Merge pull request #9247 from bashtage/pandas-3-compat

MAINT: Additional fixes for pandas 3

docs/source/release/index.rst

@@ -7,6 +7,7 @@ Release Notes
 .. toctree::
    :maxdepth: 1
 
+   version0.14.2
    version0.14.1
    version0.14.0
    version0.13.4-5

docs/source/release/version0.14.2.rst

@@ -0,0 +1,166 @@
+:orphan:
+
+==============
+Release 0.14.2
+==============
+
+Release summary
+===============
+
+statsmodels is using github to store the updated documentation. Two version are available:
+
+- `Stable <https://www.statsmodels.org/>`_, the latest release
+- `Development <https://www.statsmodels.org/devel/>`_, the latest build of the main branch
+
+**Warning**
+
+API stability is not guaranteed for new features, although even in
+this case changes will be made in a backwards compatible way if
+possible. The stability of a new feature depends on how much time it
+was already in statsmodels main and how much usage it has already
+seen.  If there are specific known problems or limitations, then they
+are mentioned in the docstrings.
+
+Stats
+-----
+**Issues Closed**: 22
+
+**Pull Requests Merged**: 24
+
+
+The Highlights
+==============
+This release brings compatibility with NumPy 2.0.0. This is the only key feature
+of this release. Several minor patches have been backported. These either
+fix bugs that have been documented, improve the documentation or are necessary for
+NumPy 2.0 compatability.
+
+NumPy 2.0 is only available for Python 3.9+. This means that the minimum Python
+has been increased to 3.9 to match. NumPy 2 is only required to build statsmodels,
+and statsmodels will continue to run on NumPy 1.22.3+.
+
+Note that when running using NumPy 2, all dependencies that use build against NumPy
+(e.g., Scipy and pandas) must be NumPy 2 compatible. You can continue to run against
+NumPy 1.22 - 1.26 along with other components of the scientific Python stack until
+all required dependencies have been updated.
+
+
+What's new - an overview
+========================
+
+The following lists the main new features of statsmodels 0.14.2. In addition,
+release 0.14.2 includes bug fixes, refactorings and improvements in many areas.
+
+Submodules
+----------
+
+
+``dependencies``
+~~~~~~~~~~~~~~~~
+- Bump github/codeql-action from 2 to 3  (:pr:`9098`)
+- Bump ts-graphviz/setup-graphviz from 1 to 2  (:pr:`9149`)
+
+
+
+``multivariate``
+~~~~~~~~~~~~~~~~
+- Add MultivariateLS  (:pr:`8919`)
+
+
+
+``robust``
+~~~~~~~~~~
+- Outlier robust covariance - rebased  (:pr:`8129`)
+
+
+
+``stats``
+~~~~~~~~~
+- Outlier robust covariance - rebased  (:pr:`8129`)
+
+
+
+``tsa.statespace``
+~~~~~~~~~~~~~~~~~~
+- Ensure ARIMA simulation is reproducable  (:pr:`9165`)
+
+
+
+
+
+bug-wrong
+---------
+
+A new issue label `type-bug-wrong` indicates bugs that cause that incorrect
+numbers are returned without warnings.
+(Regular bugs are mostly usability bugs or bugs that raise an exception for
+unsupported use cases.)
+`see tagged issues <https://github.com/statsmodels/statsmodels/issues?q=is%3Aissue+label%3Atype-bug-wrong+is%3Aclosed+milestone%3A0.14>`_
+
+
+Major Bugs Fixed
+================
+
+See github issues for a list of bug fixes included in this release
+
+- `Closed bugs <https://github.com/statsmodels/statsmodels/pulls?utf8=%E2%9C%93&q=is%3Apr+is%3Amerged+milestone%3A0.14+label%3Atype-bug>`_
+- `Closed bugs (wrong result) <https://github.com/statsmodels/statsmodels/pulls?q=is%3Apr+is%3Amerged+milestone%3A0.14+label%3Atype-bug-wrong>`_
+
+
+Development summary and credits
+===============================
+
+Besides receiving contributions for new and improved features and for bugfixes,
+important contributions to general maintenance for this release came from
+
+- Chad Fulton
+- Brock Mendel
+- Peter Quackenbush
+- Kerby Shedden
+- Kevin Sheppard
+
+and the general maintainer and code reviewer
+
+- Josef Perktold
+
+Additionally, many users contributed by participation in github issues and
+providing feedback.
+
+Thanks to all of the contributors for the 0.14.2 release (based on git log):
+
+- Josef Perktold
+- Kevin Sheppard
+- Manlai Amar
+- Michel De Ruiter
+- Trinh Quoc Anh
+- Zhengbo Wang
+- cppt
+- dependabot[bot]
+- s174139
+
+
+These lists of names are automatically generated based on git log, and may not
+be complete.
+
+Merged Pull Requests
+--------------------
+
+The following Pull Requests were merged since the last release:
+
+- :pr:`9029`: Update seasonal.py
+- :pr:`9098`: Bump github/codeql-action from 2 to 3
+- :pr:`9110`: BLD: Update minimums
+- :pr:`9111`: MAINT: Fix future issues in pandas
+- :pr:`9115`: MAINT: Clean up and silence some warnings
+- :pr:`9117`: edited requirements.txt
+- :pr:`9124`: MAINT: Fix future issues due to array shapes
+- :pr:`9142`: Fix linting error
+- :pr:`9143`: Fix string formatting
+- :pr:`9144`: MAINT: Replace quarterly string identified
+- :pr:`9149`: Bump ts-graphviz/setup-graphviz from 1 to 2
+- :pr:`9150`: MAINT: Fixes for future changes
+- :pr:`9158`: DOC: Fix broken in `linear_regression_diagnostics_plots`
+- :pr:`9165`: BUG: Ensure ARIMA simulation is reproducable
+- :pr:`9192`: DOC: fixed boxpierece typos
+- :pr:`9195`: MAINT: Make compatability with NumPy 2
+- :pr:`9200`: Cherry pick commits from 0.15 for 0.14.3

