Update app.py

app.py

@@ -13,12 +13,10 @@ st.set_page_config(layout="wide")
 st.sidebar.title("Input Parameters")
 
 with st.sidebar.expander("How to Use", expanded=False):
-    st.markdown("""### How It Works:
-    1. **Input Ticker Symbol**: Enter the stock ticker symbol in the sidebar (e.g., `AAPL` for Apple Inc.).
-    2. **Analyze**: Click the "Analyze" button to fetch and process the options data.
-    3. **Visualize**: View the visualizations and interpretations of the options data to understand market sentiment.
-    ### Understanding Implied Volatility:
-    Implied volatility is derived from the market price of an option. It reflects the market's view of the likelihood of changes in a given security's price. Higher implied volatility means the market expects the stock to have large price swings (either up or down). Here’s a simplified representation of how implied volatility is calculated. 
+    st.markdown("""
+    - 1. **Input Ticker Symbol**: Enter the stock ticker symbol in the sidebar (e.g., `AAPL` for Apple Inc.).
+    - 2. **Analyze**: Click the "Analyze" button to fetch and process the options data.
+    - 3. **Visualize**: View the visualizations and interpretations of the options data to understand market sentiment.
     """)
 
 st.title("Options Sentiment Analysis Tool")
@@ -694,25 +692,25 @@ with st.sidebar.expander("Input Parameters", expanded=True):
 if st.sidebar.button("Run Analysis"):
     options_data, recent_price = get_options_data(ticker)
     if options_data is not None:
-        st.subheader("2. Volatility Smile Plot")
+        st.subheader("Volatility Smile Plot")
         overall_avg_iv_calls, overall_avg_iv_puts, avg_iv_by_strike_calls, avg_iv_by_strike_puts, expirations = plot_volatility_smile(options_data, recent_price, ticker)
         
         with st.expander("Volatility Smile Interpretation", expanded=False):
             interpret_volatility_smile(ticker, overall_avg_iv_calls, overall_avg_iv_puts, avg_iv_by_strike_calls, avg_iv_by_strike_puts)
 
-        st.subheader("3. Open Interest")
+        st.subheader("Open Interest")
         overall_avg_oi_calls, overall_avg_oi_puts, calls_data, puts_data = plot_open_interest(options_data, recent_price, ticker)
         
         with st.expander("Open Interest Interpretation", expanded=False):
             interpret_open_interest(ticker, overall_avg_oi_calls, overall_avg_oi_puts, calls_data, puts_data)
 
-        st.subheader("4. Volume Analysis")
+        st.subheader("Volume Analysis")
         overall_avg_vol_calls, overall_avg_vol_puts, calls_data, puts_data = plot_volume(options_data, recent_price, ticker)
         
         with st.expander("Volume Analysis Interpretation", expanded=False):
             interpret_volume(ticker, overall_avg_vol_calls, overall_avg_vol_puts, calls_data, puts_data)
 
-        st.subheader("5. Volatility Surface Plot")
+        st.subheader("Volatility Surface Plot")
         col1, col2 = st.columns(2)
         with col1:
             st.markdown("### Puts")
@@ -734,19 +732,19 @@ if st.sidebar.button("Run Analysis"):
         with st.expander("Historical IV Interpretation", expanded=False):
             interpret_historical_iv(ticker, historical_iv, current_iv)
 
-        st.subheader("7. Put to Call Ratio")
+        st.subheader("Put to Call Ratio")
         total_puts, total_calls, put_call_ratio = calculate_put_call_ratio(options_data)
         
         with st.expander("Put to Call Ratio Interpretation", expanded=False):
             interpret_put_call_ratio(ticker, total_puts, total_calls, put_call_ratio)
 
-        st.subheader("8. Greeks Analysis")
+        st.subheader("Greeks Analysis")
         calls_data, puts_data = plot_greeks(options_data, recent_price, ticker)
         
         with st.expander("Greeks Analysis Interpretation", expanded=False):
             interpret_greeks(ticker, calls_data, puts_data)
 
-        st.subheader("9. Sentiment Score")
+        st.subheader("Sentiment Score")
         high_iv_calls = overall_avg_iv_calls
         low_iv_puts = overall_avg_iv_puts
         sentiment_score, sentiment_description = calculate_sentiment_score(options_data, high_iv_calls, low_iv_puts, total_calls, total_puts)