Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
from st_aggrid import AgGrid, GridOptionsBuilder
from st_aggrid.shared import GridUpdateMode

st.title("Heavy/Light CSV Table Designer")
st.write("Design actuarial heavy/light tables with this interactive tool")

# Initialize session state for the table
if 'table_data' not in st.session_state:
    # Create initial data with age and qx columns
    initial_data = pd.DataFrame({
        'age': range(0, 100),
        'qx': [0.0] * 100,
        'heavy_factor': [1.0] * 100
    })
    st.session_state.table_data = initial_data

# Sidebar controls
with st.sidebar:
    st.header("Table Controls")
    
    # Add new multiplier controls
    st.subheader("Apply Multiplier")
    age_range = st.slider("Age Range", 0, 99, (0, 99), 1)
    multiplier = st.number_input("Multiplier", min_value=0.0, value=1.0, step=0.1)
    
    if st.button("Apply Multiplier"):
        mask = (st.session_state.table_data['age'] >= age_range[0]) & \
               (st.session_state.table_data['age'] <= age_range[1])
        st.session_state.table_data.loc[mask, 'qx'] *= multiplier

    # Export options
    st.subheader("Export Options")
    if st.button("Export to CSV"):
        csv = st.session_state.table_data.to_csv(index=False)
        st.download_button(
            label="Download CSV",
            data=csv,
            file_name="mortality_table.csv",
            mime="text/csv"
        )

# Main area
st.subheader("Mortality Table Editor")

# Configure grid options
gb = GridOptionsBuilder.from_dataframe(st.session_state.table_data)
gb.configure_column("age", editable=False)
gb.configure_column("qx", editable=True, type=["numericColumn", "numberColumnFilter"])
gb.configure_column("heavy_factor", editable=True, type=["numericColumn", "numberColumnFilter"])
gb.configure_grid_options(enableRangeSelection=True)
grid_options = gb.build()

# Create the editable grid
grid_response = AgGrid(
    st.session_state.table_data,
    gridOptions=grid_options,
    height=600,
    data_return_mode='AS_INPUT',
    update_mode=GridUpdateMode.VALUE_CHANGED,
    fit_columns_on_grid_load=True
)

# Update session state with edited data
st.session_state.table_data = grid_response['data']

# Calculate and display heavy rates
st.subheader("Heavy Rates")
heavy_rates = st.session_state.table_data.copy()
heavy_rates['heavy_qx'] = heavy_rates['qx'] * heavy_rates['heavy_factor']

# Display summary statistics
st.subheader("Summary Statistics")
col1, col2 = st.columns(2)

with col1:
    st.write("Light Table Statistics")
    st.write(heavy_rates['qx'].describe())

with col2:
    st.write("Heavy Table Statistics")
    st.write(heavy_rates['heavy_qx'].describe())