previous is good

app.py

@@ -88,7 +88,6 @@ def get_data():
              df["created_at"] = pd.to_datetime(df["created_at"])
              
         # 2. FIX: Remove Timezone Information (Make it Naive)
-        # This solves the "Invalid comparison between Europe/Paris and Timestamp" error
         if pd.api.types.is_datetime64_any_dtype(df["created_at"]):
             if df["created_at"].dt.tz is not None:
                 df["created_at"] = df["created_at"].dt.tz_localize(None)
@@ -175,7 +174,26 @@ if not entities:
 
 # --- Continue only if data exists ---
 if not filtered_df.empty:
-    filtered_df["date"] = filtered_df["created_at"].dt.floor("D")
+    
+    # --- START: Smart Date Binning Logic (Max ~20 Dots) ---
+    min_date = filtered_df["created_at"].min()
+    max_date = filtered_df["created_at"].max()
+    
+    # Calculate total days in the range
+    days_span = (max_date - min_date).days + 1
+    
+    if days_span <= 20:
+        # If range is small, use Daily
+        freq = "D"
+    else:
+        # If range is large, calculate step size to result in ~20 dots
+        # e.g., 60 days / 20 = 3 days per dot -> freq="3D"
+        step = int(days_span / 20)
+        step = max(1, step) # Ensure at least 1
+        freq = f"{step}D"
+        
+    filtered_df["date"] = filtered_df["created_at"].dt.floor(freq)
+    # --- END: Smart Date Binning Logic ---
 
     if group_by_score_type:
         score_cols = ["entity_score", "title_score", "overall_score"]
@@ -235,7 +253,6 @@ if not filtered_df.empty:
             labels={"date": "Date", "score": "Score", "label": "Legend"},
             title=T[LANG]["scores_over_time"]
         )
-        # FIX: Ensure markers are shown even for single/few data points
         fig.update_traces(mode="lines+markers")
 
     else:
@@ -285,7 +302,6 @@ if not filtered_df.empty:
             labels={"date": "Date", score_type: "Score", "label": "Legend"},
             title=T[LANG]["avg_over_time"].format(score_type.replace("_", " ").title())
         )
-        # FIX: Ensure markers are shown even for single/few data points
         fig.update_traces(mode="lines+markers")
 
     # Grid lines at every integer, thicker at -5 and 5