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

Author: rhshadrach

.github/workflows/sdist.yml

@@ -30,7 +30,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
     concurrency:
       # https://github.community/t/concurrecy-not-work-for-push/183068/7
       group: ${{ github.event_name == 'push' && github.run_number || github.ref }}-${{matrix.python-version}}-sdist
@@ -42,7 +42,7 @@ jobs:
         fetch-depth: 0
 
     - name: Set up Python
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
 
@@ -86,6 +86,8 @@ jobs:
           pip install numpy==1.20.3 ;;
         3.10)
           pip install numpy==1.21.2 ;;
+        3.11)
+          pip install numpy==1.23.2 ;;
         esac
 
     - name: Import pandas

asv_bench/benchmarks/groupby.py

@@ -310,7 +310,7 @@ def time_different_python_functions_multicol(self, df):
         df.groupby(["key1", "key2"]).agg([sum, min, max])
 
     def time_different_python_functions_singlecol(self, df):
-        df.groupby("key1").agg([sum, min, max])
+        df.groupby("key1")[["value1", "value2", "value3"]].agg([sum, min, max])
 
 
 class GroupStrings:

ci/deps/actions-38-minimum_versions.yaml

@@ -25,14 +25,14 @@ dependencies:
   - blosc=1.21.0
   - bottleneck=1.3.2
   - brotlipy=0.7.0
-  - fastparquet=0.4.0
+  - fastparquet=0.6.3
   - fsspec=2021.07.0
   - html5lib=1.1
   - hypothesis=6.13.0
   - gcsfs=2021.07.0
   - jinja2=3.0.0
   - lxml=4.6.3
-  - matplotlib=3.3.2
+  - matplotlib=3.6.0
   - numba=0.53.1
   - numexpr=2.7.3
   - odfpy=1.4.1

doc/source/conf.py

@@ -105,7 +105,7 @@
 
                 if fname == "index.rst" and os.path.abspath(dirname) == source_path:
                     continue
-                elif pattern == "-api" and reldir.startswith("reference"):
+                if pattern == "-api" and reldir.startswith("reference"):
                     exclude_patterns.append(fname)
                 elif (
                     pattern == "whatsnew"

doc/source/getting_started/install.rst

@@ -310,7 +310,7 @@ Can be managed as optional_extra with ``pandas[plot, output_formatting]``, depen
 ========================= ================== ================== =============================================================
 Dependency                Minimum Version    optional_extra     Notes
 ========================= ================== ================== =============================================================
-matplotlib                3.3.2              plot               Plotting library
+matplotlib                3.6.0              plot               Plotting library
 Jinja2                    3.0.0              output_formatting  Conditional formatting with DataFrame.style
 tabulate                  0.8.9              output_formatting  Printing in Markdown-friendly format (see `tabulate`_)
 ========================= ================== ================== =============================================================

doc/source/user_guide/basics.rst

@@ -1039,34 +1039,6 @@ not noted for a particular column will be ``NaN``:
 
    tsdf.agg({"A": ["mean", "min"], "B": "sum"})
 
-.. _basics.aggregation.mixed_string:
-
-Mixed dtypes
-++++++++++++
-
-.. deprecated:: 1.4.0
-   Attempting to determine which columns cannot be aggregated and silently dropping them from the results is deprecated and will be removed in a future version. If any porition of the columns or operations provided fail, the call to ``.agg`` will raise.
-
-When presented with mixed dtypes that cannot aggregate, ``.agg`` will only take the valid
-aggregations. This is similar to how ``.groupby.agg`` works.
-
-.. ipython:: python
-
-   mdf = pd.DataFrame(
-       {
-           "A": [1, 2, 3],
-           "B": [1.0, 2.0, 3.0],
-           "C": ["foo", "bar", "baz"],
-           "D": pd.date_range("20130101", periods=3),
-       }
-   )
-   mdf.dtypes
-
-.. ipython:: python
-   :okwarning:
-
-   mdf.agg(["min", "sum"])
-
 .. _basics.aggregation.custom_describe:
 
 Custom describe

doc/source/user_guide/groupby.rst

@@ -1007,7 +1007,7 @@ functions:
 .. ipython:: python
    :okwarning:
 
-   grouped = df.groupby("A")
+   grouped = df.groupby("A")[["C", "D"]]
    grouped.agg(lambda x: x.std())
 
 But, it's rather verbose and can be untidy if you need to pass additional

doc/source/user_guide/options.rst

@@ -249,7 +249,7 @@ displayed when calling :meth:`~pandas.DataFrame.info`.
 ``display.max_info_rows``: :meth:`~pandas.DataFrame.info` will usually show null-counts for each column.
 For a large :class:`DataFrame`, this can be quite slow. ``max_info_rows`` and ``max_info_cols``
 limit this null check to the specified rows and columns respectively. The :meth:`~pandas.DataFrame.info`
-keyword argument ``null_counts=True`` will override this.
+keyword argument ``show_counts=True`` will override this.
 
 .. ipython:: python
 

doc/source/whatsnew/v0.13.0.rst

@@ -733,7 +733,7 @@ Enhancements
 
 .. _scipy: http://www.scipy.org
 .. _documentation: http://docs.scipy.org/doc/scipy/reference/interpolate.html#univariate-interpolation
-.. _guide: http://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html
+.. _guide: https://docs.scipy.org/doc/scipy/tutorial/interpolate.html
 
 - ``to_csv`` now takes a ``date_format`` keyword argument that specifies how
   output datetime objects should be formatted. Datetimes encountered in the

doc/source/whatsnew/v0.20.0.rst

@@ -104,10 +104,13 @@ aggregations. This is similar to how groupby ``.agg()`` works. (:issue:`15015`)
                       'D': pd.date_range('20130101', periods=3)})
    df.dtypes
 
-.. ipython:: python
-   :okwarning:
+.. code-block:: python
 
-   df.agg(['min', 'sum'])
+   In [10]: df.agg(['min', 'sum'])
+   Out[10]:
+        A    B          C          D
+   min  1  1.0        bar 2013-01-01
+   sum  6  6.0  foobarbaz        NaT
 
 .. _whatsnew_0200.enhancements.dataio_dtype:
 

doc/source/whatsnew/v1.5.2.rst

@@ -14,14 +14,16 @@ including other versions of pandas.
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :meth:`Series.replace` raising ``RecursionError`` with numeric dtype and when specifying ``value=None`` (:issue:`45725`)
+- Fixed regression in :meth:`DataFrame.plot` preventing :class:`~matplotlib.colors.Colormap` instance
+  from being passed using the ``colormap`` argument if Matplotlib 3.6+ is used (:issue:`49374`)
 -
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_152.bug_fixes:
 
 Bug fixes
 ~~~~~~~~~
--
+- Bug in the Copy-on-Write implementation losing track of views in certain chained indexing cases (:issue:`48996`)
 -
 
 .. ---------------------------------------------------------------------------