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import pandas as pd |
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import plotly.express as px |
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import streamlit as st |
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from process_kpi.process_wbts_capacity import WbtsCapacity, load_data |
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from utils.convert_to_excel import convert_dfs |
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st.title(" 📊 WBTS Capacity Analysis") |
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doc_col, image_col = st.columns(2) |
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with doc_col: |
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st.write( |
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"""This app allows you to analyze the capacity of WBTSs in a network. |
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It provides insights into the utilization of BB and CE resources, |
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helping you identify potential capacity issues and plan for upgrades. |
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The report should be run with a minimum of 3 days of data. |
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- Daily Aggregated |
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- WBTS level |
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- Exported in CSV format. |
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""" |
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) |
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with image_col: |
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st.image("./assets/wbts_capacity.png", width=400) |
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uploaded_file = st.file_uploader( |
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"Upload WBTS capacity report in CSV format", type="csv" |
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) |
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col1, col2, col3 = st.columns(3) |
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if uploaded_file is not None: |
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WbtsCapacity.final_results = None |
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with col1: |
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num_days = st.number_input( |
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"Number of days for analysis", |
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min_value=3, |
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max_value=30, |
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value=7, |
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) |
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with col2: |
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number_of_threshold_days = st.number_input( |
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"Number of days for threshold", |
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min_value=1, |
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max_value=30, |
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value=3, |
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) |
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with col3: |
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threshold = st.number_input("Threshold", min_value=1, max_value=100, value=80) |
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if st.button("Analyze Data", type="primary"): |
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try: |
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df = load_data(uploaded_file, num_days, threshold, number_of_threshold_days) |
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WbtsCapacity.final_results = convert_dfs([df], ["WBTS_Analysis"]) |
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if WbtsCapacity.final_results is not None: |
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st.download_button( |
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on_click="ignore", |
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type="primary", |
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label="Download the Analysis Report", |
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data=WbtsCapacity.final_results, |
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file_name="WBTS_Analysis_Report.xlsx", |
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mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", |
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) |
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st.write(df) |
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bb_comments_df = df["bb_comments"].value_counts().reset_index() |
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bb_comments_df.columns = ["bb_comments", "count"] |
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bb_col1, bb_col2 = st.columns(2) |
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with bb_col1: |
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st.write(bb_comments_df) |
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fig = px.bar( |
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bb_comments_df, |
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x="bb_comments", |
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y="count", |
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title="BB Comments Distribution", |
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) |
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fig.update_traces(texttemplate="%{value}", textposition="outside") |
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with bb_col2: |
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st.plotly_chart(fig) |
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ce_comments_df = df["ce_comments"].value_counts().reset_index() |
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ce_comments_df.columns = ["ce_comments", "count"] |
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ce_col1, ce_col2 = st.columns(2) |
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with ce_col1: |
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st.write(ce_comments_df) |
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fig = px.bar( |
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ce_comments_df, |
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x="ce_comments", |
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y="count", |
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title="CE Comments Distribution", |
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) |
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fig.update_traces(texttemplate="%{value}", textposition="outside") |
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with ce_col2: |
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st.plotly_chart(fig) |
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except Exception as e: |
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st.error(f"An error occurred. Error: {e}") |
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