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README.md

@@ -1,31 +1,92 @@
 ---
-dataset_info:
-  features:
-  - name: timestamp
-    dtype: string
-  - name: country
-    dtype: string
-  - name: city
-    dtype: string
-  - name: service_type
-    dtype: string
-  - name: wait_minutes
-    dtype: int64
-  - name: status
-    dtype: string
-  - name: notes
-    dtype: string
-  - name: source
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 13522
-    num_examples: 98
-  download_size: 5304
-  dataset_size: 13522
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+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")
+```