Update app.py

app.py

@@ -133,7 +133,7 @@ def create_component_for_analysis_for_single_df(selected_files, dfs, i):
 
     analysis_actions = st.multiselect("What analysis do you wish to do?",
                                       ['Summary of Data', 'Sample Data','Get Profile' ,'Univariate Analysis',
-                                       'Bivariate Analysis','Add a Target Column'], key='analysis_action_' + str(i))
+                                       'Bivariate Analysis'], key='analysis_action_' + str(i))
     if analysis_actions:
         
         df_for_analysis = st.session_state['filtered_data'][selected_files[i]] if filter_data else df
@@ -195,13 +195,20 @@ def create_component_for_analysis_for_single_df(selected_files, dfs, i):
                         
                         st.plotly_chart(fig, use_container_width=True)
         
-            elif action == "Add a Target Column":
-#                 create_component_to_add_target_func(selected_files, dfs, i)
-                code= "def f1(x): return str(x * 3)"
-                exec(code)
-                st.write(f1(3))
-                        
-            
+            elif action == "Bivariate Analysis":
+                create_for_bivariate_analysis(selected_files, df, i)                        
+
+def create_for_bivariate_analysis(selected_files, df, i):
+    target_column = st.selectbox("Select the target column ", df.columns.values,
+                                 key= "bivariate_target_column_" + str(i))
+    bivariate_columns = st.multiselect("Select the columns to analyse ", df.columns.values,
+                                 key= "bivariate_analysis_columns_" + str(i))
+    for col in bivariate_columns:
+        st.write(pd.crosstab(df[col], df[target_column], margins=True, aggfunc=pd.Series.count))
+# 3 any other aggregation function can be used based on column type
+        
+    
+    
 def create_component_for_data_analysis():
     if 'data_files' in st.session_state: