Merge pull request statsmodels#9683 from bashtage/fix-notebooks

DOC: Fix issues affecting notebooks

Author: bashtage

examples/notebooks/gee_score_test_simulation.ipynb

@@ -22,8 +22,9 @@
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd\n",
-    "import statsmodels.api as sm\n",
-    "from scipy.stats.distributions import norm, poisson"
+    "from scipy.stats.distributions import norm, poisson\n",
+    "\n",
+    "import statsmodels.api as sm"
    ]
   },
   {

examples/notebooks/kernel_density.ipynb

@@ -32,8 +32,9 @@
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "import statsmodels.api as sm\n",
     "from scipy import stats\n",
+    "\n",
+    "import statsmodels.api as sm\n",
     "from statsmodels.distributions.mixture_rvs import mixture_rvs"
    ]
   },

examples/notebooks/mstl_decomposition.ipynb

@@ -31,15 +31,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import matplotlib.pyplot as plt\n",
     "import datetime\n",
-    "import pandas as pd\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "import pandas as pd\n",
     "import seaborn as sns\n",
     "from pandas.plotting import register_matplotlib_converters\n",
     "\n",
-    "from statsmodels.tsa.seasonal import MSTL\n",
-    "from statsmodels.tsa.seasonal import DecomposeResult\n",
+    "from statsmodels.tsa.seasonal import MSTL, DecomposeResult\n",
     "\n",
     "register_matplotlib_converters()\n",
     "sns.set_style(\"darkgrid\")"
@@ -92,7 +92,7 @@
     "weekly_seasonality = 10 * np.sin(2 * np.pi * t / (24 * 7))\n",
     "trend = 0.0001 * t**2\n",
     "y = trend + daily_seasonality + weekly_seasonality + np.random.randn(len(t))\n",
-    "ts = pd.date_range(start=\"2020-01-01\", freq=\"H\", periods=len(t))\n",
+    "ts = pd.date_range(start=\"2020-01-01\", freq=\"h\", periods=len(t))\n",
     "df = pd.DataFrame(data=y, index=ts, columns=[\"y\"])"
    ]
   },
@@ -323,7 +323,7 @@
     "timeseries = timeseries[mask]\n",
     "\n",
     "# Resample to hourly\n",
-    "timeseries = timeseries.set_index(\"ds\").resample(\"H\").sum()\n",
+    "timeseries = timeseries.set_index(\"ds\").resample(\"h\").sum()\n",
     "timeseries.head()"
    ]
   },
@@ -478,7 +478,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -492,7 +492,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.7"
+   "version": "3.12.9"
   }
  },
  "nbformat": 4,

examples/notebooks/rolling_ls.ipynb

@@ -33,6 +33,7 @@
     "import pandas as pd\n",
     "import pandas_datareader as pdr\n",
     "import seaborn\n",
+    "\n",
     "import statsmodels.api as sm\n",
     "from statsmodels.regression.rolling import RollingOLS\n",
     "\n",

examples/notebooks/variance_components.ipynb

@@ -18,6 +18,7 @@
    "source": [
     "import numpy as np\n",
     "import pandas as pd\n",
+    "\n",
     "import statsmodels.api as sm\n",
     "from statsmodels.regression.mixed_linear_model import VCSpec"
    ]

statsmodels/nonparametric/kde.py

@@ -265,7 +265,7 @@ def entropy(self):
 
         def entr(x, s):
             pdf = kern.density(s, x)
-            return pdf * np.log(pdf + 1e-12)
+            return np.squeeze(pdf * np.log(pdf + 1e-12))
 
         kern = self.kernel