- Polars 0.20.7 introduced a breaking change by error. Pinning version until thi is fixed. pola-rs/polars#14401
- Issue #90: Informative error on reserved keyword like 'group'.
- Issue #91: get_variables_names() in class ModelStatsmodels does not return all variables which causes errors
- PyFixest: Fixed effects variables are recognized as categorical by
datagrid()
MarginalEffectsDataFrame
class now has ajacobian
attribute.
Breaking change:
datagridcf()
is deprecated. Usedatagrid(grid_type='counterfactual')
instead.
New:
- Support the
PyFixest
package. https://s3alfisc.github.io/pyfixest/
datagrid()
no longer requires specifying themodel
argument when called inside another marginaleffects function likepredictions()
.
eps_vcov
argument to control the step size in the computation of the Jacobian used for standard errors.- plot_*() use
plotnine
instead of rawmatplotlib
- plot_*()
condition
argument gets string shortcuts for numeric variables: "threenum", "fivenum", "minmax". datagrid()
gets agrid_type
argument: 'mean_or_mode', 'balance', 'counterfactual'- Plot labels are sorted for clarity and consistency.
hypotheses()
function now supports raw models for conducting (non)-linear hypothesis tests on coefficients.
Misc:
- Refactor and several bug fixes in the
plot_*()
functions. - Many bug fixes.
- Upgraded dependency on the
polars
package, with a shift from.apply()
to.map_*()
due to deprecation. - Removed
pandas
dependency.
hypothesis
accepts a float or integer to specify a different null hypothesis.- Better column order in printout when using
datagrid()
orby
- Version bump for dependencies.
- Equivalence test bug with duplicated column names.
- Minor bugs in plot_*() with unknown consequences.
- Linting.
predictions()
supports categorical predictors whennewdata
does not include all levels (internal padding).- Better sorting of output, using the
by
argument.
- New function:
datagridcf()
predictions()
supports categorical predictors whennewdata
does not include all levels (internal padding).
Breaking change:
- Rename argument to match
R
marginaleffects
:conf_int
->conf_level
Misc:
MarginaleffectsDataFrame
class inherits frompl.DataFrame
for better printing and to host useful attributes.
Misc:
- Better step size selection for the numerical derivatives used to compute delta method standard errors.
Bugs:
- When newdata was an unseen dataframe, out.columns would be referenced in sanity.py prior to assignment. Thanks to @Vinnie-Palazeti for PR #25.
Initial release