Update app.py

app.py

@@ -4,279 +4,27 @@ import streamlit as st
 st.markdown("# Main Page 🏠")
 st.sidebar.markdown("## Main Page 🏠")
 
-
-# import streamlit as st
-# import pandas as pd
-# import re
-
-# # Helper function to check if a string has more than 50% numeric characters
-# def is_mostly_numeric(s):
-#     if isinstance(s, str):
-#         # Remove any whitespace and punctuation that should not count towards the numeric content
-#         s = re.sub(r'[^\w\s]', '', s)
-#         # Calculate the number of numeric characters
-#         num_numeric = sum(c.isdigit() for c in s)
-#         # Calculate the percentage of numeric characters
-#         percent_numeric = num_numeric / len(s) if s else 0
-#         return percent_numeric > 0.5
-#     return False
-
-
-# st.set_page_config(layout="wide")
-# st.markdown("<h1 style='text-align: center;'>حسن xxx دحوم</h1>", unsafe_allow_html=True)
-
-# def header(text,h='h2'):
-#     return st.markdown(f"<{h} style='text-align: center;'>{text}</{h}>", unsafe_allow_html=True)
-    
-# # First row with three text components
-# col1, col2, col3 = st.columns(3)
-# with col1:
-#     header('Premiums','h3')
-# with col2:
-#     header("Incurred Claims & Recoveries Data",'h3')
-# with col3:
-#     header("Claims Count",'h3')
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-# # Second row with three file upload buttons
-# upload_col1, upload_col2, upload_col3 = st.columns(3)
-# with upload_col1:
-#     uploaded_file_premiums = st.file_uploader("", key="premiums")
-# with upload_col2:
-#     uploaded_file_claims_recoveries = st.file_uploader("", key="claims_recoveries")
-# with upload_col3:
-#     uploaded_file_claims_count = st.file_uploader("", key="claims_count")
-
-# # Third row with three buttons, enabled only if the corresponding file is uploaded
-# button_col1, button_col2, button_col3 = st.columns(3)
-# premiumlabel = "Select Premiums columns"
-# incurredlabel = "Select Incurred claims columns"
-# recoverlabel = "Select Recoveries columns"
-# claimscount = "Select Claims count columns"
-
-# def process_premiums_file(uploaded_file):
-#     # Read the CSV file into a DataFrame
-#     df = pd.read_csv(uploaded_file)
-    
-#     # Store the DataFrame in the session state
-#     st.session_state['premiums_df'] = df
-
-#     # Indicate that the CSV has been processed and we're ready to select columns
-#     st.session_state['select_columns'] = True
-
-# # Button to select premiums, only displayed and active if a file has been uploaded
-# with button_col1:
-#     # Check if the file has been uploaded
-#     file_uploaded = uploaded_file_premiums is not None
-#     # The button is enabled if a file has been uploaded, and disabled otherwise
-#     if st.button(premiumlabel, disabled=not file_uploaded, key="premiums_button"):
-#         # If the button is clicked (active), call the callback function
-#         process_premiums_file(uploaded_file_premiums)
-
-# with button_col2:
-#     if uploaded_file_claims_recoveries is not None:
-#         st.button(incurredlabel)
-#         st.button(recoverlabel)
-#     else:
-#         st.button(incurredlabel, disabled=True)
-#         st.button(recoverlabel, disabled=True)
-
-# with button_col3:
-#     if uploaded_file_claims_count is not None:
-#         st.button(claimscount)
-#     else:
-#         st.button(claimscount, disabled=True)
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-# # If the CSV has been processed, display the column selection UI
-# if st.session_state.get('select_columns', False):
-#     st.empty()
-#     st.write("Please choose the 'lob' column and the values to filter by:")
-
-#     # Determine columns with only string values and where no value is mostly numeric
-#     string_columns = [
-#         col for col in st.session_state['premiums_df'].columns 
-#         if not any(not isinstance(x, str) or is_mostly_numeric(x) for x in st.session_state['premiums_df'][col].dropna())
-#     ]
-
