/read_parquet.html">read_parquet()</a></code> no longer triggers a C++ alignment warning from the Acero source node (<a href="https://github.com/apache/arrow/issues/46178" class="external-link">#46178</a>).</li>
+<li>
+<code>Schema</code> metadata partial matching on <code>$metadata$r</code> no longer errors when other metadata keys start with “r” (<a href="https://github.com/apache/arrow/issues/50163" class="external-link">#50163</a>).</li>
+<li>
+<code><a href="../reference/to_arrow.html">to_arrow()</a></code> now preserves <code>group_by()</code> when converting from a dbplyr lazy table (<a href="https://github.com/apache/arrow/issues/40640" class="external-link">#40640</a>).</li>
+<li>
+<code><a href="../reference/write_parquet.html">write_parquet()</a></code> now correctly validates that <code>max_rows_per_group</code> is a positive number (<a href="https://github.com/apache/arrow/issues/40742" class="external-link">#40742</a>).</li>
+<li>Stale S3 connections no longer cause a segfault during garbage collection (<a href="https://github.com/apache/arrow/issues/50009" class="external-link">#50009</a>).</li>
+<li>Spurious “Invalid metadata$r” warnings are no longer emitted when reading files with custom schema metadata (<a href="https://github.com/apache/arrow/issues/48712" class="external-link">#48712</a>).</li>
+</ul></div>
+<div class="section level3">
+<h3 id="installation-25-0-0">Installation<a class="anchor" aria-label="anchor" href="#installation-25-0-0"></a></h3>
+<ul><li>The R package now builds under r-universe/r-wasm (<a href="https://github.com/apache/arrow/issues/49981" class="external-link">#49981</a>).</li>
+</ul></div>
 </div>
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="24.0.0" id="arrow-2400">arrow 24.0.0<a class="anchor" aria-label="anchor" href="#arrow-2400"></a></h2><p class="text-muted">CRAN release: 2026-04-29</p>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="24.0.0" id="arrow-2400-1">arrow 24.0.0<a class="anchor" aria-label="anchor" href="#arrow-2400-1"></a></h2><p class="text-muted">CRAN release: 2026-04-29</p>
 <div class="section level3">
 <h3 id="new-features-24-0-0">New features<a class="anchor" aria-label="anchor" href="#new-features-24-0-0"></a></h3>
 <ul><li>
@@ -186,7 +215,7 @@ <h3 id="new-features-21-0-0">New features<a class="anchor" aria-label="anchor" h
 <h3 id="minor-improvements-and-fixes-21-0-0">Minor improvements and fixes<a class="anchor" aria-label="anchor" href="#minor-improvements-and-fixes-21-0-0"></a></h3>
 <ul><li>Expose an option <code>check_directory_existence_before_creation</code> in <code>S3FileSystem</code> to reduce I/O calls on cloud storage (<a href="https://github.com/HaochengLIU" class="external-link">@HaochengLIU</a>, <a href="https://github.com/apache/arrow/issues/41998" class="external-link">#41998</a>).</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/case-and-replace-when.html" class="external-link">case_when()</a></code> now correctly detects objects that are not in the global environment (<a href="https://github.com/etiennebacher" class="external-link">@etiennebacher</a>, <a href="https://github.com/apache/arrow/issues/46667" class="external-link">#46667</a>).</li>
+<code>case_when()</code> now correctly detects objects that are not in the global environment (<a href="https://github.com/etiennebacher" class="external-link">@etiennebacher</a>, <a href="https://github.com/apache/arrow/issues/46667" class="external-link">#46667</a>).</li>
 <li>Negative fractional dates now correctly converted to integers by flooring values (<a href="https://github.com/apache/arrow/issues/46873" class="external-link">#46873</a>).</li>
 <li>Backwards compatibility checks for legacy Arrow C++ versions have been removed from the R package (<a href="https://github.com/apache/arrow/issues/46491" class="external-link">#46491</a>). This shouldn’t affect most users this package and would only impact you if you were building the R package from source with different R package and Arrow C++ versions.</li>
 <li>Require CMake 3.25 or greater in bundled build script for full-source builds (<a href="https://github.com/apache/arrow/issues/46834" class="external-link">#46834</a>). This shouldn’t affect most users.</li>
@@ -236,9 +265,9 @@ <h2 class="pkg-version" data-toc-text="17.0.0" id="arrow-1700">arrow 17.0.0<a cl
 <h3 id="new-features-17-0-0">New features<a class="anchor" aria-label="anchor" href="#new-features-17-0-0"></a></h3>
 <ul><li>R functions that users write that use functions that Arrow supports in dataset queries now can be used in queries too. Previously, only functions that used arithmetic operators worked. For example, <code>time_hours &lt;- function(mins) mins / 60</code> worked, but <code>time_hours_rounded &lt;- function(mins) round(mins / 60)</code> did not; now both work. These are automatic translations rather than true user-defined functions (UDFs); for UDFs, see <code><a href="../reference/register_scalar_function.html">register_scalar_function()</a></code>. (<a href="https://github.com/apache/arrow/issues/41223" class="external-link">#41223</a>)</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> expressions can now include aggregations, such as <code>x - mean(x)</code>. (<a href="https://github.com/apache/arrow/issues/41350" class="external-link">#41350</a>)</li>
