Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Deal with the mad aggregation being removed in Pandas 2 #602

Merged
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 28 additions & 4 deletions tests/dataframe/test_groupby_pytest.py
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,17 @@

from tests.common import TestData

PANDAS_MAJOR_VERSION = int(pd.__version__.split(".")[0])


# The mean absolute difference (mad) aggregation has been removed from
# pandas with major version 2:
# https://github.com/pandas-dev/pandas/issues/11787
# To compare whether eland's version of it works, we need to implement
# it here ourselves.
def mad(x):
return abs(x - x.mean()).mean()


class TestGroupbyDataFrame(TestData):
funcs = ["max", "min", "mean", "sum"]
Expand Down Expand Up @@ -71,7 +82,7 @@ def test_groupby_aggregate_single_aggs(self, pd_agg):
@pytest.mark.parametrize("dropna", [True, False])
@pytest.mark.parametrize("pd_agg", ["max", "min", "mean", "sum", "median"])
def test_groupby_aggs_numeric_only_true(self, pd_agg, dropna):
# Pandas has numeric_only applicable for the above aggs with groupby only.
# Pandas has numeric_only applicable for the above aggs with groupby only.

pd_flights = self.pd_flights().filter(self.filter_data)
ed_flights = self.ed_flights().filter(self.filter_data)
Expand All @@ -95,7 +106,14 @@ def test_groupby_aggs_mad_var_std(self, pd_agg, dropna):
pd_flights = self.pd_flights().filter(self.filter_data)
ed_flights = self.ed_flights().filter(self.filter_data)

pd_groupby = getattr(pd_flights.groupby("Cancelled", dropna=dropna), pd_agg)()
# The mad aggregation has been removed in Pandas 2, so we need to use
# our own implementation if we run the tests with Pandas 2 or higher
if PANDAS_MAJOR_VERSION >= 2 and pd_agg == "mad":
pd_groupby = pd_flights.groupby("Cancelled", dropna=dropna).aggregate(mad)
else:
pd_groupby = getattr(
pd_flights.groupby("Cancelled", dropna=dropna), pd_agg
)()
ed_groupby = getattr(ed_flights.groupby("Cancelled", dropna=dropna), pd_agg)(
numeric_only=True
)
Expand Down Expand Up @@ -211,14 +229,20 @@ def test_groupby_dataframe_mad(self):
pd_flights = self.pd_flights().filter(self.filter_data + ["DestCountry"])
ed_flights = self.ed_flights().filter(self.filter_data + ["DestCountry"])

pd_mad = pd_flights.groupby("DestCountry").mad()
if PANDAS_MAJOR_VERSION < 2:
pd_mad = pd_flights.groupby("DestCountry").mad()
else:
pd_mad = pd_flights.groupby("DestCountry").aggregate(mad)
ed_mad = ed_flights.groupby("DestCountry").mad()

assert_index_equal(pd_mad.columns, ed_mad.columns)
assert_index_equal(pd_mad.index, ed_mad.index)
assert_series_equal(pd_mad.dtypes, ed_mad.dtypes)

pd_min_mad = pd_flights.groupby("DestCountry").aggregate(["min", "mad"])
if PANDAS_MAJOR_VERSION < 2:
pd_min_mad = pd_flights.groupby("DestCountry").aggregate(["min", "mad"])
else:
pd_min_mad = pd_flights.groupby("DestCountry").aggregate(["min", mad])
ed_min_mad = ed_flights.groupby("DestCountry").aggregate(["min", "mad"])

assert_index_equal(pd_min_mad.columns, ed_min_mad.columns)
Expand Down