Add salary range filter to player data display in app.py

Enhanced the user interface by introducing salary range sliders for both Draftkings and Fanduel tables, allowing users to filter player data based on specified salary ranges. This improves data usability and provides more tailored insights for users.

app.py

@@ -109,11 +109,14 @@ with tab2:
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
         site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
         main_var2 = st.radio("Main slate or secondary slate?", ('Main Slate', 'Secondary Slate'), key='main_var2')
+        sal_var2 = st.slider("Is there a certain price range you want to view?", 5000, 25000, (5000, 25000), key='sal_var2')
     
     with col2:
         final_line_combos = line_frame[line_frame['Site'] == str(site_var2)]
         final_line_combos = final_line_combos[final_line_combos['Type'] == 'Basic']
         final_line_combos = final_line_combos[final_line_combos['Slate'] == main_var2]
+        final_line_combos = final_line_combos[final_line_combos['Salary'] >= sal_var2[0]]
+        final_line_combos = final_line_combos[final_line_combos['Salary'] <= sal_var2[1]]
         final_line_combos = final_line_combos.drop_duplicates(subset=['Player'])
         final_line_combos = final_line_combos.sort_values(by='Median', ascending=False)
         st.dataframe(final_line_combos.iloc[:, :-3].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
@@ -134,11 +137,14 @@ with tab3:
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
         site_var3 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var3')
         main_var3 = st.radio("Main slate or secondary slate?", ('Main Slate', 'Secondary Slate'), key='main_var3')
+        sal_var3 = st.slider("Is there a certain price range you want to view?", 5000, 30000, (5000, 30000), key='sal_var3')
     
     with col2:
         final_pp_combos = pp_frame[pp_frame['Site'] == str(site_var3)]
         final_pp_combos = final_pp_combos[final_pp_combos['Type'] == 'Basic']
         final_pp_combos = final_pp_combos[final_pp_combos['Slate'] == main_var3]
+        final_pp_combos = final_pp_combos[final_pp_combos['Salary'] >= sal_var3[0]]
+        final_pp_combos = final_pp_combos[final_pp_combos['Salary'] <= sal_var3[1]]
         final_pp_combos = final_pp_combos.drop_duplicates(subset=['Player'])
         final_pp_combos = final_pp_combos.sort_values(by='Median', ascending=False)
         st.dataframe(final_pp_combos.iloc[:, :-3].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)