Enhance data export functionality in app.py by adding a fourth column for stack inputs and implementing filters for minimum and maximum salary and stack counts. This update improves user experience by allowing more granular control over exported data for both DraftKings and FanDuel.

app.py

@@ -566,7 +566,7 @@ with tab2:
 with tab3:
     st.header("Optimals")
     with st.expander("Info and Filters"):
-        col1, col2, col3 = st.columns(3)
+        col1, col2, col3, col4 = st.columns(4)
         with col1:
             slate_type_var3 = st.radio("Which slate type are you loading?", ('Regular', 'Showdown'), key='slate_type_var3')
             if slate_type_var3 == 'Regular':
@@ -598,6 +598,13 @@ with tab3:
             elif site_var == 'Fanduel':
                 salary_min_var = st.number_input("Minimum salary used", min_value = 0, max_value = 35000, value = 34000, step = 100, key = 'salary_min_var')
                 salary_max_var = st.number_input("Maximum salary used", min_value = 0, max_value = 35000, value = 35000, step = 100, key = 'salary_max_var')
+        with col4:
+            if site_var == 'Draftkings':
+                min_stacks_var = st.number_input("Minimum stacks used", min_value = 0, max_value = 5, value = 3, step = 1, key = 'min_stacks_var')
+                max_stacks_var = st.number_input("Maximum stacks used", min_value = 0, max_value = 5, value = 5, step = 1, key = 'max_stacks_var')
+            elif site_var == 'Fanduel':
+                min_stacks_var = st.number_input("Minimum stacks used", min_value = 0, max_value = 4, value = 3, step = 1, key = 'min_stacks_var')
+                max_stacks_var = st.number_input("Maximum stacks used", min_value = 0, max_value = 4, value = 4, step = 1, key = 'max_stacks_var')
         
         
         if site_var == 'Draftkings':
@@ -626,71 +633,149 @@ with tab3:
             min_own = np.min(fd_lineups[:,11])
             max_own = np.max(fd_lineups[:,11])
 
