- **MFA: `column_cosine_similarities_` was not callable**. Calling `mfa.column_cosine_similarities_(X)` raised `TypeError: 'DataFrame' object is not callable` because a method override was trying to call the parent class's `@property`. The override was removed — the inherited property works correctly. Reported in [#218](https://github.com/MaxHalford/prince/issues/218).

- **MFA: `partial_row_coordinates` broken with supplementary groups**. The method crashed with a shape mismatch when supplementary groups were specified, because column weights and the data matrix had incompatible dimensions.

- **MFA: `partial_row_coordinates` used wrong scaling with supplementary rows**. The method recomputed mean/std from the input data (including supplementary rows) instead of using the fitted scaler parameters, producing incorrect results.

- **MFA: group-level results**. Added `group_coordinates_`, `group_contributions_`, and `group_cosine_similarities_` properties. These summarize how each group of variables relates to the global MFA components, corresponding to FactoMineR's `result$group$coord`, `result$group$contrib`, and `result$group$cos2`. Requested in [#217](https://github.com/MaxHalford/prince/issues/217).

- **MFA: partial axes results**. Added `partial_correlations_` and `partial_contributions_` properties. These describe how each group's own PCA axes relate to the global MFA axes, corresponding to FactoMineR's `result$partial.axes$cor` and `result$partial.axes$contrib`. Requested in [#217](https://github.com/MaxHalford/prince/issues/217).

- **MFA: partial axes correlation plot**. Added `plot_partial` method. Produces a correlation circle showing how each group's PCA axes project onto the global MFA plane, corresponding to FactoMineR's `plot.MFA(res, choix="axes")`.