Merge branch 'main' into issue57049

Author: snitish

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 <pyarrow>`
+For more information, please see the :ref:`PyArrow user guide <pyarrow>`.
 
 .. _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/

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<api.series.str>`
    that return **numeric** output will always return a nullable integer dtype,
@@ -102,7 +102,7 @@ l. For ``StringDtype``, :ref:`string accessor methods<api.series.str>`
       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
 

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):

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.
           </p>
-          <p>Make your donation in the <a href="{{ base_url }}donate.html">donate page</a></p>
+          <p>Make your donation in the <a href="https://opencollective.com/pandas">donate page</a></p>
         </div>
       </div>
     </div>