Update app.py

app.py

@@ -109,7 +109,6 @@ st.title('Pattern Recognition in Asset Prices')
 st.sidebar.title("Input Parameters")
 
 with st.sidebar.expander("How to Use", expanded=False):
-    #st.sidebar.subheader("How to Use")
     st.markdown("""
     1. Select the pattern recognition method you want to use.
     2. Set the stock ticker or crypto pair, date range, and other parameters.
@@ -289,11 +288,16 @@ def run_ta_dtw():
     st.session_state.results_ta_dtw = figs
 
 if st.sidebar.button('Run Analysis'):
-    st.session_state.data = yf.download(ticker, start=start_date, end=end_date)
-    if not st.session_state.data.empty:
+    # Fetch data with auto_adjust=False and flatten columns if multi-indexed
+    data = yf.download(ticker, start=start_date, end=end_date, auto_adjust=False)
+    if isinstance(data.columns, pd.MultiIndex):
+        data.columns = data.columns.get_level_values(0)
+
+    if not data.empty:
+        st.session_state.data = data
         st.session_state.price_data = st.session_state.data['Close']
         st.session_state.price_data_pct_change = st.session_state.price_data.pct_change().dropna()
-        st.session_state.data_with_ta = add_ta_features(st.session_state.data)
+        st.session_state.data_with_ta = add_ta_features(st.session_state.data.copy())
         st.session_state.reduced_features = extract_and_reduce_features(st.session_state.data_with_ta, n_components=2)
 
         if selected == "DTW Pattern Recognition":
@@ -302,6 +306,8 @@ if st.sidebar.button('Run Analysis'):
             run_corr()
         elif selected == "TA-Enhanced DTW Pattern Recognition":
             run_ta_dtw()
+    else:
+        st.error(f"No data returned for {ticker} from {start_date} to {end_date}")
 
 # Display results and descriptions based on the selected method
 if selected == "DTW Pattern Recognition":