Update app.py

app.py

@@ -131,7 +131,7 @@ def multi_answer(df):
             unique_values = list(set(df[i].dropna()))[0]
             friquency[str(unique_values)] = df[i].value_counts().get(unique_values, 0)
         except Exception as e:
-            st.error(f"Warning: One of the data columns has no value.: {e}")
+            #st.error(f"Warning: One of the data columns has no value.: {e}")
             friquency[i] = 0
             
 
@@ -411,6 +411,58 @@ def analyze_z_test(file):
     return result_dataframes
 
 
+def all_tabulation(df, main_dict, follow_dict):
+
+    for j in main_dict["single"]:
+
+        dataframe_list, name_list = (single_answer(df[j]),), [j]
+
+        for i in follow_dict["single"]:
+            dataframe_list = dataframe_list + (two_variable_ss(df[[j, i]], j, i)[0], )
+            name_list.append(i)
+
+        for i in follow_dict["multi"]:
+            matching_cols1 = [col for col in df.columns if is_matching_pattern(col, i)]
+            dataframe_list = dataframe_list + (two_variable_sm(df[[j] + matching_cols1], j, matching_cols1)[0], )
+            name_list.append(i)
+
+        for i in follow_dict["score"]:
+            dataframe_list = dataframe_list + (two_variable_ssc(df[[j, i]], j, i), )
+            name_list.append(i)
+
+        st.subheader(j)
+        st.markdown(j + ": " + ", ".join(follow_dict['single'] + follow_dict['multi'] + follow_dict['scor']))
+        st.dataframe(join_dataframes(name_list, dataframe_list))
+
+    for j in main_dict["multi"]:
+
+        matching_cols0 = [col for col in df.columns if is_matching_pattern(col, j)]
+        dataframe_list, name_list = (multi_answer(df[matching_cols0]), ), [j]
+
+        #for i in follow_dict["single"]:
+            #dataframe_list.append(two_variable_ms(df[matching_cols0, i], matching_cols0, i).drop(columns=['Value'])[0])
+
+        for i in follow_dict["multi"]:
+            matching_cols1 = [col for col in df.columns if is_matching_pattern(col, i)]
+            dataframe_list = dataframe_list + (two_variable_mm(df[matching_cols0 + matching_cols1], matching_cols0, matching_cols1)[0], )
+            name_list.append(i)
+
+        for i in follow_dict["score"]:
+            dataframe_list = dataframe_list + (two_variable_msc(df[matching_cols0 + [i]], matching_cols0, i), )
+            name_list.append(i)
+
+        st.subheader(j)
+        st.markdown(j + ": " + ", ".join(follow_dict['multi'] + follow_dict['scor']))
+        st.dataframe(join_dataframes(name_list, dataframe_list))
+
+    for j in main_dict["score"]:
+
+        dataframe_list, name_list = [single_answer(df[j])], [j]
+
+        st.subheader(j)
+        st.dataframe(join_dataframes(name_list, dataframe_list))
+
+
 empty_col1, main_col, empty_col2 = st.columns([1.6, 2.8, 1.6])
 
 with main_col:
@@ -442,7 +494,58 @@ if main_option == "Tabulation":
             tabulation_option = st.selectbox("Please select the type of analysis:", ["Univariate", "Multivariate", "All"])
 
             if tabulation_option == "All":
-                st.info("This section of the program is under development.")
+
+                cols = edit_strings(df.columns)
+                cols = sorted(list(set(cols)))
+                
+                st.sidebar.header("Settings")
+
+                main_dict = {"single": [], "multi": [], "score": []}
+                
+                st.sidebar.subheader("Main")
+                main_dict["single"] = st.sidebar.multiselect(
+                    'Single answer questions', 
+                    cols,
+                    default=[]
+                )
+                
+                main_dict["multi"] = st.sidebar.multiselect(
+                    'Multi answer questions',
+                    cols,
+                    default=[]
+                )
+
+                main_dict["score"] = st.sidebar.multiselect(
+                    'Score answer questions',
+                    cols,
+                    default=[]
+                )
+
+                st.sidebar.subheader("Follow")
+
+                follow_dict = {"single": [], "multi": [], "score": []}
+                
+                st.sidebar.subheader("Main")
+                follow_dict["single"] = st.sidebar.multiselect(
+                    'Single answer questions', 
+                    cols,
+                    default=[]
+                )
+                
+                follow_dict["multi"] = st.sidebar.multiselect(
+                    'Multi answer questions',
+                    cols,
+                    default=[]
+                )
+
+                follow_dict["score"] = st.sidebar.multiselect(
+                    'Score answer questions',
+                    cols,
+                    default=[]
+                )
+
+                all_tabulation(df, main_dict, follow_dict)
+                
             elif tabulation_option == "Univariate":
                 uni_option = st.selectbox("Select the type of univariate analysis:", ["Multiple answer", "Single answer", "Score answer"])