Standardize Electric Sheep Africa dataset card

README.md

@@ -5,100 +5,122 @@ language:
 task_categories:
 - tabular-classification
 - tabular-regression
-multilinguality: monolingual
+multilinguality: multilingual
 size_categories:
 - n<1K
 tags:
-- tabular
-- xlsx
-- africa
-- mauritius
-- official-statistics
-- open-data
-- energy
+- "tabular"
+- "africa"
+- "open-data"
+- "official-statistics"
+- "mauritius"
+- "mdpa"
+- "energy"
+- "environment-and-natural-resources"
+- "commercial"
+- "domestic"
+- "ceb"
+- "gwh"
+- "industrial"
+- "tarrif"
 configs:
 - config_name: default
   data_files:
   - split: train
     path: data/train-00000-of-00001.parquet
-pretty_name: "Sales of electricity by type of tariff | Africa (Mauritius official open data)"
+pretty_name: "Sales of Electricity by Type of Tariff | Africa (MDPA)"
 ---
 
-# Sales of electricity by type of tariff | Africa (Mauritius official open data)
+# Sales of Electricity by Type of Tariff | Africa (MDPA)
 
-163 rows - 1 Africa country - 2017-2021 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+**163 rows** - **1 Africa country/area** - **2017-2021** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
 
 ![rows](https://img.shields.io/badge/rows-163-blue)
 ![countries](https://img.shields.io/badge/countries-1-green)
-![years](https://img.shields.io/badge/years-2017-2021-orange)
+![period](https://img.shields.io/badge/period-2017--2021-orange)
 ![indicators](https://img.shields.io/badge/indicators-0-purple)
-![license](https://img.shields.io/badge/license-cc-by-sa-4.0-lightgrey)
+![license](https://img.shields.io/badge/license-cc--by--sa--4.0-lightgrey)
 
 ## TL;DR
 
-This dataset packages one official `XLSX` 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.
+This dataset contains **163 rows** from **MDPA**, covering **Sales of Electricity by Type of Tariff**. 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:** [Sales of electricity by type of tariff](https://data.govmu.org/dataset/sales-electricity-type-tariff)
-- **Publisher:** MDPA
-- **Resource:** [Digest_Industrial_Stats_Yr21_281022_sourceFile.xlsx](https://data.govmu.org/dataset/89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7/resource/e754caf8-029f-4b07-bd14-9265052c8860/download/digest_industrial_stats_yr21_281022_sourcefile.xlsx)
-- **Format:** `XLSX`
-- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
-- **Packaging mode:** `tabular_resource`
+Energy datasets help analysts study supply, demand, prices, generation, access, and the infrastructure behind economic activity.
+
+Source-provided context: Data shows electricity sold by type of tariff for the year 2017 to 2021
+
+## 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:** `not detected`.
+- **Time coverage basis:** source metadata.
+- **Recommended join keys:** `country_iso3` where available plus source-specific keys.
+
+## Coverage
+
+| Dimension | Value |
+|---|---:|
+| Rows | 163 |
+| Countries/areas | 1 |
+| First period | 2017 |
+| Last period | 2021 |
+| Indicators | 0 |
+| Columns | 34 |
+| 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 |
-|---------|-----:|-----------:|----------:|------|
+| Area | Rows | First year | Last year | Name |
+|------|-----:|-----------:|----------:|------|
 | `MU` | 163 | 2017 | 2021 | `Mauritius` |
 
