app.py

import streamlit as st
import pandas as pd
import plotly.graph_objects as go
import matplotlib.pyplot as plt
import seaborn as sns
#trial
# Set Streamlit page config
st.set_page_config(page_title="Legislative Visualizations", layout="wide")

st.title("Legislative Bill Analysis Dashboard")

# Upload dataset
uploaded_file = st.file_uploader("Illinois_Entire_Data_Insights_Final_v2.csv", type=["csv", "xlsx"])

if uploaded_file:
    # Load dataset
    if uploaded_file.name.endswith('.csv'):
        df = pd.read_csv(uploaded_file)
    else:
        df = pd.read_excel(uploaded_file)

    st.success("File uploaded and read successfully!")

    # Sankey Diagram
    st.header("🔗 Sankey Diagram: Intent → Stance → Beneficiaries")
    sankey_df = df[['intent_standardized', 'stance_standardized', 'intended_beneficiaries_standardized']].dropna()

    if not sankey_df.empty:
        labels = list(pd.unique(sankey_df['intent_standardized'].tolist() +
                                sankey_df['stance_standardized'].tolist() +
                                sankey_df['intended_beneficiaries_standardized'].tolist()))
        label_map = {label: i for i, label in enumerate(labels)}

        intent_stance = sankey_df.groupby(['intent_standardized', 'stance_standardized']).size().reset_index(name='count')
        stance_beneficiary = sankey_df.groupby(['stance_standardized', 'intended_beneficiaries_standardized']).size().reset_index(name='count')

        source = intent_stance['intent_standardized'].map(label_map).tolist() + stance_beneficiary['stance_standardized'].map(label_map).tolist()
        target = intent_stance['stance_standardized'].map(label_map).tolist() + stance_beneficiary['intended_beneficiaries_standardized'].map(label_map).tolist()
        value  = intent_stance['count'].tolist() + stance_beneficiary['count'].tolist()

        fig_sankey = go.Figure(data=[go.Sankey(
            node=dict(pad=15, thickness=20, line=dict(color="black", width=0.5), label=labels),
            link=dict(source=source, target=target, value=value)
        )])
        fig_sankey.update_layout(title_text="Sankey: Intent → Stance → Beneficiary", font_size=12)

        st.plotly_chart(fig_sankey, use_container_width=True)
    else:
        st.warning("Sankey input columns contain only null values or are missing.")

    # Heatmap
    st.header("🧯 Heatmap: Category vs Policy Impact Area")
    heat_df = df[['category_&_subcategory_standardized', 'policy_impact_areas_standardized']].dropna()

    if not heat_df.empty:
        heat = heat_df.pivot_table(index='category_&_subcategory_standardized',
                                   columns='policy_impact_areas_standardized',
                                   aggfunc=len,
                                   fill_value=0)

        plt.figure(figsize=(14, 8))
        sns.heatmap(heat, cmap='coolwarm', annot=False)
        plt.title("Heatmap: Category vs Policy Impact Area")
        plt.xlabel("Policy Impact Area")
        plt.ylabel("Category")
        plt.tight_layout()

        st.pyplot(plt)
    else:
        st.warning("Heatmap input columns contain only null values or are missing.")
else:
    st.info("Please upload a dataset file to view the visualizations.")