Add ML-ready official indicator dataset
Browse files- README.md +150 -0
- data/train-00000-of-00001.parquet +3 -0
- metadata/source_snapshot.json +76 -0
README.md
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| 1 |
+
---
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license: odbl
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language:
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- en
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task_categories:
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- tabular-classification
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- tabular-regression
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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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- xlsx
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- africa
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- senegal
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- official-statistics
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- open-data
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-00000-of-00001.parquet
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pretty_name: "Déficit /Excédent pluviométrique | Africa (Senegal official open data)"
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---
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# Déficit /Excédent pluviométrique | Africa (Senegal official open data)
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1 rows - 1 Africa country - not-applicable - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
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## TL;DR
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This dataset packages one official `XLSX` resource from **Senegal** as
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ML-ready Parquet. The source file is the provenance boundary; all usable
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indicators or tabular columns from the resource stay together in this repo.
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## About the source
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- **Source:** [Déficit /Excédent pluviométrique](https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique)
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- **Publisher:** ANACIM
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- **Resource:** [META DONNEES](https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx)
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- **Format:** `XLSX`
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- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
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- **Packaging mode:** `tabular_resource`
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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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| `SEN` | 1 | n/a | n/a | `Senegal` |
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## Indicators or Resource Contents
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- This source file is packaged as a normalized tabular resource.
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `source_record_id` | `string` | Stable row identifier for tabular resources. | `996d04b0-3154-4d85-b54f-00a524d30e8f:metadata:0` |
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| `country_iso3` | `category` | ISO3 country code. | `SEN` |
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| `country_name` | `category` | Country name. | `Senegal` |
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| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `METADATA` |
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| `methode_de_collecte` | `string` | Source column. | `Données d'observation` |
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| `mode_de_calcul` | `string` | Source column. | `Différence` |
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| `frequence_de_production` | `string` | Source column. | `saisonière` |
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| `delai_de_diffusion` | `string` | Source column. | `annuelle (avant la fin de saison courante)` |
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| `indicateur_diffuse` | `string` | Source column. | `non` |
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| `niveau_de_desagregation` | `string` | Source column. | `zone` |
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| `statut_de_l_indicateur` | `string` | Source column. | `définitif` |
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| `unite_echelle` | `string` | Source column. | `unité` |
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| `source` | `string` | Source column. | `ANACIM` |
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| `methode_de_acces` | `string` | Source column. | `sur demande` |
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| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` |
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| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` |
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| `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` |
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| `source_provider` | `category` | Publishing organization. | `ANACIM` |
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| `source_dataset` | `category` | Source package title. | `Déficit /Excédent pluviométrique` |
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| `source_resource` | `category` | Source resource title. | `META DONNEES` |
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| `source_package_id` | `category` | CKAN package UUID. | `abffbd69-e914-4afa-997f-6e2ce6cdfd40` |
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| `source_resource_id` | `category` | CKAN resource UUID. | `996d04b0-3154-4d85-b54f-00a524d30e8f` |
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| `source_url` | `category` | Original source resource URL. | `https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/re` |
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| `license_id` | `category` | Source license identifier. | `odc-odbl` |
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| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-07-27T11:04:43Z` |
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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-senegal-deficit-excedent-pluviometrique-eaed970a")
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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"] == "SEN"]
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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_senegal_deficit_excedent_pluviometrique_eaed970a_2026,
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title = {Déficit /Excédent pluviométrique | Africa (Senegal official open data)},
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author = {ANACIM},
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year = {2026},
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url = {https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-deficit-excedent-pluviometrique-eaed970a}}
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}
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```
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## License
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Released under [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/).
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Original data (c) ANACIM. 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 2026-07-27 via the Electric Sheep pipeline. Source URL:
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https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx
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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 sha256:76c7a6cdd25f7525754c878b90f128234acdf7e09f09e948ad2c8a85adfb0e10
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size 18408
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metadata/source_snapshot.json
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{
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"columns": [
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"source_record_id",
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| 4 |
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"country_iso3",
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"country_name",
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"source_sheet",
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"methode_de_collecte",
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"mode_de_calcul",
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| 9 |
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"frequence_de_production",
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"delai_de_diffusion",
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| 11 |
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"indicateur_diffuse",
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"niveau_de_desagregation",
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"statut_de_l_indicateur",
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"unite_echelle",
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"source",
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"methode_de_acces",
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"source_period_start_year",
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"source_period_end_year",
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"source_period_label",
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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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| 25 |
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"source_url",
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| 26 |
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"license_id",
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| 27 |
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"retrieved_at"
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],
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"generated_at": "2026-07-27T11:05:07Z",
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| 30 |
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"indicator_count": 0,
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"mode": "tabular_resource",
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"repo_id": "electricsheepafrica/africa-senegal-deficit-excedent-pluviometrique-eaed970a",
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| 33 |
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"rows": 1,
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| 34 |
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"source": {
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| 35 |
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"api_base_url": "https://agridata.ansd.sn",
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| 36 |
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"country_iso3": "SEN",
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| 37 |
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"country_name": "Senegal",
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| 38 |
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"group_names": "climat; indicateursoddnationaux",
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| 39 |
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"license_id": "odc-odbl",
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| 40 |
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"license_title": "Open Data Commons Open Database License (ODbL)",
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| 41 |
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"license_url": "http://www.opendefinition.org/licenses/odc-odbl",
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| 42 |
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"organization_id": "7b3361ae-57cc-49a8-a402-a10cd9a1e7c3",
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| 43 |
+
"organization_name": "anacim",
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| 44 |
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"organization_title": "ANACIM",
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| 45 |
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"package_author": "",
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| 46 |
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"package_id": "abffbd69-e914-4afa-997f-6e2ce6cdfd40",
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| 47 |
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"package_maintainer": "",
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| 48 |
+
"package_metadata_created": "2024-08-30T16:55:24.489866",
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| 49 |
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"package_metadata_modified": "2025-04-14T16:46:10.852854",
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| 50 |
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"package_name": "deficitouexcedentpluviometrique",
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| 51 |
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"package_notes": "Déficit /Excédent pluviométrique ANACIM",
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| 52 |
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"package_page_url": "https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique",
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| 53 |
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"package_private": "False",
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| 54 |
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"package_state": "active",
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| 55 |
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"package_title": "Déficit /Excédent pluviométrique",
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| 56 |
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"package_version": "",
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| 57 |
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"portal_url": "https://agridata.ansd.sn",
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| 58 |
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"resource_created": "2024-08-30T16:56:39.274823",
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| 59 |
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"resource_datastore_active": "True",
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| 60 |
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"resource_description": "META DATA de l'indicateur du déficit ou excédent pluviométrique",
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| 61 |
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"resource_format": "XLSX",
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| 62 |
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"resource_hash": "ba29cf78fef3157cde73ee07fc7fd298",
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| 63 |
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"resource_id": "996d04b0-3154-4d85-b54f-00a524d30e8f",
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| 64 |
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"resource_last_modified": "2024-08-30T16:56:39.217060",
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| 65 |
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"resource_mimetype": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
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| 66 |
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"resource_name": "META DONNEES",
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| 67 |
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"resource_position": "1",
|
| 68 |
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"resource_size": "8967",
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| 69 |
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"resource_state": "active",
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| 70 |
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"resource_url": "https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx",
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| 71 |
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"retrieved_at": "2026-07-27T11:03:56Z",
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| 72 |
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"tag_names": ""
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| 73 |
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},
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| 74 |
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"year_max": null,
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| 75 |
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"year_min": null
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| 76 |
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}
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