---
license: gpl
dataset_name: nigerian_energy_and_utilities_commercial_industrial_consumption
pretty_name: Nigerian Energy & Utilities – Commercial & Industrial Consumption
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 – Commercial & Industrial Consumption

    3-phase site hourly consumption with PF, reactive power, and current derived from P, V, PF.

    - **[category]** Smart Meters & Consumption
    - **[rows]** ~220,000
    - **[formats]** CSV + Parquet (snappy)
    - **[geography]** Nigeria (DisCos, substations, plants)

    ## Schema

    | column | dtype |
|---|---|
| site_id | object |
| site_type | object |
| disco | object |
| feeder_id | object |
| timestamp | object |
| active_power_kw | float64 |
| reactive_power_kvar | float64 |
| pf | float64 |
| energy_kwh | float64 |
| voltage_ll_v | float64 |
| current_a | float64 |

    ## Usage

    ```python
    import pandas as pd
    df = pd.read_parquet('data/nigerian_energy_and_utilities_commercial_industrial_consumption/nigerian_energy_and_utilities_commercial_industrial_consumption.parquet')
    df.head()
    ```

    ```python
    from datasets import load_dataset
    ds = load_dataset('electricsheepafrica/nigerian_energy_and_utilities_commercial_industrial_consumption')
    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)