Standardize Electric Sheep Africa dataset card

README.md

@@ -5,90 +5,107 @@ language:
 task_categories:
 - tabular-classification
 - tabular-regression
-multilinguality: monolingual
+multilinguality: multilingual
 size_categories:
 - n<1K
 tags:
-- tabular
-- xlsx
-- africa
-- senegal
-- official-statistics
-- open-data
+- "tabular"
+- "africa"
+- "open-data"
+- "official-statistics"
+- "senegal"
+- "anacim"
+- "climat"
+- "indicateursoddnationaux"
 configs:
 - config_name: default
   data_files:
   - split: train
     path: data/train-00000-of-00001.parquet
-pretty_name: "Déficit /Excédent pluviométrique | Africa (Senegal official open data)"
+pretty_name: "Deficit Excedent Pluviometrique | Africa (ANACIM)"
 ---
 
-# Déficit /Excédent pluviométrique | Africa (Senegal official open data)
+# Deficit Excedent Pluviometrique | Africa (ANACIM)
 
-1 rows - 1 Africa country - not-applicable - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+**1 rows** - **1 Africa country/area** - **detected** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
 
 ![rows](https://img.shields.io/badge/rows-1-blue)
 ![countries](https://img.shields.io/badge/countries-1-green)
-![years](https://img.shields.io/badge/years-not-applicable-orange)
+![period](https://img.shields.io/badge/period-detected-orange)
 ![indicators](https://img.shields.io/badge/indicators-0-purple)
 ![license](https://img.shields.io/badge/license-odbl-lightgrey)
 
 ## TL;DR
 
-This dataset packages one official `XLSX` resource from **Senegal** 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.
+This dataset contains **1 rows** from **ANACIM**, covering **Deficit Excedent Pluviometrique**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
 
-## About the source
+## What This Dataset Measures
 
-- **Source:** [Déficit /Excédent pluviométrique](https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique)
-- **Publisher:** ANACIM
-- **Resource:** [META DONNEES](https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx)
-- **Format:** `XLSX`
-- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
-- **Packaging mode:** `tabular_resource`
+Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.
+
+Source-provided context: META DATA de l'indicateur du déficit ou excédent pluviométrique
+
+## How To Read This Dataset
+
+- **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
+- **Primary geography column:** `country_iso3`.
+- **Best time column:** `source_period_start_year`.
+- **Time coverage basis:** source_period_start_year.
+- **Recommended join keys:** `country_iso3` where available plus source-specific keys.
+
+## Coverage
+
+| Dimension | Value |
+|---|---:|
+| Rows | 1 |
+| Countries/areas | 1 |
+| First period | detected |
+| Last period | detected |
+| Indicators | 0 |
+| Columns | 25 |
+| Source format | XLSX |
 
-## Geographic coverage
+## Geographic Coverage
 
-1 Africa country:
+Top areas shown below, sorted by row count when available:
 
-| Country | Rows | First year | Last year | Name |
-|---------|-----:|-----------:|----------:|------|
-| `SEN` | 1 | n/a | n/a | `Senegal` |
+| Area | Rows | First year | Last year | Name |
+|------|-----:|-----------:|----------:|------|
+| `SEN` | 1 | detected | detected | `Senegal` |
 
-## Indicators or Resource Contents
+## Indicators, Variables, Or Resource Contents
 
-- This source file is packaged as a normalized tabular resource.
+- This repo preserves one source tabular resource with its usable columns kept together.
 
 ## Schema
 
 | Column | Type | Description | Example |
 |--------|------|-------------|---------|
-| `source_record_id` | `string` | Stable row identifier for tabular resources. | `996d04b0-3154-4d85-b54f-00a524d30e8f:metadata:0` |
-| `country_iso3` | `category` | ISO3 country code. | `SEN` |
-| `country_name` | `category` | Country name. | `Senegal` |
-| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `METADATA` |
-| `methode_de_collecte` | `string` | Source column. | `Données d'observation` |
-| `mode_de_calcul` | `string` | Source column. | `Différence` |
-| `frequence_de_production` | `string` | Source column. | `saisonière` |
-| `delai_de_diffusion` | `string` | Source column. | `annuelle (avant la fin de saison courante)` |
-| `indicateur_diffuse` | `string` | Source column. | `non` |
-| `niveau_de_desagregation` | `string` | Source column. | `zone` |
-| `statut_de_l_indicateur` | `string` | Source column. | `définitif` |
-| `unite_echelle` | `string` | Source column. | `unité` |
-| `source` | `string` | Source column. | `ANACIM` |
-| `methode_de_acces` | `string` | Source column. | `sur demande` |
-| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` |
-| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` |
-| `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` |
-| `source_provider` | `category` | Publishing organization. | `ANACIM` |
-| `source_dataset` | `category` | Source package title. | `Déficit /Excédent pluviométrique` |
-| `source_resource` | `category` | Source resource title. | `META DONNEES` |
-| `source_package_id` | `category` | CKAN package UUID. | `abffbd69-e914-4afa-997f-6e2ce6cdfd40` |
-| `source_resource_id` | `category` | CKAN resource UUID. | `996d04b0-3154-4d85-b54f-00a524d30e8f` |
-| `source_url` | `category` | Original source resource URL. | `https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/re` |
-| `license_id` | `category` | Source license identifier. | `odc-odbl` |
-| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-07-27T11:04:43Z` |
+| `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `996d04b0-3154-4d85-b54f-00a524d30e8f:metadata:0` |
+| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `SEN` |
+| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `Senegal` |
+| `source_sheet` | `string` | Source column from the original resource. | `METADATA` |
+| `methode_de_collecte` | `string` | Source column from the original resource. | `Données d'observation` |
+| `mode_de_calcul` | `string` | Source column from the original resource. | `Différence` |
+| `frequence_de_production` | `string` | Source column from the original resource. | `saisonière` |
+| `delai_de_diffusion` | `string` | Source column from the original resource. | `annuelle (avant la fin de saison courante)` |
+| `indicateur_diffuse` | `string` | Source column from the original resource. | `non` |
+| `niveau_de_desagregation` | `string` | Source column from the original resource. | `zone` |
+| `statut_de_l_indicateur` | `string` | Source column from the original resource. | `définitif` |
+| `unite_echelle` | `string` | Source column from the original resource. | `unité` |
+| `source` | `string` | Source column from the original resource. | `ANACIM` |
+| `methode_de_acces` | `string` | Source column from the original resource. | `sur demande` |
+| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `` |
+| `source_period_end_year` | `int64` | End year inferred from source metadata. | `` |
+| `source_period_label` | `string` | Source column from the original resource. | `` |
+| `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `ANACIM` |
+| `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `Déficit /Excédent pluviométrique` |
+| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `META DONNEES` |
+| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `abffbd69-e914-4afa-997f-6e2ce6cdfd40` |
+| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `996d04b0-3154-4d85-b54f-00a524d30e8f` |
+| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40...` |
+| `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `odc-odbl` |
+| `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-07-27T11:04:43Z` |
 
