documentations/wcel_capacity_doc.py

import streamlit as st

st.markdown(
    """
# WCEL Capacity Documentation

## 1. Objective
Evaluate WCEL capacity and service quality using availability, congestion, and fail-related thresholds.

## 2. When to use this tool
Use this page for 3G capacity monitoring, issue prioritization, and region-level reporting.

## 3. Input files and accepted formats
- Required: WCEL capacity report in `.csv`
- Data recommendation: at least 3 days, daily aggregated, WCEL-level report

## 4. Required columns/fields
Input CSV must provide fields required by `load_and_process_wcel_capacity_data`.
Output analysis includes fields such as:
- `final_comments`
- `operational_comments`
- `fails_comments`
- coordinates (`Latitude`, `Longitude`) for map views

## 5. Step-by-step usage
1. Open `Capacity Analysis > WCEL Capacity Analysis`.
2. Upload WCEL CSV report.
3. Configure thresholds and analysis windows.
4. Click `Analyze Data`.
5. Review analysis table, distributions, and maps.
6. Download report.

## 6. Outputs generated
- detailed WCEL analysis dataframe
- KPI dataframe
- comment distribution charts (global and by region)
- map views for fails and operational comments
- downloadable file: `WCEL_Capacity_Report.xlsx`

## 7. Frequent errors and fixes
- Processing error.
  - Fix: validate CSV structure and numeric KPI fields.
- Empty maps.
  - Fix: ensure `Latitude` and `Longitude` are populated.
- Over/under sensitivity.
  - Fix: tune thresholds to match operational baseline.

## 8. Minimal reproducible example
- Input: WCEL CSV with valid KPI and coordinate fields.
- Action: run with defaults and review output charts.
- Expected result: analysis table + map visualizations + downloadable report.

## 9. Known limitations
- Depends on strict KPI schema expected by processing module.
- Coordinate gaps reduce map coverage.
- Large datasets can increase rendering time.

## 10. Version and update date
- Documentation version: 1.0
- Last update: 2026-02-23
"""
)