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README.md

@@ -16,30 +16,36 @@ tags:
 - official-statistics
 - open-data
 - tourism
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-00000-of-00001.parquet
 pretty_name: "Air seats and tourist arrivals, 2019 and 2022 – 2023 | Africa (Mauritius official open data)"
 ---
 
 # Air seats and tourist arrivals, 2019 and 2022 – 2023 | Africa (Mauritius official open data)
 
-6 rows - 1 Africa country - 1970 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+8 rows - 1 Africa country - 2019-2024 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
 
-![rows](https://img.shields.io/badge/rows-6-blue)
+![rows](https://img.shields.io/badge/rows-8-blue)
 ![countries](https://img.shields.io/badge/countries-1-green)
-![years](https://img.shields.io/badge/years-1970-orange)
-![indicators](https://img.shields.io/badge/indicators-3-purple)
+![years](https://img.shields.io/badge/years-2019-2024-orange)
+![indicators](https://img.shields.io/badge/indicators-1-purple)
 ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
 
 ## TL;DR
 
-This dataset packages one official CSV resource from **Mauritius** as
-ML-ready Parquet. The CSV is the provenance boundary; all usable indicators or
-tabular columns from the source file stay together in this repo.
+This dataset packages one official `CSV` resource from **Mauritius** as
+ML-ready Parquet. The source file is the provenance boundary; all usable
+indicators or tabular columns from the resource stay together in this repo.
 
 ## About the source
 
 - **Source:** [Air seats and tourist arrivals, 2019 and 2022 – 2023](https://data.govmu.org/dataset/air-seats-and-tourist-arrivals-2019-and-2022-2023)
 - **Publisher:** MDPA
 - **Resource:** [CSV File](https://data.govmu.org/dataset/d82e6028-8927-42d1-8e4e-87a77bb89279/resource/fd78ecf3-6674-4925-a1b3-ffd77b4b61b1/download/table1.csv)
+- **Format:** `CSV`
 - **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
 - **Packaging mode:** `indicator_long`
 
@@ -49,35 +55,35 @@ tabular columns from the source file stay together in this repo.
 
 | Country | Rows | First year | Last year | Name |
 |---------|-----:|-----------:|----------:|------|
-| `MUS` | 6 | 1970 | 1970 | `Mauritius` |
+| `MU` | 8 | 2019 | 2024 | `Mauritius` |
 
 ## Indicators or Resource Contents
 
-- `air-seats-and-tourist-arrivals-2019-and-2022-2023-d-2019-65356adc` - Air seats and tourist arrivals, 2019 and 2022 – 2023 - d 2019
-- `air-seats-and-tourist-arrivals-2019-and-2022-2023-d-2022-810ab914` - Air seats and tourist arrivals, 2019 and 2022 – 2023 - d 2022
-- `air-seats-and-tourist-arrivals-2019-and-2022-2023-d-2023-b932b7df` - Air seats and tourist arrivals, 2019 and 2022 – 2023 - d 2023
+- `air-seats-and-tourist-arrivals-2019-and-2022-2023-1732c085` - Air seats and tourist arrivals, 2019 and 2022 – 2023
 
 ## Schema
 
 | Column | Type | Description | Example |
 |--------|------|-------------|---------|
-| `indicator_id` | `object` | Stable indicator identifier. | `air-seats-and-tourist-arrivals-2019-and-2022-2023-d-2019-65356adc` |
-| `indicator_name` | `object` | Human-readable indicator name. | `Air seats and tourist arrivals, 2019 and 2022 – 2023 - d 2019` |
-| `country_iso3` | `object` | ISO3 country code. | `MUS` |
-| `country_name` | `object` | Country name. | `Mauritius` |
-| `date` | `string` | Observation date. | `1970-01-01` |
-| `year` | `Int64` | Observation year. | `1970` |
+| `indicator_id` | `string` | Stable indicator identifier. | `air-seats-and-tourist-arrivals-2019-and-2022-2023-1732c085` |
+| `indicator_name` | `string` | Human-readable indicator name. | `Air seats and tourist arrivals, 2019 and 2022 – 2023` |
+| `country_iso3` | `string` | ISO3 country code. | `MU` |
+| `country_name` | `string` | Country name. | `Mauritius` |
+| `year` | `Int64` | Observation year. | `2019` |
 | `value` | `float64` | Numeric observation value. | `2397287.0` |
-| `unit` | `object` | Measurement unit, when available. | `source_units_unspecified` |
+| `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` |
 | `dimension_year` | `string` | Source dimension. | `Total air seats` |
-| `source_provider` | `object` | Publishing organization. | `MDPA` |
-| `source_dataset` | `object` | Source package title. | `Air seats and tourist arrivals, 2019 and 2022 – 2023` |
-| `source_resource` | `object` | Source resource title. | `CSV File` |
-| `source_package_id` | `object` | CKAN package UUID. | `d82e6028-8927-42d1-8e4e-87a77bb89279` |
-| `source_resource_id` | `object` | CKAN resource UUID. | `fd78ecf3-6674-4925-a1b3-ffd77b4b61b1` |
-| `source_url` | `object` | Original CSV URL. | `https://data.govmu.org/dataset/d82e6028-8927-42d1-8e4e-87a77bb89279/reso` |
-| `license_id` | `object` | Source license identifier. | `cc-by` |
-| `retrieved_at` | `object` | UTC retrieval timestamp. | `2026-07-16T19:23:24Z` |
+| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2019` |
+| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2023` |
+| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2019-2023` |
+| `source_provider` | `category` | Publishing organization. | `MDPA` |
+| `source_dataset` | `category` | Source package title. | `Air seats and tourist arrivals, 2019 and 2022 – 2023` |
+| `source_resource` | `category` | Source resource title. | `CSV File` |
+| `source_package_id` | `category` | CKAN package UUID. | `d82e6028-8927-42d1-8e4e-87a77bb89279` |
+| `source_resource_id` | `category` | CKAN resource UUID. | `fd78ecf3-6674-4925-a1b3-ffd77b4b61b1` |
+| `source_url` | `category` | Original source resource URL. | `https://data.govmu.org/dataset/d82e6028-8927-42d1-8e4e-87a77bb89279/reso` |
+| `license_id` | `category` | Source license identifier. | `cc-by` |
+| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-08T16:26:20Z` |
 
 ## Usage
 
@@ -92,7 +98,7 @@ print(df.head())
 ### Filter to one country
 
 ```python
-sample_country = df[df["country_iso3"] == "MUS"]
+sample_country = df[df["country_iso3"] == "MU"]
 ```
 
 ### Work with indicators
@@ -106,10 +112,10 @@ if "indicator_id" in df.columns:
 ## Citation
 
 ```bibtex
-@misc{electric_sheep_africa_africa_mauritius_air_seats_and_tourist_arrivals_2019_and_2022_2023_1732c085_1970,
+@misc{electric_sheep_africa_africa_mauritius_air_seats_and_tourist_arrivals_2019_and_2022_2023_1732c085_2024,
   title        = {Air seats and tourist arrivals, 2019 and 2022 – 2023 | Africa (Mauritius official open data)},
   author       = {MDPA},
-  year         = {1970},
+  year         = {2024},
   url          = {https://data.govmu.org/dataset/air-seats-and-tourist-arrivals-2019-and-2022-2023},
   publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
   howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-air-seats-and-tourist-arrivals-2019-and-2022-2023-1732c085}}
@@ -135,5 +141,5 @@ Browse the full collection: [huggingface.co/electricsheepafrica](https://hugging
 
 ---
 
-Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL:
+Provenance: ingested 2026-08-08 via the Electric Sheep pipeline. Source URL:
 https://data.govmu.org/dataset/d82e6028-8927-42d1-8e4e-87a77bb89279/resource/fd78ecf3-6674-4925-a1b3-ffd77b4b61b1/download/table1.csv

data/train-00000-of-00001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:783da2aa6dd9bfa77b647f64c0837f01bb24de1318e9ccd8608e235dfdb2cae4
-size 12370
+oid sha256:8b192688d620028836ae50a3987044b779da83a6b9539447d36e97051b8577d5
+size 15021

metadata/source_snapshot.json

@@ -4,11 +4,13 @@
     "indicator_name",
     "country_iso3",
     "country_name",
-    "date",
     "year",
     "value",
     "unit",
     "dimension_year",
+    "source_period_start_year",
+    "source_period_end_year",
+    "source_period_label",
     "source_provider",
     "source_dataset",
     "source_resource",
@@ -18,14 +20,14 @@
     "license_id",
     "retrieved_at"
   ],
-  "generated_at": "2026-07-16T19:37:25Z",
-  "indicator_count": 3,
+  "generated_at": "2026-08-08T16:41:28Z",
+  "indicator_count": 1,
   "mode": "indicator_long",
   "repo_id": "electricsheepafrica/africa-mauritius-air-seats-and-tourist-arrivals-2019-and-2022-2023-1732c085",
-  "rows": 6,
+  "rows": 8,
   "source": {
     "api_base_url": "https://data.govmu.org",
-    "country_iso3": "MUS",
+    "country_iso3": "MU",
     "country_name": "Mauritius",
     "group_names": "travel-and-tourism",
     "license_id": "cc-by",
@@ -60,9 +62,9 @@
     "resource_size": "130",
     "resource_state": "active",
     "resource_url": "https://data.govmu.org/dataset/d82e6028-8927-42d1-8e4e-87a77bb89279/resource/fd78ecf3-6674-4925-a1b3-ffd77b4b61b1/download/table1.csv",
-    "retrieved_at": "2026-07-16T17:57:00Z",
+    "retrieved_at": "2026-08-08T16:23:36Z",
     "tag_names": "Tourism; Tourist; accommodation; air seats; arrivals; facilities; hotel; passengers; rooms"
   },
-  "year_max": 1970,
-  "year_min": 1970
+  "year_max": 2024,
+  "year_min": 2019
 }