 ## Usage
 
@@ -100,29 +117,77 @@ df = ds["train"].to_pandas()
 print(df.head())
 ```
 
-### Filter to one country
+### Inspect Columns
 
 ```python
-sample_country = df[df["country_iso3"] == "SEN"]
+print(df.info())
+print(df.head())
 ```
 
-### Work with indicators
+### Filter By Geography
 
 ```python
-if "indicator_id" in df.columns:
-    print(df["indicator_id"].value_counts().head())
-    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
+if "country_iso3" in df.columns:
+    sample = df[df["country_iso3"] == "SEN"]
 ```
 
+### Time-Series Pattern
+
+```python
+if "value" in df.columns and "source_period_start_year" in df.columns:
+    trend = df.sort_values("source_period_start_year")
+```
+
+### Pivot For Analysis
+
+```python
+if {"indicator_id", "year", "value"}.issubset(df.columns):
+    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
+    print(matrix.tail())
+```
+
+## Data Quality Notes
+
+- Canonical time field: `source_period_start_year`.
+- Missing values are preserved rather than silently imputed.
+- Column names are standardized for machine use; source meanings are preserved where known.
+- Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.
+
+## Source And Provenance
+
+- **Source:** [ANACIM](https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique)
+- **Publisher:** ANACIM
+- **Portal:** [https://agridata.ansd.sn](https://agridata.ansd.sn)
+- **Resource:** [META DONNEES](https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx)
+- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
+- **Retrieved/generated:** `2026-07-27T11:05:07Z`
+- **Hugging Face repo:** [electricsheepafrica/africa-senegal-deficit-excedent-pluviometrique-eaed970a](https://huggingface.co/datasets/electricsheepafrica/africa-senegal-deficit-excedent-pluviometrique-eaed970a)
+
+## Transformations Applied
+
+- Converted the source table to Parquet for efficient analytics and ML workflows.
+- Added or preserved source provenance columns where available.
+- Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
+- Preserved source-reported values without analytical imputation.
+
+## Suggested Analyses
+
+- Profile the distribution of values
+- Compare categories or geographies
+- Join with complementary public datasets
+- Build time-series views and period-over-period comparisons
+- Check missingness before modeling
+- Use `country_iso3` as the safest geography join key when present
+
 ## Citation
 
 ```bibtex
 @misc{electric_sheep_africa_africa_senegal_deficit_excedent_pluviometrique_eaed970a_2026,
-  title        = {Déficit /Excédent pluviométrique | Africa (Senegal official open data)},
+  title        = {Deficit Excedent Pluviometrique | Africa (ANACIM)},
   author       = {ANACIM},
   year         = {2026},
   url          = {https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique},
-  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
   howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-deficit-excedent-pluviometrique-eaed970a}}
 }
 ```
@@ -131,20 +196,14 @@ if "indicator_id" in df.columns:
 
 Released under [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/).
 
-Original data (c) ANACIM. When using this dataset, please cite both the
-original source above and the Electric Sheep Africa repackaging.
-
-## About Electric Sheep
+Original data is published by ANACIM. Electric Sheep Africa
+engineering standardizes the data for discovery, loading, and analysis on
+Hugging Face. Cite both the original source and this ML-ready dataset when used.
 
-Electric Sheep Africa is part of the Electric Sheep mission: a unified,
-ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
-open sources, normalize the schemas, package as Parquet, and publish with
-consistent dataset cards so researchers and developers can use `load_dataset()`
-to start working in seconds.
+## About Electric Sheep Africa
 
-Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
+Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
 
 ---
 
-Provenance: ingested 2026-07-27 via the Electric Sheep pipeline. Source URL:
-https://agridata.ansd.sn/dataset/abffbd69-e914-4afa-997f-6e2ce6cdfd40/resource/996d04b0-3154-4d85-b54f-00a524d30e8f/download/metadata.xlsx
+Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://agridata.ansd.sn/dataset/deficitouexcedentpluviometrique