+<code>mutate()</code> expressions can now include aggregations, such as <code>x - mean(x)</code>. (<a href="https://github.com/apache/arrow/issues/41350" class="external-link">#41350</a>)</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code> supports more complex expressions, and correctly handles cases where column names are reused in expressions. (<a href="https://github.com/apache/arrow/issues/41223" class="external-link">#41223</a>)</li>
+<code>summarize()</code> supports more complex expressions, and correctly handles cases where column names are reused in expressions. (<a href="https://github.com/apache/arrow/issues/41223" class="external-link">#41223</a>)</li>
 <li>The <code>na_matches</code> argument to the <code>dplyr::*_join()</code> functions is now supported. This argument controls whether <code>NA</code> values are considered equal when joining. (<a href="https://github.com/apache/arrow/issues/41358" class="external-link">#41358</a>)</li>
 <li>R metadata, stored in the Arrow schema to support round-tripping data between R and Arrow/Parquet, is now serialized and deserialized more strictly. This makes it safer to load data from files from unknown sources into R data.frames. (<a href="https://github.com/apache/arrow/issues/41969" class="external-link">#41969</a>)</li>
 </ul></div>
@@ -391,7 +420,7 @@ <h3 id="minor-improvements-and-fixes-13-0-0">Minor improvements and fixes<a clas
 <li>Ensure that the RStringViewer helper class does not own any Array references (<a href="https://github.com/apache/arrow/issues/35812" class="external-link">#35812</a>)</li>
 <li>
 <code><a href="https://rdrr.io/r/base/strptime.html" class="external-link">strptime()</a></code> in arrow will return a timezone-aware timestamp if <code>%z</code> is part of the format string (<a href="https://github.com/apache/arrow/issues/35671" class="external-link">#35671</a>)</li>
-<li>Column ordering when combining <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across()</a></code> now matches dplyr (<a href="https://github.com/eitsupi" class="external-link">@eitsupi</a>, <a href="https://github.com/apache/arrow/issues/35473" class="external-link">#35473</a>)</li>
+<li>Column ordering when combining <code>group_by()</code> and <code>across()</code> now matches dplyr (<a href="https://github.com/eitsupi" class="external-link">@eitsupi</a>, <a href="https://github.com/apache/arrow/issues/35473" class="external-link">#35473</a>)</li>
 </ul></div>
 <div class="section level3">
 <h3 id="installation-13-0-0">Installation<a class="anchor" aria-label="anchor" href="#installation-13-0-0"></a></h3>
@@ -421,7 +450,7 @@ <h3 id="new-features-12-0-0">New features<a class="anchor" aria-label="anchor" h
 <ul><li>The <code><a href="../reference/read_parquet.html">read_parquet()</a></code> and <code><a href="../reference/read_feather.html">read_feather()</a></code> functions can now accept URL arguments (<a href="https://github.com/apache/arrow/issues/33287" class="external-link">#33287</a>, <a href="https://github.com/apache/arrow/issues/34708" class="external-link">#34708</a>).</li>
 <li>The <code>json_credentials</code> argument in <code>GcsFileSystem$create()</code> now accepts a file path containing the appropriate authentication token (<a href="https://github.com/amoeba" class="external-link">@amoeba</a>, <a href="https://github.com/apache/arrow/issues/34421" class="external-link">#34421</a>, <a href="https://github.com/apache/arrow/issues/34524" class="external-link">#34524</a>).</li>
 <li>The <code>$options</code> member of <code>GcsFileSystem</code> objects can now be inspected (<a href="https://github.com/amoeba" class="external-link">@amoeba</a>, <a href="https://github.com/apache/arrow/issues/34422" class="external-link">#34422</a>, <a href="https://github.com/apache/arrow/issues/34477" class="external-link">#34477</a>).</li>
-<li>The <code><a href="../reference/read_delim_arrow.html">read_csv_arrow()</a></code> and <code><a href="../reference/read_json_arrow.html">read_json_arrow()</a></code> functions now accept literal text input wrapped in <code><a href="https://rdrr.io/r/base/AsIs.html" class="external-link">I()</a></code> to improve compatability with <code>readr::read_csv()</code> (<a href="https://github.com/eitsupi" class="external-link">@eitsupi</a>, <a href="https://github.com/apache/arrow/issues/18487" class="external-link">#18487</a>, <a href="https://github.com/apache/arrow/issues/33968" class="external-link">#33968</a>).</li>
+<li>The <code><a href="../reference/read_delim_arrow.html">read_csv_arrow()</a></code> and <code><a href="../reference/read_json_arrow.html">read_json_arrow()</a></code> functions now accept literal text input wrapped in <code><a href="https://rdrr.io/r/base/AsIs.html" class="external-link">I()</a></code> to improve compatability with <code><a href="https://readr.tidyverse.org/reference/read_delim.html" class="external-link">readr::read_csv()</a></code> (<a href="https://github.com/eitsupi" class="external-link">@eitsupi</a>, <a href="https://github.com/apache/arrow/issues/18487" class="external-link">#18487</a>, <a href="https://github.com/apache/arrow/issues/33968" class="external-link">#33968</a>).</li>
 <li>Nested fields can now be accessed using <code>$</code> and <code>[[</code> in dplyr expressions (<a href="https://github.com/apache/arrow/issues/18818" class="external-link">#18818</a>, <a href="https://github.com/apache/arrow/issues/19706" class="external-link">#19706</a>).</li>
 </ul></div>
 <div class="section level3">
@@ -478,7 +507,7 @@ <h4 id="readingwriting-data-11-0-0-2">Reading/writing data<a class="anchor" aria
 </ul></div>
 <div class="section level4">
 <h4 id="dplyr-compatibility-11-0-0-2">dplyr compatibility<a class="anchor" aria-label="anchor" href="#dplyr-compatibility-11-0-0-2"></a></h4>
-<ul><li>New dplyr (1.1.0) function <code><a href="https://dplyr.tidyverse.org/reference/join_by.html" class="external-link">join_by()</a></code> has been implemented for dplyr joins on Arrow objects (equality conditions only). (<a href="https://github.com/apache/arrow/issues/33664" class="external-link">#33664</a>)</li>
+<ul><li>New dplyr (1.1.0) function <code>join_by()</code> has been implemented for dplyr joins on Arrow objects (equality conditions only). (<a href="https://github.com/apache/arrow/issues/33664" class="external-link">#33664</a>)</li>
 <li>Output is accurate when multiple <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">dplyr::group_by()</a></code>/<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarise()</a></code> calls are used. (<a href="https://github.com/apache/arrow/issues/14905" class="external-link">#14905</a>)</li>
 <li>
 <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarize()</a></code> works with division when divisor is a variable. (<a href="https://github.com/apache/arrow/issues/14933" class="external-link">#14933</a>)</li>
@@ -534,7 +563,7 @@ <h2 class="pkg-version" data-toc-text="10.0.0" id="arrow-1000">arrow 10.0.0<a cl
 <h3 id="arrow-dplyr-queries-10-0-0">Arrow dplyr queries<a class="anchor" aria-label="anchor" href="#arrow-dplyr-queries-10-0-0"></a></h3>
 <p>Several new functions can be used in queries:</p>
 <ul><li>
-<code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">dplyr::across()</a></code> can be used to apply the same computation across multiple columns, and the <code><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where()</a></code> selection helper is supported in <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across()</a></code>;</li>
+<code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">dplyr::across()</a></code> can be used to apply the same computation across multiple columns, and the <code>where()</code> selection helper is supported in <code>across()</code>;</li>
 <li>
 <code><a href="../reference/add_filename.html">add_filename()</a></code> can be used to get the filename a row came from (only available when querying <code><a href="../reference/Dataset.html">?Dataset</a></code>);</li>
 <li>Added five functions in the <code>slice_*</code> family: <code><a href="https://dplyr.tidyverse.org/reference/slice.html" class="external-link">dplyr::slice_min()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/slice.html" class="external-link">dplyr::slice_max()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/slice.html" class="external-link">dplyr::slice_head()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/slice.html" class="external-link">dplyr::slice_tail()</a></code>, and <code><a href="https://dplyr.tidyverse.org/reference/slice.html" class="external-link">dplyr::slice_sample()</a></code>.</li>
@@ -749,9 +778,9 @@ <h2 class="pkg-version" data-toc-text="7.0.0" id="arrow-700">arrow 7.0.0<a class
 <div class="section level3">
 <h3 id="enhancements-to-dplyr-and-datasets-7-0-0">Enhancements to dplyr and datasets<a class="anchor" aria-label="anchor" href="#enhancements-to-dplyr-and-datasets-7-0-0"></a></h3>
 <ul><li>Additional <a href="https://lubridate.tidyverse.org" class="external-link">lubridate</a> features: <code>week()</code>, more of the <code>is.*()</code> functions, and the label argument to <code>month()</code> have been implemented.</li>
-<li>More complex expressions inside <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code>, such as <code>ifelse(n() &gt; 1, mean(y), mean(z))</code>, are supported.</li>
+<li>More complex expressions inside <code>summarize()</code>, such as <code>ifelse(n() &gt; 1, mean(y), mean(z))</code>, are supported.</li>
 <li>When adding columns in a dplyr pipeline, one can now use <code>tibble</code> and <code>data.frame</code> to create columns of tibbles or data.frames respectively (e.g. <code>... %&gt;% mutate(df_col = tibble(a, b)) %&gt;% ...</code>).</li>
-<li>Dictionary columns (R <code>factor</code> type) are supported inside of <code><a href="https://dplyr.tidyverse.org/reference/coalesce.html" class="external-link">coalesce()</a></code>.</li>
+<li>Dictionary columns (R <code>factor</code> type) are supported inside of <code>coalesce()</code>.</li>
 <li>
 <code><a href="../reference/open_dataset.html">open_dataset()</a></code> accepts the <code>partitioning</code> argument when reading Hive-style partitioned files, even though it is not required.</li>
 <li>The experimental <code><a href="../reference/map_batches.html">map_batches()</a></code> function for custom operations on dataset has been restored.</li>
@@ -766,7 +795,7 @@ <h3 id="csv-7-0-0">CSV<a class="anchor" aria-label="anchor" href="#csv-7-0-0"></
 <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code> no longer hangs on large CSV datasets.</li>
 <li>There is an improved error message when there is a conflict between a header in the file and schema/column names provided as arguments.</li>
 <li>
-<code><a href="../reference/write_csv_arrow.html">write_csv_arrow()</a></code> now follows the signature of <code>readr::write_csv()</code>.</li>
+<code><a href="../reference/write_csv_arrow.html">write_csv_arrow()</a></code> now follows the signature of <code><a href="https://readr.tidyverse.org/reference/write_delim.html" class="external-link">readr::write_csv()</a></code>.</li>
 </ul></div>
 <div class="section level3">
 <h3 id="other-improvements-and-fixes-7-0-0">Other improvements and fixes<a class="anchor" aria-label="anchor" href="#other-improvements-and-fixes-7-0-0"></a></h3>
@@ -813,10 +842,10 @@ <h2 class="pkg-version" data-toc-text="6.0.0" id="arrow-600">arrow 6.0.0<a class
 <p>There are now two ways to query Arrow data:</p>
 <div class="section level3">
 <h3 id="id_1-expanded-arrow-native-queries-aggregation-and-joins-6-0-0">1. Expanded Arrow-native queries: aggregation and joins<a class="anchor" aria-label="anchor" href="#id_1-expanded-arrow-native-queries-aggregation-and-joins-6-0-0"></a></h3>
-<p><code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarize()</a></code>, both grouped and ungrouped, is now implemented for Arrow Datasets, Tables, and RecordBatches. Because data is scanned in chunks, you can aggregate over larger-than-memory datasets backed by many files. Supported aggregation functions include <code><a href="https://dplyr.tidyverse.org/reference/context.html" class="external-link">n()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct()</a></code>, <code>min(),</code> <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum()</a></code>, <code><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean()</a></code>, <code><a href="https://rdrr.io/r/stats/cor.html" class="external-link">var()</a></code>, <code><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd()</a></code>, <code><a href="https://rdrr.io/r/base/any.html" class="external-link">any()</a></code>, and <code><a href="https://rdrr.io/r/base/all.html" class="external-link">all()</a></code>. <code><a href="https://rdrr.io/r/stats/median.html" class="external-link">median()</a></code> and <code><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile()</a></code> with one probability are also supported and currently return approximate results using the t-digest algorithm.</p>
-<p>Along with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code>, you can also call <code><a href="https://dplyr.tidyverse.org/reference/count.html" class="external-link">count()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/count.html" class="external-link">tally()</a></code>, and <code><a href="https://dplyr.tidyverse.org/reference/distinct.html" class="external-link">distinct()</a></code>, which effectively wrap <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code>.</p>
-<p>This enhancement does change the behavior of <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/compute.html" class="external-link">collect()</a></code> in some cases: see “Breaking changes” below for details.</p>
-<p>In addition to <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code>, mutating and filtering equality joins (<code><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">inner_join()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">left_join()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">right_join()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">full_join()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/filter-joins.html" class="external-link">semi_join()</a></code>, and <code><a href="https://dplyr.tidyverse.org/reference/filter-joins.html" class="external-link">anti_join()</a></code>) with are also supported natively in Arrow.</p>
+<p><code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarize()</a></code>, both grouped and ungrouped, is now implemented for Arrow Datasets, Tables, and RecordBatches. Because data is scanned in chunks, you can aggregate over larger-than-memory datasets backed by many files. Supported aggregation functions include <code>n()</code>, <code>n_distinct()</code>, <code>min(),</code> <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum()</a></code>, <code><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean()</a></code>, <code><a href="https://rdrr.io/r/stats/cor.html" class="external-link">var()</a></code>, <code><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd()</a></code>, <code><a href="https://rdrr.io/r/base/any.html" class="external-link">any()</a></code>, and <code><a href="https://rdrr.io/r/base/all.html" class="external-link">all()</a></code>. <code><a href="https://rdrr.io/r/stats/median.html" class="external-link">median()</a></code> and <code><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile()</a></code> with one probability are also supported and currently return approximate results using the t-digest algorithm.</p>
+<p>Along with <code>summarize()</code>, you can also call <code>count()</code>, <code>tally()</code>, and <code>distinct()</code>, which effectively wrap <code>summarize()</code>.</p>
+<p>This enhancement does change the behavior of <code>summarize()</code> and <code>collect()</code> in some cases: see “Breaking changes” below for details.</p>
