feat: replace datapane by Panel

README.md

@@ -189,7 +189,7 @@ One of the schedulers you can use is Apache Airflow. To use it, you can read the
 ## 🔬 Built With
 This section list libraries used in Eurybia.
 - [Shapash](https://github.com/MAIF/shapash/tree/master/shapash)
-- [Datapane](https://github.com/datapane/datapane)
+- [Panel](https://github.com/holoviz/panel)
 - [Plotly](https://github.com/plotly/plotly.py)
 - [Catboost](https://github.com/catboost/catboost)
 

eurybia/core/smartplotter.py

@@ -148,11 +148,15 @@ def generate_fig_univariate_continuous(
         """
         df_all.loc[:, col].fillna(0, inplace=True)
         datasets = [df_all[df_all[hue] == val][col].values.tolist() for val in df_all[hue].unique()]
+        group_labels = [str(val) for val in df_all[hue].unique()]
+        colors = list(self._style_dict["univariate_cont_bar"].values())
+        if group_labels[0] == 'Current dataset':
+            group_labels = ['Baseline dataset', 'Current dataset']
 
         fig = ff.create_distplot(
             datasets,
-            group_labels=[str(val) for val in df_all[hue].unique()],
-            colors=list(self._style_dict["univariate_cont_bar"].values()),
+            group_labels=group_labels,
+            colors=list(colors),
             show_hist=False,
             show_curve=True,
             show_rug=False,
@@ -285,7 +289,7 @@ def generate_fig_univariate_categorical(
             color=hue,
             text="Percent_displayed",
         )
-        fig1.update_traces(marker_color=list(self._style_dict["univariate_cat_bar"].values())[0], showlegend=True)
+        fig1.update_traces(marker_color=list(self._style_dict["univariate_cat_bar"].values())[1], showlegend=True)
 
         fig2 = px.bar(
             df_cat[df_cat[hue] == modalities[1]],
@@ -296,7 +300,7 @@ def generate_fig_univariate_categorical(
             color=hue,
             text="Percent_displayed",
         )
-        fig2.update_traces(marker_color=list(self._style_dict["univariate_cat_bar"].values())[1], showlegend=True)
+        fig2.update_traces(marker_color=list(self._style_dict["univariate_cat_bar"].values())[0], showlegend=True)
 
         fig = fig1.add_trace(fig2.data[0])