Add ML-ready official indicator dataset
Browse files- README.md +142 -0
- data/train-00000-of-00001.parquet +3 -0
- metadata/source_snapshot.json +72 -0
README.md
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| 1 |
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---
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license: cc-by-sa-4.0
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language:
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- en
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task_categories:
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- tabular-regression
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- time-series-forecasting
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multilinguality: monolingual
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size_categories:
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- n<1K
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tags:
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- tabular
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- csv
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- africa
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- mauritius
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- official-statistics
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- open-data
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pretty_name: "Data_Budget Data 2016-2017 - Judiciary | Africa (Mauritius official open data)"
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---
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# Data_Budget Data 2016-2017 - Judiciary | Africa (Mauritius official open data)
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264 rows - 1 Africa country - 2015-2018 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
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## TL;DR
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This dataset packages one official CSV resource from **Mauritius** as
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ML-ready Parquet. The CSV is the provenance boundary; all usable indicators or
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tabular columns from the source file stay together in this repo.
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## About the source
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- **Source:** [Data_Budget Data 2016-2017 - Judiciary](https://data.govmu.org/dataset/databudget-data-2016-2017-judiciary)
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- **Publisher:** MDPA
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- **Resource:** [Data-_Judiciary-20162017_0.csv](https://data.govmu.org/dataset/970bb7f7-8138-4293-8c0d-ccb888f4bf54/resource/85939184-9e93-4e28-a8ef-34484f6bd3c0/download/data-_judiciary-20162017_0.csv)
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- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
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- **Packaging mode:** `indicator_long`
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## Geographic coverage
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1 Africa country:
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| Country | Rows | First year | Last year | Name |
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|---------|-----:|-----------:|----------:|------|
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| `MUS` | 264 | 2015 | 2018 | `Mauritius` |
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## Indicators or Resource Contents
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- `data-budget-data-2016-2017-judiciary-item-no-0a9a39c4` - Data_Budget Data 2016-2017 - Judiciary - item no
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- `data-budget-data-2016-2017-judiciary-end-financial-year-51664213` - Data_Budget Data 2016-2017 - Judiciary - end financial year
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- `data-budget-data-2016-2017-judiciary-amount-152d916a` - Data_Budget Data 2016-2017 - Judiciary - amount
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `indicator_id` | `object` | Stable indicator identifier. | `data-budget-data-2016-2017-judiciary-item-no-0a9a39c4` |
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| `indicator_name` | `object` | Human-readable indicator name. | `Data_Budget Data 2016-2017 - Judiciary - item no` |
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| `country_iso3` | `object` | ISO3 country code. | `MUS` |
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| `country_name` | `object` | Country name. | `Mauritius` |
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| `year` | `Int64` | Observation year. | `2015` |
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| `value` | `float64` | Numeric observation value. | `21110.0` |
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| `unit` | `object` | Measurement unit, when available. | `source_units_unspecified` |
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| `dimension_head` | `string` | Source dimension. | `THE JUDICIARY` |
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| `dimension_sub_head` | `string` | Source dimension. | `THE JUDICIARY` |
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| `dimension_expense_type` | `string` | Source dimension. | `Reccurrent Expenditure` |
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| `dimension_category` | `string` | Source dimension. | `Compensation of Employees` |
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| `dimension_sub_category` | `string` | Source dimension. | `Personal Emoluments` |
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| `dimension_financial_status` | `string` | Source dimension. | `Estimates` |
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| `source_provider` | `object` | Publishing organization. | `MDPA` |
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| `source_dataset` | `object` | Source package title. | `Data_Budget Data 2016-2017 - Judiciary` |
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| `source_resource` | `object` | Source resource title. | `Data-_Judiciary-20162017_0.csv` |
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| `source_package_id` | `object` | CKAN package UUID. | `970bb7f7-8138-4293-8c0d-ccb888f4bf54` |
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| `source_resource_id` | `object` | CKAN resource UUID. | `85939184-9e93-4e28-a8ef-34484f6bd3c0` |
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| `source_url` | `object` | Original CSV URL. | `https://data.govmu.org/dataset/970bb7f7-8138-4293-8c0d-ccb888f4bf54/reso` |
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| `license_id` | `object` | Source license identifier. | `CC-BY-SA-4.0` |
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| `retrieved_at` | `object` | UTC retrieval timestamp. | `2026-07-16T19:23:24Z` |
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("electricsheepafrica/africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a")
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df = ds["train"].to_pandas()
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print(df.head())
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```
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### Filter to one country
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```python
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sample_country = df[df["country_iso3"] == "MUS"]
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```
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### Work with indicators
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```python
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if "indicator_id" in df.columns:
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print(df["indicator_id"].value_counts().head())
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sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
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```
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## Citation
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```bibtex
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@misc{electric_sheep_africa_africa_mauritius_data_budget_data_2016_2017_judiciary_2a4ede9a_2018,
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title = {Data_Budget Data 2016-2017 - Judiciary | Africa (Mauritius official open data)},
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author = {MDPA},
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year = {2018},
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url = {https://data.govmu.org/dataset/databudget-data-2016-2017-judiciary},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a}}
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}
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```
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## License
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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 (c) MDPA. When using this dataset, please cite both the
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original source above and the Electric Sheep Africa repackaging.
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## About Electric Sheep
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Electric Sheep Africa is part of the Electric Sheep mission: a unified,
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ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
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open sources, normalize the schemas, package as Parquet, and publish with
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consistent dataset cards so researchers and developers can use `load_dataset()`
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to start working in seconds.
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Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
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---
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Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL:
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https://data.govmu.org/dataset/970bb7f7-8138-4293-8c0d-ccb888f4bf54/resource/85939184-9e93-4e28-a8ef-34484f6bd3c0/download/data-_judiciary-20162017_0.csv
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:22df570e8d343dacf424760dee1434383bf50cbc8f3b4840f9025ebe467ae2ce
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size 16867
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metadata/source_snapshot.json
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{
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"columns": [
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"indicator_id",
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"indicator_name",
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"country_iso3",
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"country_name",
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"year",
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"value",
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"unit",
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"dimension_head",
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"dimension_sub_head",
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"dimension_expense_type",
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"dimension_category",
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"dimension_sub_category",
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"dimension_financial_status",
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"source_provider",
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"source_dataset",
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"source_resource",
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"source_package_id",
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"source_resource_id",
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"source_url",
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"license_id",
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"retrieved_at"
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],
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"generated_at": "2026-07-16T19:40:57Z",
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"indicator_count": 3,
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"mode": "indicator_long",
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"repo_id": "electricsheepafrica/africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a",
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"rows": 264,
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"source": {
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"api_base_url": "https://data.govmu.org",
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"country_iso3": "MUS",
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"country_name": "Mauritius",
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"group_names": "finance-and-trade",
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"license_id": "CC-BY-SA-4.0",
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"license_title": "CC-BY-SA-4.0",
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"license_url": "",
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"organization_id": "fba989d1-7b9a-4338-901c-978558936a9b",
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"organization_name": "mdpa",
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| 40 |
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"organization_title": "MDPA",
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| 41 |
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"package_author": "",
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"package_id": "970bb7f7-8138-4293-8c0d-ccb888f4bf54",
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| 43 |
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"package_maintainer": "Open Data Mauritius",
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| 44 |
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"package_metadata_created": "2024-09-30T11:56:20.570216",
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| 45 |
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"package_metadata_modified": "2025-10-21T09:49:56.981601",
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"package_name": "databudget-data-2016-2017-judiciary",
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"package_notes": "",
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| 48 |
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"package_page_url": "https://data.govmu.org/dataset/databudget-data-2016-2017-judiciary",
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| 49 |
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"package_private": "False",
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| 50 |
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"package_state": "active",
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| 51 |
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"package_title": "Data_Budget Data 2016-2017 - Judiciary",
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| 52 |
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"package_version": "",
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| 53 |
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"portal_url": "https://data.govmu.org",
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| 54 |
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"resource_created": "2024-09-30T11:56:21.124566",
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| 55 |
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"resource_datastore_active": "True",
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| 56 |
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"resource_description": "",
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| 57 |
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"resource_format": "CSV",
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| 58 |
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"resource_hash": "",
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| 59 |
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"resource_id": "85939184-9e93-4e28-a8ef-34484f6bd3c0",
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| 60 |
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"resource_last_modified": "2024-09-30T11:56:21.100265",
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| 61 |
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"resource_mimetype": "text/csv",
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| 62 |
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"resource_name": "Data-_Judiciary-20162017_0.csv",
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| 63 |
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"resource_position": "1",
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| 64 |
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"resource_size": "11128",
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| 65 |
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"resource_state": "active",
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| 66 |
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"resource_url": "https://data.govmu.org/dataset/970bb7f7-8138-4293-8c0d-ccb888f4bf54/resource/85939184-9e93-4e28-a8ef-34484f6bd3c0/download/data-_judiciary-20162017_0.csv",
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| 67 |
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"retrieved_at": "2026-07-16T17:57:00Z",
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| 68 |
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"tag_names": "Judiciary; budget data; budget data judiciary 2016-2017; estimates; recurrent expenditure"
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| 69 |
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},
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| 70 |
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"year_max": 2018,
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"year_min": 2015
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}
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