Update app.py

app.py

@@ -517,182 +517,182 @@ if uploaded_file:
         if main_option == "Tabulation":
             st.header("Tabulation Analysis")
     
-                tabulation_option = st.selectbox("Please select the type of analysis:", ["Univariate", "Multivariate", "All"])
-    
-                if tabulation_option == "All":
-    
-                    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(
-                        'Main: Single answer questions', 
-                        cols,
-                        default=[]
-                    )
-                    
-                    main_dict["multi"] = st.sidebar.multiselect(
-                        'Main: Multi answer questions',
-                        cols,
-                        default=[]
-                    )
-    
-                    main_dict["score"] = st.sidebar.multiselect(
-                        'Main: Score answer questions',
-                        cols,
-                        default=[]
-                    )
-    
-                    st.sidebar.subheader("Follow")
-    
-                    follow_dict = {"single": [], "multi": [], "score": []}
-                    
-                    st.sidebar.subheader("Main")
-                    follow_dict["single"] = st.sidebar.multiselect(
-                        'Follow: Single answer questions', 
-                        cols,
-                        default=[]
-                    )
-                    
-                    follow_dict["multi"] = st.sidebar.multiselect(
-                        'Follow: Multi answer questions',
-                        cols,
-                        default=[]
-                    )
+            tabulation_option = st.selectbox("Please select the type of analysis:", ["Univariate", "Multivariate", "All"])
+
+            if tabulation_option == "All":
+
+                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(
+                    'Main: Single answer questions', 
+                    cols,
+                    default=[]
+                )
+                
+                main_dict["multi"] = st.sidebar.multiselect(
+                    'Main: Multi answer questions',
+                    cols,
+                    default=[]
+                )
 
-                    follow_dict["score"] = st.sidebar.multiselect(
-                        'Follow: 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"])
-    
-                    if uni_option == "Single answer":
-                        var = st.text_input("Please enter the name of the desired column:")
-                        if var:
-                            if var in df.columns:
-                                result_df = single_answer(df[var])
-                                st.subheader("Univariate Analysis Results")
-                                st.dataframe(result_df)
-    
-                                fig = figo('Bar', result_df["Percentage"][:-1, ], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
-                                st.plotly_chart(fig, use_container_width=True)
-                            else:
-                                st.error("The entered column was not found.")
-                    elif uni_option == "Multiple answer":
-                        var = st.text_input("Please enter the name of the desired column:")
-                        if var:
-                            matching_cols = [col for col in df.columns if is_matching_pattern(col, var)]
-                            if matching_cols:
-                                subset_df = df[matching_cols]
-                                result_df = multi_answer(subset_df)
-                                    
-                                st.subheader("Multiple Answer Analysis Results")
-                                st.dataframe(result_df)
+                main_dict["score"] = st.sidebar.multiselect(
+                    'Main: Score answer questions',
+                    cols,
+                    default=[]
+                )
+
+                st.sidebar.subheader("Follow")
+
+                follow_dict = {"single": [], "multi": [], "score": []}
+                
+                st.sidebar.subheader("Main")
+                follow_dict["single"] = st.sidebar.multiselect(
+                    'Follow: Single answer questions', 
+                    cols,
+                    default=[]
+                )
+                
+                follow_dict["multi"] = st.sidebar.multiselect(
+                    'Follow: Multi answer questions',
+                    cols,
+                    default=[]
+                )
+
+                follow_dict["score"] = st.sidebar.multiselect(
+                    'Follow: 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"])
+
+                if uni_option == "Single answer":
+                    var = st.text_input("Please enter the name of the desired column:")
+                    if var:
+                        if var in df.columns:
+                            result_df = single_answer(df[var])
+                            st.subheader("Univariate Analysis Results")
+                            st.dataframe(result_df)
+
+                            fig = figo('Bar', result_df["Percentage"][:-1, ], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
+                            st.plotly_chart(fig, use_container_width=True)
+                        else:
+                            st.error("The entered column was not found.")
+                elif uni_option == "Multiple answer":
+                    var = st.text_input("Please enter the name of the desired column:")
+                    if var:
+                        matching_cols = [col for col in df.columns if is_matching_pattern(col, var)]
+                        if matching_cols:
+                            subset_df = df[matching_cols]
+                            result_df = multi_answer(subset_df)
                                 
