Fixing helpscout trend analysis

visualization/app.py

@@ -8,7 +8,6 @@ import streamlit as st
 import sys
 from pathlib import Path
 import json
-from datetime import date
 
 # Add parent directory to path
 parent_dir = Path(__file__).resolve().parent
@@ -131,13 +130,10 @@ def main():
             max_date = dashboard_df['comment_timestamp'].max().date()
 
             prev_range = prev.get('date_range')
-            # default_range = (
-            #     (prev_range[0], prev_range[1]) if prev_range and len(prev_range) == 2
-            #     else (min_date, max_date)
-            # )
-
-            default_range= (date(2026, 1, 1), max_date)  # year, month, day
-
+            default_range = (
+                (prev_range[0], prev_range[1]) if prev_range and len(prev_range) == 2
+                else (min_date, max_date)
+            )
             date_range = st.date_input(
                 "Date Range",
                 value=default_range,

visualization/components/helpscout_dashboard.py

@@ -164,7 +164,21 @@ def render_helpscout_dashboard(data_loader):
                                 index=1, key="hs_dash_freq")
         st.plotly_chart(charts.create_volume_timeline(hs_df, freq=freq), use_container_width=True)
         st.plotly_chart(charts.create_sentiment_timeline(hs_df, freq=freq), use_container_width=True)
-        st.plotly_chart(charts.create_topic_timeline(hs_df, freq=freq), use_container_width=True)
+
+        all_topics_ranked = charts.get_all_topics_ranked(hs_df)
+        topic_options = {t: topic_label(t, charts.taxonomy) for t in all_topics_ranked}
+        default_topics = all_topics_ranked[:5]
+        selected_topics = st.multiselect(
+            "Topics to display",
+            options=list(topic_options.keys()),
+            default=default_topics,
+            format_func=lambda t: topic_options[t],
+            key="hs_dash_topic_select",
+        )
+        st.plotly_chart(
+            charts.create_topic_timeline(hs_df, freq=freq, selected_topics=selected_topics or default_topics),
+            use_container_width=True,
+        )
         st.plotly_chart(charts.create_refund_cancel_timeline(hs_df, freq=freq), use_container_width=True)
 
     # ── Duration & Thread Count ───────────────────────────────────────────────

visualization/visualizations/helpscout_charts.py

@@ -176,21 +176,36 @@ class HelpScoutCharts:
                           yaxis_title="Topic", height=self.chart_height + 100)
         return fig
 
+    def get_all_topics_ranked(self, df):
+        """Return all topic_ids sorted by total volume (descending)."""
+        exploded = explode_topics(df)
+        if exploded.empty:
+            return []
+        return exploded["topic_id"].value_counts().index.tolist()
+
     def create_topic_timeline(self, df, title="Topic Volume Over Time",
-                              freq="W", top_n=5):
+                              freq="W", top_n=5, selected_topics=None):
         if "first_message_at" not in df.columns:
             return self._empty_fig(title, "No timestamp data")
         exploded = explode_topics(df)
         if exploded.empty:
             return self._empty_fig(title, "No topic data")
 
-        top_topics = exploded["topic_id"].value_counts().head(top_n).index.tolist()
-        exploded = exploded[exploded["topic_id"].isin(top_topics)].copy()
+        all_ranked = exploded["topic_id"].value_counts().index.tolist()
+        if selected_topics is not None:
+            topics = [t for t in all_ranked if t in selected_topics]
+        else:
+            topics = all_ranked[:top_n]
+
+        if not topics:
+            return self._empty_fig(title, "No topics selected")
+
+        exploded = exploded[exploded["topic_id"].isin(topics)].copy()
         exploded["date"] = pd.to_datetime(exploded["first_message_at"]).dt.to_period(freq).dt.to_timestamp()
         agg = exploded.groupby(["date", "topic_id"]).size().reset_index(name="count")
 
         fig = go.Figure()
-        for t in top_topics:
+        for t in topics:
             d = agg[agg["topic_id"] == t]
             if not d.empty:
                 fig.add_trace(go.Scatter(