Update app.py

app.py

@@ -78,14 +78,14 @@ def convert_df(array):
 
 @st.cache_data
 def calculate_DK_value_frequencies(np_array):
-    unique, counts = np.unique(np_array[:8], return_counts=True)
+    unique, counts = np.unique(np_array[2:10], return_counts=True)
     frequencies = counts / len(np_array)  # Normalize by the number of rows 
     combined_array = np.column_stack((unique, frequencies))  
     return combined_array 
 
 @st.cache_data
 def calculate_FD_value_frequencies(np_array):
-    unique, counts = np.unique(np_array[:7], return_counts=True)
+    unique, counts = np.unique(np_array[1:9], return_counts=True)
     frequencies = counts / len(np_array)  # Normalize by the number of rows 
     combined_array = np.column_stack((unique, frequencies))  
     return combined_array
@@ -144,7 +144,7 @@ with tab1:
             st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 13], stack_var2)]
             st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:1000], columns=column_names)
             
-#            st.session_state.data_export_freq = calculate_DK_value_frequencies(st.session_state.working_seed)
+            st.session_state.data_export_freq = calculate_DK_value_frequencies(st.session_state.working_seed)
             
         elif site_var1 == 'Fanduel':
             
@@ -153,7 +153,7 @@ with tab1:
             st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 12], stack_var2)]
             st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:1000], columns=column_names)
             
-#            st.session_state.data_export_freq = calculate_FD_value_frequencies(st.session_state.working_seed)
+            st.session_state.data_export_freq = calculate_FD_value_frequencies(st.session_state.working_seed)
             
         with st.container():
             if 'data_export_display' in st.session_state: