---
license: cc-by-4.0
language:
  - en
  - pt
  - es
size_categories:
  - n<1K
tags:
  - public-service
  - government
  - south-america
  - brazil
  - argentina
  - quality-improvement
  - merged
---

# Merged BR–AR Hourly Public Service Quality

Cleaned, merged public-service response dataset for **Brazil (São Paulo state)** and
**Argentina (Buenos Aires province)**, produced by a South America regional
government public-service improvement program.

- **Rows:** 98 (after cleaning; < 100 as required)
- **Granularity:** hourly service-call records
- **Coverage:** 2026-08-11T03:00:00Z → 2026-08-14T01:15:00Z

## Sources

| Source system | Dataset | Country | Rows (raw) |
|---|---|---|---|
| Brazil / São Paulo | [`toolathon123/sao-paulo-service-calls-hourly`](https://huggingface.co/datasets/toolathon123/sao-paulo-service-calls-hourly) | `BR` | 54 |
| Argentina / Buenos Aires | [`toolathon123/buenos-aires-service-calls-hourly`](https://huggingface.co/datasets/toolathon123/buenos-aires-service-calls-hourly) | `AR` | 48 |

Raw merged rows: **102** → final rows: **98**.

## Schema

| Column | Type | Description |
|---|---|---|
| `timestamp` | string | Request time, normalized to UTC ISO 8601 (`YYYY-MM-DDTHH:MM:SSZ`) |
| `country` | string | `BR` or `AR` |
| `city` | string | Lowercase, accent-free, spaces → underscores (e.g. `sao_paulo`, `bahia_blanca`) |
| `service_type` | string | Unified category: `health`, `transport`, `water`, `electricity`, `public_safety`, `other` |
| `wait_minutes` | int | Wait time in minutes (missing filled with country+service median) |
| `status` | string | Response status (`UNKNOWN` where missing) |
| `notes` | string | Free-text note (kept from source, PT/ES) |
| `source` | string | Provenance dataset id |

## Cleaning & standardization steps

1. **Load** both sources with `datasets.load_dataset`.
2. **Merge** preserving record-level integrity (BR rows first, then AR).
3. **Timestamp unification** — all `timestamp` / `created_at` values converted to UTC
   ISO 8601 (BR timezone `America/Sao_Paulo`, AR timezone `America/Argentina/Buenos_Aires`).
4. **Country & city standardization** — `country` → `BR`/`AR`; city lowercased,
   accent-stripped (NFKD), spaces → underscores.
5. **Service-type mapping** — PT/ES taxonomies → `health`/`transport`/`water`/
   `electricity`/`public_safety`/`other`.
6. **Missing values** — `wait_minutes` filled with the median per (country, service_type);
   `status` filled with `UNKNOWN`.
7. **Deduplication** — exact duplicates removed, first occurrence kept.

## Quality checks

| Metric | Value |
|---|---|
| Duplicate records removed | 4 |
| Missing `wait_minutes` filled | 21 |
| Missing `status` filled | 17 |
| Missing values filled (total) | 38 |
| Time-format anomalies (non-dominant raw formats) | 16 |
| Unparseable timestamps | 0 |
| Final rows | 98 (< 100) |

### Hourly continuity (UTC hour buckets)

| Country | Min hour (UTC) | Max hour (UTC) | Hours spanned | Hours with calls | Empty hourly slots |
|---|---|---|---|---|---|
| BR | 2026-08-11T04:00Z | 2026-08-14T01:00Z | 70 | 32 | 38 |
| AR | 2026-08-11T03:00Z | 2026-08-14T00:00Z | 70 | 32 | 38 |

Service calls are event-based, so not every hour has a call; gaps are expected and
reported above for transparency.

## Load

```python
from datasets import load_dataset
ds = load_dataset("toolathon123/merged-br-ar-hourly-public-service-quality", split="train")
```