Merge branch 'main' of https://github.com/pandas-dev/pandas into depr_core_groupby

Author: rhshadrach

ci/code_checks.sh

@@ -176,9 +176,8 @@ fi
 
 ### SINGLE-PAGE DOCS ###
 if [[ -z "$CHECK" || "$CHECK" == "single-docs" ]]; then
-    python doc/make.py --warnings-are-errors --single pandas.Series.value_counts
-    python doc/make.py --warnings-are-errors --single pandas.Series.str.split
-    python doc/make.py clean
+    python doc/make.py --warnings-are-errors --no-browser --single pandas.Series.value_counts
+    python doc/make.py --warnings-are-errors --no-browser --single pandas.Series.str.split
 fi
 
 exit $RET

doc/make.py

@@ -45,12 +45,14 @@ def __init__(
         single_doc=None,
         verbosity=0,
         warnings_are_errors=False,
+        no_browser=False,
     ) -> None:
         self.num_jobs = num_jobs
         self.include_api = include_api
         self.whatsnew = whatsnew
         self.verbosity = verbosity
         self.warnings_are_errors = warnings_are_errors
+        self.no_browser = no_browser
 
         if single_doc:
             single_doc = self._process_single_doc(single_doc)
@@ -234,11 +236,11 @@ def html(self):
             os.remove(zip_fname)
 
         if ret_code == 0:
-            if self.single_doc_html is not None:
+            if self.single_doc_html is not None and not self.no_browser:
                 self._open_browser(self.single_doc_html)
             else:
                 self._add_redirects()
-                if self.whatsnew:
+                if self.whatsnew and not self.no_browser:
                     self._open_browser(os.path.join("whatsnew", "index.html"))
 
         return ret_code
@@ -349,6 +351,12 @@ def main():
         action="store_true",
         help="fail if warnings are raised",
     )
+    argparser.add_argument(
+        "--no-browser",
+        help="Don't open browser",
+        default=False,
+        action="store_true",
+    )
     args = argparser.parse_args()
 
     if args.command not in cmds:
@@ -374,6 +382,7 @@ def main():
         args.single,
         args.verbosity,
         args.warnings_are_errors,
+        args.no_browser,
     )
     return getattr(builder, args.command)()
 

doc/source/development/contributing_codebase.rst

@@ -540,7 +540,7 @@ xfail during the testing phase. To do so, use the ``request`` fixture:
 
     def test_xfail(request):
         mark = pytest.mark.xfail(raises=TypeError, reason="Indicate why here")
-        request.node.add_marker(mark)
+        request.applymarker(mark)
 
 xfail is not to be used for tests involving failure due to invalid user arguments.
 For these tests, we need to verify the correct exception type and error message

doc/source/getting_started/comparison/comparison_with_sql.rst

@@ -164,24 +164,24 @@ The pandas equivalent would be:
 
     tips.groupby("sex").size()
 
-Notice that in the pandas code we used :meth:`~pandas.core.groupby.DataFrameGroupBy.size` and not
-:meth:`~pandas.core.groupby.DataFrameGroupBy.count`. This is because
-:meth:`~pandas.core.groupby.DataFrameGroupBy.count` applies the function to each column, returning
+Notice that in the pandas code we used :meth:`.DataFrameGroupBy.size` and not
+:meth:`.DataFrameGroupBy.count`. This is because
+:meth:`.DataFrameGroupBy.count` applies the function to each column, returning
 the number of ``NOT NULL`` records within each.
 
 .. ipython:: python
 
     tips.groupby("sex").count()
 
-Alternatively, we could have applied the :meth:`~pandas.core.groupby.DataFrameGroupBy.count` method
+Alternatively, we could have applied the :meth:`.DataFrameGroupBy.count` method
 to an individual column:
 
 .. ipython:: python
 
     tips.groupby("sex")["total_bill"].count()
 
 Multiple functions can also be applied at once. For instance, say we'd like to see how tip amount
-differs by day of the week - :meth:`~pandas.core.groupby.DataFrameGroupBy.agg` allows you to pass a dictionary
+differs by day of the week - :meth:`.DataFrameGroupBy.agg` allows you to pass a dictionary
 to your grouped DataFrame, indicating which functions to apply to specific columns.
 
 .. code-block:: sql

doc/source/user_guide/10min.rst

@@ -525,7 +525,7 @@ See the :ref:`Grouping section <groupby>`.
    df
 
 Grouping by a column label, selecting column labels, and then applying the
-:meth:`~pandas.core.groupby.DataFrameGroupBy.sum` function to the resulting
+:meth:`.DataFrameGroupBy.sum` function to the resulting
 groups:
 
 .. ipython:: python

doc/source/user_guide/enhancingperf.rst

@@ -453,7 +453,7 @@ by evaluate arithmetic and boolean expression all at once for large :class:`~pan
    :func:`~pandas.eval` is many orders of magnitude slower for
    smaller expressions or objects than plain Python. A good rule of thumb is
    to only use :func:`~pandas.eval` when you have a
-   :class:`~pandas.core.frame.DataFrame` with more than 10,000 rows.
+   :class:`.DataFrame` with more than 10,000 rows.
 