-                                fig = figo('Bar', result_df["Percentage"][:-1], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
-                                st.plotly_chart(fig, use_container_width=True)
-                            else:
-                                st.error("No columns matching the entered pattern were found.")
-    
-                    elif uni_option == "Score answer":
-                        var = st.text_input("Please enter the name of the desired column:")
-                        if var:
-                            subset_df = df[var]
-                            result_df = score_answer(subset_df)
-    
-                            st.subheader("Score Answer Analysis Results")
+                            st.subheader("Multiple Answer Analysis Results")
                             st.dataframe(result_df)
                             
-                            fig = figo('Bar', result_df["Percentage"][:-2], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
+                            fig = figo('Bar', result_df["Percentage"][:-1], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
                             st.plotly_chart(fig, use_container_width=True)
                         else:
                             st.error("No columns matching the entered pattern were found.")
+
+                elif uni_option == "Score answer":
+                    var = st.text_input("Please enter the name of the desired column:")
+                    if var:
+                        subset_df = df[var]
+                        result_df = score_answer(subset_df)
+
+                        st.subheader("Score Answer Analysis Results")
+                        st.dataframe(result_df)
+                        
+                        fig = figo('Bar', result_df["Percentage"][:-2], title='Percentage Histogram', xlabel=var, ylabel='Percentage', colorscale='Plotly3')
+                        st.plotly_chart(fig, use_container_width=True)
+                    else:
+                        st.error("No columns matching the entered pattern were found.")
+                        
+            elif tabulation_option == "Multivariate":
+                st.subheader("Multivariate Analysis")
+                var1 = st.text_input("Please enter the name of the first column:")
+                var2 = st.text_input("Please enter the name of the second column:")
+
+                if var1 and var2:
+                    type1 = st.selectbox("Select the type of analysis for the first column:", ["Multiple answer", "Single answer"], key='type1')
+                    type2 = st.selectbox("Select the type of analysis for the second column:", ["Multiple answer", "Single answer", "Score answer"], key='type2')
+
+                    if type1 == "Single answer" and type2 == "Single answer":
+                        percentile_df, frequency_df = two_variable_ss(df[[var1, var2]], var1, var2)
+                        st.subheader("Percentage Table")
+                        st.write(z_test_data(percentile_df))
+
+                        st.subheader("Frequency Table")
+                        st.dataframe(frequency_df)
+
+                        row, col = df.shape
+                        fig = figo('Scatter', percentile_df.iloc[:-1,:], title='Percentage Scatter plot', width=(col*5)+5, height=(row*25) + 10)
+                        st.plotly_chart(fig, use_container_width=True)
+
+                    elif type1 == "Single answer" and type2 == "Multiple answer":
+                        matching_cols = [col for col in df.columns if is_matching_pattern(col, var2)]
+                        if matching_cols:
+                            percentile_df, frequency_df = two_variable_sm(df[[var1] + matching_cols], var1, matching_cols)
+                            st.subheader("Percentage Table")
+                            st.write(z_test_data(percentile_df))
+
+                            st.subheader("Frequency Table")
+                            st.dataframe(frequency_df)
+
+                            row, col = df.shape
+                            fig = figo('Scatter', percentile_df.iloc[:-1,:], title='Percentage Scatter plot', width=(col*5)+5, height=(row*25) + 10)
+                            st.plotly_chart(fig, use_container_width=True)
                             
