From 2b466c2b808f2e9711f598647791675fb250a38d Mon Sep 17 00:00:00 2001
From: koushik-rout-samsung
<146946876+koushik-rout-samsung@users.noreply.github.com>
Date: Mon, 24 Feb 2025 07:42:06 +0000
Subject: [PATCH 1/3] WEB: Fix donation page (#60995)
---
web/pandas/contribute.md | 2 +-
web/pandas/donate.md | 14 --------------
2 files changed, 1 insertion(+), 15 deletions(-)
delete mode 100644 web/pandas/donate.md
diff --git a/web/pandas/contribute.md b/web/pandas/contribute.md
index 258ba149f1849..3307ddcfb1a0a 100644
--- a/web/pandas/contribute.md
+++ b/web/pandas/contribute.md
@@ -48,7 +48,7 @@ and about current sponsors in the [sponsors page]({{ base_url }}about/sponsors.h
infrastructure, travel expenses for our volunteer contributors to attend
the in-person sprints, or to give small grants to develop features.
- Make your donation in the donate page
+ Make your donation in the donate page
diff --git a/web/pandas/donate.md b/web/pandas/donate.md
deleted file mode 100644
index 69db7e4648e77..0000000000000
--- a/web/pandas/donate.md
+++ /dev/null
@@ -1,14 +0,0 @@
-# Donate to pandas
-
-
-
-
-
-_pandas_ is a Sponsored Project of [NumFOCUS](https://numfocus.org/), a 501(c)(3) nonprofit charity in the United States.
-NumFOCUS provides _pandas_ with fiscal, legal, and administrative support to help ensure the
-health and sustainability of the project. Visit numfocus.org for more information.
-
-Donations to _pandas_ are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible
-to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.
From 6bd74fab5f2dfe3512ecbd2797808399411bd452 Mon Sep 17 00:00:00 2001
From: "Christine P. Chai"
Date: Mon, 24 Feb 2025 10:25:34 -0800
Subject: [PATCH 2/3] DOC: Add missing punctuation to pandas documentation
(#60982)
* DOC: Add missing punctuation in text.rst
* DOC: Also add missing punctuation in arrays.rst
---
doc/source/reference/arrays.rst | 6 +++---
doc/source/user_guide/text.rst | 12 ++++++------
2 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/doc/source/reference/arrays.rst b/doc/source/reference/arrays.rst
index a631cd517e3c2..5be08f163e6ce 100644
--- a/doc/source/reference/arrays.rst
+++ b/doc/source/reference/arrays.rst
@@ -61,7 +61,7 @@ is an :class:`ArrowDtype`.
support as NumPy including first-class nullability support for all data types, immutability and more.
The table below shows the equivalent pyarrow-backed (``pa``), pandas extension, and numpy (``np``) types that are recognized by pandas.
-Pyarrow-backed types below need to be passed into :class:`ArrowDtype` to be recognized by pandas e.g. ``pd.ArrowDtype(pa.bool_())``
+Pyarrow-backed types below need to be passed into :class:`ArrowDtype` to be recognized by pandas e.g. ``pd.ArrowDtype(pa.bool_())``.
=============================================== ========================== ===================
PyArrow type pandas extension type NumPy type
@@ -114,7 +114,7 @@ values.
ArrowDtype
-For more information, please see the :ref:`PyArrow user guide `
+For more information, please see the :ref:`PyArrow user guide `.
.. _api.arrays.datetime:
@@ -495,7 +495,7 @@ a :class:`CategoricalDtype`.
CategoricalDtype.categories
CategoricalDtype.ordered
-Categorical data can be stored in a :class:`pandas.Categorical`
+Categorical data can be stored in a :class:`pandas.Categorical`:
.. autosummary::
:toctree: api/
diff --git a/doc/source/user_guide/text.rst b/doc/source/user_guide/text.rst
index 827e7a3c884d9..e96faecd9a266 100644
--- a/doc/source/user_guide/text.rst
+++ b/doc/source/user_guide/text.rst
@@ -13,7 +13,7 @@ Text data types
There are two ways to store text data in pandas:
-1. ``object`` -dtype NumPy array.
+1. ``object`` dtype NumPy array.
2. :class:`StringDtype` extension type.
We recommend using :class:`StringDtype` to store text data.
@@ -40,20 +40,20 @@ to significantly increase the performance and lower the memory overhead of
and parts of the API may change without warning.
For backwards-compatibility, ``object`` dtype remains the default type we
-infer a list of strings to
+infer a list of strings to:
.. ipython:: python
pd.Series(["a", "b", "c"])
-To explicitly request ``string`` dtype, specify the ``dtype``
+To explicitly request ``string`` dtype, specify the ``dtype``:
.. ipython:: python
pd.Series(["a", "b", "c"], dtype="string")
pd.Series(["a", "b", "c"], dtype=pd.StringDtype())
-Or ``astype`` after the ``Series`` or ``DataFrame`` is created
+Or ``astype`` after the ``Series`` or ``DataFrame`` is created:
.. ipython:: python
@@ -88,7 +88,7 @@ Behavior differences
^^^^^^^^^^^^^^^^^^^^
These are places where the behavior of ``StringDtype`` objects differ from
-``object`` dtype
+``object`` dtype:
l. For ``StringDtype``, :ref:`string accessor methods`
that return **numeric** output will always return a nullable integer dtype,
@@ -102,7 +102,7 @@ l. For ``StringDtype``, :ref:`string accessor methods`
s.str.count("a")
s.dropna().str.count("a")
- Both outputs are ``Int64`` dtype. Compare that with object-dtype
+ Both outputs are ``Int64`` dtype. Compare that with object-dtype:
.. ipython:: python
From d575eeaeed67828bc4ae53afb1ee74654a149fd8 Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
Date: Mon, 24 Feb 2025 13:39:27 -0800
Subject: [PATCH 3/3] TST: Change sqlite test query string values to single
quotes (#61000)
---
pandas/tests/io/test_sql.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/pandas/tests/io/test_sql.py b/pandas/tests/io/test_sql.py
index 97c856d3b6c40..13576c891ad2c 100644
--- a/pandas/tests/io/test_sql.py
+++ b/pandas/tests/io/test_sql.py
@@ -4282,11 +4282,11 @@ def test_xsqlite_execute_fail(sqlite_buildin):
cur.execute(create_sql)
with sql.pandasSQL_builder(sqlite_buildin) as pandas_sql:
- pandas_sql.execute('INSERT INTO test VALUES("foo", "bar", 1.234)')
- pandas_sql.execute('INSERT INTO test VALUES("foo", "baz", 2.567)')
+ pandas_sql.execute("INSERT INTO test VALUES('foo', 'bar', 1.234)")
+ pandas_sql.execute("INSERT INTO test VALUES('foo', 'baz', 2.567)")
with pytest.raises(sql.DatabaseError, match="Execution failed on sql"):
- pandas_sql.execute('INSERT INTO test VALUES("foo", "bar", 7)')
+ pandas_sql.execute("INSERT INTO test VALUES('foo', 'bar', 7)")
def test_xsqlite_execute_closed_connection():
@@ -4304,7 +4304,7 @@ def test_xsqlite_execute_closed_connection():
cur.execute(create_sql)
with sql.pandasSQL_builder(conn) as pandas_sql:
- pandas_sql.execute('INSERT INTO test VALUES("foo", "bar", 1.234)')
+ pandas_sql.execute("INSERT INTO test VALUES('foo', 'bar', 1.234)")
msg = "Cannot operate on a closed database."
with pytest.raises(sqlite3.ProgrammingError, match=msg):