Comments (2)
matthewwardrop
commented on July 19, 2024
Good catch. Casting dtypes is not always safe, though. Would you want a warning through here, or an explicit cast? Or maybe the option to do both?
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matthewwardrop
commented on July 19, 2024
Hi again @lorentzenchr ! At some point in the past, this seems to be have been resolved (at least for categorical codings). If this recurs, let me know!
It is still is the case that if a is a numerical vector, and the datatype of the vector changes between source dataframes, that the output data type will vary. I think this is fine.
Given that the main issues appears to be resolved, I'm going to close this one out. Feel free to reopen if this recurs!
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Related Issues (20)
- DOC: Explicitly mention support for multiple variables on the left hand side HOT 3
- Terms not being evaluated in get_model_matrix() HOT 2
- 17 tests fail: ModuleNotFoundError: No module named 'interface_meta' HOT 2
- How can the encoding choices for one dataset be reused for another? HOT 3
- Intercept term breaks when RHS formula begins with a parentheses HOT 2
- How do I set the reference level for a categorical term? HOT 4
- Support for sympy >= 1.10 HOT 3
- ENH: Preserve variable order as they appear in formulas HOT 5
- 2 tests fail HOT 1
- Interaction between two categorical covariates sometimes switches order, causing error HOT 3
- Intercept is not added after being removed HOT 4
- Proposal: support columns representing multiple features HOT 3
- Formulaic struggles with NAs and `poly()` syntax HOT 3
- Escaped variables and functions HOT 3
- How to include structural zeros? HOT 1
- Retain Column Names for sparse model matrices HOT 4
- Formulaic not raising an exception when required fields are missing in the dataset HOT 2
- Allow formatting the categorical encoded variables HOT 4
- Throw error when formula has parameters that are not available HOT 2
- Support polars HOT 5
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