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Standardize Electric Sheep Africa dataset card

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  1. README.md +146 -85
README.md CHANGED
@@ -5,102 +5,120 @@ language:
5
  task_categories:
6
  - tabular-regression
7
  - time-series-forecasting
8
- multilinguality: monolingual
9
  size_categories:
10
  - n<1K
11
  tags:
12
- - tabular
13
- - csv
14
- - africa
15
- - mauritius
16
- - official-statistics
17
- - open-data
18
- - tourism
 
 
 
19
  configs:
20
  - config_name: default
21
  data_files:
22
  - split: train
23
  path: data/train-00000-of-00001.parquet
24
- pretty_name: "Arrival and Departure of Tourist by year, age group and gender | Africa (Mauritius official open data)"
25
  ---
26
 
27
- # Arrival and Departure of Tourist by year, age group and gender | Africa (Mauritius official open data)
28
 
29
- 136 rows - 1 Africa country - 2019-2020 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
30
 
31
  ![rows](https://img.shields.io/badge/rows-136-blue)
32
  ![countries](https://img.shields.io/badge/countries-1-green)
33
- ![years](https://img.shields.io/badge/years-2019-2020-orange)
34
  ![indicators](https://img.shields.io/badge/indicators-17-purple)
35
- ![license](https://img.shields.io/badge/license-cc-by-sa-4.0-lightgrey)
36
 
37
  ## TL;DR
38
 
39
- This dataset packages one official `CSV` resource from **Mauritius** as
40
- ML-ready Parquet. The source file is the provenance boundary; all usable
41
- indicators or tabular columns from the resource stay together in this repo.
42
 
43
- ## About the source
44
 
45
- - **Source:** [Arrival and Departure of Tourist by year, age group and gender](https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender)
46
- - **Publisher:** MDPA
47
- - **Resource:** [Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv](https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/resource/53d5103d-9498-4765-be6f-fa94eaf90293/download/arrival-and-departure-of-tourist-by-year-age-group-and-gender_0.csv)
48
- - **Format:** `CSV`
49
- - **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
50
- - **Packaging mode:** `indicator_long`
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
51
 
52
- ## Geographic coverage
53
 
54
- 1 Africa country:
55
 
56
- | Country | Rows | First year | Last year | Name |
57
- |---------|-----:|-----------:|----------:|------|
58
  | `MU` | 136 | 2019 | 2020 | `Mauritius` |
59
 
60
- ## Indicators or Resource Contents
61
-
62
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1-56b9f4ae` - Arrival and Departure of Tourist by year, age group and gender - under 1
63
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-1-4-a76f519e` - Arrival and Departure of Tourist by year, age group and gender - d 1 4
64
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-5-9-027c859a` - Arrival and Departure of Tourist by year, age group and gender - d 5 9
65
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-10-14-51e75f59` - Arrival and Departure of Tourist by year, age group and gender - d 10 14
66
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-15-19-58d9ff8a` - Arrival and Departure of Tourist by year, age group and gender - d 15 19
67
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-20-24-c9e1f7c0` - Arrival and Departure of Tourist by year, age group and gender - d 20 24
68
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-25-29-c769dd67` - Arrival and Departure of Tourist by year, age group and gender - d 25 29
69
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-30-34-9a285493` - Arrival and Departure of Tourist by year, age group and gender - d 30 34
70
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-35-39-569157ac` - Arrival and Departure of Tourist by year, age group and gender - d 35 39
71
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-40-44-44ca86a4` - Arrival and Departure of Tourist by year, age group and gender - d 40 44
72
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-45-49-b278edc1` - Arrival and Departure of Tourist by year, age group and gender - d 45 49
73
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-50-54-6065293c` - Arrival and Departure of Tourist by year, age group and gender - d 50 54
74
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-55-59-0f0932ef` - Arrival and Departure of Tourist by year, age group and gender - d 55 59
75
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-60-64-3964f3d5` - Arrival and Departure of Tourist by year, age group and gender - d 60 64
76
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-65-69-ed4ebc88` - Arrival and Departure of Tourist by year, age group and gender - d 65 69
77
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-70-and-o-bd9c9022` - Arrival and Departure of Tourist by year, age group and gender - d 70 and over
78
- - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-not-stated-2391a5c4` - Arrival and Departure of Tourist by year, age group and gender - not stated
79
 
80
  ## Schema
81
 
82
  | Column | Type | Description | Example |
83
  |--------|------|-------------|---------|
84
- | `indicator_id` | `string` | Stable indicator identifier. | `arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1-56` |
85
  | `indicator_name` | `string` | Human-readable indicator name. | `Arrival and Departure of Tourist by year, age group and gender - under 1` |
86
- | `country_iso3` | `string` | ISO3 country code. | `MU` |
87
- | `country_name` | `string` | Country name. | `Mauritius` |
88
- | `year` | `Int64` | Observation year. | `2019` |
89
- | `value` | `float64` | Numeric observation value. | `4822.0` |
90
- | `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` |
91
- | `dimension_status` | `string` | Source dimension. | `Arrival` |
92
- | `dimension_gender` | `string` | Source dimension. | `Male` |
93
- | `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` |
94
- | `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` |
95
- | `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` |
96
- | `source_provider` | `category` | Publishing organization. | `MDPA` |
97
- | `source_dataset` | `category` | Source package title. | `Arrival and Departure of Tourist by year, age group and gender` |
98
- | `source_resource` | `category` | Source resource title. | `Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv` |
99
- | `source_package_id` | `category` | CKAN package UUID. | `452a5676-4fec-4451-808f-6edfeb3ea6de` |
100
- | `source_resource_id` | `category` | CKAN resource UUID. | `53d5103d-9498-4765-be6f-fa94eaf90293` |
101
- | `source_url` | `category` | Original source resource URL. | `https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/reso` |
102
- | `license_id` | `category` | Source license identifier. | `CC-BY-SA-4.0` |
103
- | `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-08T16:26:20Z` |
104
 
105
  ## Usage
106
 
@@ -112,29 +130,78 @@ df = ds["train"].to_pandas()
112
  print(df.head())
113
  ```
114
 
115
- ### Filter to one country
116
 
117
  ```python
118
- sample_country = df[df["country_iso3"] == "MU"]
 
