PyPSA / linopy

Linear optimization with N-D labeled arrays in Python
https://linopy.readthedocs.io
MIT License
155 stars 43 forks source link

explicitly use `from_pandas_multiindex` in groupby function #182

Closed FabianHofmann closed 9 months ago

FabianHofmann commented 9 months ago

to avoid future warning

codecov[bot] commented 9 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (094f8ad) 89.21% compared to head (85c6f59) 89.22%. Report is 2 commits behind head on master.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #182 +/- ## ======================================= Coverage 89.21% 89.22% ======================================= Files 15 15 Lines 3134 3136 +2 Branches 723 723 ======================================= + Hits 2796 2798 +2 Misses 234 234 Partials 104 104 ``` | [Files](https://app.codecov.io/gh/PyPSA/linopy/pull/182?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PyPSA) | Coverage Δ | | |---|---|---| | [linopy/expressions.py](https://app.codecov.io/gh/PyPSA/linopy/pull/182?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PyPSA#diff-bGlub3B5L2V4cHJlc3Npb25zLnB5) | `89.71% <100.00%> (+0.03%)` | :arrow_up: |

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