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docs: Update changelog
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lewisjared committed Apr 1, 2023
1 parent 0eaf616 commit 620626c
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Showing 4 changed files with 12 additions and 3 deletions.
2 changes: 1 addition & 1 deletion .github/workflows/ci-cd-workflow.yml
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Expand Up @@ -55,7 +55,7 @@ jobs:
strategy:
matrix:
os: ["ubuntu-latest", "macos-latest", "windows-latest"]
python-version: [3.7, 3.8, 3.9]
python-version: [3.7, 3.9, 3.11]
exclude:
# netCDF4>=1.6.0 doesn't include prebuilt wheels for windows/Python3.7
# Older netCDF4 or self-built versions will likely work
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1 change: 1 addition & 0 deletions CHANGELOG.rst
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Expand Up @@ -4,6 +4,7 @@ Changelog
master
------

- (`#223 <https://github.com/openscm/scmdata/pull/223>`_) Loosen the pandas requirement to cover pandas>=1.4.3. Also support officially support Python 3.10 and 3.11
- (`#218 <https://github.com/openscm/scmdata/pull/218>`_) Replaced internal calls to ``RunGroupby.map`` with ``RunGroupby.apply``
- (`#210 <https://github.com/openscm/scmdata/pull/210>`_) Update github actions to avoid the use of a deprecated workflow command

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2 changes: 2 additions & 0 deletions setup.cfg
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Expand Up @@ -23,6 +23,8 @@ classifiers =
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
Programming Language :: Python :: 3.11

[options]
packages = find:
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10 changes: 8 additions & 2 deletions tests/integration/test_processing.py
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Expand Up @@ -414,7 +414,9 @@ def test_exceedance_probabilities_over_time(
exp = pd.DataFrame(
np.array(exp_vals)[np.newaxis, :],
index=exp_idx,
columns=test_processing_scm_df.time_points.to_index(),
# This forces the coercion to a DateTimeIndex which now happens automatically for
# pandas>=1.4.3
columns=pd.Index(test_processing_scm_df.time_points.to_index()),
)
exp.index = exp.index.set_levels(
[_get_calculate_exeedance_probs_expected_name(output_name, threshold)],
Expand Down Expand Up @@ -444,7 +446,11 @@ def test_exceedance_probabilities_over_time_multiple_res(
start.meta.drop(["ensemble_member"], axis="columns").drop_duplicates()
)

exp = pd.DataFrame(exp_vals, index=exp_idx, columns=start.time_points.to_index())
exp = pd.DataFrame(
exp_vals,
index=exp_idx,
columns=pd.Index(start.time_points.to_index()),
)
exp.index = exp.index.set_levels(
[_get_calculate_exeedance_probs_expected_name(None, threshold)],
level="variable",
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