fix: broken frontend displays after API changes

frontend/src/pages/Stats.tsx

@@ -28,17 +28,15 @@ const StatPage = () => {
 
   useEffect(() => {
     Promise.all([
-      axios.get("http://localhost:5000/stats/events_per_day"),
-      axios.get("http://localhost:5000/stats/heatmap"),
+      axios.get("http://localhost:5000/stats/time"),
       axios.get("http://localhost:5000/stats/word_frequencies"),
     ])
-      .then(([eventsRes, heatmapRes, wordsRes]) => {
-        setPostsPerDay(
-          eventsRes.data.filter(
-            (d: any) => new Date(d.date) >= new Date("2026-01-10")
-          )
-        );
-        setHeatmapData(heatmapRes.data);
+      .then(([timeRes, wordsRes]) => {
+        setPostsPerDay(timeRes.data["events_per_day"].filter(
+          (d: any) => new Date(d.date) >= new Date('2026-01-10')
+        ))
+        setHeatmapData(timeRes.data["weekday_hour_heatmap"])
+
         setWordFrequencyData(
           wordsRes.data.map((d: BackendWord) => ({
             text: d.word,
@@ -76,8 +74,8 @@ const StatPage = () => {
               <Tooltip />
               <Line
                 type="monotone"
-                dataKey="posts_count"
-                name="Posts"
+                dataKey="count"
+                name="Events"
               />
             </LineChart>
           </ResponsiveContainer>

frontend/src/stats/ActivityHeatmap.tsx

@@ -1,6 +1,6 @@
 import { ResponsiveHeatMap } from "@nivo/heatmap";
 
-type ApiRow = Record<string, number>;
+type ApiRow = Record<number, number>;
 type ActivityHeatmapProps = {
   data: ApiRow[];
 };

server/stat_gen.py

@@ -50,21 +50,27 @@ class StatGen:
             "Thursday", "Friday", "Saturday", "Sunday"
         ]
 
+        self.df["weekday"] = pd.Categorical(
+            self.df["weekday"],
+            categories=weekday_order,
+            ordered=True
+        )
+
         heatmap = (
             self.df
-            .assign(weekday=pd.Categorical(self.df["weekday"], weekday_order, ordered=True))
-            .groupby(["weekday", "hour"])
+            .groupby(["weekday", "hour"], observed=True)
             .size()
             .unstack(fill_value=0)
             .reindex(columns=range(24), fill_value=0)
         )
+    
         heatmap.columns = heatmap.columns.map(str)
         
         burst_index = per_day["count"].std() / max(per_day["count"].mean(), 1)
 
         return {
             "events_per_day": per_day.to_dict(orient="records"),
-            "weekday_hour_heatmap": heatmap.reset_index().to_dict(orient="records"),
+            "weekday_hour_heatmap": heatmap.to_dict(orient="records"),
             "burstiness": round(burst_index, 2)
         }