Datasets:

electricsheepafrica
/

nigerian_energy_and_utilities_retail_tariffs

@@ -1,52 +1,142 @@
 ---
-license: gpl
-dataset_name: nigerian_energy_and_utilities_retail_tariffs
-pretty_name: Nigerian Energy & Utilities – Retail Tariffs
-size_categories: [10K<n<1M, 1M<n<10M]
-task_categories: [time-series-forecasting, tabular-regression, other]
-tags: [nigeria, energy, utilities, power, grid, smart-meter, renewables]
-language: [en]
-created: 2025-10-11
 ---
-    # Nigerian Energy & Utilities – Retail Tariffs
-    Retail tariff schedules by band, class, hour (TOU).
-    - **[category]** Market & Pricing
-    - **[rows]** ~90,000
-    - **[formats]** CSV + Parquet (snappy)
-    - **[geography]** Nigeria (DisCos, substations, plants)
-    ## Schema
-    | column | dtype |
 |---|---|
-| as_of_date | object |
-| disco | object |
-| customer_class | object |
-| tariff_band | object |
-| hour | int64 |
-| price_ngn_kwh | float64 |
-    ## Usage
-    ```python
-    import pandas as pd
-    df = pd.read_parquet('data/nigerian_energy_and_utilities_retail_tariffs/nigerian_energy_and_utilities_retail_tariffs.parquet')
-    df.head()
-    ```
-    ```python
-    from datasets import load_dataset
-    ds = load_dataset('electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs')
-    ds
-    ```
-    ## Notes
-    - Data generated with Nigeria-specific parameters (DisCos, tariff bands, 50 Hz grid)
-    - Time-of-use shapes and seasonal/weather effects included where applicable
-    - Values are internally consistent (e.g., kWh ~ kW*h; voltage/current ~ power)

 ---
+license: other
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- 10K<n<100K
+tags:
+- "africa"
+- "electric-sheep-africa"
+- "open-data"
+- "metadata-backed"
+- "energy"
+- "parquet"
+- "tabular"
+- "text"
+- "nigeria"
+- "utilities"
+- "power"
+- "grid"
+- "smart-meter"
+- "renewables"
+pretty_name: "Nigerian Energy & Utilities – Retail Tariffs | Africa (Electric Sheep Africa metadata inventory)"
 ---
+# Nigerian Energy & Utilities – Retail Tariffs | Africa (Electric Sheep Africa metadata inventory)
+**Size category:** `10K<n<100K` - **Formats:** `parquet` - **Sector:** energy - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+![size](https://img.shields.io/badge/size-10K%3Cn%3C100K-blue)
+![sector](https://img.shields.io/badge/sector-energy-green)
+![downloads](https://img.shields.io/badge/HF_downloads-10-orange)
+![license](https://img.shields.io/badge/license-other-lightgrey)
+## TL;DR
+This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
+## What This Dataset Covers
+Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
+Dataset context from the existing Hugging Face card: # Nigerian Energy & Utilities – Retail Tariffs Retail tariff schedules by band, class, hour (TOU). - **[category]** Market & Pricing - **[rows]** ~90,000 - **[formats]** CSV + Parquet (snappy) - **[geography]** Nigeria (DisCos, substations, plants) ## Schema | column | dtype | |---|---| | as_of_date | object | | disco | object | | customer_class | object | | tariff_band | object | | hour | int64 | | price_ngn_kwh | float64 | ## Usage ```python import pandas as pd df =… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs.
+## Dataset Profile
+| Field | Value |
 |---|---|
+| Hugging Face repo | [`electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs`](https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs) |
+| Sector | energy |
+| Topic tags | nigeria, energy, utilities, power, grid, smart-meter, renewables |
+| Modalities | `tabular`, `text` |
+| Formats | `parquet` |
+| Size category | `10K<n<100K` |
+| Countries | Nigeria |
+| ISO3 coverage | `NGA` |
+| Last modified on HF | `2025-10-11 18:13:24+00:00` |
+| Inventory snapshot | `2026-07-16T16:00:34Z` |
+## How To Read This Dataset
+- Start from the repository files and the dataset viewer when available.
+- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
+- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
+- Preserve missing values until you have a defensible imputation rule.
+## Usage
+```python
+from datasets import load_dataset
+ds = load_dataset("electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs")
+print(ds)
+split_name = next(iter(ds))
+table = ds[split_name]
+print(table.features)
+print(table[:3])
+```
+### Convert To Pandas When Tabular
+```python
+from datasets import Dataset
+first_split = ds[next(iter(ds))]
+if isinstance(first_split, Dataset):
+    df = first_split.to_pandas()
+    print(df.head())
+```
+## Data Quality Notes
+- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
+- Exact schema, row counts, and source files should be inspected in the repository data files.
+- Metadata gaps from the inventory: upstream_publisher.
+- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
+## Source And Provenance
+- **Source context:** Electric Sheep Africa metadata inventory
+- **Publisher/source attribution:** Public dataset metadata
+- **License:** gpl
+- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs](https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs)
+- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
+## Suggested Analyses
+- Inspect schema and missingness before modeling.
+- Profile variables by geography, time, and subgroup columns where present.
+- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
+- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
+## Citation
+```bibtex
+@misc{electric_sheep_africa_nigerian_energy_and_utilities_retail_tariffs_2026,
+  title        = {Nigerian Energy & Utilities – Retail Tariffs | Africa (Electric Sheep Africa metadata inventory)},
+  author       = {Public dataset metadata},
+  year         = {2026},
+  url          = {https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/nigerian_energy_and_utilities_retail_tariffs}}
+}
+```
+## License
+Released under gpl.
+Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
+## About Electric Sheep Africa
+Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
+---
+Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.