-                elif tabulation_option == "Multivariate":
-                    st.subheader("Multivariate Analysis")
-                    var1 = st.text_input("Please enter the name of the first column:")
-                    var2 = st.text_input("Please enter the name of the second column:")
-    
-                    if var1 and var2:
-                        type1 = st.selectbox("Select the type of analysis for the first column:", ["Multiple answer", "Single answer"], key='type1')
-                        type2 = st.selectbox("Select the type of analysis for the second column:", ["Multiple answer", "Single answer", "Score answer"], key='type2')
-    
-                        if type1 == "Single answer" and type2 == "Single answer":
-                            percentile_df, frequency_df = two_variable_ss(df[[var1, var2]], var1, var2)
+                        else:
+                            st.error("No columns matching the entered pattern were found.")
+
+                    elif type1 == "Multiple answer" and type2 == "Multiple answer":
+                        matching_cols1 = [col for col in df.columns if is_matching_pattern(col, var1)]
+                        matching_cols2 = [col for col in df.columns if is_matching_pattern(col, var2)]
+                        if matching_cols1 and matching_cols2:
+                            percentile_df, frequency_df = two_variable_mm(df[matching_cols1 + matching_cols2], matching_cols1, matching_cols2)
                             st.subheader("Percentage Table")
                             st.write(z_test_data(percentile_df))
-    
+
                             st.subheader("Frequency Table")
                             st.dataframe(frequency_df)
-    
+
                             row, col = df.shape
                             fig = figo('Scatter', percentile_df.iloc[:-1,:], title='Percentage Scatter plot', width=(col*5)+5, height=(row*25) + 10)
                             st.plotly_chart(fig, use_container_width=True)
-    
-                        elif type1 == "Single answer" and type2 == "Multiple answer":
-                            matching_cols = [col for col in df.columns if is_matching_pattern(col, var2)]
-                            if matching_cols:
-                                percentile_df, frequency_df = two_variable_sm(df[[var1] + matching_cols], var1, matching_cols)
-                                st.subheader("Percentage Table")
-                                st.write(z_test_data(percentile_df))
-    
-                                st.subheader("Frequency Table")
-                                st.dataframe(frequency_df)
-    
-                                row, col = df.shape
-                                fig = figo('Scatter', percentile_df.iloc[:-1,:], title='Percentage Scatter plot', width=(col*5)+5, height=(row*25) + 10)
-                                st.plotly_chart(fig, use_container_width=True)
-                                
-                            else:
-                                st.error("No columns matching the entered pattern were found.")
-    
-                        elif type1 == "Multiple answer" and type2 == "Multiple answer":
-                            matching_cols1 = [col for col in df.columns if is_matching_pattern(col, var1)]
-                            matching_cols2 = [col for col in df.columns if is_matching_pattern(col, var2)]
-                            if matching_cols1 and matching_cols2:
-                                percentile_df, frequency_df = two_variable_mm(df[matching_cols1 + matching_cols2], matching_cols1, matching_cols2)
-                                st.subheader("Percentage Table")
-                                st.write(z_test_data(percentile_df))
-    
-                                st.subheader("Frequency Table")
-                                st.dataframe(frequency_df)
-    
-                                row, col = df.shape
-                                fig = figo('Scatter', percentile_df.iloc[:-1,:], title='Percentage Scatter plot', width=(col*5)+5, height=(row*25) + 10)
-                                st.plotly_chart(fig, use_container_width=True)
-    
-                        elif type1 == "Single answer" and type2 == "Score answer":
-    
-                            mean_df = two_variable_ssc(df[[var1, var2]], var1, var2)
+
+                    elif type1 == "Single answer" and type2 == "Score answer":
+
+                        mean_df = two_variable_ssc(df[[var1, var2]], var1, var2)
+                        st.subheader("Mean Table")
+                        st.write(t_test_data(mean_df))
+
+                        row, col = df.shape
+                        fig = figo('Bar', mean_df["Mean"][:-1], title='Mean Histogram', xlabel=var1, ylabel='Mean', colorscale='Plotly3')
+                        st.plotly_chart(fig, use_container_width=True)                            
+
+
+                    elif type1 == "Multiple answer" and type2 == "Score answer":
+                        matching_cols1 = [col for col in df.columns if is_matching_pattern(col, var1)]
+                        if matching_cols1:
+                            mean_df = two_variable_msc(df[matching_cols1 + [var2]], matching_cols1, var2)
                             st.subheader("Mean Table")
                             st.write(t_test_data(mean_df))
-    
+
                             row, col = df.shape
                             fig = figo('Bar', mean_df["Mean"][:-1], title='Mean Histogram', xlabel=var1, ylabel='Mean', colorscale='Plotly3')
-                            st.plotly_chart(fig, use_container_width=True)                            
-    
-    
-                        elif type1 == "Multiple answer" and type2 == "Score answer":
-                            matching_cols1 = [col for col in df.columns if is_matching_pattern(col, var1)]
-                            if matching_cols1:
-                                mean_df = two_variable_msc(df[matching_cols1 + [var2]], matching_cols1, var2)
-                                st.subheader("Mean Table")
-                                st.write(t_test_data(mean_df))
-    
-                                row, col = df.shape
-                                fig = figo('Bar', mean_df["Mean"][:-1], title='Mean Histogram', xlabel=var1, ylabel='Mean', colorscale='Plotly3')
-                                st.plotly_chart(fig, use_container_width=True)                    
-                        else:
-                            st.info("This section of the program is under development.")
+                            st.plotly_chart(fig, use_container_width=True)                    
+                    else:
+                        st.info("This section of the program is under development.")
 
         elif main_option == "Funnel":
             st.header("Funnel")