This is an automated email from the ASF dual-hosted git repository.
github-bot pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/arrow-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new c47f4a96c67 Updating dev docs (build )
c47f4a96c67 is described below
commit c47f4a96c6747fe7ad4da15475643e07e2546c10
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Mon Jan 26 00:41:06 2026 +0000
Updating dev docs (build )
---
...id-8ff51316a5bfe716c8346df112ea33beaa5228f4.svg | 2 +-
docs/dev/python/data.html | 46 +++----
docs/dev/python/dataset.html | 136 ++++++++++-----------
docs/dev/python/getstarted.html | 2 +-
docs/dev/python/memory.html | 8 +-
docs/dev/python/pandas.html | 6 +-
docs/dev/python/parquet.html | 12 +-
docs/dev/r/articles/data_wrangling.html | 24 ++--
docs/dev/r/articles/data_wrangling.md | 24 ++--
docs/dev/r/pkgdown.yml | 2 +-
docs/dev/r/reference/to_arrow.html | 6 +-
docs/dev/r/reference/to_arrow.md | 6 +-
docs/dev/r/search.json | 2 +-
docs/dev/searchindex.js | 2 +-
14 files changed, 139 insertions(+), 139 deletions(-)
diff --git
a/docs/dev/_images/mermaid-8ff51316a5bfe716c8346df112ea33beaa5228f4.svg
b/docs/dev/_images/mermaid-8ff51316a5bfe716c8346df112ea33beaa5228f4.svg
index 2116cde91aa..d4339fb23e3 100644
--- a/docs/dev/_images/mermaid-8ff51316a5bfe716c8346df112ea33beaa5228f4.svg
+++ b/docs/dev/_images/mermaid-8ff51316a5bfe716c8346df112ea33beaa5228f4.svg
@@ -1 +1 @@
-<svg id="my-svg" width="100%" xmlns="http://www.w3.org/2000/svg";
xmlns:xlink="http://www.w3.org/1999/xlink"; class="flowchart" style="max-width:
1645.73px; background-color: white;" viewBox="0 0 1645.734375 786.1171875"
role="graphics-document document"
aria-roledescription="flowchart-v2"><style>#my-svg{font-family:"trebuchet
ms",verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes
edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes
dash{to{stroke-dashoffset:0;}}#my-svg .e [...]
\ No newline at end of file
+<svg id="my-svg" width="100%" xmlns="http://www.w3.org/2000/svg";
xmlns:xlink="http://www.w3.org/1999/xlink"; class="flowchart" style="max-width:
1645.73px; background-color: white;" viewBox="0 0 1645.734375 786.1171875"
role="graphics-document document"
aria-roledescription="flowchart-v2"><style>#my-svg{font-family:"trebuchet
ms",verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes
edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes
dash{to{stroke-dashoffset:0;}}#my-svg .e [...]
\ No newline at end of file
diff --git a/docs/dev/python/data.html b/docs/dev/python/data.html
index 063f591739d..dad5ad637f8 100644
--- a/docs/dev/python/data.html
+++ b/docs/dev/python/data.html
@@ -1719,7 +1719,7 @@ for you:</p>
<span class="gp">In [29]: </span><span class="n">arr</span>
<span class="gh">Out[29]: </span>
-<span class="go"><pyarrow.lib.Int64Array object at 0x7fad07701360></span>
+<span class="go"><pyarrow.lib.Int64Array object at 0x7f2f8d809240></span>
<span class="go">[</span>
<span class="go"> 1,</span>
<span class="go"> 2,</span>
@@ -1731,7 +1731,7 @@ for you:</p>
<p>But you may also pass a specific data type to override type inference:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [30]: </span><span
class="n">pa</span><span class="o">.</span><span class="n">array</span><span
class="p">([</span><span class="mi">1</span><span class="p">,</span> <span
class="mi">2</span><span class="p">],</span> <span class="nb">type</span><span
class="o">=</span><span class="n">pa</span><span class="o">.</span><span
class="n">uint16</span><span class="p">())</span>
<span class="gh">Out[30]: </span>
-<span class="go"><pyarrow.lib.UInt16Array object at
0x7fad077018a0></span>
+<span class="go"><pyarrow.lib.UInt16Array object at
0x7f2f8d809720></span>
<span class="go">[</span>
<span class="go"> 1,</span>
<span class="go"> 2</span>
@@ -1766,7 +1766,7 @@ nulls:</p>
<p>Arrays can be sliced without copying:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [36]: </span><span
class="n">arr</span><span class="p">[</span><span class="mi">1</span><span
class="p">:</span><span class="mi">3</span><span class="p">]</span>
<span class="gh">Out[36]: </span>
-<span class="go"><pyarrow.lib.Int64Array object at 0x7fad077025c0></span>
+<span class="go"><pyarrow.lib.Int64Array object at 0x7f2f8d80a4a0></span>
<span class="go">[</span>
<span class="go"> 2,</span>
<span class="go"> null</span>
@@ -1819,7 +1819,7 @@ This allows for ListView arrays to specify out-of-order
offsets:</p>
<span class="gp">In [45]: </span><span class="n">arr</span>
<span class="gh">Out[45]: </span>
-<span class="go"><pyarrow.lib.ListViewArray object at
0x7fad077032e0></span>
+<span class="go"><pyarrow.lib.ListViewArray object at
0x7f2f8d80af20></span>
<span class="go">[</span>
<span class="go"> [</span>
<span class="go"> 5,</span>
@@ -1844,7 +1844,7 @@ This allows for ListView arrays to specify out-of-order
offsets:</p>
dictionaries:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [46]: </span><span
class="n">pa</span><span class="o">.</span><span class="n">array</span><span
class="p">([{</span><span class="s1">'x'</span><span class="p">:</span>
<span class="mi">1</span><span class="p">,</span> <span
class="s1">'y'</span><span class="p">:</span> <span
class="kc">True</span><span class="p">},</span> <span class="p">{</span><span
class="s1">'z& [...]
<span class="gh">Out[46]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7fad077035e0></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f8d80b4c0></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- child 0 type: int64</span>
<span class="go"> [</span>
@@ -1871,7 +1871,7 @@ you must explicitly pass the type:</p>
<span class="gp">In [48]: </span><span class="n">pa</span><span
class="o">.</span><span class="n">array</span><span class="p">([{</span><span
class="s1">'x'</span><span class="p">:</span> <span
class="mi">1</span><span class="p">,</span> <span
class="s1">'y'</span><span class="p">:</span> <span
class="kc">True</span><span class="p">},</span> <span class="p">{</span><span
class="s1">'x'</span><span class="p">:</span> <span
class="mi">2</span><span class="p">,</span [...]
<span class="gh">Out[48]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7fad07703b80></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f8d80bb20></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- child 0 type: int8</span>
<span class="go"> [</span>
@@ -1886,7 +1886,7 @@ you must explicitly pass the type:</p>
<span class="gp">In [49]: </span><span class="n">pa</span><span
class="o">.</span><span class="n">array</span><span class="p">([(</span><span
class="mi">3</span><span class="p">,</span> <span class="kc">True</span><span
class="p">),</span> <span class="p">(</span><span class="mi">4</span><span
class="p">,</span> <span class="kc">False</span><span class="p">)],</span>
<span class="nb">type</span><span class="o">=</span><span
class="n">ty</span><span class="p">)</span>
<span class="gh">Out[49]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7fad07703d00></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f8d80bca0></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- child 0 type: int8</span>
<span class="go"> [</span>
@@ -1905,7 +1905,7 @@ level and at the individual field level. If initializing
from a sequence
of Python dicts, a missing dict key is handled as a null value:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [50]: </span><span
class="n">pa</span><span class="o">.</span><span class="n">array</span><span
class="p">([{</span><span class="s1">'x'</span><span class="p">:</span>
<span class="mi">1</span><span class="p">},</span> <span
class="kc">None</span><span class="p">,</span> <span class="p">{</span><span
class="s1">'y'</span><span class="p">:</span> <span class="kc">None</s
[...]
<span class="gh">Out[50]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7fad07703d60></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f8d80bac0></span>
<span class="go">-- is_valid:</span>
<span class="go"> [</span>
<span class="go"> true,</span>
@@ -1940,7 +1940,7 @@ individual arrays, and no copy is involved:</p>
<span class="gp">In [55]: </span><span class="n">arr</span>
<span class="gh">Out[55]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7fad077506a0></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f8d858640></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- child 0 type: int16</span>
<span class="go"> [</span>
@@ -1967,7 +1967,7 @@ the type is explicitly passed into <a class="reference
internal" href="generated
<span class="gp">In [58]: </span><span class="n">pa</span><span
class="o">.</span><span class="n">array</span><span class="p">(</span><span
class="n">data</span><span class="p">,</span> <span class="nb">type</span><span
class="o">=</span><span class="n">ty</span><span class="p">)</span>
<span class="gh">Out[58]: </span>
-<span class="go"><pyarrow.lib.MapArray object at 0x7fad07750a00></span>
+<span class="go"><pyarrow.lib.MapArray object at 0x7f2f8d8589a0></span>
<span class="go">[</span>
<span class="go"> keys:</span>
<span class="go"> [</span>
@@ -2001,7 +2001,7 @@ their row, use the <a class="reference internal"
href="generated/pyarrow.ListArr
<span class="gp">In [60]: </span><span class="n">arr</span><span
class="o">.</span><span class="n">keys</span>
<span class="gh">Out[60]: </span>
-<span class="go"><pyarrow.lib.StringArray object at
0x7fad07750ca0></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f2f8d858ca0></span>
<span class="go">[</span>
<span class="go"> "x",</span>
<span class="go"> "y",</span>
@@ -2010,7 +2010,7 @@ their row, use the <a class="reference internal"
href="generated/pyarrow.ListArr
<span class="gp">In [61]: </span><span class="n">arr</span><span
class="o">.</span><span class="n">items</span>
<span class="gh">Out[61]: </span>
-<span class="go"><pyarrow.lib.Int64Array object at 0x7fad07750be0></span>
+<span class="go"><pyarrow.lib.Int64Array object at 0x7f2f8d858ac0></span>
<span class="go">[</span>
<span class="go"> 4,</span>
<span class="go"> 5,</span>
@@ -2019,7 +2019,7 @@ their row, use the <a class="reference internal"
href="generated/pyarrow.ListArr
<span class="gp">In [62]: </span><span class="n">pa</span><span
class="o">.</span><span class="n">ListArray</span><span class="o">.</span><span
class="n">from_arrays</span><span class="p">(</span><span
class="n">arr</span><span class="o">.</span><span class="n">offsets</span><span
class="p">,</span> <span class="n">arr</span><span class="o">.</span><span
class="n">keys</span><span class="p">)</span>
<span class="gh">Out[62]: </span>
-<span class="go"><pyarrow.lib.ListArray object at 0x7fad07751060></span>
+<span class="go"><pyarrow.lib.ListArray object at 0x7f2f8d859060></span>
<span class="go">[</span>
<span class="go"> [</span>
<span class="go"> "x",</span>
@@ -2032,7 +2032,7 @@ their row, use the <a class="reference internal"
href="generated/pyarrow.ListArr
<span class="gp">In [63]: </span><span class="n">pa</span><span
class="o">.</span><span class="n">ListArray</span><span class="o">.</span><span
class="n">from_arrays</span><span class="p">(</span><span
class="n">arr</span><span class="o">.</span><span class="n">offsets</span><span
class="p">,</span> <span class="n">arr</span><span class="o">.</span><span
class="n">items</span><span class="p">)</span>
<span class="gh">Out[63]: </span>
-<span class="go"><pyarrow.lib.ListArray object at 0x7fad07751000></span>
+<span class="go"><pyarrow.lib.ListArray object at 0x7f2f8d859000></span>
<span class="go">[</span>
<span class="go"> [</span>
<span class="go"> 4,</span>
@@ -2067,7 +2067,7 @@ selected:</p>
<span class="gp">In [69]: </span><span class="n">union_arr</span>
<span class="gh">Out[69]: </span>
-<span class="go"><pyarrow.lib.UnionArray object at 0x7fad07751720></span>
+<span class="go"><pyarrow.lib.UnionArray object at 0x7f2f8d859720></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- type_ids: [</span>
<span class="go"> 0,</span>
@@ -2106,7 +2106,7 @@ each offset in the selected child array it can be
found:</p>
