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5.91 kB
| 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)* | |
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|  | |
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| ## 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`. | |