Update app.py

app.py

@@ -15,7 +15,6 @@ from datetime import datetime
 st.set_page_config(page_title='Stocks Analysis',  layout='wide', page_icon=':rocket:')
 
 st.sidebar.title("Stock Option")
-# Custom CSS to change the sidebar color
 sidebar_css = """
 <style>
     div[data-testid="stSidebar"] > div:first-child {
@@ -120,8 +119,6 @@ try:
         else:
             st.write("Price-to-Book (P/B) Ratio information not available for this stock.")
 
-        ## ............................................... ##
-        # Display more detailed information
         st.subheader('Company Summary')
         if 'longBusinessSummary' in stock_info:
             LongBusinessSummary = stock_info['longBusinessSummary']
@@ -157,11 +154,8 @@ try:
         else:
             st.write("Company Officers information not available for this stock.")
 
-        ## ............................................... ##
-        # Display the latest news
         st.subheader('Latest News')
 
-        # Prepare the data for the DataFrame
         news_data_for_dataframe = []
         for news_item in news_data:
             news_title = news_item['title']
@@ -171,30 +165,21 @@ try:
             news_link = f"[Link]({news_item['link']})"
             news_data_for_dataframe.append([news_title, news_publisher, news_provider_publish_time, news_type, news_link])
 
-        # Create a Pandas DataFrame
         df = pd.DataFrame(news_data_for_dataframe, columns=["Title", "Publisher", "Provider Publish Time", "Type", "Link"])
 
-        # Display the DataFrame using Markdown without the index column
         st.markdown(df.to_markdown(index=False), unsafe_allow_html=True)
 
-    ## ............................................... ##
-    # Enhanced title with larger font size and a different color
     title = f"<h1 style='color: white; font-size: 25px; text-align: center; '>{stock_name}'s Technical Analysis</h1>"
     st.markdown(title, unsafe_allow_html=True)
 
     with st.expander("Expand"):
-        # Describing the data
         st.subheader(f'Data from {start_date} - {end_date}')
         data = yf.download(user_input, start_date, end_date)
 
         if data.empty:
-            # Display a message to the user when no data is available
             st.warning(f"No data available for stock symbol {stock_name} in the specified date range.")
         else:
-            # Reset the index to add the date column
             data = data.reset_index()
-
-            # Display data in a Plotly table
             fig = go.Figure(data=[go.Table(
                     header=dict(values=list(data.columns),
                                 font=dict(size=12, color='white'),
@@ -212,7 +197,6 @@ try:
 
             st.plotly_chart(fig, use_container_width=True)
 
-            ### ............................................... ##
             # Stock Price Over Time
             g1, g2, g3 = st.columns((1.2,1.2,1))
 
@@ -283,8 +267,6 @@ try:
             fig9.update_layout(title_text="MACD", title_x=0, margin=dict(l=0, r=10, b=10, t=30), yaxis_title=None, xaxis_title=None)
             g9.plotly_chart(fig9, use_container_width=True)
 
-            ### ............................................... ##
-
             # Relative Strength Index (RSI)
             
             delta = data['Close'].diff()
@@ -308,7 +290,6 @@ try:
             fig11.update_layout(title_text="Candlestick Chart", title_x=0, margin=dict(l=0, r=10, b=10, t=30))
             g11.plotly_chart(fig11, use_container_width=True)
 
-            ### ............................................... ##
             # Price Rate of Change (ROC)
             n = 12
             data['ROC'] = ((data['Close'] - data['Close'].shift(n)) / data['Close'].shift(n)) * 100