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82a012a
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1 Parent(s): 5218bf9

Update app.py

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  1. app.py +44 -3
app.py CHANGED
@@ -3,6 +3,33 @@ import pandas as pd
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  import matplotlib.pyplot as plt
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  # (Import other necessary libraries for visualization and Gemini API interaction)
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  st.title("Event Management Financial Forecaster")
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  # Sidebar
@@ -23,12 +50,26 @@ venue_rental = st.sidebar.slider("Venue Rental", 0, 50000, 25000)
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  # Main Area
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  st.subheader("Projected P&L Statement")
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- # (Create P&L bar chart using matplotlib or other visualization library)
 
 
 
 
 
 
 
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  st.subheader("Cash Flow Forecast")
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- # (Create cash flow line chart)
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- # (Add other visualizations for sensitivity analysis and KPIs)
 
 
 
 
 
 
 
 
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  # Optional: AI-Powered Insights (using Gemini API)
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  if gemini_api_key:
 
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  import matplotlib.pyplot as plt
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  # (Import other necessary libraries for visualization and Gemini API interaction)
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+ # Define Color Palette
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+ primary_color = "#3498db" # Example: Bright blue
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+ secondary_color = "#e74c3c" # Example: Vibrant red
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+ background_color = "#f0f0f0" # Example: Light gray
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+ text_color = "#2c3e50" # Example: Dark gray
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+
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+ # Apply Styling
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+ st.markdown(
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+ f"""
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+ <style>
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+ .stApp {{
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+ background-color: {background_color};
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+ color: {text_color};
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+ }}
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+ .sidebar .sidebar-content {{
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+ background-color: {primary_color};
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+ color: white;
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+ }}
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+ .stButton button {{
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+ background-color: {secondary_color};
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+ color: white;
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+ }}
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+ </style>
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+ """,
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+ unsafe_allow_html=True,
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+ )
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+
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  st.title("Event Management Financial Forecaster")
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  # Sidebar
 
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  # Main Area
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  st.subheader("Projected P&L Statement")
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+
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+ # Visualization Styling for P&L
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+ fig_pl, ax_pl = plt.subplots()
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+ # ... (plot P&L data)
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+ ax_pl.set_facecolor(background_color)
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+ plt.grid(color="white", linestyle="--", linewidth=0.5)
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+ # ... (other plot customizations)
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+ st.pyplot(fig_pl)
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  st.subheader("Cash Flow Forecast")
 
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+ # Visualization Styling for Cash Flow
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+ fig_cf, ax_cf = plt.subplots()
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+ # ... (plot cash flow data)
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+ ax_cf.set_facecolor(background_color)
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+ plt.grid(color="white", linestyle="--", linewidth=0.5)
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+ # ... (other plot customizations)
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+ st.pyplot(fig_cf)
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+
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+ # (Add other visualizations for sensitivity analysis and KPIs with similar styling)
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  # Optional: AI-Powered Insights (using Gemini API)
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  if gemini_api_key: