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Update app.py
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app.py
CHANGED
@@ -1,69 +1,94 @@
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import streamlit as st
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import plotly.express as px
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from salesforce_integration import fetch_poles
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st.title("π‘ VIEP Smart Poles Dashboard")
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#
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except Exception as e:
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st.error(f"β οΈ Error connecting to Salesforce:\n\n{e}")
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st.stop()
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st.sidebar.header("π Filter Data")
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#
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filtered_df = df[
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(df["Alert_Level__c"].isin(
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(df["Site__c"].isin(selected_sites))
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]
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if selected_camera_status != "All":
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filtered_df = filtered_df[filtered_df["Camera_Status__c"] == selected_camera_status]
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#
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col2.metric("Red Alerts", filtered_df[filtered_df["Alert_Level__c"] == "Red"].shape[0])
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col3.metric("Power Issues", filtered_df[filtered_df["Power_Sufficient__c"] == "No"].shape[0])
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col4.metric("Offline Cameras", filtered_df[filtered_df["Camera_Status__c"] == "Offline"].shape[0])
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#
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st.subheader("π Pole Table")
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st.dataframe(filtered_df)
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#
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filtered_df,
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x="
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y=
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)
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st.plotly_chart(
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# β
Camera Status
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st.subheader("π₯ Camera Status Distribution")
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fig2 = px.pie(filtered_df, names="Camera_Status__c", hole=0.4)
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st.plotly_chart(fig2)
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# β
Tilt vs Vibration
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if "Tilt__c" in filtered_df.columns and "Vibration__c" in filtered_df.columns:
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st.subheader("π Tilt vs Vibration")
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fig3 = px.scatter(
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filtered_df,
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x="Tilt__c",
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y="Vibration__c",
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color="Alert_Level__c",
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hover_name="Name"
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)
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st.plotly_chart(fig3)
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else:
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st.warning("Tilt or Vibration data not available in records.")
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# app.py
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import streamlit as st
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from salesforce_integration import fetch_poles
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from modules.visuals import display_dashboard, display_charts
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import plotly.express as px
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import pandas as pd
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# Title
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st.title("π‘ VIEP Smart Poles Dashboard")
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# Get data
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df = fetch_poles()
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# Fetch the raw data from Salesforce
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df = fetch_poles()
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# Sidebar Filters (your code should go here!)
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st.sidebar.header("π Filter Data")
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selected_alert_levels = st.sidebar.multiselect(
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"Alert Level", ["Red", "Yellow", "Green"], default=["Red", "Yellow", "Green"]
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)
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selected_sites = st.sidebar.multiselect(
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"Site", ["Hyderabad", "Gadwal", "Kurnool", "Ballari"],
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default=["Hyderabad", "Gadwal", "Kurnool", "Ballari"]
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)
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selected_camera_status = st.sidebar.selectbox(
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"Camera Status", ["All", "Online", "Offline"]
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)
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# Apply filters to create filtered_df
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filtered_df = df[
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(df["Alert_Level__c"].isin(selected_alert_levels)) &
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(df["Site__c"].isin(selected_sites))
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]
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if selected_camera_status != "All":
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filtered_df = filtered_df[filtered_df["Camera_Status__c"] == selected_camera_status]
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# Now use filtered_df everywhere
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# Show system summary
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display_dashboard(filtered_df)
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# Show pole table
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st.subheader("π Pole Table")
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st.dataframe(filtered_df)
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# Show charts
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display_charts(filtered_df)
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# Tilt vs Vibration Scatter Plot
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st.subheader("π Tilt vs Vibration")
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fig_tv = px.scatter(
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filtered_df,
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x="Tilt_Angle__c",
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y="Vibration_Level__c",
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color="Alert_Level__c",
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hover_name="Name",
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title="Tilt Angle vs Vibration Level"
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)
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st.plotly_chart(fig_tv)
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# 1. System Summary (Show first)
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display_dashboard(df)
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# 2. Pole Table
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st.subheader("π Pole Table")
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st.dataframe(df, use_container_width=True)
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# 3. Charts
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st.subheader("β Energy Generation (Solar vs Wind)")
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st.plotly_chart(px.bar(df, x="Name", y=["Solar_Generation__c", "Wind_Generation__c"], barmode="group"))
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# 4. Charts (Energy + Alert Breakdown)
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display_charts(df)
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import plotly.express as df
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st.subheader("π Tilt vs Vibration")
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fig_tv = px.scatter(
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filtered_df,
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x="Tilt_Angle__c", # make sure this is your column name
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y="Vibration_Level__c", # make sure this is your column name
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color="Alert_Level__c",
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hover_name="Name",
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title="Tilt Angle vs Vibration Level"
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st.plotly_chart(fig_tv)
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