[superset] branch master updated: chore: Bump pandas to 1.4.4 (#21285)

[vi...@apache.org]

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villebro pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/superset.git


The following commit(s) were added to refs/heads/master by this push:
     new 60db0bb47e chore: Bump pandas to 1.4.4 (#21285)
60db0bb47e is described below

commit 60db0bb47e5c2f73aec57b3d503e8111c30f2e44
Author: EugeneTorap <ev...@gmail.com>
AuthorDate: Fri Sep 2 13:05:22 2022 +0300

    chore: Bump pandas to 1.4.4 (#21285)
---
 requirements/base.txt                                | 2 +-
 setup.py                                             | 2 +-
 superset/utils/pandas_postprocessing/contribution.py | 3 ---
 3 files changed, 2 insertions(+), 5 deletions(-)

diff --git a/requirements/base.txt b/requirements/base.txt
index ead18fba5b..b969448295 100644
--- a/requirements/base.txt
+++ b/requirements/base.txt
@@ -185,7 +185,7 @@ packaging==21.3
     # via
     #   bleach
     #   deprecation
-pandas==1.4.3
+pandas==1.4.4
     # via apache-superset
 parsedatetime==2.6
     # via apache-superset
diff --git a/setup.py b/setup.py
index dc2f4e208c..dcfc3726ba 100644
--- a/setup.py
+++ b/setup.py
@@ -100,7 +100,7 @@ setup(
         "markdown>=3.0",
         "msgpack>=1.0.0, <1.1",
         "numpy==1.22.1",
-        "pandas>=1.4.3, <1.5",
+        "pandas>=1.4.4, <1.5",
         "parsedatetime",
         "pgsanity",
         "polyline",
diff --git a/superset/utils/pandas_postprocessing/contribution.py b/superset/utils/pandas_postprocessing/contribution.py
index 86ef271397..2bfc6f4be6 100644
--- a/superset/utils/pandas_postprocessing/contribution.py
+++ b/superset/utils/pandas_postprocessing/contribution.py
@@ -49,9 +49,6 @@ def contribution(
     """
     contribution_df = df.copy()
     numeric_df = contribution_df.select_dtypes(include=["number", Decimal])
-    # TODO: copy needed due to following regression in 1.4, remove if not needed:
-    # https://github.com/pandas-dev/pandas/issues/48090
-    numeric_df = numeric_df.copy()
     numeric_df.fillna(0, inplace=True)
     # verify column selections
     if columns: