Update app.py

app.py

@@ -562,19 +562,21 @@ def ticker_insider_trades_page():
             help="Enter the stock ticker symbol (e.g., AAPL for Apple Inc.).").upper()
 
     if st.sidebar.button("Fetch Data"):
-        with st.spinner("Fetching insider trading data..."):
+        with st.spinner(f"Fetching insider trading data for {symbol}..."):
             try:
                 latest_transactions, trade_statistics = get_insider_trading_data(symbol)
                 # Save to session state
                 st.session_state['ticker_insider_trades']['symbol'] = symbol
                 st.session_state['ticker_insider_trades']['latest_transactions'] = latest_transactions
                 st.session_state['ticker_insider_trades']['trade_statistics'] = trade_statistics
-                st.success("Data fetched successfully!")
+                st.success(f"Data for {symbol} fetched successfully!")
+                #st.success("Data fetched successfully!")
             except Exception as e:
                 st.error(f"Error fetching data: {e}")
 
     # Check if data is available
     if 'latest_transactions' in st.session_state['ticker_insider_trades']:
+        symbol = st.session_state['ticker_insider_trades']['symbol']
         latest_transactions = st.session_state['ticker_insider_trades']['latest_transactions']
         trade_statistics = st.session_state['ticker_insider_trades']['trade_statistics']
 
@@ -582,8 +584,8 @@ def ticker_insider_trades_page():
         #st.subheader("Insider Trading Activity Insights")
 
         # Chart 1: Monthly Transactions and Securities Transacted
+        st.markdown(f"### Monthly Transactions and Securities Transacted for {symbol}")
         st.markdown("""
-        ### Monthly Transactions and Securities Transacted
         This chart visualizes the number of acquisition and disposition transactions each month, alongside the total volume of securities transacted. 
         - **Lines** represent the count of transactions.
         - **Bars** represent the volume of securities transacted.
@@ -592,8 +594,8 @@ def ticker_insider_trades_page():
         st.plotly_chart(create_monthly_transactions_chart(latest_transactions), use_container_width=True)
 
         # Chart 2: Trade Statistics Over Time
+        st.markdown(f"### Trade Statistics Over Time for {symbol}")
         st.markdown("""
-        ### Trade Statistics Over Time
         This chart displays the trends in purchases, sales, and the buy/sell ratio over different quarters.
         - **Purchases and Sales**: Represent the count of buy and sell transactions.
         - **Buy/Sell Ratio**: Indicates the balance between buying and selling activities.
@@ -601,8 +603,8 @@ def ticker_insider_trades_page():
         st.plotly_chart(create_trade_statistics_over_time_chart(trade_statistics), use_container_width=True)
 
         # Chart 3: Total and Average Bought/Sold
+        st.markdown(f"### Average Bought/Sold and Buy/Sell Ratio for {symbol}")
         st.markdown("""
-        ### Total and Average Bought/Sold with Average Buy/Sell Ratio Over Time
         This chart combines total and average amounts of securities bought and sold, along with the average buy/sell ratio.
         - **Bars** show the total bought and sold.
         - **Lines** indicate the average bought and sold per transaction.
@@ -611,14 +613,14 @@ def ticker_insider_trades_page():
         st.plotly_chart(create_total_avg_bought_sold_chart(trade_statistics), use_container_width=True)
 
         # Display DataFrames
-        st.subheader("Latest Transactional Data")
+        st.subheader(f"Latest Transactional Data for {symbol}")
         st.markdown("""
         Below is the detailed table of the most recent insider transactions for the selected ticker. 
         It includes information such as the date of transaction, type (acquisition or disposition), and the number of securities transacted.
         """)
         st.dataframe(latest_transactions, use_container_width=True)
 
-        st.subheader("Trade Statistics Data")
+        st.subheader(f"Trade Statistics Data for {symbol}")
         st.markdown("""
         This table presents aggregated trade statistics over time, including total purchases, sales, and the buy/sell ratio for each quarter.
         """)