 Supported syntax
 ~~~~~~~~~~~~~~~~

doc/source/user_guide/groupby.rst

@@ -458,7 +458,7 @@ Selecting a group
 -----------------
 
 A single group can be selected using
-:meth:`~pandas.core.groupby.DataFrameGroupBy.get_group`:
+:meth:`.DataFrameGroupBy.get_group`:
 
 .. ipython:: python
 
@@ -1531,7 +1531,7 @@ Enumerate groups
 
 To see the ordering of the groups (as opposed to the order of rows
 within a group given by ``cumcount``) you can use
-:meth:`~pandas.core.groupby.DataFrameGroupBy.ngroup`.
+:meth:`.DataFrameGroupBy.ngroup`.
 
 
 
@@ -1660,7 +1660,7 @@ Regroup columns of a DataFrame according to their sum, and sum the aggregated on
 Multi-column factorization
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-By using :meth:`~pandas.core.groupby.DataFrameGroupBy.ngroup`, we can extract
+By using :meth:`.DataFrameGroupBy.ngroup`, we can extract
 information about the groups in a way similar to :func:`factorize` (as described
 further in the :ref:`reshaping API <reshaping.factorize>`) but which applies
 naturally to multiple columns of mixed type and different

doc/source/user_guide/io.rst

@@ -2701,7 +2701,7 @@ in the method ``to_string`` described above.
 .. note::
 
    Not all of the possible options for ``DataFrame.to_html`` are shown here for
-   brevity's sake. See :func:`~pandas.core.frame.DataFrame.to_html` for the
+   brevity's sake. See :func:`.DataFrame.to_html` for the
    full set of options.
 
 .. note::
@@ -6020,7 +6020,7 @@ Stata format
 Writing to stata format
 '''''''''''''''''''''''
 
-The method :func:`~pandas.core.frame.DataFrame.to_stata` will write a DataFrame
+The method :func:`.DataFrame.to_stata` will write a DataFrame
 into a .dta file. The format version of this file is always 115 (Stata 12).
 
 .. ipython:: python
@@ -6060,7 +6060,7 @@ outside of this range, the variable is cast to ``int16``.
 .. warning::
 
   :class:`~pandas.io.stata.StataWriter` and
-  :func:`~pandas.core.frame.DataFrame.to_stata` only support fixed width
+  :func:`.DataFrame.to_stata` only support fixed width
   strings containing up to 244 characters, a limitation imposed by the version
   115 dta file format. Attempting to write *Stata* dta files with strings
   longer than 244 characters raises a ``ValueError``.

doc/source/whatsnew/v0.17.1.rst

@@ -43,7 +43,7 @@ We've added *experimental* support for conditional HTML formatting:
 the visual styling of a DataFrame based on the data.
 The styling is accomplished with HTML and CSS.
 Accesses the styler class with the :attr:`pandas.DataFrame.style`, attribute,
-an instance of :class:`~pandas.core.style.Styler` with your data attached.
+an instance of :class:`.Styler` with your data attached.
 
 Here's a quick example:
 
@@ -58,7 +58,7 @@ We can render the HTML to get the following table.
 .. raw:: html
    :file: whatsnew_0171_html_table.html
 
-:class:`~pandas.core.style.Styler` interacts nicely with the Jupyter Notebook.
+:class:`.Styler` interacts nicely with the Jupyter Notebook.
 See the :ref:`documentation </user_guide/style.ipynb>` for more.
 
 .. _whatsnew_0171.enhancements:

doc/source/whatsnew/v0.20.2.rst

@@ -28,8 +28,8 @@ Enhancements
 - Unblocked access to additional compression types supported in pytables: 'blosc:blosclz, 'blosc:lz4', 'blosc:lz4hc', 'blosc:snappy', 'blosc:zlib', 'blosc:zstd' (:issue:`14478`)
 - ``Series`` provides a ``to_latex`` method (:issue:`16180`)
 
-- A new groupby method :meth:`~pandas.core.groupby.GroupBy.ngroup`,
-  parallel to the existing :meth:`~pandas.core.groupby.GroupBy.cumcount`,
+- A new groupby method :meth:`.GroupBy.ngroup`,
+  parallel to the existing :meth:`.GroupBy.cumcount`,
   has been added to return the group order (:issue:`11642`); see
   :ref:`here <groupby.ngroup>`.