119
  ```
120
 
121
- ### Work with indicators
122
 
123
  ```python
124
- if "indicator_id" in df.columns:
125
- print(df["indicator_id"].value_counts().head())
126
- sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
127
  ```
128
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
129
  ## Citation
130
 
131
  ```bibtex
132
  @misc{electric_sheep_africa_africa_mauritius_arrival_and_departure_of_tourist_by_year_age_group_and_gen_647d_2020,
133
- title = {Arrival and Departure of Tourist by year, age group and gender | Africa (Mauritius official open data)},
134
  author = {MDPA},
135
  year = {2020},
136
  url = {https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender},
137
- publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
138
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9}}
139
  }
140
  ```
@@ -143,20 +210,14 @@ if "indicator_id" in df.columns:
143
 
144
  Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).
145
 
146
- Original data (c) MDPA. When using this dataset, please cite both the
147
- original source above and the Electric Sheep Africa repackaging.
148
-
149
- ## About Electric Sheep
150
 
151
- Electric Sheep Africa is part of the Electric Sheep mission: a unified,
152
- ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
153
- open sources, normalize the schemas, package as Parquet, and publish with
154
- consistent dataset cards so researchers and developers can use `load_dataset()`
155
- to start working in seconds.
156
 
157
- Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
158
 
159
  ---
160
 
161
- Provenance: ingested 2026-08-08 via the Electric Sheep pipeline. Source URL:
162
- https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/resource/53d5103d-9498-4765-be6f-fa94eaf90293/download/arrival-and-departure-of-tourist-by-year-age-group-and-gender_0.csv
 
5
  task_categories:
6
  - tabular-regression
7
  - time-series-forecasting
8
+ multilinguality: multilingual
9
  size_categories:
10
  - n<1K
11
  tags:
12
+ - "tabular"
13
+ - "africa"
14
+ - "open-data"
15
+ - "official-statistics"
16
+ - "mauritius"
17
+ - "mdpa"
18
+ - "demographics"
19
+ - "travel-and-tourism"
20
+ - "arrival"
21
+ - "departure"
22
  configs:
23
  - config_name: default
24
  data_files:
25
  - split: train
26
  path: data/train-00000-of-00001.parquet
27
+ pretty_name: "Arrival and Departure of Tourist by Year Age Group and Gen | Africa (MDPA)"
28
  ---
29
 
30
+ # Arrival and Departure of Tourist by Year Age Group and Gen | Africa (MDPA)
31
 
32
+ **136 rows** - **1 Africa country/area** - **2019-2020** - **17 indicators** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
33
 
34
  ![rows](https://img.shields.io/badge/rows-136-blue)
35
  ![countries](https://img.shields.io/badge/countries-1-green)
36
+ ![period](https://img.shields.io/badge/period-2019--2020-orange)
37
  ![indicators](https://img.shields.io/badge/indicators-17-purple)
38
+ ![license](https://img.shields.io/badge/license-cc--by--sa--4.0-lightgrey)
39
 
40
  ## TL;DR
41
 
42
+ This dataset contains **136 rows** from **MDPA**, covering **Arrival and Departure of Tourist by Year Age Group and Gen**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
 
 
43
 
44
+ ## What This Dataset Measures
45
 
46
+ Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.
47
+
48
+ Source-provided context: The data shows number of arrival and departure of tourist by year, by travel status, by age group and by gender
49
+
50
+ ## How To Read This Dataset
51
+
52
+ - **One row means:** one indicator observation for one geography, time period, and optional source dimensions.
53
+ - **Primary geography column:** `country_iso3`.
54
+ - **Best time column:** `year`.
55
+ - **Time coverage basis:** year.
56
+ - **Recommended join keys:** `country_iso3`, `year`, `indicator_id`.
57
+
58
+ ## Coverage
59
+
60
+ | Dimension | Value |
61
+ |---|---:|
62
+ | Rows | 136 |
63
+ | Countries/areas | 1 |
64
+ | First period | 2019 |
65
+ | Last period | 2020 |
66
+ | Indicators | 17 |
67
+ | Columns | 20 |
68
+ | Source format | CSV |
69
 
70
+ ## Geographic Coverage
71
 
72
+ Top areas shown below, sorted by row count when available:
73
 
74
+ | Area | Rows | First year | Last year | Name |
75
+ |------|-----:|-----------:|----------:|------|
76
  | `MU` | 136 | 2019 | 2020 | `Mauritius` |
77
 
78
+ ## Indicators, Variables, Or Resource Contents
79
+
80
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1-56b9f4ae` - Arrival and Departure of Tourist by year, age group and gender - under 1(source_units_unspecified)
81
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-1-4-a76f519e` - Arrival and Departure of Tourist by year, age group and gender - d 1 4(source_units_unspecified)
82
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-5-9-027c859a` - Arrival and Departure of Tourist by year, age group and gender - d 5 9(source_units_unspecified)
83
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-10-14-51e75f59` - Arrival and Departure of Tourist by year, age group and gender - d 10 14(source_units_unspecified)
84
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-15-19-58d9ff8a` - Arrival and Departure of Tourist by year, age group and gender - d 15 19(source_units_unspecified)
85
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-20-24-c9e1f7c0` - Arrival and Departure of Tourist by year, age group and gender - d 20 24(source_units_unspecified)
86
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-25-29-c769dd67` - Arrival and Departure of Tourist by year, age group and gender - d 25 29(source_units_unspecified)
87
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-30-34-9a285493` - Arrival and Departure of Tourist by year, age group and gender - d 30 34(source_units_unspecified)
88
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-35-39-569157ac` - Arrival and Departure of Tourist by year, age group and gender - d 35 39(source_units_unspecified)
89
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-40-44-44ca86a4` - Arrival and Departure of Tourist by year, age group and gender - d 40 44(source_units_unspecified)
90
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-45-49-b278edc1` - Arrival and Departure of Tourist by year, age group and gender - d 45 49(source_units_unspecified)
91
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-50-54-6065293c` - Arrival and Departure of Tourist by year, age group and gender - d 50 54(source_units_unspecified)
92
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-55-59-0f0932ef` - Arrival and Departure of Tourist by year, age group and gender - d 55 59(source_units_unspecified)
93
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-60-64-3964f3d5` - Arrival and Departure of Tourist by year, age group and gender - d 60 64(source_units_unspecified)
94
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-65-69-ed4ebc88` - Arrival and Departure of Tourist by year, age group and gender - d 65 69(source_units_unspecified)
95
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-d-70-and-o-bd9c9022` - Arrival and Departure of Tourist by year, age group and gender - d 70 and over(source_units_unspecified)
96
+ - `arrival-and-departure-of-tourist-by-year-age-group-and-gender-not-stated-2391a5c4` - Arrival and Departure of Tourist by year, age group and gender - not stated(source_units_unspecified)
97
 
98
  ## Schema
99
 
100
  | Column | Type | Description | Example |
101
  |--------|------|-------------|---------|
102
+ | `indicator_id` | `string` | Stable source or Electric Sheep Africa indicator identifier. | `arrival-and-departure-of-tourist-by-year-age-group-and-gender-under-1...` |
103
  | `indicator_name` | `string` | Human-readable indicator name. | `Arrival and Departure of Tourist by year, age group and gender - under 1` |
104
+ | `country_iso3` | `string` | ISO3 country or area code. | `MU` |
105
+ | `country_name` | `string` | Country or area name. | `Mauritius` |
106
+ | `year` | `int64` | Observation year. | `2019` |
107
+ | `value` | `double` | Numeric observation value. | `4822.0` |
108
+ | `unit` | `string` | Measurement unit, when supplied by the source. | `source_units_unspecified` |
109
+ | `dimension_status` | `string` | Source dimension retained during long-form normalization. | `Arrival` |
110
+ | `dimension_gender` | `string` | Source dimension retained during long-form normalization. | `Male` |
111
+ | `source_period_start_year` | `int64` | Start year inferred from source metadata. | `` |
112
+ | `source_period_end_year` | `int64` | End year inferred from source metadata. | `` |
113
+ | `source_period_label` | `string` | Source column from the original resource. | `` |
114
+ | `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `MDPA` |
115
+ | `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `Arrival and Departure of Tourist by year, age group and gender` |
116
+ | `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv` |
117
+ | `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `452a5676-4fec-4451-808f-6edfeb3ea6de` |
118
+ | `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `53d5103d-9498-4765-be6f-fa94eaf90293` |
119
+ | `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/r...` |
120
+ | `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `CC-BY-SA-4.0` |
121
+ | `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-08-08T16:26:20Z` |
122
 
123
  ## Usage
124
 
 
130
  print(df.head())
131
  ```
132
 
133
+ ### Inspect Columns
134
 
135
  ```python
136
+ print(df.info())
137
+ print(df.head())
138
  ```
139
 
140
+ ### Filter By Geography
141
 
142
  ```python
143
+ if "country_iso3" in df.columns:
144
+ sample = df[df["country_iso3"] == "MU"]
 
145
  ```
146
 
147
+ ### Time-Series Pattern
148
+
149
+ ```python
150
+ if "value" in df.columns and "year" in df.columns:
151
+ trend = df.sort_values("year")
152
+ ```
153
+
154
+ ### Pivot For Analysis
155
+
156
+ ```python
157
+ if {"indicator_id", "year", "value"}.issubset(df.columns):
158
+ matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
159
+ print(matrix.tail())
160
+ ```
161
+
162
+ ## Data Quality Notes
163
+
164
+ - Canonical time field: `year`.
165
+ - Missing values are preserved rather than silently imputed.
166
+ - Column names are standardized for machine use; source meanings are preserved where known.
167
+ - Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.
168
+
169
+ ## Source And Provenance
170
+
171
+ - **Source:** [MDPA](https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender)
172
+ - **Publisher:** MDPA
173
+ - **Portal:** [https://data.govmu.org](https://data.govmu.org)
174
+ - **Resource:** [Arrival-and-Departure-of-Tourist-by-year-age-group-and-gender_0.csv](https://data.govmu.org/dataset/452a5676-4fec-4451-808f-6edfeb3ea6de/resource/53d5103d-9498-4765-be6f-fa94eaf90293/download/arrival-and-departure-of-tourist-by-year-age-group-and-gender_0.csv)
175
+ - **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
176
+ - **Retrieved/generated:** `2026-08-08T16:42:03Z`
177
+ - **Hugging Face repo:** [electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9](https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9)
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+
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+ ## Transformations Applied
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+
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+ - Converted the source table to Parquet for efficient analytics and ML workflows.
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+ - Added or preserved source provenance columns where available.
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+ - Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
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+ - Preserved source-reported values without analytical imputation.
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+
186
+ ## Suggested Analyses
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+
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+ - Build demographic profiles
189
+ - Normalize indicators per capita
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+ - Join with service-delivery datasets
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+ - Build time-series views and period-over-period comparisons
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+ - Pivot to geography x period or indicator x period matrices
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+ - Check missingness before modeling
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+ - Use `country_iso3` as the safest geography join key when present
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+
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  ## Citation
197
 
198
  ```bibtex
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  @misc{electric_sheep_africa_africa_mauritius_arrival_and_departure_of_tourist_by_year_age_group_and_gen_647d_2020,
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+ title = {Arrival and Departure of Tourist by Year Age Group and Gen | Africa (MDPA)},
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  author = {MDPA},
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  year = {2020},
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  url = {https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender},
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+ publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
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  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-arrival-and-departure-of-tourist-by-year-age-group-and-gen-647d1ea9}}
206
  }
207
  ```
 
210
 
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  Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).
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+ Original data is published by MDPA. Electric Sheep Africa
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+ engineering standardizes the data for discovery, loading, and analysis on
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+ Hugging Face. Cite both the original source and this ML-ready dataset when used.
 
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+ ## About Electric Sheep Africa
 
 
 
 
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+ Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
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  ---
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+ Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/arrival-and-departure-tourist-year-age-group-and-gender