<span class="gp">In [76]: </span><span class="n">union_arr</span>
<span class="gh">Out[76]: </span>
-<span class="go"><pyarrow.lib.UnionArray object at 0x7fad07701c60></span>
+<span class="go"><pyarrow.lib.UnionArray object at 0x7f2f8d859cc0></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- type_ids: [</span>
<span class="go"> 0,</span>
@@ -2155,7 +2155,7 @@ consider an example:</p>
<span class="gp">In [80]: </span><span class="n">dict_array</span>
<span class="gh">Out[80]: </span>
-<span class="go"><pyarrow.lib.DictionaryArray object at
0x7fad07727220></span>
+<span class="go"><pyarrow.lib.DictionaryArray object at
0x7f2f8d833220></span>
<span class="go">-- dictionary:</span>
<span class="go"> [</span>
@@ -2182,7 +2182,7 @@ consider an example:</p>
<span class="gp">In [82]: </span><span class="n">dict_array</span><span
class="o">.</span><span class="n">indices</span>
<span class="gh">Out[82]: </span>
-<span class="go"><pyarrow.lib.Int64Array object at 0x7fad077522c0></span>
+<span class="go"><pyarrow.lib.Int64Array object at 0x7f2f8d85a6e0></span>
<span class="go">[</span>
<span class="go"> 0,</span>
<span class="go"> 1,</span>
@@ -2196,7 +2196,7 @@ consider an example:</p>
<span class="gp">In [83]: </span><span class="n">dict_array</span><span
class="o">.</span><span class="n">dictionary</span>
<span class="gh">Out[83]: </span>
-<span class="go"><pyarrow.lib.StringArray object at
0x7fad07752500></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f2f8d85a740></span>
<span class="go">[</span>
<span class="go"> "foo",</span>
<span class="go"> "bar",</span>
@@ -2252,7 +2252,7 @@ instances. Let’s consider a collection of arrays:</p>
<span class="gp">In [90]: </span><span class="n">batch</span><span
class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="gh">Out[90]: </span>
-<span class="go"><pyarrow.lib.StringArray object at
0x7fad07752fe0></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f2f8d85ad40></span>
<span class="go">[</span>
<span class="go"> "foo",</span>
<span class="go"> "bar",</span>
@@ -2266,7 +2266,7 @@ instances. Let’s consider a collection of arrays:</p>
<span class="gp">In [92]: </span><span class="n">batch2</span><span
class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="gh">Out[92]: </span>
-<span class="go"><pyarrow.lib.StringArray object at
0x7fad07752f20></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f2f8d85b400></span>
<span class="go">[</span>
<span class="go"> "bar",</span>
<span class="go"> "baz",</span>
@@ -2310,7 +2310,7 @@ container for one or more arrays of the same type.</p>
<span class="gp">In [98]: </span><span class="n">c</span>
<span class="gh">Out[98]: </span>
-<span class="go"><pyarrow.lib.ChunkedArray object at
0x7fad077534c0></span>
+<span class="go"><pyarrow.lib.ChunkedArray object at
0x7f2f8d8092a0></span>
<span class="go">[</span>
<span class="go"> [</span>
<span class="go"> 1,</span>
@@ -2344,7 +2344,7 @@ container for one or more arrays of the same type.</p>
<span class="gp">In [100]: </span><span class="n">c</span><span
class="o">.</span><span class="n">chunk</span><span class="p">(</span><span
class="mi">0</span><span class="p">)</span>
<span class="gh">Out[100]: </span>
-<span class="go"><pyarrow.lib.Int64Array object at 0x7fad07753b80></span>
+<span class="go"><pyarrow.lib.Int64Array object at 0x7f2f8d85b940></span>
<span class="go">[</span>
<span class="go"> 1,</span>
<span class="go"> 2,</span>
diff --git a/docs/dev/python/dataset.html b/docs/dev/python/dataset.html
index 918711cb60b..a539ed82275 100644
--- a/docs/dev/python/dataset.html
+++ b/docs/dev/python/dataset.html
@@ -1605,7 +1605,7 @@ can pass it the path to the directory containing the data
files:</p>
<span class="gp">In [12]: </span><span class="n">dataset</span> <span
class="o">=</span> <span class="n">ds</span><span class="o">.</span><span
class="n">dataset</span><span class="p">(</span><span class="n">base</span>
<span class="o">/</span> <span
class="s2">"parquet_dataset"</span><span class="p">,</span> <span
class="nb">format</span><span class="o">=</span><span
class="s2">"parquet"</span><span class="p">)</span>
<span class="gp">In [13]: </span><span class="n">dataset</span>
-<span class="gh">Out[13]: </span><span
class="go"><pyarrow._dataset.FileSystemDataset at 0x7fad077e1840></span>
+<span class="gh">Out[13]: </span><span
class="go"><pyarrow._dataset.FileSystemDataset at 0x7f2f8d8e9ae0></span>
</pre></div>
</div>
<p>In addition to searching a base directory, <a class="reference internal"
href="generated/pyarrow.dataset.dataset.html#pyarrow.dataset.dataset"
title="pyarrow.dataset.dataset"><code class="xref py py-func docutils literal
notranslate"><span class="pre">dataset()</span></code></a> accepts a path to a
@@ -1614,8 +1614,8 @@ single file or a list of file paths.</p>
needed, it only crawls the directory to find all the files:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [14]: </span><span
class="n">dataset</span><span class="o">.</span><span class="n">files</span>
<span class="gh">Out[14]: </span>
-<span
class="go">['/tmp/pyarrow-ykkfdkpp/parquet_dataset/data1.parquet',</span>
-<span class="go">
'/tmp/pyarrow-ykkfdkpp/parquet_dataset/data2.parquet']</span>
+<span
class="go">['/tmp/pyarrow-rnj8x4pg/parquet_dataset/data1.parquet',</span>
+<span class="go">
'/tmp/pyarrow-rnj8x4pg/parquet_dataset/data2.parquet']</span>
</pre></div>
</div>
<p>… and infers the dataset’s schema (by default from the first file):</p>
@@ -1636,23 +1636,23 @@ this can require a lot of memory, see below on
filtering / iterative loading):</
<span class="go">c: int64</span>
<span class="gt">----</span>
<span class="ne">a</span>: [[0,1,2,3,4],[5,6,7,8,9]]
-<span class="ne">b</span>:
[[-0.3844232144373551,-1.431199832889868,-2.7222924674479207,-1.15843502006728,2.5562432969049156],[1.1845791548338684,-1.9145909728065522,-0.0628499258975066,-0.13085975025056282,-1.1068435199461821]]
+<span class="ne">b</span>:
