Update stls.py

stls.py

@@ -6,8 +6,8 @@ import pytz
 import os 
 
 mongo_url = os.environ['MongoURL']
-df_logo = pd.read_csv('https://raw.githubusercontent.com/jarvisx17/nifty500/main/Nifty500.csv')
-df_logo = df_logo[['Symbol','Industry', "logo"]]
+df_logo = pd.read_csv('https://raw.githubusercontent.com/jarvisx17/nifty500/main/Stocks.csv')
+df_logo = df_logo[['Symbol','Industry', "logo", "FNO"]]
 tz = pytz.timezone('Asia/Kolkata')
 def UpdatedCollectionName():
   current_time = datetime.now(tz)
@@ -80,11 +80,11 @@ def Stocks():
             
     filtered_data = pd.concat(filtered_data_by_stock)
     filtered_data.reset_index(drop=True, inplace=True)
-    filtered_data[['Open', 'High','Low', 'Close', 'RSI', 'Prev_RSI','SMA20', 'PercentageChange']] = filtered_data[['Open', 'High','Low', 'Close', 'RSI', 'Prev_RSI', 'SMA20', 'PercentageChange']].round(2)
+    filtered_data[['Open', 'High','Low', 'Close', 'RSI', 'Prev_RSI','SMA20','FNO', 'PercentageChange']] = filtered_data[['Open', 'High','Low', 'Close', 'RSI', 'Prev_RSI', 'SMA20','FNO', 'PercentageChange']].round(2)
     filtered_data = filtered_data.sort_values(by='PercentageChange', ascending=False)
     filtered_data.reset_index(drop=True, inplace=True)
     filtered_data = pd.merge(filtered_data, df_logo, on='Symbol', how='inner') 
-    filtered_data = filtered_data[['Symbol', 'Date', 'Open', 'High', 'Low', 'Close', 'RSI', 'Prev_RSI','PercentageChange','Industry', "logo"]]
+    filtered_data = filtered_data[['Symbol', 'Date', 'Open', 'High', 'Low', 'Close', 'RSI', 'Prev_RSI','PercentageChange','Industry','FNO', "logo"]]
     client = MongoClient(mongo_url)
     db = client['mydatabase']
     collection_name = UpdatedCollectionName()