+<p>In addition to <code>summarize()</code>, mutating and filtering equality joins (<code>inner_join()</code>, <code>left_join()</code>, <code>right_join()</code>, <code>full_join()</code>, <code>semi_join()</code>, and <code>anti_join()</code>) with are also supported natively in Arrow.</p>
 <p>Grouped aggregation and (especially) joins should be considered somewhat experimental in this release. We expect them to work, but they may not be well optimized for all workloads. To help us focus our efforts on improving them in the next release, please let us know if you encounter unexpected behavior or poor performance.</p>
 <p>New non-aggregating compute functions include string functions like <code>str_to_title()</code> and <code><a href="https://rdrr.io/r/base/strptime.html" class="external-link">strftime()</a></code> as well as compute functions for extracting date parts (e.g. <code>year()</code>, <code>month()</code>) from dates. This is not a complete list of additional compute functions; for an exhaustive list of available compute functions see <code><a href="../reference/list_compute_functions.html">list_compute_functions()</a></code>.</p>
 <p>We’ve also worked to fill in support for all data types, such as <code>Decimal</code>, for functions added in previous releases. All type limitations mentioned in previous release notes should be no longer valid, and if you find a function that is not implemented for a certain data type, please <a href="https://issues.apache.org/jira/projects/ARROW/issues" class="external-link">report an issue</a>.</p>
@@ -828,11 +857,11 @@ <h3 id="id_2-duckdb-integration-6-0-0">2. DuckDB integration<a class="anchor" ar
 </div>
 <div class="section level3">
 <h3 id="breaking-changes-6-0-0">Breaking changes<a class="anchor" aria-label="anchor" href="#breaking-changes-6-0-0"></a></h3>
-<ul><li>Row order of data from a Dataset query is no longer deterministic. If you need a stable sort order, you should explicitly <code><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange()</a></code> the query result. For calls to <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarize()</a></code>, you can set <code>options(arrow.summarise.sort = TRUE)</code> to match the current <code>dplyr</code> behavior of sorting on the grouping columns.</li>
+<ul><li>Row order of data from a Dataset query is no longer deterministic. If you need a stable sort order, you should explicitly <code>arrange()</code> the query result. For calls to <code>summarize()</code>, you can set <code>options(arrow.summarise.sort = TRUE)</code> to match the current <code>dplyr</code> behavior of sorting on the grouping columns.</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarize()</a></code> on an in-memory Arrow Table or RecordBatch no longer eagerly evaluates. Call <code><a href="https://dplyr.tidyverse.org/reference/compute.html" class="external-link">compute()</a></code> or <code><a href="https://dplyr.tidyverse.org/reference/compute.html" class="external-link">collect()</a></code> to evaluate the query.</li>
+<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarize()</a></code> on an in-memory Arrow Table or RecordBatch no longer eagerly evaluates. Call <code>compute()</code> or <code>collect()</code> to evaluate the query.</li>
 <li>
-<code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code> and <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">tail()</a></code> also no longer eagerly evaluate, both for in-memory data and for Datasets. Also, because row order is no longer deterministic, they will effectively give you a random slice of data from somewhere in the dataset unless you <code><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange()</a></code> to specify sorting.</li>
+<code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code> and <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">tail()</a></code> also no longer eagerly evaluate, both for in-memory data and for Datasets. Also, because row order is no longer deterministic, they will effectively give you a random slice of data from somewhere in the dataset unless you <code>arrange()</code> to specify sorting.</li>
 <li>Simple Feature (SF) columns no longer save all of their metadata when converting to Arrow tables (and thus when saving to Parquet or Feather). This also includes any dataframe column that has attributes on each element (in other words: row-level metadata). Our previous approach to saving this metadata is both (computationally) inefficient and unreliable with Arrow queries + datasets. This will most impact saving SF columns. For saving these columns we recommend either converting the columns to well-known binary representations (using <code>sf::st_as_binary(col)</code>) or using the <a href="https://CRAN.R-project.org/package=sfarrow" class="external-link">sfarrow package</a> which handles some of the intricacies of this conversion process. We have plans to improve this and re-enable custom metadata like this in the future when we can implement the saving in a safe and efficient way. If you need to preserve the pre-6.0.0 behavior of saving this metadata, you can set <code>options(arrow.preserve_row_level_metadata = TRUE)</code>. We will be removing this option in a coming release. We strongly recommend avoiding using this workaround if possible since the results will not be supported in the future and can lead to surprising and inaccurate results. If you run into a custom class besides sf columns that are impacted by this please <a href="https://issues.apache.org/jira/projects/ARROW/issues" class="external-link">report an issue</a>.</li>
 <li>Datasets are officially no longer supported on 32-bit Windows on R &lt; 4.0 (Rtools 3.5). 32-bit Windows users should upgrade to a newer version of R in order to use datasets.</li>
 </ul></div>
@@ -854,7 +883,7 @@ <h3 id="other-enhancements-and-fixes-6-0-0">Other enhancements and fixes<a class
 <li>
 <code><a href="../reference/write_parquet.html">write_parquet()</a></code> no longer errors when used with a grouped data.frame</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/case-and-replace-when.html" class="external-link">case_when()</a></code> now errors cleanly if an expression is not supported in Arrow</li>
+<code>case_when()</code> now errors cleanly if an expression is not supported in Arrow</li>
 <li>
 <code><a href="../reference/open_dataset.html">open_dataset()</a></code> now works on CSVs without header rows</li>
 <li>Fixed a minor issue where the short readr-style types <code>T</code> and <code>t</code> were reversed in <code><a href="../reference/read_delim_arrow.html">read_csv_arrow()</a></code>
@@ -882,19 +911,19 @@ <h2 class="pkg-version" data-toc-text="5.0.0" id="arrow-500">arrow 5.0.0<a class
 <div class="section level3">
 <h3 id="more-dplyr-5-0-0">More dplyr<a class="anchor" aria-label="anchor" href="#more-dplyr-5-0-0"></a></h3>
 <ul><li>
-<p>There are now more than 250 compute functions available for use in <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">dplyr::filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code>, etc. Additions in this release include:</p>
+<p>There are now more than 250 compute functions available for use in <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">dplyr::filter()</a></code>, <code>mutate()</code>, etc. Additions in this release include:</p>
 <ul><li>String operations: <code><a href="https://rdrr.io/r/base/strsplit.html" class="external-link">strsplit()</a></code> and <code>str_split()</code>; <code><a href="https://rdrr.io/r/base/strptime.html" class="external-link">strptime()</a></code>; <code><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste()</a></code>, <code><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0()</a></code>, and <code>str_c()</code>; <code><a href="https://rdrr.io/r/base/substr.html" class="external-link">substr()</a></code> and <code>str_sub()</code>; <code>str_like()</code>; <code>str_pad()</code>; <code>stri_reverse()</code>
 </li>
 <li>Date/time operations: <code>lubridate</code> methods such as <code>year()</code>, <code>month()</code>, <code>wday()</code>, and so on</li>
 <li>Math: logarithms (<code><a href="https://rdrr.io/r/base/Log.html" class="external-link">log()</a></code> et al.); trigonometry (<code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">sin()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">cos()</a></code>, et al.); <code><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs()</a></code>; <code><a href="https://rdrr.io/r/base/sign.html" class="external-link">sign()</a></code>; <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">pmin()</a></code> and <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">pmax()</a></code>; <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling()</a></code>, <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor()</a></code>, and <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">trunc()</a></code>
 </li>
-<li>Conditional functions, with some limitations on input type in this release: <code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/if_else.html" class="external-link">if_else()</a></code> for all but <code>Decimal</code> types; <code><a href="https://dplyr.tidyverse.org/reference/case-and-replace-when.html" class="external-link">case_when()</a></code> for logical, numeric, and temporal types only; <code><a href="https://dplyr.tidyverse.org/reference/coalesce.html" class="external-link">coalesce()</a></code> for all but lists/structs. Note also that in this release, factors/dictionaries are converted to strings in these functions.</li>
+<li>Conditional functions, with some limitations on input type in this release: <code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> and <code>if_else()</code> for all but <code>Decimal</code> types; <code>case_when()</code> for logical, numeric, and temporal types only; <code>coalesce()</code> for all but lists/structs. Note also that in this release, factors/dictionaries are converted to strings in these functions.</li>
 <li>
-<code>is.*</code> functions are supported and can be used inside <code><a href="https://dplyr.tidyverse.org/reference/relocate.html" class="external-link">relocate()</a></code>
+<code>is.*</code> functions are supported and can be used inside <code>relocate()</code>
 </li>
 </ul></li>
-<li><p>The print method for <code>arrow_dplyr_query</code> now includes the expression and the resulting type of columns derived by <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code>.</p></li>
-<li><p><code><a href="https://dplyr.tidyverse.org/reference/transmute.html" class="external-link">transmute()</a></code> now errors if passed arguments <code>.keep</code>, <code>.before</code>, or <code>.after</code>, for consistency with the behavior of <code>dplyr</code> on <code>data.frame</code>s.</p></li>
+<li><p>The print method for <code>arrow_dplyr_query</code> now includes the expression and the resulting type of columns derived by <code>mutate()</code>.</p></li>
+<li><p><code>transmute()</code> now errors if passed arguments <code>.keep</code>, <code>.before</code>, or <code>.after</code>, for consistency with the behavior of <code>dplyr</code> on <code>data.frame</code>s.</p></li>
 </ul></div>
 <div class="section level3">
 <h3 id="csv-writing-5-0-0">CSV writing<a class="anchor" aria-label="anchor" href="#csv-writing-5-0-0"></a></h3>
@@ -905,8 +934,8 @@ <h3 id="csv-writing-5-0-0">CSV writing<a class="anchor" aria-label="anchor" href
 </ul></div>
 <div class="section level3">
 <h3 id="c-interface-5-0-0">C interface<a class="anchor" aria-label="anchor" href="#c-interface-5-0-0"></a></h3>
-<ul><li>Added bindings for the remainder of C data interface: Type, Field, and RecordBatchReader (from the experimental C stream interface). These also have <code><a href="https://rstudio.github.io/reticulate/reference/r-py-conversion.html" class="external-link">reticulate::py_to_r()</a></code> and <code><a href="https://rstudio.github.io/reticulate/reference/r-py-conversion.html" class="external-link">r_to_py()</a></code> methods. Along with the addition of the <code>Scanner$ToRecordBatchReader()</code> method, you can now build up a Dataset query in R and pass the resulting stream of batches to another tool in process.</li>
-<li>C interface methods are exposed on Arrow objects (e.g. <code>Array$export_to_c()</code>, <code>RecordBatch$import_from_c()</code>), similar to how they are in <code>pyarrow</code>. This facilitates their use in other packages. See the <code><a href="https://rstudio.github.io/reticulate/reference/r-py-conversion.html" class="external-link">py_to_r()</a></code> and <code><a href="https://rstudio.github.io/reticulate/reference/r-py-conversion.html" class="external-link">r_to_py()</a></code> methods for usage examples.</li>
+<ul><li>Added bindings for the remainder of C data interface: Type, Field, and RecordBatchReader (from the experimental C stream interface). These also have <code><a href="https://rstudio.github.io/reticulate/reference/r-py-conversion.html" class="external-link">reticulate::py_to_r()</a></code> and <code>r_to_py()</code> methods. Along with the addition of the <code>Scanner$ToRecordBatchReader()</code> method, you can now build up a Dataset query in R and pass the resulting stream of batches to another tool in process.</li>
+<li>C interface methods are exposed on Arrow objects (e.g. <code>Array$export_to_c()</code>, <code>RecordBatch$import_from_c()</code>), similar to how they are in <code>pyarrow</code>. This facilitates their use in other packages. See the <code>py_to_r()</code> and <code>r_to_py()</code> methods for usage examples.</li>
 </ul></div>
 <div class="section level3">
 <h3 id="other-enhancements-5-0-0">Other enhancements<a class="anchor" aria-label="anchor" href="#other-enhancements-5-0-0"></a></h3>
@@ -943,9 +972,9 @@ <h2 class="pkg-version" data-toc-text="4.0.0" id="arrow-400">arrow 4.0.0<a class
 <h3 id="dplyr-methods-4-0-0">dplyr methods<a class="anchor" aria-label="anchor" href="#dplyr-methods-4-0-0"></a></h3>
 <p>Many more <code>dplyr</code> verbs are supported on Arrow objects:</p>
 <ul><li>
-<code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">dplyr::mutate()</a></code> is now supported in Arrow for many applications. For queries on <code>Table</code> and <code>RecordBatch</code> that are not yet supported in Arrow, the implementation falls back to pulling data into an in-memory R <code>data.frame</code> first, as in the previous release. For queries on <code>Dataset</code> (which can be larger than memory), it raises an error if the function is not implemented. The main <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> features that cannot yet be called on Arrow objects are (1) <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> after <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> (which is typically used in combination with aggregation) and (2) queries that use <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">dplyr::across()</a></code>.</li>
+<code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">dplyr::mutate()</a></code> is now supported in Arrow for many applications. For queries on <code>Table</code> and <code>RecordBatch</code> that are not yet supported in Arrow, the implementation falls back to pulling data into an in-memory R <code>data.frame</code> first, as in the previous release. For queries on <code>Dataset</code> (which can be larger than memory), it raises an error if the function is not implemented. The main <code>mutate()</code> features that cannot yet be called on Arrow objects are (1) <code>mutate()</code> after <code>group_by()</code> (which is typically used in combination with aggregation) and (2) queries that use <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">dplyr::across()</a></code>.</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/transmute.html" class="external-link">dplyr::transmute()</a></code> (which calls <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code>)</li>
+<code><a href="https://dplyr.tidyverse.org/reference/transmute.html" class="external-link">dplyr::transmute()</a></code> (which calls <code>mutate()</code>)</li>
 <li>
 <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">dplyr::group_by()</a></code> now preserves the <code>.drop</code> argument and supports on-the-fly definition of columns</li>
 <li>
@@ -1065,7 +1094,7 @@ <h3 id="datasets-2-0-0">Datasets<a class="anchor" aria-label="anchor" href="#dat
 <code><a href="../reference/write_dataset.html">write_dataset()</a></code> to Feather or Parquet files with partitioning. See the end of <code><a href="../articles/dataset.html">vignette("dataset", package = "arrow")</a></code> for discussion and examples.</li>
 <li>Datasets now have <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code>, <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">tail()</a></code>, and take (<code>[</code>) methods. <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code> is optimized but the others may not be performant.</li>
 <li>
-<code><a href="https://dplyr.tidyverse.org/reference/compute.html" class="external-link">collect()</a></code> gains an <code>as_data_frame</code> argument, default <code>TRUE</code> but when <code>FALSE</code> allows you to evaluate the accumulated <code>select</code> and <code>filter</code> query but keep the result in Arrow, not an R <code>data.frame</code>
+<code>collect()</code> gains an <code>as_data_frame</code> argument, default <code>TRUE</code> but when <code>FALSE</code> allows you to evaluate the accumulated <code>select</code> and <code>filter</code> query but keep the result in Arrow, not an R <code>data.frame</code>
 </li>
 <li>
 <code><a href="../reference/read_delim_arrow.html">read_csv_arrow()</a></code> supports specifying column types, both with a <code>Schema</code> and with the compact string representation for types used in the <code>readr</code> package. It also has gained a <code>timestamp_parsers</code> argument that lets you express a set of <code>strptime</code> parse strings that will be tried to convert columns designated as <code>Timestamp</code> type.</li>
@@ -1132,7 +1161,7 @@ <h3 id="arrow-format-conversion-1-0-0">Arrow format conversion<a class="anchor"
 <code>character</code> vectors that exceed 2GB are converted to Arrow <code>large_utf8</code> type</li>
 <li>
 <code>POSIXlt</code> objects can now be converted to Arrow (<code>struct</code>)</li>
-<li>R <code><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes()</a></code> are preserved in Arrow metadata when converting to Arrow RecordBatch and table and are restored when converting from Arrow. This means that custom subclasses, such as <code>haven::labelled</code>, are preserved in round trip through Arrow.</li>
+<li>R <code><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes()</a></code> are preserved in Arrow metadata when converting to Arrow RecordBatch and table and are restored when converting from Arrow. This means that custom subclasses, such as <code><a href="https://haven.tidyverse.org/reference/labelled.html" class="external-link">haven::labelled</a></code>, are preserved in round trip through Arrow.</li>
 <li>Schema metadata is now exposed as a named list, and it can be modified by assignment like <code>batch$metadata$new_key &lt;- "new value"</code>
 </li>
 <li>Arrow types <code>int64</code>, <code>uint32</code>, and <code>uint64</code> now are converted to R <code>integer</code> if all values fit in bounds</li>
@@ -1236,7 +1265,7 @@ <h2 class="pkg-version" data-toc-text="0.16.0.2" id="arrow-01602">arrow 0.16.0.2
 <h2 class="pkg-version" data-toc-text="0.16.0" id="arrow-0160">arrow 0.16.0<a class="anchor" aria-label="anchor" href="#arrow-0160"></a></h2><p class="text-muted">CRAN release: 2020-02-09</p>
 <div class="section level3">
 <h3 id="multi-file-datasets-0-16-0">Multi-file datasets<a class="anchor" aria-label="anchor" href="#multi-file-datasets-0-16-0"></a></h3>
-<p>This release includes a <code>dplyr</code> interface to Arrow Datasets, which let you work efficiently with large, multi-file datasets as a single entity. Explore a directory of data files with <code><a href="../reference/open_dataset.html">open_dataset()</a></code> and then use <code>dplyr</code> methods to <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code>, etc. Work will be done where possible in Arrow memory. When necessary, data is pulled into R for further computation. <code>dplyr</code> methods are conditionally loaded if you have <code>dplyr</code> available; it is not a hard dependency.</p>
+<p>This release includes a <code>dplyr</code> interface to Arrow Datasets, which let you work efficiently with large, multi-file datasets as a single entity. Explore a directory of data files with <code><a href="../reference/open_dataset.html">open_dataset()</a></code> and then use <code>dplyr</code> methods to <code>select()</code>, <code><a href="https://rdrr.io/r/stats/filter.html" class="external-link">filter()</a></code>, etc. Work will be done where possible in Arrow memory. When necessary, data is pulled into R for further computation. <code>dplyr</code> methods are conditionally loaded if you have <code>dplyr</code> available; it is not a hard dependency.</p>
 <p>See <code><a href="../articles/dataset.html">vignette("dataset", package = "arrow")</a></code> for details.</p>
 </div>
 <div class="section level3">