-#     # Create two columns: one for the 'lob' column dropdown, one for the checkboxes
-#     col1, col2 = st.columns(2)
-    
-#     # Dropdown to select the 'lob' column, filtered to only string columns
-#     with col1:
-#         lob_column = st.selectbox('Choose the column for "lob":', string_columns, key='lob_column')
-#     # Initialize an empty list to hold the selected values
-#     selected_lob_values = []
-
-#     # Generate checkboxes for each unique value in the 'lob' column
-#     with col2:
-#         st.write("Select values for filtering:")
-#         # Ensure that 'lob_column' is in the session state and it's in the DataFrame columns
-#         if 'lob_column' in st.session_state and st.session_state['lob_column'] in st.session_state['premiums_df'].columns:
-#             # Retrieve unique values from the 'lob' column
-#             unique_values = st.session_state['premiums_df'][st.session_state['lob_column']].unique()
-#             # Sort the values for consistent checkbox ordering
-#             unique_values.sort()
-#             for value in unique_values:
-#                 # Create a checkbox for each unique value in the 'lob' column
-#                 if st.checkbox(f"{value}", key=f"checkbox_{value}"):
-#                     selected_lob_values.append(value)
-
-#     # Filter the DataFrame based on selected 'lob' values
-#     if selected_lob_values:
-#         filtered_df = st.session_state['premiums_df'][st.session_state['premiums_df'][lob_column].isin(selected_lob_values)]
-#         st.session_state['filtered_premiums_df'] = filtered_df
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-#         # Display other column selections after 'lob' has been selected and DataFrame has been filtered
-#         st.write("Now, select the columns for other parameters:")
-#         valuation_as_at = st.selectbox('Valuation As At:', filtered_df.columns, key='valuation_as_at')
-#         quarter_bracket = st.selectbox('Quarter Bracket:', filtered_df.columns, key='quarter_bracket')
-#         # Continue with other selections as required...
-
-#         # Store the column selections in the session state
-#         st.session_state['column_selections'] = {
-#             'valuation_as_at': valuation_as_at,
-#             'quarter_bracket': quarter_bracket,
-#             # ... include other selections as well
-#         }
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-# # Initialize session state variables
-# st.session_state.setdefault('current_page', 'home')
-# st.session_state.setdefault('premiums_df', None)
-# st.session_state.setdefault('claims_recoveries_df', None)
-# st.session_state.setdefault('claims_count_df', None)
-# st.session_state.setdefault('back_to_home', False)  # Flag for back to home button
-
-# # Helper function to check if a string has more than 50% numeric characters
-# def is_mostly_numeric(s):
-#     if isinstance(s, str):
-#         num_numeric = sum(c.isdigit() for c in s)
-#         percent_numeric = num_numeric / len(s) if s else 0
-#         return percent_numeric > 0.5
-#     return False
-
-# def process_file(uploaded_file, key):
-#     df = pd.read_csv(uploaded_file)
-#     st.session_state[key + '_df'] = df
-#     st.session_state['current_page'] = key + '_selection'
-
-# # Function to display the column selection UI
-# def column_selection_ui(dataframe_key, selection_key):
-#     st.write(f"Please choose the 'lob' column and the values to filter by for {selection_key}:")
-
-#     string_columns = [
-#         col for col in st.session_state[dataframe_key].columns 
-#         if not any(not isinstance(x, str) or is_mostly_numeric(x) for x in st.session_state[dataframe_key][col].dropna())
-#     ]
-
-#     col1, col2 = st.columns(2)
-#     with col1:
-#         lob_column = st.selectbox('Choose the column for "lob":', string_columns, key=f'lob_column_{selection_key}')
-#     selected_lob_values = []
-
-#     with col2:
-#         st.write("Select values for filtering:")
-#         if lob_column in st.session_state[dataframe_key].columns:
-#             unique_values = st.session_state[dataframe_key][lob_column].unique()
-#             unique_values.sort()
-#             for value in unique_values:
-#                 if st.checkbox(f"{value}", key=f"checkbox_{value}_{selection_key}"):
-#                     selected_lob_values.append(value)
-
-#     # Initialize the variables to prevent UnboundLocalError
-#     valuation_as_at = None
-#     quarter_bracket = None
-
-#     # Filter the DataFrame based on selected 'lob' values
-#     if selected_lob_values:
-#         filtered_df = st.session_state[dataframe_key][st.session_state[dataframe_key][lob_column].isin(selected_lob_values)]
-#         st.session_state['filtered_' + dataframe_key] = filtered_df
-
-#         # Display other column selections after 'lob' has been selected and DataFrame has been filtered
-#         st.write("Now, select the columns for other parameters:")
-#         valuation_as_at = st.selectbox('Valuation As At:', filtered_df.columns, key='valuation_as_at_' + selection_key)
-#         quarter_bracket = st.selectbox('Quarter Bracket:', filtered_df.columns, key='quarter_bracket_' + selection_key)
-
-#     # Store the column selections in the session state
-#     st.session_state[f'{selection_key}_selections'] = {
-#         'lob_column': lob_column,
-#         'selected_lob_values': selected_lob_values,
-#         'valuation_as_at': valuation_as_at,
-#         'quarter_bracket': quarter_bracket,
-#     }
-
-# # File uploaders and buttons
-# if st.session_state.current_page == 'home':
-#     upload_col1, upload_col2, upload_col3 = st.columns(3)
-#     with upload_col1:
-#         uploaded_file_premiums = st.file_uploader("Upload Premiums Data", key="premiums_file")
-#     with upload_col2:
-#         uploaded_file_claims_recoveries = st.file_uploader("Upload Claims Recoveries Data", key="claims_recoveries_file")
-#     with upload_col3:
-#         uploaded_file_claims_count = st.file_uploader("Upload Claims Count Data", key="claims_count_file")
-
-#     button_col1, button_col2, button_col3 = st.columns(3)
-#     with button_col1:
-#         if uploaded_file_premiums and st.button("Select Premiums columns"):
-#             process_file(uploaded_file_premiums, 'premiums')
-#     with button_col2:
-#         if uploaded_file_claims_recoveries:
-#             if st.button("Select Incurred claims columns"):
-#                 process_file(uploaded_file_claims_recoveries, 'claims_recoveries')
-#             if st.button("Select Recoveries columns"):
-#                 process_file(uploaded_file_claims_recoveries, 'claims_recoveries')
-#     with button_col3:
-#         if uploaded_file_claims_count and st.button("Select Claims count columns"):
-#             process_file(uploaded_file_claims_count, 'claims_count')
-
-# # Conditional rendering based on the current page
-# if st.session_state.current_page.endswith('_selection'):
-#     dataframe_key = st.session_state.current_page.replace('_selection', '_df')
-#     column_selection_ui(dataframe_key, dataframe_key.replace('_df', ''))
-
-# # Back to Home button
-# if st.session_state.current_page != 'home':
-#     if st.button("Back to Home"):
-#         st.session_state['back_to_home'] = True
-
-# # Handling the back to home action
-# if st.session_state['back_to_home']:
-#     st.session_state['current_page'] = 'home'
-#     st.session_state['back_to_home'] = False
+# streamlit_app.py
+import streamlit as st
+import page_1
+import page_2
+
+# Initialize session state
+if 'page' not in st.session_state:
+    st.session_state.page = 'main'
+
+# Main Page
+if st.session_state.page == 'main':
+    st.markdown("# Main Page 🏠")
+    if st.button('Go to Page 1'):
+        st.session_state.page = 'page_1'
+    elif st.button('Go to Page 2'):
+        st.session_state.page = 'page_2'
+
+# Page 1
+elif st.session_state.page == 'page_1':
+    page_1.run()
+
+# Page 2
+elif st.session_state.page == 'page_2':
+    page_2.run()