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The following commit(s) were added to refs/heads/asf-site by this push:
new 9c195cb84de Updating dev docs (build nightly-tests-2025-06-12-0)
9c195cb84de is described below
commit 9c195cb84de302cb519099d20f14b3de744d0560
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Fri Jun 13 00:34:54 2025 +0000
Updating dev docs (build nightly-tests-2025-06-12-0)
---
docs/dev/python/data.html | 46 ++++++------
docs/dev/python/dataset.html | 136 ++++++++++++++++++------------------
docs/dev/python/getstarted.html | 2 +-
docs/dev/python/memory.html | 6 +-
docs/dev/python/pandas.html | 6 +-
docs/dev/python/parquet.html | 12 ++--
docs/dev/r/pkgdown.yml | 2 +-
docs/dev/r/reference/to_duckdb.html | 10 +--
docs/dev/r/search.json | 2 +-
docs/dev/searchindex.js | 2 +-
10 files changed, 112 insertions(+), 112 deletions(-)
diff --git a/docs/dev/python/data.html b/docs/dev/python/data.html
index 1370d9349fb..f8b2f2a657e 100644
--- a/docs/dev/python/data.html
+++ b/docs/dev/python/data.html
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</pre></div>
</div>
<p>… and infers the dataset’s schema (by default from the first file):</p>
@@ -603,23 +603,23 @@ this can require a lot of memory, see below on filtering
/ iterative loading):</
<span class="go">c: int64</span>
<span class="gt">----</span>
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<span class="c1"># converting to pandas to see the contents of the scanned
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<span class="gh">Out[17]: </span>
<span class="go"> a b c</span>
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-<span class="go">1 1 0.613741 2</span>
-<span class="go">2 2 0.297535 1</span>
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</pre></div>
</div>
</section>
@@ -642,11 +642,11 @@ supported; more formats are planned in the future.</p>
<span class="gp">In [21]: </span><span class="n">dataset</span><span
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<span class="gh">Out[21]: </span>
<span class="go"> a b c</span>
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-<span class="go">1 1 0.613741 2</span>
-<span class="go">2 2 0.297535 1</span>
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</pre></div>
</div>
</section>
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+<span class="go">1 1 0.267676</span>
+<span class="go">2 2 0.773966</span>
+<span class="go">3 3 0.592954</span>
+<span class="go">4 4 -0.547113</span>
+<span class="go">5 5 1.254677</span>
+<span class="go">6 6 -1.222568</span>
+<span class="go">7 7 0.690540</span>
+<span class="go">8 8 -0.975163</span>
+<span class="go">9 9 1.825765</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
@@ -696,18 +696,18 @@ 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 -1.054974 2</span>
-<span class="go">1 8 0.057430 1</span>
-<span class="go">2 9 1.814216 2</span>
+<span class="go">0 7 0.690540 2</span>
+<span class="go">1 8 -0.975163 1</span>
+<span class="go">2 9 1.825765 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 0.613741 2</span>
-<span class="go">1 3 -0.650007 2</span>
-<span class="go">2 5 0.099074 2</span>
-<span class="go">3 7 -1.054974 2</span>
-<span class="go">4 9 1.814216 2</span>
+<span class="go">0 1 0.267676 2</span>
+<span class="go">1 3 0.592954 2</span>
+<span class="go">2 5 1.254677 2</span>
+<span class="go">3 7 0.690540 2</span>
+<span class="go">4 9 1.825765 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
@@ -752,11 +752,11 @@ 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 -1.029086 True</span>
-<span class="go">1 1 0.613741 False</span>
-<span class="go">2 2 0.297535 True</span>
-<span class="go">3 3 -0.650007 False</span>
-<span class="go">4 4 0.448808 True</span>
+<span class="go">0 0 -0.620125 True</span>
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+<span class="go">2 2 0.773966 True</span>
+<span class="go">3 3 0.592954 False</span>
+<span class="go">4 4 -0.547113 True</span>
</pre></div>