-        if st.button("Prepare full data export", key='data_export'):
-            name_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
-            data_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
-            if site_var == 'Draftkings':
-                if slate_type_var3 == 'Regular':
-                    map_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
-                elif slate_type_var3 == 'Showdown':
-                    map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
-                for col_idx in map_columns:
-                    data_export[col_idx] = data_export[col_idx].map(dk_id_map)
-            elif site_var == 'Fanduel':
-                if slate_type_var3 == 'Regular':
-                    map_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
-                elif slate_type_var3 == 'Showdown':
-                    map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4']
-                for col_idx in map_columns:
-                    data_export[col_idx] = data_export[col_idx].map(fd_id_map)
-            reg_opt_col, pm_opt_col, blank_col = st.columns([2, 2, 6])
-            with reg_opt_col:
-                st.download_button(
-                    label="Export optimals set (IDs)",
-                    data=convert_df(data_export),
-                    file_name='MLB_optimals_export.csv',
-                    mime='text/csv',
-                )
-                st.download_button(
-                    label="Export optimals set (Names)",
-                    data=convert_df(name_export),
-                    file_name='MLB_optimals_export.csv',
-                    mime='text/csv',
-                )
-            with pm_opt_col:
+        reg_dl_col, filtered_dl_col, blank_dl_col = st.columns([2, 2, 6])
+        with reg_dl_col:
+            if st.button("Prepare full data export", key='data_export'):
+                name_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
+                data_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
                 if site_var == 'Draftkings':
                     if slate_type_var3 == 'Regular':
-                        data_export = data_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
                     elif slate_type_var3 == 'Showdown':
-                        data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
+                    for col_idx in map_columns:
+                        data_export[col_idx] = data_export[col_idx].map(dk_id_map)
                 elif site_var == 'Fanduel':
                     if slate_type_var3 == 'Regular':
-                        data_export = data_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
                     elif slate_type_var3 == 'Showdown':
-                        data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
-                st.download_button(
-                    label="Portfolio Manager Export (IDs)",
-                    data=convert_pm_df(data_export),
-                    file_name='MLB_optimals_export.csv',
-                    mime='text/csv',
-                )
-                
+                        map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4']
+                    for col_idx in map_columns:
+                        data_export[col_idx] = data_export[col_idx].map(fd_id_map)
+                reg_opt_col, pm_opt_col, blank_col = st.columns([2, 2, 6])
+                with reg_opt_col:
+                    st.download_button(
+                        label="Export optimals set (IDs)",
+                        data=convert_df(data_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                    st.download_button(
+                        label="Export optimals set (Names)",
+                        data=convert_df(name_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                with pm_opt_col:
+                    if site_var == 'Draftkings':
+                        if slate_type_var3 == 'Regular':
+                            data_export = data_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    elif site_var == 'Fanduel':
+                        if slate_type_var3 == 'Regular':
+                            data_export = data_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    st.download_button(
+                        label="Portfolio Manager Export (IDs)",
+                        data=convert_pm_df(data_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                    
+                    if site_var == 'Draftkings':
+                        if slate_type_var3 == 'Regular':
+                            name_export = name_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    elif site_var == 'Fanduel':
+                        if slate_type_var3 == 'Regular':
+                            name_export = name_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    st.download_button(
+                        label="Portfolio Manager Export (Names)",
+                        data=convert_pm_df(name_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+        with filtered_dl_col:
+            if st.button("Prepare full data export (Filtered)", key='data_export_filtered'):
+                name_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
+                data_export = pd.DataFrame(st.session_state.working_seed.copy(), columns=column_names)
                 if site_var == 'Draftkings':
                     if slate_type_var3 == 'Regular':
-                        name_export = name_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
                     elif slate_type_var3 == 'Showdown':
-                        name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
+                    for col_idx in map_columns:
+                        data_export[col_idx] = data_export[col_idx].map(dk_id_map)
                 elif site_var == 'Fanduel':
                     if slate_type_var3 == 'Regular':
-                        name_export = name_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        map_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
                     elif slate_type_var3 == 'Showdown':
-                        name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
-                st.download_button(
-                    label="Portfolio Manager Export (Names)",
-                    data=convert_pm_df(name_export),
-                    file_name='MLB_optimals_export.csv',
-                    mime='text/csv',
-                )
+                        map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4']
+                    for col_idx in map_columns:
+                        data_export[col_idx] = data_export[col_idx].map(fd_id_map)
+                data_export = data_export[data_export['salary'] >= salary_min_var]
+                data_export = data_export[data_export['salary'] <= salary_max_var]
+                data_export = data_export[data_export['Team_count'] >= min_stacks_var]
+                data_export = data_export[data_export['Team_count'] <= max_stacks_var]
+
+                name_export = name_export[name_export['salary'] >= salary_min_var]
+                name_export = name_export[name_export['salary'] <= salary_max_var]
+                name_export = name_export[name_export['Team_count'] >= min_stacks_var]
+                name_export = name_export[name_export['Team_count'] <= max_stacks_var]
+                
+                reg_opt_col, pm_opt_col, blank_col = st.columns([2, 2, 6])
+                with reg_opt_col:
+                    st.download_button(
+                        label="Export optimals set (IDs)",
+                        data=convert_df(data_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                    st.download_button(
+                        label="Export optimals set (Names)",
+                        data=convert_df(name_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                with pm_opt_col:
+                    if site_var == 'Draftkings':
+                        if slate_type_var3 == 'Regular':
+                            data_export = data_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    elif site_var == 'Fanduel':
+                        if slate_type_var3 == 'Regular':
+                            data_export = data_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            data_export = data_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    st.download_button(
+                        label="Portfolio Manager Export (IDs)",
+                        data=convert_pm_df(data_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
+                    
+                    if site_var == 'Draftkings':
+                        if slate_type_var3 == 'Regular':
+                            name_export = name_export.set_index('SP1').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    elif site_var == 'Fanduel':
+                        if slate_type_var3 == 'Regular':
+                            name_export = name_export.set_index('P').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                        elif slate_type_var3 == 'Showdown':
+                            name_export = name_export.set_index('CPT').drop(columns=['salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own'], axis=1)
+                    st.download_button(
+                        label="Portfolio Manager Export (Names)",
+                        data=convert_pm_df(name_export),
+                        file_name='MLB_optimals_export.csv',
+                        mime='text/csv',
+                    )
         
     if site_var == 'Draftkings':
         if 'working_seed' in st.session_state: