Update app.py

app.py

@@ -6,6 +6,7 @@ import requests
 from io import BytesIO
 import streamlit as st
 import streamlit.components.v1 as components
+import plotly.express as px
 
 # Load data from Excel URL with error handling
 def load_data(url):
@@ -94,23 +95,36 @@ def calculate_impact(df, center):
     # Return the new statistics
     return latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before
 
-# Display the impact of the data center on latency and bandwidth
-def display_impact(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before):
-    impact_data = {
-        "Before Data Center": {
-            "Latency": f"{avg_latency_before:.2f} ms",
-            "Download Speed": f"{avg_download_before:.2f} Mbps",
-            "Upload Speed": f"{avg_upload_before:.2f} Mbps"
-        },
-        "After Data Center": {
-            "Latency": f"{latency_reduction:.2f} ms",
-            "Download Speed": f"{download_increase:.2f} Mbps",
-            "Upload Speed": f"{upload_increase:.2f} Mbps"
-        }
-    }
+# Display the 3D bar chart for impact
+def display_3d_bar_chart(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before):
+    if latency_reduction is None:
+        st.write("No data to display in the chart.")
+        return
     
-    st.write("Impact of Data Center on Latency and Bandwidth:")
-    st.write(impact_data)
+    # Create data for plotting
+    metrics = ['Latency (ms)', 'Download Speed (Mbps)', 'Upload Speed (Mbps)']
+    before = [avg_latency_before, avg_download_before, avg_upload_before]
+    after = [latency_reduction, download_increase, upload_increase]
+
+    impact_data = pd.DataFrame({
+        'Metric': metrics,
+        'Before': before,
+        'After': after
+    })
+
+    # Create a 3D bar chart using Plotly
+    fig = px.bar(
+        impact_data,
+        x='Metric',
+        y=['Before', 'After'],
+        barmode='group',
+        title="Impact of Data Center on Latency and Bandwidth",
+        labels={"value": "Speed / Latency", "Metric": "Metric"},
+        height=400
+    )
+
+    # Display the chart in the Streamlit app
+    st.plotly_chart(fig)
 
 # Main function to run the application
 def main():
@@ -137,7 +151,7 @@ def main():
     # Calculate the impact of adding the data center
     latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before = calculate_impact(df, center)
     if latency_reduction is not None:
-        display_impact(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before)
+        display_3d_bar_chart(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before)
 
 if __name__ == "__main__":
     main()