Update app.py

app.py

@@ -207,11 +207,13 @@ def transfer_learning_forecasting():
             st.session_state.df = df
         
         columns = df.columns.tolist()  # Convert Index to list
-        if 'ds' in columns and 'unique_id' in columns:
-            options = columns.remove('ds')
-            options.remove('unique_id')
+        opt = []
         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=options, index=0)
+        if 'ds' in columns and 'unique_id' in columns:
+            columns.pop('ds')
+            columns.pop('unique_id')
+            opt = columns
+        y_col = st.selectbox("Select Target column", options=opt, index=0)
 
     st.session_state.ds_col = ds_col
     st.session_state.y_col = y_col
@@ -290,11 +292,13 @@ def dynamic_forecasting():
             st.session_state.df = df
         
         columns = df.columns.tolist()  # Convert Index to list
-        if 'ds' in columns and 'unique_id' in columns:
-            options = columns.remove('ds')
-            options.remove('unique_id')
+        opt = []
         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=options, index=0)
+        if 'ds' in columns and 'unique_id' in columns:
+            columns.pop('ds')
+            columns.pop('unique_id')
+            opt = columns
+        y_col = st.selectbox("Select Target column", options=opt, index=0)
 
     df = df.rename(columns={ds_col: 'ds', y_col: 'y'})
     
@@ -331,13 +335,14 @@ def timegpt_fcst():
             df = load_default()
             st.session_state.df = df
         
-        # Column selection
         columns = df.columns.tolist()  # Convert Index to list
-        if 'ds' in columns and 'unique_id' in columns:
-            options = columns.remove('ds')
-            options.remove('unique_id')
+        opt = []
         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=options, index=0)
+        if 'ds' in columns and 'unique_id' in columns:
+            columns.pop('ds')
+            columns.pop('unique_id')
+            opt = columns
+        y_col = st.selectbox("Select Target column", options=opt, index=0)
 
         df = df.rename(columns={ds_col: 'ds', y_col: 'y'})
 
@@ -375,13 +380,14 @@ def timegpt_anom():
             df = load_default()
             st.session_state.df = df
         
-        # Column selection
         columns = df.columns.tolist()  # Convert Index to list
-        if 'ds' in columns and 'unique_id' in columns:
-            options = columns.remove('ds')
-            options.remove('unique_id')
+        opt = []
         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=options, index=0)
+        if 'ds' in columns and 'unique_id' in columns:
+            columns.pop('ds')
+            columns.pop('unique_id')
+            opt = columns
+        y_col = st.selectbox("Select Target column", options=opt, index=0)
 
         df = df.rename(columns={ds_col: 'ds', y_col: 'y'})