Refactor tab2 layout: Consolidate data loading and filtering controls

Simplified the layout of tab2 by moving controls into an expander and removing unnecessary column divisions. Streamlined the data loading logic for both DraftKings and FanDuel sites, maintaining the existing functionality while improving code readability and user interface.

app.py

@@ -608,20 +608,19 @@ with tab1:
                     )
 
 with tab2:
-    col1, col2 = st.columns([1, 7])
-    with col1:
+    with st.expander("Info and Filters"):
         if st.button("Load/Reset Data", key='reset1'):
-              st.cache_data.clear()
-              for key in st.session_state.keys():
-                  del st.session_state[key]
-              DK_seed = init_DK_seed_frames(10000)
-              FD_seed = init_FD_seed_frames(10000)
-              DK_secondary = init_DK_secondary_seed_frames(10000)
-              FD_secondary = init_FD_secondary_seed_frames(10000)
-              dk_raw, fd_raw, dk_secondary, fd_secondary = init_baselines()
-              dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
-              fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
-              
+                st.cache_data.clear()
+                for key in st.session_state.keys():
+                    del st.session_state[key]
+                DK_seed = init_DK_seed_frames(10000)
+                FD_seed = init_FD_seed_frames(10000)
+                DK_secondary = init_DK_secondary_seed_frames(10000)
+                FD_secondary = init_FD_secondary_seed_frames(10000)
+                dk_raw, fd_raw, dk_secondary, fd_secondary = init_baselines()
+                dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
+                fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
+                
         slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate'), key='slate_var1')
         site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='site_var1')
         sharp_split_var = st.number_input("How many lineups do you want?", value=10000, max_value=500000, min_value=10000, step=10000)
@@ -714,55 +713,54 @@ with tab2:
                 mime='text/csv',
             )
             
-    with col2:
-        if st.button("Load Data", key='load_data'):
-            if site_var1 == 'Draftkings':
-                if 'working_seed' in st.session_state:
-                    st.session_state.working_seed = st.session_state.working_seed
-                    if player_var1 == 'Specific Players':
-                        st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
-                elif 'working_seed' not in st.session_state:
-                    if slate_var1 == 'Main Slate':
-                        st.session_state.working_seed = init_DK_seed_frames(sharp_split_var)
-                        dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
-
-                        raw_baselines = dk_raw
-                        column_names = dk_columns
-                    elif slate_var1 == 'Secondary Slate':
-                        st.session_state.working_seed = init_DK_secondary_seed_frames(sharp_split_var)
-                        dk_id_dict = dict(zip(dk_secondary.Player, dk_secondary.player_id))
+    if st.button("Load Data", key='load_data'):
+        if site_var1 == 'Draftkings':
+            if 'working_seed' in st.session_state:
+                st.session_state.working_seed = st.session_state.working_seed
+                if player_var1 == 'Specific Players':
+                    st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+                st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            elif 'working_seed' not in st.session_state:
+                if slate_var1 == 'Main Slate':
+                    st.session_state.working_seed = init_DK_seed_frames(sharp_split_var)
+                    dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
 
-                        raw_baselines = dk_secondary
-                        column_names = dk_columns
-                
-                    if player_var1 == 'Specific Players':
-                        st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
-                
-            elif site_var1 == 'Fanduel':
-                if 'working_seed' in st.session_state:
-                    st.session_state.working_seed = st.session_state.working_seed
-                    if player_var1 == 'Specific Players':
-                        st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
-                elif 'working_seed' not in st.session_state:
-                    if slate_var1 == 'Main Slate':
-                        st.session_state.working_seed = init_FD_seed_frames(sharp_split_var)
-                        fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
+                    raw_baselines = dk_raw
+                    column_names = dk_columns
+                elif slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_DK_secondary_seed_frames(sharp_split_var)
+                    dk_id_dict = dict(zip(dk_secondary.Player, dk_secondary.player_id))
 
-                        raw_baselines = fd_raw
-                        column_names = fd_columns
-                    elif slate_var1 == 'Secondary Slate':
-                        st.session_state.working_seed = init_FD_secondary_seed_frames(sharp_split_var)
-                        fd_id_dict = dict(zip(fd_secondary.Player, fd_secondary.player_id))
-                    
-                        raw_baselines = fd_secondary
-                        column_names = fd_columns
+                    raw_baselines = dk_secondary
+                    column_names = dk_columns
+            
+                if player_var1 == 'Specific Players':
+                    st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+                st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            
+        elif site_var1 == 'Fanduel':
+            if 'working_seed' in st.session_state:
+                st.session_state.working_seed = st.session_state.working_seed
+                if player_var1 == 'Specific Players':
+                    st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+                st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            elif 'working_seed' not in st.session_state:
+                if slate_var1 == 'Main Slate':
+                    st.session_state.working_seed = init_FD_seed_frames(sharp_split_var)
+                    fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
 
-                    if player_var1 == 'Specific Players':
-                        st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+                    raw_baselines = fd_raw
+                    column_names = fd_columns
+                elif slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_FD_secondary_seed_frames(sharp_split_var)
+                    fd_id_dict = dict(zip(fd_secondary.Player, fd_secondary.player_id))
                 
-            if 'data_export_display' in st.session_state:
-                st.dataframe(st.session_state.data_export_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=500, use_container_width = True)
+                    raw_baselines = fd_secondary
+                    column_names = fd_columns
+
+                if player_var1 == 'Specific Players':
+                    st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+                st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            
+        if 'data_export_display' in st.session_state:
+            st.dataframe(st.session_state.data_export_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=500, use_container_width = True)