From ac68115b3beb0f1c3ce6dba4800ebccf34e1cfdf Mon Sep 17 00:00:00 2001
From: Thomas Li <47963215+lithomas1@users.noreply.github.com>
Date: Fri, 16 Jul 2021 06:15:37 -0700
Subject: [PATCH 1/2] CI: Remove xfail for xpassing test for Python 3.8
 (#42558)

---
 pandas/tests/scalar/timedelta/test_arithmetic.py | 12 +-----------
 1 file changed, 1 insertion(+), 11 deletions(-)

diff --git a/pandas/tests/scalar/timedelta/test_arithmetic.py b/pandas/tests/scalar/timedelta/test_arithmetic.py
index 9f6cdbb81bd89..7dfda0463ecaf 100644
--- a/pandas/tests/scalar/timedelta/test_arithmetic.py
+++ b/pandas/tests/scalar/timedelta/test_arithmetic.py
@@ -10,7 +10,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import is_numpy_dev
 from pandas.errors import OutOfBoundsTimedelta
 
 import pandas as pd
@@ -18,7 +17,6 @@
     NaT,
     Timedelta,
     Timestamp,
-    compat,
     offsets,
 )
 import pandas._testing as tm
@@ -434,15 +432,7 @@ def test_td_div_numeric_scalar(self):
         "nan",
         [
             np.nan,
-            pytest.param(
-                np.float64("NaN"),
-                marks=pytest.mark.xfail(
-                    # Works on numpy dev only in python 3.9
-                    is_numpy_dev and not compat.PY39,
-                    raises=RuntimeWarning,
-                    reason="https://github.com/pandas-dev/pandas/issues/31992",
-                ),
-            ),
+            np.float64("NaN"),
             float("nan"),
         ],
     )

From 318bed9f7c16c3352178cbf68e8dddfaba32ed6d Mon Sep 17 00:00:00 2001
From: GYvan <78673871+GYvan@users.noreply.github.com>
Date: Fri, 16 Jul 2021 15:26:03 +0200
Subject: [PATCH 2/2] Modified ecosystem.rst to include ibis (#42554)

---
 doc/source/ecosystem.rst | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/doc/source/ecosystem.rst b/doc/source/ecosystem.rst
index ee061e7b7d3e6..e58779c090d8f 100644
--- a/doc/source/ecosystem.rst
+++ b/doc/source/ecosystem.rst
@@ -445,6 +445,12 @@ provides a familiar ``DataFrame`` interface for out-of-core, parallel and distri
 
 Dask-ML enables parallel and distributed machine learning using Dask alongside existing machine learning libraries like Scikit-Learn, XGBoost, and TensorFlow.
 
+`Ibis <https://ibis-project.org/docs/>`__
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Ibis offers a standard way to write analytics code, that can be run in multiple engines. It helps in bridging the gap between local Python environments (like pandas) and remote storage and execution systems like Hadoop components (like HDFS, Impala, Hive, Spark) and SQL databases (Postgres, etc.).
+
+
 `Koalas <https://koalas.readthedocs.io/en/latest/>`__
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~