PyFixest 0.12.0

Enhancements:

• Good performance improvements for singleton fixed effects detection. Thanks to @styfenschaer for the PR! See #229.
• Uses the r2u project for installing R and R packages on github actions, with great performance improvements.
• Allows to pass polars data frames to feols(), fepois() and predict(). #232. Thanks to @vincentarelbundock for the suggestion!

Bug Fixes:

• Missing variables in features were not always handled correctly in predict() with newdata not None in the presence of missing data, which would lead to an error. See #246 for details.
• Categorical variables were not always handled correctly in predict() with newdata not None, because the number of fixed effects levels in newdata might be smaller than in data. In consequence, some levels were not found, which lead to an error. See #245 for details. Thanks to @jiafengkevinchen for the pointer!
• Multicollinearity checks for over-identified IV was not implemented correctly, which lead to a dimension error. See #236 for details. Thanks to @jiafengkevinchen for the pointer!
• The number of degrees of freedom k was computed incorrectly if columns were dropped from the design matrix X in the presence of multicollinearity. See #235 for details. Thanks to @jiafengkevinchen for the pointer!
• If all variables were dropped due to multicollinearity, an unclear and imprecise error message was produced. See #228 for details. Thanks to @manferdinig for the pointer!
• If selection fixef_rm = 'singleton', feols() and fepois() would fail, which has been fixed. #192

Dependency Requirements:

• For now, sets formulaic versions to be 0.6.6 or lower as version 1.0.0 seems to have introduced a problem with the i() operator, See #244 for details.
• Drops dependency on pyhdfe.