Update plot colors and labels

pages/clustering.py

@@ -235,7 +235,12 @@ def plot_rfm_distribution(df_rfm: pd.DataFrame, cluster_info: Dict[str, List[int
     """Plots 3 histograms for the RFM metrics."""
 
     for x in ("Revenue", "Frequency", "Recency"):
-        fig = px.histogram(df_rfm, x=x, log_y=True, title=f"{x} metric")
+        fig = px.histogram(
+            df_rfm,
+            x=x,
+            log_y=True,
+            title=f"{x} metric",
+        )
         # Get the max value in the cluster info. The cluster info is a list of min - max
         # values per cluster.
         values = cluster_info[f"{x}_cluster"]
@@ -247,6 +252,11 @@ def plot_rfm_distribution(df_rfm: pd.DataFrame, cluster_info: Dict[str, List[int
                 line_dash="dot",
                 annotation=dict(textangle=90, font_color="red"),
             )
+
+        fig.update_layout(
+            yaxis_title="Count (log scale)",
+        )
+
         st.plotly_chart(fig)
 
 

recommender_system.py

@@ -254,7 +254,7 @@ def display_recommendation_plots(
             opacity=0.8,
             name="Similar bought by user",
             marker_symbol="square-open",
-            marker_color="darkviolet",
+            marker_color="#010CFA",
             marker_size=10,
             hovertext=contribution_description.loc[contributions].values.squeeze(),
         )
@@ -268,6 +268,7 @@ def display_recommendation_plots(
             name="Product bought by similar users",
             opacity=0.7,
             marker_symbol="circle-open",
+            marker_color="#FA5F19",
             marker_size=10,
             hovertext=items_other_description.loc[
                 bought_by_similar_users
@@ -281,7 +282,7 @@ def display_recommendation_plots(
             y=suggestion_dec[:, 1],
             mode="markers",
             name="Suggested",
-            marker_color="red",
+            marker_color="#1A9626",
             marker_symbol="star",
             marker_size=10,
             hovertext=suggestion_description.loc[suggestions].values.squeeze(),