new metrics in detailed view

app.py

@@ -450,6 +450,7 @@ with gr.Blocks(title="Swift Stock Screener, by Reddgr") as front:
             display_col = rename_columns.get("ticker", "ticker")
             ticker = last_result_df.iloc[row_i][display_col]
             print(f"DEBUG ticker extracted: {ticker}")
+            selected_ticker = ticker      # keep global state in sync
         else:
             # Filter by column returns (df, pagination_label, page_number, summary)
             filtered_df, pagination, page, summary = filter_by_column(evt)

json/app_column_config.json

@@ -13,6 +13,8 @@
         "beta",
         "beta_norm",
         "category",
+		"totalRevenue",
+		"ebitda",
         "country_num_norm",
         "debtToEquity_norm",
         "fullTimeEmployees_norm",
@@ -75,6 +77,8 @@
         "country",
         "sector",
         "marketCap",
+		"totalRevenue",
+		"ebitda",
         "ret_365",
         "vol_365",
         "trailingPE",

src/app_utils.py

@@ -30,8 +30,9 @@ def format_results(df: pd.DataFrame, rename_columns: dict) -> pd.DataFrame:
         df["Search dist."] = df["Search dist."].apply(lambda n: "-" if pd.isna(n) else f"{n:.2f}")
 
     # Cantidades monetarias grandes
-    if "marketCap" in df.columns:
-        df["marketCap"] = df["marketCap"].apply(lambda n: "-" if pd.isna(n) else format_large_number(n, 1))
+    for col in ["marketCap", "totalRevenue", "ebitda"]:
+        if col in df.columns:
+            df[col] = df[col].apply(lambda n: "-" if pd.isna(n) else format_large_number(n, 1))
     # Porcentajes 1 decimal
     for col in ["ret_365", "revenueGrowth"]:
         if col in df.columns: