Update app.py

app.py

@@ -141,9 +141,10 @@ def create_component_for_analysis_for_single_df(selected_files, dfs, i):
         for action in analysis_actions:
 
             if action == 'Sample Data':
+                clear_chart_type_session_var()
                 st.write(df_for_analysis.sample(10))
             elif action == 'Get Profile':
-
+                clear_chart_type_session_var()
                 full_data_check = st.checkbox("Report on all columns",key="filter_data_check"+str(i))
 
                 if full_data_check:
@@ -160,12 +161,11 @@ def create_component_for_analysis_for_single_df(selected_files, dfs, i):
                         st_profile_report(pr)
                 
             elif action == 'Summary of Data':
+                clear_chart_type_session_var()
                 st.write(df_for_analysis.describe())
-#                 col_to_filter = st.selectbox("Select the field to Filter on ", df.columns.values,
-#                                              key=action + "_col_filter_" + str(i))
-#                 selected_filter_vals = st.multiselect("Select Values to Filter on ", df[col_to_filter].unique(),
-#                                                       key=action + "_col_filter_val_" + str(i))
+                
             elif action == 'Univariate Analysis':
+                clear_chart_type_session_var()
                 cols_for_analysis = st.multiselect("Select Columns for Univariate Analysis",options= df_for_analysis.columns.values)
                 for col in cols_for_analysis:
                     if str(df_for_analysis[col].dtype) in ['int64','float64'] and df_for_analysis[col].nunique() > 10 :
@@ -194,14 +194,23 @@ def create_component_for_analysis_for_single_df(selected_files, dfs, i):
 #                         fig.update_layout(height=200, width=400, title_text=f"{col} data distribution")
                         
                         st.plotly_chart(fig, use_container_width=True)
-        
             elif action == "Bivariate Analysis":
+                add_chart_options_to_sidebar()
                 create_for_bivariate_analysis(selected_files, df, i)                        
 
+def clear_chart_type_session_var():
+    if 'chart_type' in st.session_state:
+        del st.session_state[chart_type]
+    
+def add_chart_options_to_sidebar():
+    if 'chart_type' not in st.session_state :
+        with st.sidebar:
+            viz_type = st.radio("Graph Type",('None','Cross Tab','Pivot Table','Box Plot'))
+        if viz_type and viz_type != 'None':
+            st.session_state['chart_type'] == viz_type
+    
 def create_for_bivariate_analysis(selected_files, df, i):
-    with st.sidebar:
-        # st.subheader("Visualisation Type")
-        viz_type = st.radio("What type of Visualisation?",("Cross Tab",'Box Plot'))  
+        
     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,
@@ -209,10 +218,11 @@ def create_for_bivariate_analysis(selected_files, df, i):
     
     col_vals = []
     
-    if col_vals:
+    if bivariate_columns:
         for col in bivariate_columns:
             col_vals.append(df[col])
-        if viz_type == 'Cross Tab':
+            
+        if st.session_state['chart_type'] == 'Cross Tab':
             if len(col_vals) > 3 :
                 st.warning("Too many columns to split on. Please consider reducing the no of columns")
             crosstab_df = pd.crosstab(df[target_column], col_vals, margins=True)
@@ -246,52 +256,53 @@ def create_component_for_data_analysis():
         st.write("Upload a file to start analysis")
 
 
-# def build_interface_for_model_analysis():
-st.title("Model Results Analyzer")
-with st.sidebar:
+def main():
     
+    st.title("Model Results Analyzer")
+    with st.sidebar:
 
-    selected_menu = option_menu(None, ["Home", "Upload Data", "Add Features","Analyze Data"],
-                                icons=['house', 'cloud-upload', "list-task", 'gear'],
-                                menu_icon="cast", default_index=0, orientation="vertical",
-                                styles={
-                                    "container": {"padding": "0!important", "background-color": "#fafafa"},
-                                    "icon": {"color": "orange", "font-size": "15px"},
-                                    "nav-link": {"font-size": "15px", "text-align": "left", "margin": "0px",
-                                                 "--hover-color": "#eee"},
-                                    "nav-link-selected": {"background-color": "green"},
-                                })
+        selected_menu = option_menu(None, ["Home", "Upload Data", "Add Features","Analyze Data"],
+                                    icons=['house', 'cloud-upload', "list-task", 'gear'],
+                                    menu_icon="cast", default_index=0, orientation="vertical",
+                                    styles={
+                                        "container": {"padding": "0!important", "background-color": "#fafafa"},
+                                        "icon": {"color": "orange", "font-size": "15px"},
+                                        "nav-link": {"font-size": "15px", "text-align": "left", "margin": "0px",
+                                                     "--hover-color": "#eee"},
+                                        "nav-link-selected": {"background-color": "green"},
+                                    })
 
-if selected_menu == "Home":
-    st.markdown('**This is to analyse models performance.**')
+    if selected_menu == "Home":
+        st.markdown('**This is to analyse models performance.**')
 
-elif selected_menu == "Upload Data":
+    elif selected_menu == "Upload Data":
 
-    create_upload_file_component()
+        create_upload_file_component()
 
-    if 'data_files' in st.session_state:
-        st.write(pd.DataFrame(
-            data={"File Name": pd.DataFrame.from_dict(st.session_state['data_files'], orient='index').index}))
+        if 'data_files' in st.session_state:
+            st.write(pd.DataFrame(
+                data={"File Name": pd.DataFrame.from_dict(st.session_state['data_files'], orient='index').index}))
 
-elif selected_menu == "Analyze Data":
-    create_component_for_data_analysis()
+    elif selected_menu == "Analyze Data":
+        create_component_for_data_analysis()
 
-elif selected_menu == "Add Features":
-    if 'data_files' in st.session_state:
-        selected_file = st.selectbox("Select the File(S) to analyze", st.session_state['data_files'].keys())
-        
-        if selected_file:
-            df =  st.session_state['data_frames'][selected_file]
-            st.header("Enter the function definiton to create a new feature")
-            feature_name = st.text_input("Enter the New Feature Name")
-            st.warning("please retain the function signature as 'add_feature(row)'")
-            
-            content = st_ace(language="python",value="def add_feature(row):")
-            
-            if content != 'def add_feature(row):':
-                exec(content)
-                df[feature_name] = df.apply(lambda x:add_feature(x),axis=1)
-               
-                st.session_state['data_frames'][selected_file] = df
-                st.write(df.columns.values)
-  
+    elif selected_menu == "Add Features":
+        if 'data_files' in st.session_state:
+            selected_file = st.selectbox("Select the File(S) to analyze", st.session_state['data_files'].keys())
+
+            if selected_file:
+                df =  st.session_state['data_frames'][selected_file]
+                st.header("Enter the function definiton to create a new feature")
+                feature_name = st.text_input("Enter the New Feature Name")
+                st.warning("please retain the function signature as 'add_feature(row)'")
+
+                content = st_ace(language="python",value="def add_feature(row):")
+
+                if content != 'def add_feature(row):':
+                    exec(content)
+                    df[feature_name] = df.apply(lambda x:add_feature(x),axis=1)
+
+                    st.session_state['data_frames'][selected_file] = df
+                    st.write(df.columns.values)
+
+main()