docs/source/release/version0.6.rst

@@ -98,7 +98,7 @@ We added a naive seasonal decomposition tool in the same vein as R's ``decompose
 
     dta = sm.datasets.co2.load_pandas().data
     # deal with missing values. see issue
-    dta.co2.interpolate(inplace=True)
+    dta = dta.co2.interpolate()
 
     res = sm.tsa.seasonal_decompose(dta.co2)
     res.plot()

examples/notebooks/autoregressive_distributed_lag.ipynb

@@ -456,7 +456,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "greene = pd.read_fwf(\"http://www.stern.nyu.edu/~wgreene/Text/Edition7/TableF5-2.txt\")\n",
+    "greene = pd.read_fwf(\"https://raw.githubusercontent.com/statsmodels/smdatasets/main/data/autoregressive-distributed-lag/green/ardl_data.txt\")\n",
     "greene.head()"
    ]
   },
@@ -718,9 +718,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

examples/notebooks/glm_formula.ipynb

@@ -20,6 +20,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -66,6 +67,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -87,6 +89,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -114,20 +117,21 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
    },
    "outputs": [],
    "source": [
-    "print(mod1.params[1])\n",
-    "print(mod2.params[1] * 2)"
+    "print(mod1.params.iloc[1])\n",
+    "print(mod2.params.iloc[1] * 2)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -141,7 +145,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/notebooks/multivariate_ls.ipynb

@@ -513,7 +513,7 @@
     "ex = pd.DataFrame(data_exog[\"prog\"].unique(), columns=[\"prog\"])\n",
     "mean_ex = data_mvreg[['read', 'write', 'science']].mean()\n",
     "\n",
-    "ex[['read', 'write', 'science']] = mean_ex\n",
+    "ex.loc[:, ['read', 'write', 'science']] = mean_ex.values\n",
     "ex"
    ]
   },
@@ -605,14 +605,6 @@
    "source": [
     "plt.plot(res._hat_matrix_diag, res.resid_distance, \".\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c4fdeb7f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -631,7 +623,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/notebooks/rolling_ls.ipynb

@@ -277,7 +277,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -291,7 +291,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.12"
   },
   "pycharm": {
    "stem_cell": {