Refactor app.py layout for improved user experience: reorganize UI components into a container for better structure, enhance data loading functionality with a reset button, and streamline league and site selection processes, ensuring a more intuitive interface for managing NBA and WNBA lineups.

app.py

@@ -359,49 +359,48 @@ fd_wnba_sd_lineups = pd.DataFrame(columns=fd_wnba_sd_columns)
 
 t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
-tab1, tab2 = st.tabs(['Range of Outcomes', 'Optimals'])
+with st.container():
+    st.info("Advanced view includes all stats and thresholds, simple includes just basic columns for ease of use on mobile")
+reset_col, view_col, site_col, league_col = st.columns(4)
+with reset_col:
+    # First row - timestamp and reset button
+    col1, col2 = st.columns([3, 3])
+    with col1:
+        st.info(t_stamp)
+    with col2:
+        if st.button("Load/Reset Data", key='reset1'):
+            st.cache_data.clear()
+            dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, sd_raw, dk_sd_raw, fd_sd_raw, timestamp = load_overall_stats('NBA')
+            salary_dict = dict(zip(roo_raw.Player, roo_raw.Salary))
+            id_dict = dict(zip(roo_raw.Player, roo_raw.player_ID))
+            salary_dict_sd = dict(zip(sd_raw.Player, sd_raw.Salary))
+            dk_id_dict_sd = dict(zip(dk_sd_raw.Player, dk_sd_raw.player_ID))
+            fd_id_dict_sd = dict(zip(fd_sd_raw.Player, fd_sd_raw.player_ID))
+            dk_nba_lineups = pd.DataFrame(columns=dk_nba_columns)
+            dk_nba_sd_lineups = pd.DataFrame(columns=dk_nba_sd_columns)
+            fd_nba_lineups = pd.DataFrame(columns=fd_nba_columns)
+            fd_nba_sd_lineups = pd.DataFrame(columns=fd_nba_sd_columns)
+
+            dk_wnba_lineups = pd.DataFrame(columns=dk_wnba_columns)
+            dk_wnba_sd_lineups = pd.DataFrame(columns=dk_wnba_sd_columns)
+            fd_wnba_lineups = pd.DataFrame(columns=fd_wnba_columns)
+            fd_wnba_sd_lineups = pd.DataFrame(columns=fd_wnba_sd_columns)
+            t_stamp = f"Last Update: " + str(timestamp) + f" CST"
+            for key in st.session_state.keys():
+                del st.session_state[key]
+with view_col:
+        view_var2 = st.radio("View Type", ('Simple', 'Advanced'), key='view_var2')
+with site_col:
+    site_var2 = st.radio("Site", ('Draftkings', 'Fanduel'), key='site_var2')
+    if 'working_seed' in st.session_state:
+        del st.session_state['working_seed']
+with league_col:
+    league_var = st.radio("What League to load:", ('WNBA', 'NBA'), key='league_var')
+    dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, sd_raw, dk_sd_raw, fd_sd_raw, timestamp = load_overall_stats(league_var)
 
+tab1, tab2 = st.tabs(['Range of Outcomes', 'Optimals'])
 with tab1:
     
-    
-    with st.container():
-        st.info("Advanced view includes all stats and thresholds, simple includes just basic columns for ease of use on mobile")
-    reset_col, view_col, site_col, league_col = st.columns(4)
-    with reset_col:
-        # First row - timestamp and reset button
-        col1, col2 = st.columns([3, 1])
-        with col1:
-            st.info(t_stamp)
-        with col2:
-            if st.button("Load/Reset Data", key='reset1'):
-                st.cache_data.clear()
-                dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, sd_raw, dk_sd_raw, fd_sd_raw, timestamp = load_overall_stats('NBA')
-                salary_dict = dict(zip(roo_raw.Player, roo_raw.Salary))
-                id_dict = dict(zip(roo_raw.Player, roo_raw.player_ID))
-                salary_dict_sd = dict(zip(sd_raw.Player, sd_raw.Salary))
-                dk_id_dict_sd = dict(zip(dk_sd_raw.Player, dk_sd_raw.player_ID))
-                fd_id_dict_sd = dict(zip(fd_sd_raw.Player, fd_sd_raw.player_ID))
-                dk_nba_lineups = pd.DataFrame(columns=dk_nba_columns)
-                dk_nba_sd_lineups = pd.DataFrame(columns=dk_nba_sd_columns)
-                fd_nba_lineups = pd.DataFrame(columns=fd_nba_columns)
-                fd_nba_sd_lineups = pd.DataFrame(columns=fd_nba_sd_columns)
-
-                dk_wnba_lineups = pd.DataFrame(columns=dk_wnba_columns)
-                dk_wnba_sd_lineups = pd.DataFrame(columns=dk_wnba_sd_columns)
-                fd_wnba_lineups = pd.DataFrame(columns=fd_wnba_columns)
-                fd_wnba_sd_lineups = pd.DataFrame(columns=fd_wnba_sd_columns)
-                t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-                for key in st.session_state.keys():
-                    del st.session_state[key]
-    with view_col:
-            view_var2 = st.radio("View Type", ('Simple', 'Advanced'), key='view_var2')
-    with site_col:
-        site_var2 = st.radio("Site", ('Draftkings', 'Fanduel'), key='site_var2')
-        if 'working_seed' in st.session_state:
-            del st.session_state['working_seed']
-    with league_col:
-        league_var = st.radio("What League to load:", ('WNBA', 'NBA'), key='league_var')
-        dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, sd_raw, dk_sd_raw, fd_sd_raw, timestamp = load_overall_stats(league_var)
     with st.expander("Info and Filters"):
         col1, col2, col3 = st.columns(3)