Update app.py

app.py

@@ -208,7 +208,7 @@ def transfer_learning_forecasting():
         # Column selection
         columns = df.columns.tolist()  # Convert Index to list
         ds_col = st.selectbox("Select Date/Time column", options=columns, index=columns.index('ds') if 'ds' in columns else 0)
-        y_col = st.selectbox("Select Target column", options=columns, index=columns.index('y') if 'y' in columns else 1)
+        y_col = st.selectbox("Select Target column", options=columns)
         # unique_id_col = st.text_input("Unique ID column (default: '1')", value="1")
 
     st.session_state.ds_col = ds_col
@@ -290,7 +290,7 @@ def dynamic_forecasting():
         # Column selection
         columns = df.columns.tolist()  # Convert Index to list
         ds_col = st.selectbox("Select Date/Time column", options=columns, index=columns.index('ds') if 'ds' in columns else 0)
-        y_col = st.selectbox("Select Target column", options=columns, index=columns.index('y') if 'y' in columns else 1)
+        y_col = st.selectbox("Select Target column", options=columns)
         # unique_id_col = st.text_input("Unique ID column (default: '1')", value="1")
 
     df = df.rename(columns={ds_col: 'ds', y_col: 'y'})
@@ -331,12 +331,12 @@ def timegpt():
         # Column selection
         columns = df.columns.tolist()  # Convert Index to list
         ds_col = st.selectbox("Select Date/Time column", options=columns, index=columns.index('ds') if 'ds' in columns else 0)
-        y_col = st.selectbox("Select Target column", options=columns, index=columns.index('y') if 'y' in columns else 1)
+        y_col = st.selectbox("Select Target column", options=columns)
 
 
         nixtla_client.plot(
             df,
-            id_col= y_col
+            id_col= y_col,
             time_col=ds_col,
             target_col=y_col,
             max_insample_length=365