[[-1.0125565244987083,-1.1188067155189187,-0.09827986783140845,0.574867183751739,0.2443648653987485],[0.3460542786318528,-0.2477905494892927,-0.01351496102139165,-1.8143867924548172,0.23355192566689306]]
<span class="ne">c</span>: [[1,2,1,2,1],[2,1,2,1,2]]
<span class="c1"># converting to pandas to see the contents of the scanned
table</span>
<span class="gp">In [17]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">()</span><span
class="o">.</span><span class="n">to_pandas</span><span class="p">()</span>
<span class="gh">Out[17]: </span>
<span class="go"> a b c</span>
-<span class="go">0 0 -0.384423 1</span>
-<span class="go">1 1 -1.431200 2</span>
-<span class="go">2 2 -2.722292 1</span>
-<span class="go">3 3 -1.158435 2</span>
-<span class="go">4 4 2.556243 1</span>
-<span class="go">5 5 1.184579 2</span>
-<span class="go">6 6 -1.914591 1</span>
-<span class="go">7 7 -0.062850 2</span>
-<span class="go">8 8 -0.130860 1</span>
-<span class="go">9 9 -1.106844 2</span>
+<span class="go">0 0 -1.012557 1</span>
+<span class="go">1 1 -1.118807 2</span>
+<span class="go">2 2 -0.098280 1</span>
+<span class="go">3 3 0.574867 2</span>
+<span class="go">4 4 0.244365 1</span>
+<span class="go">5 5 0.346054 2</span>
+<span class="go">6 6 -0.247791 1</span>
+<span class="go">7 7 -0.013515 2</span>
+<span class="go">8 8 -1.814387 1</span>
+<span class="go">9 9 0.233552 2</span>
</pre></div>
</div>
</section>
@@ -1675,11 +1675,11 @@ supported; more formats are planned in the future.</p>
<span class="gp">In [21]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">()</span><span
class="o">.</span><span class="n">to_pandas</span><span
class="p">()</span><span class="o">.</span><span class="n">head</span><span
class="p">()</span>
<span class="gh">Out[21]: </span>
<span class="go"> a b c</span>
-<span class="go">0 0 -0.384423 1</span>
-<span class="go">1 1 -1.431200 2</span>
-<span class="go">2 2 -2.722292 1</span>
-<span class="go">3 3 -1.158435 2</span>
-<span class="go">4 4 2.556243 1</span>
+<span class="go">0 0 -1.012557 1</span>
+<span class="go">1 1 -1.118807 2</span>
+<span class="go">2 2 -0.098280 1</span>
+<span class="go">3 3 0.574867 2</span>
+<span class="go">4 4 0.244365 1</span>
</pre></div>
</div>
</section>
@@ -1711,16 +1711,16 @@ supported; more formats are planned in the future.</p>
<span class="gp">In [23]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">(</span><span
class="n">columns</span><span class="o">=</span><span class="p">[</span><span
class="s1">'a'</span><span class="p">,</span> <span
class="s1">'b'</span><span class="p">])</span><span
class="o">.</span><span class="n">to_pandas</span><span class="p">()</span>
<span class="gh">Out[23]: </span>
<span class="go"> a b</span>
-<span class="go">0 0 -0.384423</span>
-<span class="go">1 1 -1.431200</span>
-<span class="go">2 2 -2.722292</span>
-<span class="go">3 3 -1.158435</span>
-<span class="go">4 4 2.556243</span>
-<span class="go">5 5 1.184579</span>
-<span class="go">6 6 -1.914591</span>
-<span class="go">7 7 -0.062850</span>
-<span class="go">8 8 -0.130860</span>
-<span class="go">9 9 -1.106844</span>
+<span class="go">0 0 -1.012557</span>
+<span class="go">1 1 -1.118807</span>
+<span class="go">2 2 -0.098280</span>
+<span class="go">3 3 0.574867</span>
+<span class="go">4 4 0.244365</span>
+<span class="go">5 5 0.346054</span>
+<span class="go">6 6 -0.247791</span>
+<span class="go">7 7 -0.013515</span>
+<span class="go">8 8 -1.814387</span>
+<span class="go">9 9 0.233552</span>
</pre></div>
</div>
<p>With the <code class="docutils literal notranslate"><span
class="pre">filter</span></code> keyword, rows which do not match the filter
predicate will
@@ -1729,18 +1729,18 @@ not be included in the returned table. The keyword
expects a boolean
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [24]: </span><span
class="n">dataset</span><span class="o">.</span><span
class="n">to_table</span><span class="p">(</span><span
class="nb">filter</span><span class="o">=</span><span class="n">ds</span><span
class="o">.</span><span class="n">field</span><span class="p">(</span><span
class="s1">'a'</span><span class="p">)</span> <span
class="o">>=</span> <span class="mi">7</sp [...]
<span class="gh">Out[24]: </span>
<span class="go"> a b c</span>
-<span class="go">0 7 -0.062850 2</span>
-<span class="go">1 8 -0.130860 1</span>
-<span class="go">2 9 -1.106844 2</span>
+<span class="go">0 7 -0.013515 2</span>
+<span class="go">1 8 -1.814387 1</span>
+<span class="go">2 9 0.233552 2</span>
<span class="gp">In [25]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">(</span><span
class="nb">filter</span><span class="o">=</span><span class="n">ds</span><span
class="o">.</span><span class="n">field</span><span class="p">(</span><span
class="s1">'c'</span><span class="p">)</span> <span class="o">==</span>
<span class="mi">2</span><span class="p">)</span><span class="o">.</span><span
class="n">to_pandas</span><spa [...]
<span class="gh">Out[25]: </span>
<span class="go"> a b c</span>
-<span class="go">0 1 -1.431200 2</span>
-<span class="go">1 3 -1.158435 2</span>
-<span class="go">2 5 1.184579 2</span>
-<span class="go">3 7 -0.062850 2</span>
-<span class="go">4 9 -1.106844 2</span>
+<span class="go">0 1 -1.118807 2</span>
+<span class="go">1 3 0.574867 2</span>
+<span class="go">2 5 0.346054 2</span>
+<span class="go">3 7 -0.013515 2</span>
+<span class="go">4 9 0.233552 2</span>
</pre></div>
</div>
<p>The easiest way to construct those <a class="reference internal"
href="generated/pyarrow.dataset.Expression.html#pyarrow.dataset.Expression"
title="pyarrow.dataset.Expression"><code class="xref py py-class docutils
literal notranslate"><span class="pre">Expression</span></code></a> objects is
by using the
@@ -1785,11 +1785,11 @@ values:</p>
<span class="gp">In [30]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">(</span><span
class="n">columns</span><span class="o">=</span><span
class="n">projection</span><span class="p">)</span><span
