Update app.py

app.py

@@ -42,9 +42,9 @@ data_df['open'] = pd.to_numeric(data_df['open'])
 data_df['close'] = pd.to_numeric(data_df['close'])
 
 # Filter out stocks that meet the conditions
-# data_df = data_df[(data_df["open"] >= 0.98 * data_df["close"].shift(1).fillna(0)) & (data_df["open"] <= 1.02 * data_df["close"].shift(1).fillna(0))] 
-# data_df = data_df[(data_df["high"] == data_df["close"]) & (data_df["low"] == data_df["close"])]  # limit-up condition
-# data_df = data_df[(data_df["open"]!= 0) & (data_df["close"]!= 0)]  # exclude zero prices
+  data_df = data_df[(data_df["open"] >= 0.98 * data_df["close"].shift(1).fillna(0)) & (data_df["open"] <= 1.02 * data_df["close"].shift(1).fillna(0))] 
+  data_df = data_df[(data_df["high"] == data_df["close"]) & (data_df["low"] == data_df["close"])]  # limit-up condition
+  data_df = data_df[(data_df["open"]!= 0) & (data_df["close"]!= 0)]  # exclude zero prices
 
 # Check if data_df is empty before proceeding
 if data_df.empty: