From 4f32f3990fbba0ee440af47e23a9354fdb7a0285 Mon Sep 17 00:00:00 2001
From: Kevin Sheppard <kevin.sheppard@gmail.com>
Date: Fri, 12 Mar 2021 10:52:38 +0000
Subject: [PATCH] MAINT: Fix issues arising from future changes

Fix issues due to changes in SciPy and pandas
---
 statsmodels/regression/tests/test_rolling.py | 6 ++++--
 statsmodels/stats/descriptivestats.py        | 8 +++++++-
 statsmodels/stats/stattools.py               | 4 +++-
 3 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/statsmodels/regression/tests/test_rolling.py b/statsmodels/regression/tests/test_rolling.py
index 050de605f..f02e076d6 100644
--- a/statsmodels/regression/tests/test_rolling.py
+++ b/statsmodels/regression/tests/test_rolling.py
@@ -1,5 +1,6 @@
 from io import BytesIO
 from itertools import product
+import warnings
 
 import numpy as np
 import pandas as pd
@@ -261,8 +262,9 @@ def test_plot():
         res.plot_recursive_coefficient(variables="x4")
 
     fig = plt.Figure()
-    with pytest.warns(Warning):
-        # Just silence the warning
+    # Just silence the warning
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
         out = res.plot_recursive_coefficient(fig=fig)
     assert out is fig
     res.plot_recursive_coefficient(alpha=None, figsize=(30, 7))
diff --git a/statsmodels/stats/descriptivestats.py b/statsmodels/stats/descriptivestats.py
index 96d455ca1..d5ad2f2a5 100644
--- a/statsmodels/stats/descriptivestats.py
+++ b/statsmodels/stats/descriptivestats.py
@@ -446,8 +446,14 @@ class Description:
         else:
             iqr = mean
 
+        def _safe_jarque_bera(c):
+            a = np.asarray(c)
+            if a.shape[0] < 2:
+                return (np.nan,) * 4
+            return jarque_bera(a)
+
         jb = df.apply(
-            lambda x: list(jarque_bera(x.dropna())), result_type="expand"
+            lambda x: list(_safe_jarque_bera(x.dropna())), result_type="expand"
         ).T
         nan_mean = mean.copy()
         nan_mean.loc[nan_mean == 0] = np.nan
diff --git a/statsmodels/stats/stattools.py b/statsmodels/stats/stattools.py
index d349c472d..2ee1a6e0b 100644
--- a/statsmodels/stats/stattools.py
+++ b/statsmodels/stats/stattools.py
@@ -118,7 +118,9 @@ def jarque_bera(resids, axis=0):
     where n is the number of data points, S is the sample skewness, and K is
     the sample kurtosis of the data.
     """
-    resids = np.asarray(resids)
+    resids = np.atleast_1d(np.asarray(resids, dtype=float))
+    if resids.size < 2:
+        raise ValueError("resids must contain at least 2 elements")
     # Calculate residual skewness and kurtosis
     skew = stats.skew(resids, axis=axis)
     kurtosis = 3 + stats.kurtosis(resids, axis=axis)
-- 
2.32.0

From a9e21aef508ea98da8c5889547b8e5748986dae1 Mon Sep 17 00:00:00 2001
From: Kevin Sheppard <kevin.k.sheppard@gmail.com>
Date: Wed, 7 Apr 2021 09:52:25 +0100
Subject: [PATCH] MAINT: Fix descriptive stats with extension dtypes

Add special path for extension dtypes to remove N/A
---
 statsmodels/stats/descriptivestats.py | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/statsmodels/stats/descriptivestats.py b/statsmodels/stats/descriptivestats.py
index d5ad2f2a5..0fd3eb542 100644
--- a/statsmodels/stats/descriptivestats.py
+++ b/statsmodels/stats/descriptivestats.py
@@ -441,8 +441,20 @@ class Description:
         loc = count > 0
         mode_freq = np.full(mode.shape[0], np.nan)
         mode_freq[loc] = mode_counts[loc] / count.loc[loc]
+        # TODO: Workaround for pandas AbstractMethodError in extension
+        #  types. Remove when quantile is supported for these
+        _df = df
+        try:
+            from pandas.api.types import is_extension_array_dtype
+            _df = df.copy()
+            for col in df:
+                if is_extension_array_dtype(df[col].dtype):
+                    _df[col] = _df[col].astype(object).fillna(np.nan)
+        except ImportError:
+            pass
+
         if df.shape[1] > 0:
-            iqr = df.quantile(0.75) - df.quantile(0.25)
+            iqr = _df.quantile(0.75) - _df.quantile(0.25)
         else:
             iqr = mean
 
@@ -493,7 +505,8 @@ class Description:
             return results_df
         # Pandas before 1.0 cannot handle empty DF
         if df.shape[1] > 0:
-            perc = df.quantile(self._percentiles / 100).astype(float)
+            # TODO: Remove when extension types support quantile
+            perc = _df.quantile(self._percentiles / 100).astype(float)
         else:
             perc = pd.DataFrame(index=self._percentiles / 100, dtype=float)
         if np.all(np.floor(100 * perc.index) == (100 * perc.index)):
-- 
2.32.0