class="o">.</span><span class="n">to_pandas</span><span
class="p">()</span><span class="o">.</span><span class="n">head</span><span
class="p">()</span>
<span class="gh">Out[30]: </span>
<span class="go"> a_renamed b_as_float32 c_1</span>
-<span class="go">0 0 -0.384423 True</span>
-<span class="go">1 1 -1.431200 False</span>
-<span class="go">2 2 -2.722292 True</span>
-<span class="go">3 3 -1.158435 False</span>
-<span class="go">4 4 2.556243 True</span>
+<span class="go">0 0 -1.012557 True</span>
+<span class="go">1 1 -1.118807 False</span>
+<span class="go">2 2 -0.098280 True</span>
+<span class="go">3 3 0.574867 False</span>
+<span class="go">4 4 0.244365 True</span>
</pre></div>
</div>
<p>The dictionary also determines the column selection (only the keys in the
@@ -1803,11 +1803,11 @@ build up the dictionary from the dataset schema:</p>
<span class="gp">In [33]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">(</span><span
class="n">columns</span><span class="o">=</span><span
class="n">projection</span><span class="p">)</span><span
class="o">.</span><span class="n">to_pandas</span><span
class="p">()</span><span class="o">.</span><span class="n">head</span><span
class="p">()</span>
<span class="gh">Out[33]: </span>
<span class="go"> a b c b_large</span>
-<span class="go">0 0 -0.384423 1 False</span>
-<span class="go">1 1 -1.431200 2 False</span>
-<span class="go">2 2 -2.722292 1 False</span>
-<span class="go">3 3 -1.158435 2 False</span>
-<span class="go">4 4 2.556243 1 True</span>
+<span class="go">0 0 -1.012557 1 False</span>
+<span class="go">1 1 -1.118807 2 False</span>
+<span class="go">2 2 -0.098280 1 False</span>
+<span class="go">3 3 0.574867 2 False</span>
+<span class="go">4 4 0.244365 1 False</span>
</pre></div>
</div>
</section>
@@ -1860,8 +1860,8 @@ should use a hive-like partitioning scheme with the <code
class="docutils litera
<span class="gp">In [37]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">files</span>
<span class="gh">Out[37]: </span>
-<span
class="go">['parquet_dataset_partitioned/part=a/6300d21f33d14348b679adc3c138ecdf-0.parquet',</span>
-<span class="go">
'parquet_dataset_partitioned/part=b/6300d21f33d14348b679adc3c138ecdf-0.parquet']</span>
+<span
class="go">['parquet_dataset_partitioned/part=a/9f7ed09a3cf741d4bd4e694a73ff5948-0.parquet',</span>
+<span class="go">
'parquet_dataset_partitioned/part=b/9f7ed09a3cf741d4bd4e694a73ff5948-0.parquet']</span>
</pre></div>
</div>
<p>Although the partition fields are not included in the actual Parquet files,
@@ -1869,9 +1869,9 @@ they will be added back to the resulting table when
scanning this dataset:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [38]: </span><span
class="n">dataset</span><span class="o">.</span><span
class="n">to_table</span><span class="p">()</span><span class="o">.</span><span
class="n">to_pandas</span><span class="p">()</span><span
class="o">.</span><span class="n">head</span><span class="p">(</span><span
class="mi">3</span><span class="p">)</span>
<span class="gh">Out[38]: </span>
<span class="go"> a b c part</span>
-<span class="go">0 0 -0.752930 1 a</span>
-<span class="go">1 1 -0.861988 2 a</span>
-<span class="go">2 2 -0.173845 1 a</span>
+<span class="go">0 0 -0.271646 1 a</span>
+<span class="go">1 1 1.193938 2 a</span>
+<span class="go">2 2 0.021726 1 a</span>
</pre></div>
</div>
<p>We can now filter on the partition keys, which avoids loading files
@@ -1879,11 +1879,11 @@ altogether if they do not match the filter:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [39]: </span><span
class="n">dataset</span><span class="o">.</span><span
class="n">to_table</span><span class="p">(</span><span
class="nb">filter</span><span class="o">=</span><span class="n">ds</span><span
class="o">.</span><span class="n">field</span><span class="p">(</span><span
class="s2">"part"</span><span class="p">)</span> <span
class="o">==</span> <span class="s2">&qu [...]
<span class="gh">Out[39]: </span>
<span class="go"> a b c part</span>
-<span class="go">0 5 -0.036214 2 b</span>
-<span class="go">1 6 -0.790616 1 b</span>
-<span class="go">2 7 0.807806 2 b</span>
-<span class="go">3 8 1.854369 1 b</span>
-<span class="go">4 9 -0.978501 2 b</span>
+<span class="go">0 5 0.823205 2 b</span>
+<span class="go">1 6 1.083786 1 b</span>
+<span class="go">2 7 0.363844 2 b</span>
+<span class="go">3 8 0.826962 1 b</span>
+<span class="go">4 9 0.879916 2 b</span>
</pre></div>
</div>
<section id="different-partitioning-schemes">
@@ -2015,19 +2015,19 @@ is materialized as columns when reading the data and
can be used for filtering:<
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [47]: </span><span
class="n">dataset</span><span class="o">.</span><span
class="n">to_table</span><span class="p">()</span><span class="o">.</span><span
class="n">to_pandas</span><span class="p">()</span>
<span class="gh">Out[47]: </span>
<span class="go"> year col1 col2</span>
-<span class="go">0 2018 0 0.789639</span>
-<span class="go">1 2018 1 -1.908832</span>
-<span class="go">2 2018 2 0.716007</span>
-<span class="go">3 2019 0 0.789639</span>
-<span class="go">4 2019 1 -1.908832</span>
-<span class="go">5 2019 2 0.716007</span>
+<span class="go">0 2018 0 -0.535310</span>
+<span class="go">1 2018 1 0.504106</span>
+<span class="go">2 2018 2 0.029304</span>
+<span class="go">3 2019 0 -0.535310</span>
+<span class="go">4 2019 1 0.504106</span>
+<span class="go">5 2019 2 0.029304</span>
<span class="gp">In [48]: </span><span class="n">dataset</span><span
class="o">.</span><span class="n">to_table</span><span class="p">(</span><span
class="nb">filter</span><span class="o">=</span><span class="n">ds</span><span
class="o">.</span><span class="n">field</span><span class="p">(</span><span
class="s1">'year'</span><span class="p">)</span> <span
class="o">==</span> <span class="mi">2019</span><span class="p">)</span><span
class="o">.</span><span class="n">to_pandas</spa [...]