-## 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. | `e754caf8-029f-4b07-bd14-9265052c8860:symbols-abbreviation-acronym:0` |
-| `country_iso3` | `category` | ISO3 country code. | `MU` |
-| `country_name` | `category` | Country name. | `Mauritius` |
-| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `Symbols, Abbreviation & Acronym` |
-| `column` | `string` | Source column. | `N.A : Not available` |
-| `not_applicable_or_nil` | `string` | Source column. | `` |
-| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2017` |
-| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2021` |
-| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2017-2021` |
-| `source_provider` | `category` | Publishing organization. | `MDPA` |
-| `source_dataset` | `category` | Source package title. | `Sales of electricity by type of tariff` |
-| `source_resource` | `category` | Source resource title. | `Digest_Industrial_Stats_Yr21_281022_sourceFile.xlsx` |
-| `source_package_id` | `category` | CKAN package UUID. | `89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7` |
-| `source_resource_id` | `category` | CKAN resource UUID. | `e754caf8-029f-4b07-bd14-9265052c8860` |
-| `source_url` | `category` | Original source resource URL. | `https://data.govmu.org/dataset/89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7/reso` |
-| `license_id` | `category` | Source license identifier. | `CC-BY-SA-4.0` |
-| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-08T16:26:20Z` |
-| `d_1_mining_and_quarrying` | `string` | Source column. | `` |
-| `the_activity_of_mining_and_quarrying_comprises_activitie` | `string` | Source column. | `` |
-| `productivity_and_unit_labour_cost_indices` | `string` | Source column. | `` |
-| `introduction` | `string` | Source column. | `` |
-| `d_1_coverage` | `string` | Source column. | `` |
-| `the_industrial_sector_according_to_the_international_rec` | `string` | Source column. | `` |
-| `2017` | `string` | Source column. | `` |
-| `d_872_698676` | `float64` | Source column. | `` |
-| `d_420876` | `float64` | Source column. | `` |
-| `d_951_9582607637849` | `float64` | Source column. | `` |
-| `d_42761` | `float64` | Source column. | `` |
-| `d_755_253732` | `float64` | Source column. | `` |
-| `d_6353` | `float64` | Source column. | `` |
-| `d_38_212101636206356` | `float64` | Source column. | `` |
-| `d_676` | `float64` | Source column. | `` |
-| `d_2618_122770399991` | `float64` | Source column. | `` |
-| `d_470666` | `float64` | Source column. | `` |
+| `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `e754caf8-029f-4b07-bd14-9265052c8860:symbols-abbreviation-acronym:0` |
+| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `MU` |
+| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `Mauritius` |
+| `source_sheet` | `string` | Source column from the original resource. | `Symbols, Abbreviation & Acronym` |
+| `column` | `string` | Source column from the original resource. | `N.A : Not available` |
+| `not_applicable_or_nil` | `string` | Source column from the original resource. | `` |
+| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2017` |
+| `source_period_end_year` | `int64` | End year inferred from source metadata. | `2021` |
+| `source_period_label` | `dictionary<values=string, indices=int8, ordered=0>` | Source column from the original resource. | `2017-2021` |
+| `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `MDPA` |
+| `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `Sales of electricity by type of tariff` |
+| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `Digest_Industrial_Stats_Yr21_281022_sourceFile.xlsx` |
+| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7` |
+| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `e754caf8-029f-4b07-bd14-9265052c8860` |
+| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://data.govmu.org/dataset/89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7/r...` |
+| `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `CC-BY-SA-4.0` |
+| `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-08-08T16:26:20Z` |
+| `d_1_mining_and_quarrying` | `string` | Source column from the original resource. | `` |
+| `the_activity_of_mining_and_quarrying_comprises_activitie` | `string` | Source column from the original resource. | `` |
+| `productivity_and_unit_labour_cost_indices` | `string` | Source column from the original resource. | `` |
+| `introduction` | `string` | Source column from the original resource. | `` |
+| `d_1_coverage` | `string` | Source column from the original resource. | `` |
+| `the_industrial_sector_according_to_the_international_rec` | `string` | Source column from the original resource. | `` |
+| `2017` | `string` | Source column from the original resource. | `` |
+| `d_872_698676` | `double` | Source column from the original resource. | `` |
+| `d_420876` | `double` | Source column from the original resource. | `` |
+| `d_951_9582607637849` | `double` | Source column from the original resource. | `` |
+| `d_42761` | `double` | Source column from the original resource. | `` |
+| `d_755_253732` | `double` | Source column from the original resource. | `` |
+| `d_6353` | `double` | Source column from the original resource. | `` |
+| `d_38_212101636206356` | `double` | Source column from the original resource. | `` |
+| `d_676` | `double` | Source column from the original resource. | `` |
+| `d_2618_122770399991` | `double` | Source column from the original resource. | `` |
+| `d_470666` | `double` | Source column from the original resource. | `` |
 
 ## Usage
 
@@ -110,29 +132,76 @@ df = ds["train"].to_pandas()
 print(df.head())
 ```
 
-### Filter to one country
+### Inspect Columns
 
 ```python
-sample_country = df[df["country_iso3"] == "MU"]
+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"] == "MU"]
 ```
 
+### Time-Series Pattern
+
+```python
+if "value" in df.columns and "year" in df.columns:
+    trend = df.sort_values("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
+
+- No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
+- 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:** [MDPA](https://data.govmu.org/dataset/sales-electricity-type-tariff)
+- **Publisher:** MDPA
+- **Portal:** [https://data.govmu.org](https://data.govmu.org)
+- **Resource:** [Digest_Industrial_Stats_Yr21_281022_sourceFile.xlsx](https://data.govmu.org/dataset/89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7/resource/e754caf8-029f-4b07-bd14-9265052c8860/download/digest_industrial_stats_yr21_281022_sourcefile.xlsx)
+- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
+- **Retrieved/generated:** `2026-08-08T16:33:00Z`
+- **Hugging Face repo:** [electricsheepafrica/africa-mauritius-sales-of-electricity-by-type-of-tariff-fc65bded](https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-sales-of-electricity-by-type-of-tariff-fc65bded)
+
+## 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
+
+- Track supply or price trends
+- Compare energy sources
+- Join with population, industry, or emissions data
+- Check missingness before modeling
+- Use `country_iso3` as the safest geography join key when present
+
 ## Citation
 
 ```bibtex
 @misc{electric_sheep_africa_africa_mauritius_sales_of_electricity_by_type_of_tariff_fc65bded_2021,
-  title        = {Sales of electricity by type of tariff | Africa (Mauritius official open data)},
+  title        = {Sales of Electricity by Type of Tariff | Africa (MDPA)},
   author       = {MDPA},
   year         = {2021},
   url          = {https://data.govmu.org/dataset/sales-electricity-type-tariff},
-  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-mauritius-sales-of-electricity-by-type-of-tariff-fc65bded}}
 }
 ```
@@ -141,20 +210,14 @@ if "indicator_id" in df.columns:
 
 Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).
 
-Original data (c) MDPA. 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 MDPA. 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 2026-08-08 via the Electric Sheep pipeline. Source URL:
-https://data.govmu.org/dataset/89d7ecdc-fff6-4dce-a4a0-7edcc597b5c7/resource/e754caf8-029f-4b07-bd14-9265052c8860/download/digest_industrial_stats_yr21_281022_sourcefile.xlsx
+Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/sales-electricity-type-tariff