Update app.py

app.py

@@ -34,7 +34,6 @@ if 'symbol_ownership_params' not in st.session_state:
 def page1():
     st.title("CIK and Name Combinations")
     st.markdown("""
-    **Description:**  
     Fetch and display the list of Central Index Key (CIK). CIK is a unique identifier assigned by the SEC to entities that file disclosures.
     """)
 
@@ -85,7 +84,6 @@ def fetch_cik_name_combinations():
 def page2():
     st.title("Portfolio Allocation Over Time")
     st.markdown("""
-    **Description:**  
     Fetch and visualize portfolio allocation data over time for a specific CIK. Enter the CIK and specify a start date to analyze the portfolio's composition.
     """)
 
@@ -187,8 +185,7 @@ def page2():
         
         # Time-series plots for trends
         st.subheader("Portfolio Allocation Trends by Symbol")
-        st.markdown("""
-        **Explanation:**  
+        st.markdown(""" 
         This chart shows the trends in portfolio allocation by individual symbols over time. The top N symbols by weight are displayed to highlight the most significant contributors to the portfolio.
         """)
         fig3 = plot_allocation_trends(allocation_data, "symbol", top_n)
@@ -196,7 +193,6 @@ def page2():
         
         st.subheader("Portfolio Allocation Trends by Industry")
         st.markdown("""
-        **Explanation:**  
         This chart illustrates the trends in portfolio allocation across different industries over time. The top N industries by weight are displayed to emphasize the major sectors in the portfolio.
         """)
         fig4 = plot_allocation_trends(allocation_data, "industryTitle", top_n)
@@ -206,15 +202,13 @@ def page2():
         st.markdown("---")
         st.subheader("Transposed Ticker Data")
         st.markdown("""
-        **Explanation:**  
         This table presents the portfolio allocation weights and market values for each ticker across different dates. It provides a detailed view of how each stock's weight and market value have evolved over time.
         """)
         transposed_ticker_data = transpose_data(allocation_data, "symbol")
         st.dataframe(transposed_ticker_data, use_container_width=True)
         
         st.subheader("Transposed Industry Data")
-        st.markdown("""
-        **Explanation:**  
+        st.markdown(""" 
         This table displays the portfolio allocation weights and market values for each industry across different dates. It offers insights into the sector-wise distribution and changes in the portfolio.
         """)
         transposed_industry_data = transpose_data(allocation_data, "industryTitle")
@@ -438,7 +432,6 @@ def format_market_value(value):
 def page3():
     st.title("Investor Performance")
     st.markdown("""
-    **Description:**  
     Fetch and visualize various performance metrics for a specific institutional investor identified by their CIK. Analyze portfolio value, market value changes, performance relative to benchmarks, turnover metrics, and more.
     """)
 
@@ -538,7 +531,6 @@ def page3():
         # Plotting
         st.subheader("Portfolio Value and Change in Market Value (%)")
         st.markdown("""
-        **Explanation:**  
         This chart displays the portfolio's total market value over time alongside the percentage change in market value. It helps in understanding the growth or decline of the portfolio's value.
         """)
         fig1 = plot_portfolio_value_and_change(data)
@@ -546,7 +538,6 @@ def page3():
         
         st.subheader("Performance and Relative Performance to S&P 500")
         st.markdown("""
-        **Explanation:**  
         This chart compares the portfolio's performance against the S&P 500 benchmark. It shows how well the portfolio is performing relative to the broader market.
         """)
         fig2 = plot_performance_and_relative(data)
@@ -554,7 +545,6 @@ def page3():
         
         st.subheader("Portfolio Turnover Metrics")
         st.markdown("""
-        **Explanation:**  
         This chart illustrates the portfolio's turnover rate, including buy and sell activities. Turnover metrics provide insight into the trading frequency and strategy.
         """)
         fig3 = plot_turnover_metrics(data)
@@ -562,7 +552,6 @@ def page3():
         
         st.subheader("Cumulative Performance Over Time")
         st.markdown("""
-        **Explanation:**  
         This chart shows the cumulative performance of the portfolio over different time horizons (1-year, 3-year, 5-year, and since inception). It highlights long-term growth trends.
         """)
         fig4 = plot_cumulative_performance(data)
@@ -570,7 +559,6 @@ def page3():
         
         st.subheader("Holding Periods")
         st.markdown("""
-        **Explanation:**  
         This chart depicts the average holding periods for the portfolio and its top holdings. Holding periods indicate the investment duration and strategy stability.
         """)
         fig5 = plot_holding_periods(data)
@@ -578,7 +566,6 @@ def page3():
         
         st.subheader("Portfolio Activity")
         st.markdown("""
-        **Explanation:**  
         This chart displays portfolio size changes and the number of securities added or removed. It provides an overview of portfolio expansion or contraction.
         """)
         fig6 = plot_portfolio_activity(data)
@@ -586,7 +573,6 @@ def page3():
         
         st.subheader("Market Value and Securities Count")
         st.markdown("""
-        **Explanation:**  
         This chart compares the portfolio's total market value against the number of securities held. It helps in understanding the diversification and valuation aspects of the portfolio.
         """)
         fig7 = plot_market_value_and_securities(data)