<span class="gh">Out[48]: </span>
<span class="go"> year col1 col2</span>
-<span class="go">0 2019 0 0.789639</span>
-<span class="go">1 2019 1 -1.908832</span>
-<span class="go">2 2019 2 0.716007</span>
+<span class="go">0 2019 0 -0.535310</span>
+<span class="go">1 2019 1 0.504106</span>
+<span class="go">2 2019 2 0.029304</span>
</pre></div>
</div>
<p>Another benefit of manually listing the files is that the order of the files
@@ -2279,7 +2279,7 @@ to supply a visitor that will be called as each file is
created:</p>
<span class="gp"> ....: </span>
<span class="go">path=dataset_visited/c=1/part-0.parquet</span>
<span class="go">size=824 bytes</span>
-<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7fad077a2930></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f2f8db50ef0></span>
<span class="go"> created_by: parquet-cpp-arrow version 24.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 2</span>
<span class="go"> num_rows: 5</span>
@@ -2288,7 +2288,7 @@ to supply a visitor that will be called as each file is
created:</p>
<span class="go"> serialized_size: 0</span>
<span class="go">path=dataset_visited/c=2/part-0.parquet</span>
<span class="go">size=826 bytes</span>
-<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7fad077a2930></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f2f8e66f8d0></span>
<span class="go"> created_by: parquet-cpp-arrow version 24.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 2</span>
<span class="go"> num_rows: 5</span>
diff --git a/docs/dev/python/getstarted.html b/docs/dev/python/getstarted.html
index d26076a66bf..9b0114ee6f6 100644
--- a/docs/dev/python/getstarted.html
+++ b/docs/dev/python/getstarted.html
@@ -1630,7 +1630,7 @@ it’s possible to apply transformations to the data</p>
<span class="gp">In [12]: </span><span class="n">pc</span><span
class="o">.</span><span class="n">value_counts</span><span
class="p">(</span><span class="n">birthdays_table</span><span
class="p">[</span><span class="s2">"years"</span><span
class="p">])</span>
<span class="gh">Out[12]: </span>
-<span class="go"><pyarrow.lib.StructArray object at
0x7facdb4c6200></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f2f5c6122c0></span>
<span class="go">-- is_valid: all not null</span>
<span class="go">-- child 0 type: int16</span>
<span class="go"> [</span>
diff --git a/docs/dev/python/memory.html b/docs/dev/python/memory.html
index 272daeb2f19..24dd61c8b2f 100644
--- a/docs/dev/python/memory.html
+++ b/docs/dev/python/memory.html
@@ -1579,7 +1579,7 @@ a bytes object:</p>
<span class="gp">In [3]: </span><span class="n">buf</span> <span
class="o">=</span> <span class="n">pa</span><span class="o">.</span><span
class="n">py_buffer</span><span class="p">(</span><span
class="n">data</span><span class="p">)</span>
<span class="gp">In [4]: </span><span class="n">buf</span>
-<span class="gh">Out[4]: </span><span class="go"><pyarrow.Buffer
address=0x7facdce32110 size=26 is_cpu=True is_mutable=False></span>
+<span class="gh">Out[4]: </span><span class="go"><pyarrow.Buffer
address=0x7f2f5e185110 size=26 is_cpu=True is_mutable=False></span>
<span class="gp">In [5]: </span><span class="n">buf</span><span
class="o">.</span><span class="n">size</span>
<span class="gh">Out[5]: </span><span class="go">26</span>
@@ -1592,7 +1592,7 @@ referenced using the <a class="reference internal"
href="generated/pyarrow.forei
<p>Buffers can be used in circumstances where a Python buffer or memoryview is
required, and such conversions are zero-copy:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [6]: </span><span
class="nb">memoryview</span><span class="p">(</span><span
class="n">buf</span><span class="p">)</span>
-<span class="gh">Out[6]: </span><span class="go"><memory at
0x7facdb301300></span>
+<span class="gh">Out[6]: </span><span class="go"><memory at
0x7f2f5c605300></span>
</pre></div>
</div>
<p>The Buffer’s <a class="reference internal"
href="generated/pyarrow.Buffer.html#pyarrow.Buffer.to_pybytes"
title="pyarrow.Buffer.to_pybytes"><code class="xref py py-meth docutils literal
notranslate"><span class="pre">to_pybytes()</span></code></a> method converts
the Buffer’s data to a
@@ -1791,7 +1791,7 @@ into Arrow Buffer objects, use <code class="docutils
literal notranslate"><span
<span class="gp">In [32]: </span><span class="n">buf</span> <span
class="o">=</span> <span class="n">mmap</span><span class="o">.</span><span
class="n">read_buffer</span><span class="p">(</span><span
class="mi">4</span><span class="p">)</span>
<span class="gp">In [33]: </span><span class="nb">print</span><span
class="p">(</span><span class="n">buf</span><span class="p">)</span>
-<span class="go"><pyarrow.Buffer address=0x7fadb4d11000 size=4 is_cpu=True
is_mutable=False></span>
+<span class="go"><pyarrow.Buffer address=0x7f303ad14000 size=4 is_cpu=True
is_mutable=False></span>
<span class="gp">In [34]: </span><span class="n">buf</span><span
class="o">.</span><span class="n">to_pybytes</span><span class="p">()</span>
<span class="gh">Out[34]: </span><span class="go">b'some'</span>
@@ -1813,7 +1813,7 @@ file interfaces that can read and write to Arrow
Buffers.</p>
<span class="gp">In [37]: </span><span class="n">buf</span> <span
class="o">=</span> <span class="n">writer</span><span class="o">.</span><span
class="n">getvalue</span><span class="p">()</span>
<span class="gp">In [38]: </span><span class="n">buf</span>
-<span class="gh">Out[38]: </span><span class="go"><pyarrow.Buffer
address=0x7fad484600c0 size=14 is_cpu=True is_mutable=True></span>
+<span class="gh">Out[38]: </span><span class="go"><pyarrow.Buffer
address=0x7f2fce4600c0 size=14 is_cpu=True is_mutable=True></span>
<span class="gp">In [39]: </span><span class="n">buf</span><span
class="o">.</span><span class="n">size</span>
<span class="gh">Out[39]: </span><span class="go">14</span>
diff --git a/docs/dev/python/pandas.html b/docs/dev/python/pandas.html
index 1fc55105f3e..5b1837827db 100644
--- a/docs/dev/python/pandas.html
+++ b/docs/dev/python/pandas.html
@@ -1753,7 +1753,7 @@ same categories of the Pandas DataFrame.</p>
<span class="gp">In [10]: </span><span class="n">chunk</span><span
class="o">.</span><span class="n">dictionary</span>
<span class="gh">Out[10]: </span>
-<span class="go"><pyarrow.lib.StringArray object at
0x7facda2999c0></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f2f5b5e9840></span>
<span class="go">[</span>
<span class="go"> "a",</span>
<span class="go"> "b",</span>
@@ -1762,7 +1762,7 @@ same categories of the Pandas DataFrame.</p>
<span class="gp">In [11]: </span><span class="n">chunk</span><span
class="o">.</span><span class="n">indices</span>
<span class="gh">Out[11]: </span>
-<span class="go"><pyarrow.lib.Int8Array object at 0x7facda299c60></span>
+<span class="go"><pyarrow.lib.Int8Array object at 0x7f2f5b5e97e0></span>
<span class="go">[</span>
<span class="go"> 0,</span>
<span class="go"> 1,</span>
@@ -1888,7 +1888,7 @@ converted to an Arrow <code class="docutils literal
notranslate"><span class="pr
