Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import plotly.graph_objects as go
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+# 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.")