Update app.py

app.py

@@ -1,11 +1,11 @@
 import streamlit as st
 import pandas as pd
-import altair as alt
 import datetime
 import re
 import os
 import asyncio
 import aiohttp
+import plotly.graph_objects as go
 
 from dateutil.relativedelta import relativedelta
 
@@ -77,7 +77,6 @@ st.sidebar.title("Filters")
 with st.sidebar.expander("Parameters", expanded=True):
     default_start_date = datetime.date.today() - relativedelta(months=2)
     start_date = st.date_input("Start transaction date", value=default_start_date)
-    #start_date = st.date_input("Start transaction date", value=datetime.date(2025, 1, 1))
     top_n = st.slider("Top N stocks", min_value=1, max_value=20, value=10, 
                       help="Select the top N stock by trade amount and volume.")
 
@@ -158,21 +157,36 @@ if run_button:
             .groupby(["ticker", "chamber", "tradeType"], as_index=False)
             .agg({"amount": "sum", "count": "sum"})
         )
-        base = alt.Chart(chart_data).encode(
-            x=alt.X("ticker:N", axis=alt.Axis(labelAngle=-45)),
-            xOffset="chamber:N",
-            y=alt.Y("amount:Q", title="Total Amount", stack="zero"),
-            color=alt.Color("tradeType:N", scale=alt.Scale(domain=["purchase", "sale"], range=["green", "red"]))
+        # Create Plotly figure
+        fig = go.Figure()
+        for chamber in chart_data["chamber"].unique():
+            for trade in ["purchase", "sale"]:
+                df_subset = chart_data[(chart_data["chamber"] == chamber) & (chart_data["tradeType"] == trade)]
+                if not df_subset.empty:
+                    color = "green" if trade == "purchase" else "red"
+                    fig.add_trace(go.Bar(
+                        x=df_subset["ticker"],
+                        y=df_subset["amount"],
+                        text=df_subset["count"],
+                        textposition="auto",
+                        name=f"{chamber} {trade}",
+                        offsetgroup=chamber,
+                        marker_color=color
+                    ))
+        fig.update_layout(
+            barmode="stack",
+            xaxis_tickangle=-45,
+            width=40 * len(top_tickers),
+            height=400,
+            title="Total Amount per Ticker"
         )
-        bars = base.mark_bar()
-        text = base.mark_text(dy=-5, color="black").encode(text=alt.Text("count:Q"))
-        chart = alt.layer(bars, text).properties(width=40 * len(top_tickers), height=400)
-        st.altair_chart(chart, use_container_width=True)
+        with st.container(border=True):
+            st.plotly_chart(fig, use_container_width=True)
 
     # Reorder Senate columns
     if not senate_data.empty:
         desired_order_senate = [
-            "office",  # name
+            "office",  
             "dateRecieved",  
             "symbol",        
             "type",          
@@ -187,7 +201,7 @@ if run_button:
     # Reorder House columns
     if not house_data.empty:
         desired_order_house = [
-            "representative",  # name
+            "representative",  
             "disclosureDate",  
             "ticker",          
             "type",            
@@ -199,13 +213,15 @@ if run_button:
         reordered_house_cols = existing_house_cols + remaining_house_cols
         house_data = house_data[reordered_house_cols]
 
-    st.subheader("Senate Data")
-    st.write("Latest Transaction in Senate. Please sort the table by **`disclosureDate`** and/or **`dateRecieved`** columns.")
-    st.dataframe(senate_data, use_container_width=True)
+    with st.container(border=True):
+        st.subheader("Senate Data")
+        st.write("Latest Transaction in Senate. Please sort the table by **`disclosureDate`** and/or **`dateRecieved`** columns.")
+        st.dataframe(senate_data, use_container_width=True)
 
-    st.subheader("House Data")
-    st.write("Latest Transaction in House. Please sort the table by **`disclosureDate`** and/or **`transactionDate`** columns.")
-    st.dataframe(house_data, use_container_width=True)
+    with st.container(border=True):
+        st.subheader("House Data")
+        st.write("Latest Transaction in House. Please sort the table by **`disclosureDate`** and/or **`transactionDate`** columns.")
+        st.dataframe(house_data, use_container_width=True)
 else:
     st.write("Set filters and press Run to load data.")