<span class="gp">In [33]: </span><span class="n">arr</span>
<span class="gh">Out[33]: </span>
-<span class="go"><pyarrow.lib.Time64Array object at
0x7facda29b9a0></span>
+<span class="go"><pyarrow.lib.Time64Array object at
0x7f2f5b5eb8e0></span>
<span class="go">[</span>
<span class="go"> 01:01:01.000000,</span>
<span class="go"> 02:02:02.000000</span>
diff --git a/docs/dev/python/parquet.html b/docs/dev/python/parquet.html
index 818e2590def..124e3bbb364 100644
--- a/docs/dev/python/parquet.html
+++ b/docs/dev/python/parquet.html
@@ -1724,7 +1724,7 @@ you may choose to omit it by passing <code
class="docutils literal notranslate">
<span class="gp">In [20]: </span><span class="n">parquet_file</span><span
class="o">.</span><span class="n">metadata</span>
<span class="gh">Out[20]: </span>
-<span class="go"><pyarrow._parquet.FileMetaData object at
0x7facdb5de200></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f2f8d8d2e30></span>
<span class="go"> created_by: parquet-cpp-arrow version 24.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
@@ -1734,7 +1734,7 @@ you may choose to omit it by passing <code
class="docutils literal notranslate">
<span class="gp">In [21]: </span><span class="n">parquet_file</span><span
class="o">.</span><span class="n">schema</span>
<span class="gh">Out[21]: </span>
-<span class="go"><pyarrow._parquet.ParquetSchema object at
0x7facdd7628c0></span>
+<span class="go"><pyarrow._parquet.ParquetSchema object at
0x7f2f5eaaf540></span>
<span class="go">required group field_id=-1 schema {</span>
<span class="go"> optional double field_id=-1 one;</span>
<span class="go"> optional binary field_id=-1 two (String);</span>
@@ -1792,7 +1792,7 @@ concatenate them into a single table. You can read
individual row groups with
<span class="gp">In [30]: </span><span class="n">metadata</span>
<span class="gh">Out[30]: </span>
-<span class="go"><pyarrow._parquet.FileMetaData object at
0x7facdf02a980></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f2f8d748db0></span>
<span class="go"> created_by: parquet-cpp-arrow version 24.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
@@ -1806,7 +1806,7 @@ concatenate them into a single table. You can read
individual row groups with
such as the row groups and column chunk metadata and statistics:</p>
<div class="highlight-ipython notranslate"><div
class="highlight"><pre><span></span><span class="gp">In [31]: </span><span
class="n">metadata</span><span class="o">.</span><span
class="n">row_group</span><span class="p">(</span><span
class="mi">0</span><span class="p">)</span>
<span class="gh">Out[31]: </span>
-<span class="go"><pyarrow._parquet.RowGroupMetaData object at
0x7facda2e2e30></span>
+<span class="go"><pyarrow._parquet.RowGroupMetaData object at
0x7f2f8d7484a0></span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
<span class="go"> total_byte_size: 290</span>
@@ -1814,7 +1814,7 @@ such as the row groups and column chunk metadata and
statistics:</p>
<span class="gp">In [32]: </span><span class="n">metadata</span><span
class="o">.</span><span class="n">row_group</span><span class="p">(</span><span
class="mi">0</span><span class="p">)</span><span class="o">.</span><span
class="n">column</span><span class="p">(</span><span class="mi">0</span><span
class="p">)</span>
<span class="gh">Out[32]: </span>
-<span class="go"><pyarrow._parquet.ColumnChunkMetaData object at
0x7facda2e3830></span>
+<span class="go"><pyarrow._parquet.ColumnChunkMetaData object at
0x7f301df2b150></span>
<span class="go"> file_offset: 0</span>
<span class="go"> file_path: </span>
<span class="go"> physical_type: DOUBLE</span>
@@ -1822,7 +1822,7 @@ such as the row groups and column chunk metadata and
statistics:</p>
<span class="go"> path_in_schema: one</span>
<span class="go"> is_stats_set: True</span>
<span class="go"> statistics:</span>
-<span class="go"> <pyarrow._parquet.Statistics object at
0x7facdbf47dd0></span>
+<span class="go"> <pyarrow._parquet.Statistics object at
0x7f301df2b1a0></span>
<span class="go"> has_min_max: True</span>
<span class="go"> min: -1.0</span>
<span class="go"> max: 2.5</span>
diff --git a/docs/dev/r/articles/data_wrangling.html
b/docs/dev/r/articles/data_wrangling.html
index dcef9559d3b..110ae4d3e16 100644
--- a/docs/dev/r/articles/data_wrangling.html
+++ b/docs/dev/r/articles/data_wrangling.html
@@ -409,18 +409,18 @@ paying a performance penalty using the helper function
<span> <span class="co"># perform other arrow operations...</span></span>
<span> <span class="fu"><a
href="https://dplyr.tidyverse.org/reference/compute.html";
class="external-link">collect</a></span><span class="op">(</span><span
class="op">)</span></span></code></pre></div>
<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble:
28 x 4</span></span></span>
-<span><span class="co">## name height mass
hair_color</span></span>
-<span><span class="co">## <span style="color: #949494; font-style:
italic;"><chr></span> <span style="color: #949494;
font-style: italic;"><int></span> <span style="color: #949494;
font-style: italic;"><dbl></span> <span style="color: #949494;
font-style: italic;"><chr></span> </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span> <span
style="color: #949494;">"</span>Yoda<span style="color: #949494;">"</span>
66 17 white </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span> <span
style="color: #949494;">"</span>Luke Skywalker<span style="color:
#949494;">"</span> 172 77 blond </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span> <span
style="color: #949494;">"</span>Finis Valorum<span style="color:
#949494;">"</span> 170 <span style="color: #BB0000;">NA</span>
blond </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span> <span
style="color: #949494;">"</span>Leia Organa<span style="color:
#949494;">"</span> 150 49 brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span> <span
style="color: #949494;">"</span>Beru Whitesun Lars<span style="color:
#949494;">"</span> 165 75 brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span> <span
style="color: #949494;">"</span>Wedge Antilles<span style="color:
#949494;">"</span> 170 77 brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span> <span
style="color: #949494;">"</span>Wicket Systri Warrick<span style="color:
#949494;">"</span> 88 20 brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span> <span
style="color: #949494;">"</span>Cord\u00e9<span style="color:
#949494;">"</span> 157 <span style="color: #BB0000;">NA</span>
brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span> <span
style="color: #949494;">"</span>Dorm\u00e9<span style="color:
#949494;">"</span> 165 <span style="color: #BB0000;">NA</span>
brown </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span> <span
style="color: #949494;">"</span>Watto<span style="color: #949494;">"</span>
137 <span style="color: #BB0000;">NA</span> black
</span></span>
+<span><span class="co">## name height mass
hair_color</span></span>
+<span><span class="co">## <span style="color: #949494; font-style:
italic;"><chr></span> <span style="color: #949494; font-style:
italic;"><int></span> <span style="color: #949494; font-style:
italic;"><dbl></span> <span style="color: #949494; font-style:
italic;"><chr></span> </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 1</span> Yoda
66 17 white </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 2</span> Luke
Skywalker 172 77 blond </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 3</span> Finis
Valorum 170 <span style="color: #BB0000;">NA</span> blond
</span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 4</span> Watto
137 <span style="color: #BB0000;">NA</span> black </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 5</span> Shmi
Skywalker 163 <span style="color: #BB0000;">NA</span> black
</span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 6</span> Eeth Koth
171 <span style="color: #BB0000;">NA</span> black </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 7</span> Luminara
Unduli 170 56.2 black </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 8</span> Barriss
Offee 166 50 black </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;"> 9</span> R4-P17
96 <span style="color: #BB0000;">NA</span> none </span></span>
+<span><span class="co">## <span style="color: #BCBCBC;">10</span> Lobot
175 79 none </span></span>
<span><span class="co">## <span style="color: #949494;"># i 18 more
rows</span></span></span></code></pre>
</div>
<div class="section level2">
diff --git a/docs/dev/r/articles/data_wrangling.md
b/docs/dev/r/articles/data_wrangling.md
index 026b79fd640..bcbea665767 100644
--- a/docs/dev/r/articles/data_wrangling.md
+++ b/docs/dev/r/articles/data_wrangling.md
@@ -414,18 +414,18 @@ sw |>
</div>
## # A tibble: 28 x 4
- ## name height mass hair_color
- ## <chr> <int> <dbl> <chr>
- ## 1 "Yoda" 66 17 white
- ## 2 "Luke Skywalker" 172 77 blond
- ## 3 "Finis Valorum" 170 NA blond
- ## 4 "Leia Organa" 150 49 brown
- ## 5 "Beru Whitesun Lars" 165 75 brown
- ## 6 "Wedge Antilles" 170 77 brown
- ## 7 "Wicket Systri Warrick" 88 20 brown
- ## 8 "Cord\u00e9" 157 NA brown
- ## 9 "Dorm\u00e9" 165 NA brown
- ## 10 "Watto" 137 NA black
+ ## name height mass hair_color
+ ## <chr> <int> <dbl> <chr>
+ ## 1 Yoda 66 17 white
+ ## 2 Luke Skywalker 172 77 blond
+ ## 3 Finis Valorum 170 NA blond
+ ## 4 Watto 137 NA black
+ ## 5 Shmi Skywalker 163 NA black
+ ## 6 Eeth Koth 171 NA black
+ ## 7 Luminara Unduli 170 56.2 black
+ ## 8 Barriss Offee 166 50 black
+ ## 9 R4-P17 96 NA none
+ ## 10 Lobot 175 79 none
## # i 18 more rows
</div>
diff --git a/docs/dev/r/pkgdown.yml b/docs/dev/r/pkgdown.yml
index b4878cdbb52..c817337e535 100644
--- a/docs/dev/r/pkgdown.yml
+++ b/docs/dev/r/pkgdown.yml
@@ -21,7 +21,7 @@ articles:
read_write: read_write.html
developers/setup: developers/setup.html
developers/workflow: developers/workflow.html
-last_built: 2026-01-24T01:30Z
+last_built: 2026-01-25T01:36Z
urls:
reference: https://arrow.apache.org/docs/r/reference
article: https://arrow.apache.org/docs/r/articles
diff --git a/docs/dev/r/reference/to_arrow.html
b/docs/dev/r/reference/to_arrow.html
index a2e7f2e3f97..a4c327b86f3 100644
--- a/docs/dev/r/reference/to_arrow.html
+++ b/docs/dev/r/reference/to_arrow.html
@@ -121,9 +121,9 @@ result to materialize the entire Table in-memory.</p>
<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#949494;"># A tibble: 3 x 2</span></span>
<span class="r-out co"><span class="r-pr">#></span> cyl mean_mpg</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#949494; font-style: italic;"><dbl></span> <span style="color:
#949494; font-style: italic;"><dbl></span></span>
-<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">1</span> 6 19.7</span>
-<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">2</span> 8 15.1</span>
-<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">3</span> 4 23.7</span>
+<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">1</span> 4 23.7</span>
+<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">2</span> 6 19.7</span>
+<span class="r-out co"><span class="r-pr">#></span> <span style="color:
#BCBCBC;">3</span> 8 15.1</span>
</code></pre></div>
</div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of
contents"><h2>On this page</h2>
diff --git a/docs/dev/r/reference/to_arrow.md b/docs/dev/r/reference/to_arrow.md
index 2e97f18caa2..e5dc03d0ac9 100644
--- a/docs/dev/r/reference/to_arrow.md
+++ b/docs/dev/r/reference/to_arrow.md
@@ -74,9 +74,9 @@ ds |>
#> # A tibble: 3 x 2
#> cyl mean_mpg
#> <dbl> <dbl>
-#> 1 6 19.7
-#> 2 8 15.1
-#> 3 4 23.7
+#> 1 4 23.7
+#> 2 6 19.7
+#> 3 8 15.1
```
</div>
diff --git a/docs/dev/r/search.json b/docs/dev/r/search.json
index 01c2f19c8c0..de1997d1830 100644
--- a/docs/dev/r/search.json
+++ b/docs/dev/r/search.json
@@ -1 +1 @@
-[{"path":"https://arrow.apache.org/docs/r/PACKAGING.html","id":null,"dir":"","previous_headings":"","what":"Packaging
Checklist for CRAN Release","title":"Packaging Checklist for CRAN
Release","text":"high-level overview Arrow release process see Apache Arrow
Release Management
Guide.","code":""},{"path":"https://arrow.apache.org/docs/r/PACKAGING.html","id":"before-the-arrow-release-candidate-is-created","dir":"","previous_headings":"","what":"Before
the Arrow Release Candidate Is Create [...]
+[{"path":"https://arrow.apache.org/docs/r/PACKAGING.html","id":null,"dir":"","previous_headings":"","what":"Packaging
Checklist for CRAN Release","title":"Packaging Checklist for CRAN
Release","text":"high-level overview Arrow release process see Apache Arrow
Release Management
Guide.","code":""},{"path":"https://arrow.apache.org/docs/r/PACKAGING.html","id":"before-the-arrow-release-candidate-is-created","dir":"","previous_headings":"","what":"Before
the Arrow Release Candidate Is Create [...]
diff --git a/docs/dev/searchindex.js b/docs/dev/searchindex.js
index e48cdedee6c..3e7dc2edc28 100644
--- a/docs/dev/searchindex.js
+++ b/docs/dev/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles":{"1st pass":[[83,"st-pass"]],"2nd
pass":[[83,"nd-pass"]],"32-bit hash vs 64-bit
hash":[[83,"bit-hash-vs-64-bit-hash"]],"8-bit Boolean":[[126,"bit-boolean"]],"A
Database":[[9,"a-database"]],"A Library for Data
Scientists":[[9,"a-library-for-data-scientists"]],"A Note on
Linking":[[38,"a-note-on-linking"]],"A note on transactions & ACID
guarantees":[[42,"a-note-on-transactions-acid-guarantees"],[166,"a-note-on-transactions-acid-guarantees"]],"ABI
Structures":[[ [...]
\ No newline at end of file
+Search.setIndex({"alltitles":{"1st pass":[[83,"st-pass"]],"2nd
pass":[[83,"nd-pass"]],"32-bit hash vs 64-bit
hash":[[83,"bit-hash-vs-64-bit-hash"]],"8-bit Boolean":[[126,"bit-boolean"]],"A
Database":[[9,"a-database"]],"A Library for Data
Scientists":[[9,"a-library-for-data-scientists"]],"A Note on
Linking":[[38,"a-note-on-linking"]],"A note on transactions & ACID
guarantees":[[42,"a-note-on-transactions-acid-guarantees"],[166,"a-note-on-transactions-acid-guarantees"]],"ABI
Structures":[[ [...]
\ No newline at end of file