</div>
<p>The dictionary also determines the column selection (only the keys in the
@@ -770,11 +770,11 @@ 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 -1.029086 1 False</span>
-<span class="go">1 1 0.613741 2 False</span>
-<span class="go">2 2 0.297535 1 False</span>
-<span class="go">3 3 -0.650007 2 False</span>
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+<span class="go">0 0 -0.620125 1 False</span>
+<span class="go">1 1 0.267676 2 False</span>
+<span class="go">2 2 0.773966 1 False</span>
+<span class="go">3 3 0.592954 2 False</span>
+<span class="go">4 4 -0.547113 1 False</span>
</pre></div>
</div>
</section>
@@ -827,8 +827,8 @@ 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/a0c5f8769ce347b0a889238eabae52e3-0.parquet',</span>
-<span class="go">
'parquet_dataset_partitioned/part=b/a0c5f8769ce347b0a889238eabae52e3-0.parquet']</span>
+<span
class="go">['parquet_dataset_partitioned/part=a/dd39454549ab42389c8ef4b39720ea81-0.parquet',</span>
+<span class="go">
'parquet_dataset_partitioned/part=b/dd39454549ab42389c8ef4b39720ea81-0.parquet']</span>
</pre></div>
</div>
<p>Although the partition fields are not included in the actual Parquet files,
@@ -836,9 +836,9 @@ 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 -0.670100 1 a</span>
-<span class="go">1 1 -0.188930 2 a</span>
-<span class="go">2 2 -1.110971 1 a</span>
+<span class="go">0 0 -1.131522 1 a</span>
+<span class="go">1 1 -2.197228 2 a</span>
+<span class="go">2 2 -1.136329 1 a</span>
</pre></div>
</div>
<p>We can now filter on the partition keys, which avoids loading files
@@ -846,11 +846,11 @@ 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 0.809998 2 b</span>
-<span class="go">1 6 0.909870 1 b</span>
-<span class="go">2 7 1.269374 2 b</span>
-<span class="go">3 8 -2.480534 1 b</span>
-<span class="go">4 9 0.303719 2 b</span>
+<span class="go">0 5 1.010856 2 b</span>
+<span class="go">1 6 2.105195 1 b</span>
+<span class="go">2 7 -0.995974 2 b</span>
+<span class="go">3 8 -0.106245 1 b</span>
+<span class="go">4 9 -0.626722 2 b</span>
</pre></div>
</div>
<section id="different-partitioning-schemes">
@@ -982,19 +982,19 @@ 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 -0.053477</span>
-<span class="go">1 2018 1 -1.627205</span>
-<span class="go">2 2018 2 0.390661</span>
-<span class="go">3 2019 0 -0.053477</span>
-<span class="go">4 2019 1 -1.627205</span>
-<span class="go">5 2019 2 0.390661</span>
+<span class="go">0 2018 0 1.179551</span>
+<span class="go">1 2018 1 -1.075784</span>
+<span class="go">2 2018 2 1.558932</span>
+<span class="go">3 2019 0 1.179551</span>
+<span class="go">4 2019 1 -1.075784</span>
+<span class="go">5 2019 2 1.558932</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 -0.053477</span>
-<span class="go">1 2019 1 -1.627205</span>
-<span class="go">2 2019 2 0.390661</span>
+<span class="go">0 2019 0 1.179551</span>
+<span class="go">1 2019 1 -1.075784</span>
+<span class="go">2 2019 2 1.558932</span>
</pre></div>
</div>
<p>Another benefit of manually listing the files is that the order of the files
@@ -1246,7 +1246,7 @@ 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=816 bytes</span>
-<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f71040dfe70></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f385e14dd00></span>
<span class="go"> created_by: parquet-cpp-arrow version 21.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 2</span>
<span class="go"> num_rows: 5</span>
@@ -1255,7 +1255,7 @@ 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=818 bytes</span>
-<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f71040dfe70></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f386247fa10></span>
<span class="go"> created_by: parquet-cpp-arrow version 21.0.0-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 784247b58cc..853256c4235 100644
--- a/docs/dev/python/getstarted.html
+++ b/docs/dev/python/getstarted.html
@@ -597,7 +597,7 @@ 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
0x7f70d4727100></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f383288d4e0></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 ba7e99d3d3d..5efa5645595 100644
--- a/docs/dev/python/memory.html
+++ b/docs/dev/python/memory.html
@@ -546,7 +546,7 @@ 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=0x7f70d331a850 size=26 is_cpu=True is_mutable=False></span>
+<span class="gh">Out[4]: </span><span class="go"><pyarrow.Buffer
address=0x7f38316b9cd0 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>
@@ -559,7 +559,7 @@ 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
0x7f70d47428c0></span>
+<span class="gh">Out[6]: </span><span class="go"><memory at
0x7f38328a68c0></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
@@ -758,7 +758,7 @@ 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=0x7f716b810000 size=4 is_cpu=True
is_mutable=False></span>
+<span class="go"><pyarrow.Buffer address=0x7f38c9ab0000 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>
diff --git a/docs/dev/python/pandas.html b/docs/dev/python/pandas.html
index ca38276bc95..f6e5576179f 100644
--- a/docs/dev/python/pandas.html
+++ b/docs/dev/python/pandas.html
@@ -720,7 +720,7 @@ 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
0x7f71515371c0></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f3831569660></span>
<span class="go">[</span>
<span class="go"> "a",</span>
<span class="go"> "b",</span>
@@ -729,7 +729,7 @@ 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 0x7f7151537d60></span>
+<span class="go"><pyarrow.lib.Int8Array object at 0x7f3831569600></span>
<span class="go">[</span>
<span class="go"> 0,</span>
<span class="go"> 1,</span>
@@ -855,7 +855,7 @@ 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
0x7f71515d1960></span>
+<span class="go"><pyarrow.lib.Time64Array object at
0x7f383156b9a0></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 9850809bb17..2f80bb691f6 100644
--- a/docs/dev/python/parquet.html
+++ b/docs/dev/python/parquet.html
@@ -691,7 +691,7 @@ 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
0x7f70d48c3bf0></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f38622db380></span>
<span class="go"> created_by: parquet-cpp-arrow version 21.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
@@ -701,7 +701,7 @@ 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
0x7f7151482900></span>
+<span class="go"><pyarrow._parquet.ParquetSchema object at
0x7f38afb9a980></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>
@@ -759,7 +759,7 @@ 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
0x7f715153fb50></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f38afbe1440></span>
<span class="go"> created_by: parquet-cpp-arrow version 21.0.0-SNAPSHOT</span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
@@ -773,7 +773,7 @@ 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
0x7f7151491530></span>
+<span class="go"><pyarrow._parquet.RowGroupMetaData object at
0x7f38afbe1f80></span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
<span class="go"> total_byte_size: 282</span>
@@ -781,7 +781,7 @@ 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
0x7f70d33cde90></span>
+<span class="go"><pyarrow._parquet.ColumnChunkMetaData object at
0x7f3831675e90></span>
<span class="go"> file_offset: 0</span>
<span class="go"> file_path: </span>
<span class="go"> physical_type: DOUBLE</span>
@@ -789,7 +789,7 @@ 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
0x7f71040fefc0></span>
+<span class="go"> <pyarrow._parquet.Statistics object at
0x7f38afbe20c0></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/pkgdown.yml b/docs/dev/r/pkgdown.yml
index f486d8e34c4..35cefe781e0 100644
--- a/docs/dev/r/pkgdown.yml
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@@ -21,7 +21,7 @@ articles:
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</code></pre></div>
</div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of
contents"><h2>On this page</h2>
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