Update main.py

main.py

@@ -44,7 +44,7 @@ def read_root():
 def data_download(ticker: str):
     # Define the list of tickers
     index_list = [
-        Ticker, '^VIX', '^VVIX', '^VIX9D', '^VIX3M', '^VIX6M', '^FVX', '^TNX', '^TYX'
+        ticker, '^VIX', '^VVIX', '^VIX9D', '^VIX3M', '^VIX6M', '^FVX', '^TNX', '^TYX'
     ]
 
     data = yf.download(index_list, start="1994-01-01", end=None)['Adj Close']
@@ -66,7 +66,7 @@ def data_download(ticker: str):
     
 def data_manipolation(df):
     # MA calculation for all columns 
-    New_Names=[Ticker,'VIX','VIX_Index','VIX9D','VIX3M','VIX6M','T5Y','T10Y','T30Y']
+    New_Names=[ticker,'VIX','VIX_Index','VIX9D','VIX3M','VIX6M','T5Y','T10Y','T30Y']
     for col in New_Names:
         df[col + "_MA30"] = df[col].rolling(window=30).mean().round(2)
         df[col + "/_MA30"] = (df[col]/df[col + "_MA30"]).round(4)
@@ -88,7 +88,7 @@ def data_manipolation(df):
     suffixes = ['_p', '_c1', '_MA30', '/_MA30']
     basic_cols = ['T5Y', 'T10Y', 'T30Y', 'VIX']
     to_keep = basic_cols + [f"{col}{suffix}" for col in basic_cols for suffix in suffixes]
-    ticker_columns = [Ticker + suffix for suffix in ['_c1']]
+    ticker_columns = [ticker + suffix for suffix in ['_c1']]
     to_keep.extend(ticker_columns)
 
     # Filter the DataFrame to keep only specified columns and drop rows with missing values
@@ -97,8 +97,8 @@ def data_manipolation(df):
     return df
        
 def data_split_train_test(df):
-    X = df.loc[:,df.columns !=  Ticker + '_c1']
-    y = df[ Ticker + '_c1']
+    X = df.loc[:,df.columns !=  ticker + '_c1']
+    y = df[ ticker + '_c1']
     recent_data_size = int(0.3 * len(X))  # Adjust the percentage as needed
     print (recent_data_size)