Update app.py

app.py

@@ -1,68 +1,32 @@
 import streamlit as st
 import pandas as pd
-import plotly.graph_objects as go
 import matplotlib.pyplot as plt
-import seaborn as sns
 import os
 
-st.set_page_config(page_title="Legislative Visualizations", layout="wide")
-
-st.title("Legislative Bill Analysis Dashboard")
+st.title("Basic Bar Chart from Legislative Data")
 
 DATA_PATH = "Illinois_Entire_Data_Insights_Final_v2.csv"
 
-if os.path.exists(DATA_PATH):
-    df = pd.read_csv(DATA_PATH)
-    st.success(f"Loaded dataset from {DATA_PATH}")
-
-    # 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)
+if not os.path.exists(DATA_PATH):
+    st.error(f"Data file {DATA_PATH} not found in repo.")
+    st.stop()
 
-        st.plotly_chart(fig_sankey, use_container_width=True)
-    else:
-        st.warning("Sankey input columns contain only null values or are missing.")
+df = pd.read_csv(DATA_PATH)
+st.success(f"Loaded {DATA_PATH}")
 
-    # Heatmap
-    st.header("🧯 Heatmap: Category vs Policy Impact Area")
-    heat_df = df[['category_&_subcategory_standardized', 'policy_impact_areas_standardized']].dropna()
+# For example: count of bills by 'intent_standardized'
+if 'intent_standardized' not in df.columns:
+    st.error("Column 'intent_standardized' not found in data.")
+    st.stop()
 
-    if not heat_df.empty:
-        heat = heat_df.pivot_table(index='category_&_subcategory_standardized',
-                                   columns='policy_impact_areas_standardized',
-                                   aggfunc=len,
-                                   fill_value=0)
+counts = df['intent_standardized'].value_counts()
 
-        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.write("### Count of Bills by Intent")
 
-        st.pyplot(plt)
-    else:
-        st.warning("Heatmap input columns contain only null values or are missing.")
+fig, ax = plt.subplots()
+counts.plot(kind='bar', ax=ax)
+ax.set_xlabel("Intent")
+ax.set_ylabel("Count")
+plt.xticks(rotation=45)
 
-else:
-    st.error(f"Data file {DATA_PATH} not found in Space repo.")
-    st.stop()
+st.pyplot(fig)