Updates for pandas 1.5.0 compatibility#2291
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Codecov Report
@@ Coverage Diff @@
## main #2291 +/- ##
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- Coverage 99.32% 99.31% -0.02%
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Files 148 148
Lines 17706 17706
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- Hits 17586 17584 -2
- Misses 120 122 +2
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From what I can tell, the change in coverage is due a change in an error raised by pandas. What was previously an |
| >>> lag_periods = Lag(periods=3) | ||
| >>> lag_periods(["hello", "world", "test", "foo", "bar"], pd.Series(pd.date_range(start="2020-01-01", periods=5, freq='D'))).tolist() | ||
| [nan, nan, nan, 'hello', 'world'] | ||
| >>> lag_periods([True, False, False, True, True], pd.Series(pd.date_range(start="2020-01-01", periods=5, freq='D'))).tolist() |
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Can we have a string lag and a boolean lag in the example?
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We could, but I'm not sure it's so simple: #2291 (comment)
If we added a string lag, the doctest wouldn't pass for all of the pandas version we currently support because of the None vs nan output difference. Unless we added some extra conversion to the output to make sure we always get the same missing value representation.
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Just want to point out, that once Woodwork gets initialized in the feature matrix we will always end up with the same missing value representation, but since that doesn't happen at the primitive function level, this difference in output will be present when calling it like we do in the doctest examples.
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Ah I see. Let's put a note in the docstring about this OR comment in the code
3 participants
Various changes needed for compatibility with pandas 1.5.0.