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new 3f7c9a9e078 Updating dev docs (build nightly-tests-2025-07-06-0)
3f7c9a9e078 is described below
commit 3f7c9a9e078fa6addd475b7a59bbf0df3b7fa111
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Mon Jul 7 00:38:02 2025 +0000
Updating dev docs (build nightly-tests-2025-07-06-0)
---
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 c162fc5f694..31a9e44e231 100644
--- a/docs/dev/python/data.html
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<p>… and infers the dataset’s schema (by default from the first file):</p>
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<span class="go"> a b</span>
-<span class="go">0 0 -1.550883</span>
-<span class="go">1 1 0.461952</span>
-<span class="go">2 2 0.967634</span>
-<span class="go">3 3 -1.007872</span>
-<span class="go">4 4 -1.940305</span>
-<span class="go">5 5 0.388870</span>
-<span class="go">6 6 0.019156</span>
-<span class="go">7 7 -0.224324</span>
-<span class="go">8 8 1.630983</span>
-<span class="go">9 9 0.238716</span>
+<span class="go">0 0 0.586858</span>
+<span class="go">1 1 0.618969</span>
+<span class="go">2 2 -1.027270</span>
+<span class="go">3 3 0.185268</span>
+<span class="go">4 4 0.180689</span>
+<span class="go">5 5 -0.623352</span>
+<span class="go">6 6 -0.253550</span>
+<span class="go">7 7 0.268437</span>
+<span class="go">8 8 1.119990</span>
+<span class="go">9 9 1.352846</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
@@ -1695,18 +1695,18 @@ 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 -0.224324 2</span>
-<span class="go">1 8 1.630983 1</span>
-<span class="go">2 9 0.238716 2</span>
+<span class="go">0 7 0.268437 2</span>
+<span class="go">1 8 1.119990 1</span>
+<span class="go">2 9 1.352846 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 0.461952 2</span>
-<span class="go">1 3 -1.007872 2</span>
-<span class="go">2 5 0.388870 2</span>
-<span class="go">3 7 -0.224324 2</span>
-<span class="go">4 9 0.238716 2</span>
+<span class="go">0 1 0.618969 2</span>
+<span class="go">1 3 0.185268 2</span>
+<span class="go">2 5 -0.623352 2</span>
+<span class="go">3 7 0.268437 2</span>
+<span class="go">4 9 1.352846 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
@@ -1751,11 +1751,11 @@ 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 -1.550883 True</span>
-<span class="go">1 1 0.461952 False</span>
-<span class="go">2 2 0.967634 True</span>
-<span class="go">3 3 -1.007872 False</span>
-<span class="go">4 4 -1.940305 True</span>
+<span class="go">0 0 0.586858 True</span>
+<span class="go">1 1 0.618969 False</span>
+<span class="go">2 2 -1.027270 True</span>
+<span class="go">3 3 0.185268 False</span>
+<span class="go">4 4 0.180689 True</span>
</pre></div>
</div>
<p>The dictionary also determines the column selection (only the keys in the
@@ -1769,11 +1769,11 @@ 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 -1.550883 1 False</span>
-<span class="go">1 1 0.461952 2 False</span>
-<span class="go">2 2 0.967634 1 False</span>
-<span class="go">3 3 -1.007872 2 False</span>
-<span class="go">4 4 -1.940305 1 False</span>
+<span class="go">0 0 0.586858 1 False</span>
+<span class="go">1 1 0.618969 2 False</span>
+<span class="go">2 2 -1.027270 1 False</span>
+<span class="go">3 3 0.185268 2 False</span>
+<span class="go">4 4 0.180689 1 False</span>
</pre></div>
</div>
</section>
@@ -1826,8 +1826,8 @@ 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/0afab988b86d4387b956c460b56c8cfc-0.parquet',</span>
-<span class="go">
'parquet_dataset_partitioned/part=b/0afab988b86d4387b956c460b56c8cfc-0.parquet']</span>
+<span
class="go">['parquet_dataset_partitioned/part=a/e1ca2aa0c1a14df2a62c5f99e004e31c-0.parquet',</span>
+<span class="go">
'parquet_dataset_partitioned/part=b/e1ca2aa0c1a14df2a62c5f99e004e31c-0.parquet']</span>
</pre></div>
</div>
<p>Although the partition fields are not included in the actual Parquet files,
@@ -1835,9 +1835,9 @@ 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 -1.213455 1 a</span>
-<span class="go">1 1 -1.101675 2 a</span>
-<span class="go">2 2 -0.714892 1 a</span>
+<span class="go">0 0 0.361993 1 a</span>
+<span class="go">1 1 1.081140 2 a</span>
+<span class="go">2 2 -1.338426 1 a</span>
</pre></div>
</div>
<p>We can now filter on the partition keys, which avoids loading files
@@ -1845,11 +1845,11 @@ 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 -1.462209 2 b</span>
-<span class="go">1 6 -1.365225 1 b</span>
-<span class="go">2 7 -0.322173 2 b</span>
-<span class="go">3 8 0.448351 1 b</span>
-<span class="go">4 9 0.678461 2 b</span>
+<span class="go">0 5 0.076543 2 b</span>
+<span class="go">1 6 -0.262385 1 b</span>
+<span class="go">2 7 1.108006 2 b</span>
+<span class="go">3 8 0.258402 1 b</span>
+<span class="go">4 9 0.300451 2 b</span>
</pre></div>
</div>
<section id="different-partitioning-schemes">
@@ -1981,19 +1981,19 @@ 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 -0.591372</span>
-<span class="go">1 2018 1 -1.723943</span>
-<span class="go">2 2018 2 -1.141440</span>
-<span class="go">3 2019 0 -0.591372</span>
-<span class="go">4 2019 1 -1.723943</span>
-<span class="go">5 2019 2 -1.141440</span>
+<span class="go">0 2018 0 0.022905</span>
+<span class="go">1 2018 1 -0.213899</span>
+<span class="go">2 2018 2 -0.163938</span>
+<span class="go">3 2019 0 0.022905</span>
+<span class="go">4 2019 1 -0.213899</span>
+<span class="go">5 2019 2 -0.163938</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 -0.591372</span>
-<span class="go">1 2019 1 -1.723943</span>
-<span class="go">2 2019 2 -1.141440</span>
+<span class="go">0 2019 0 0.022905</span>
+<span class="go">1 2019 1 -0.213899</span>
+<span class="go">2 2019 2 -0.163938</span>
</pre></div>
</div>
<p>Another benefit of manually listing the files is that the order of the files
@@ -2245,7 +2245,7 @@ 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
0x7fbccadf34c0></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f0fae7d3060></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>
@@ -2254,7 +2254,7 @@ 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
0x7fbccaee1f80></span>
+<span class="go">metadata=<pyarrow._parquet.FileMetaData object at
0x7f0fae7d3060></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 af8d6805d3a..53af42b1980 100644
--- a/docs/dev/python/getstarted.html
+++ b/docs/dev/python/getstarted.html
@@ -1596,7 +1596,7 @@ 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
0x7fbca06fe560></span>
+<span class="go"><pyarrow.lib.StructArray object at
0x7f0f840e2620></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 5e845fef97d..3f97d1282c0 100644
--- a/docs/dev/python/memory.html
+++ b/docs/dev/python/memory.html
@@ -1545,7 +1545,7 @@ 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=0x7fbc9e03da10 size=26 is_cpu=True is_mutable=False></span>
+<span class="gh">Out[4]: </span><span class="go"><pyarrow.Buffer
address=0x7f0f81a08ad0 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>
@@ -1558,7 +1558,7 @@ 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
0x7fbca05a6140></span>
+<span class="gh">Out[6]: </span><span class="go"><memory at
0x7f0f81f7a140></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
@@ -1757,7 +1757,7 @@ 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=0x7fbd35637000 size=4 is_cpu=True
is_mutable=False></span>
+<span class="go"><pyarrow.Buffer address=0x7f1018c9c000 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 f1e676c3277..a02c53713f0 100644
--- a/docs/dev/python/pandas.html
+++ b/docs/dev/python/pandas.html
@@ -1719,7 +1719,7 @@ 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
0x7fbc9df6f0a0></span>
+<span class="go"><pyarrow.lib.StringArray object at
0x7f0ffbf12c80></span>
<span class="go">[</span>
<span class="go"> "a",</span>
<span class="go"> "b",</span>
@@ -1728,7 +1728,7 @@ 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 0x7fbc9df6f040></span>
+<span class="go"><pyarrow.lib.Int8Array object at 0x7f0ffbf12980></span>
<span class="go">[</span>
<span class="go"> 0,</span>
<span class="go"> 1,</span>
@@ -1854,7 +1854,7 @@ 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
0x7fbc9dfe8820></span>
+<span class="go"><pyarrow.lib.Time64Array object at
0x7f0ffbfb8a60></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 685c44dd54d..6d566d6cf55 100644
--- a/docs/dev/python/parquet.html
+++ b/docs/dev/python/parquet.html
@@ -1690,7 +1690,7 @@ 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
0x7fbca0503380></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f0f84017bf0></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>
@@ -1700,7 +1700,7 @@ 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
0x7fbd17f9a8c0></span>
+<span class="go"><pyarrow._parquet.ParquetSchema object at
0x7f0ffbe6ab80></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>
@@ -1758,7 +1758,7 @@ 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
0x7fbca0500e50></span>
+<span class="go"><pyarrow._parquet.FileMetaData object at
0x7f0ffbe6e070></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>
@@ -1772,7 +1772,7 @@ 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
0x7fbd17fb17b0></span>
+<span class="go"><pyarrow._parquet.RowGroupMetaData object at
0x7f0ffbe6ebb0></span>
<span class="go"> num_columns: 4</span>
<span class="go"> num_rows: 3</span>
<span class="go"> total_byte_size: 282</span>
@@ -1780,7 +1780,7 @@ 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
0x7fbd17fb1c10></span>
+<span class="go"><pyarrow._parquet.ColumnChunkMetaData object at
0x7f0ffbe6ed90></span>
<span class="go"> file_offset: 0</span>
<span class="go"> file_path: </span>
<span class="go"> physical_type: DOUBLE</span>
@@ -1788,7 +1788,7 @@ 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>
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</main><aside class="col-md-3"><nav id="toc" aria-label="Table of
contents"><h2>On this page</h2>
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