electricsheepafrica/africa-re4r-project-assessment-phase-survey-gihembe-enterprises

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- energy
- environment
- facilities-infrastructure
- livelihoods
- poverty
- rwa
pretty_name: "RE4R Project Assessment Phase Survey (Enterprises)"
dataset_info:
splits:
- name: train
num_examples: 51
- name: test
num_examples: 12
---

# RE4R Project Assessment Phase Survey (Enterprises)

**Publisher:** Practical Action (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/re4r-project-assessment-phase-survey-gihembe-enterprises) · **License:** `cc-by` · **Updated:** 2023-05-02

---

## Abstract

Enterprise surveys for Gihembe, Kigeme and Nyabiheke refugee camp in Rwanda. The datasets contain information on enterprise type and operations, energy for lighting and productive uses, access to electricity technologies, respondent needs and priorities, and other energy-related issues.

Each row in this dataset represents geolocated point observations. Data was last updated on HDX on 2023-05-02. Geographic scope: **RWA**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Poverty and economic vulnerability |
| **Unit of observation** | Geolocated point observations |
| **Rows (total)** | 64 |
| **Columns** | 199 (12 numeric, 32 categorical, 0 datetime) |
| **Train split** | 51 rows |
| **Test split** | 12 rows |
| **Geographic scope** | RWA |
| **Publisher** | Practical Action (inactive) |
| **HDX last updated** | 2023-05-02 |

---

## Variables

**Geographic** — `respondent_type` (Respondent manages a business, Respondent owns a business), `enterprise_category` (Trade/retail shop (including phone charging), None of the above, Hospitality (hotel/restaurant/bar)), `building_type` (UNHCR housing (non-tent), Tent (not provided by UNHCR), Pre-constructed building or structure), `number_of_staff_host_community` (0, No response, 1), `approximate_monthly_revenue_local_currency` (range 12.0–100000.0) and 163 others.

**Temporal** — `enterprise_start_date` (###############################################################################################################################################################################################################################################################, 19/04/15 00:00, 19/11/13 00:00), `months_of_operation` (range 0.0–12.0), `seasonal_variance_of_lighting_needs`, `proportion_of_time_lighting_is_available`, `number_of_unscheduled_inturruptions_per_week_for_lighting` (range 1.0–12.0).

**Demographic** — `respondent_gender` (Female, Male), `appliances_for_lighting_have_been_unusable_or_damaged_because_of_voltage_issues`.

**Outcome / Measurement** — `number_of_rooms_used` (range 0.0–6.0), `number_of_staff_camp_residents` (range 1.0–5.0), `number_of_staff_other` (0, No response).

**Identifier / Metadata** — `loans_from_other_camp_residents_used`, `no_other_source_used_for_lighting`, `generator_power_source_for_heating`, `esa_source`, `esa_processed`.

**Other** — `participation`, `consent_given`, `enterprise_description` (trade, Bar, retail shop), `microfinance_used`, `grants_from_unhcr_other_donors_used` and 11 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-re4r-project-assessment-phase-survey-gihembe-enterprises")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `participation` | bool | 0.0% | |
| `consent_given` | bool | 0.0% | |
| `respondent_type` | object | 0.0% | Respondent manages a business, Respondent owns a business |
| `respondent_gender` | object | 0.0% | Female, Male |
| `enterprise_category` | object | 0.0% | Trade/retail shop (including phone charging), None of the above, Hospitality (hotel/restaurant/bar) |
| `enterprise_description` | object | 0.0% | trade, Bar, retail shop |
| `enterprise_start_date` | object | 0.0% | ###############################################################################################################################################################################################################################################################, 19/04/15 00:00, 19/11/13 00:00 |
| `building_type` | object | 0.0% | UNHCR housing (non-tent), Tent (not provided by UNHCR), Pre-constructed building or structure |
| `number_of_rooms_used` | int64 | 0.0% | 0.0 – 6.0 (mean 1.8906) |
| `number_of_staff_camp_residents` | int64 | 0.0% | 1.0 – 5.0 (mean 1.7969) |
| `number_of_staff_host_community` | object | 0.0% | 0, No response, 1 |
| `number_of_staff_other` | object | 0.0% | 0, No response |
| `approximate_monthly_revenue_local_currency` | int64 | 0.0% | 12.0 – 100000.0 (mean 25000.5938) |
| `microfinance_used` | bool | 0.0% | |
| `loans_from_other_camp_residents_used` | bool | 0.0% | |
| `paying_suppliers_in_installments_used` | bool | 0.0% | |
| `grants_from_unhcr_other_donors_used` | bool | 0.0% | |
| `loans_from_banks_moneylenders_used` | bool | 0.0% | |
| `no_financial_services_used` | bool | 0.0% | |
| `months_of_operation` | float64 | 0.0% | 0.0 – 12.0 (mean 11.4531) |
| `days_per_week_of_operation` | float64 | 0.0% | 3.0 – 7.0 (mean 6.1484) |
| `hours_per_day_of_operation` | int64 | 0.0% | 2.0 – 19.0 (mean 12.1562) |
| `lighing_regularly_used` | bool | 0.0% | |
| `ict_and_entertainment_inc_charging_regularly_used` | bool | 0.0% | |
| `motive_power_regularly_used` | bool | 0.0% | |
| `heating_regularly_used` | bool | 0.0% | |
| `cooling_regularly_used` | bool | 0.0% | |
| `no_energy_applications_regularly_used` | bool | 0.0% | |
| `importance_of_lighting_to_success_of_activities` | object | 32.8% | Critical, Important |
| `reason_why_lighting_is_not_used` | object | 0.0% | Already use it, Too expensive, Don't need it |
| `reason_why_ict_and_entertainment_inc_charging_is_not_used` | object | 0.0% | |
| `reason_why_motive_power_is_not_used` | object | 0.0% | |
| `reason_why_heating_is_not_used` | object | 0.0% | |
| `reason_why_cooling_is_not_used` | object | 0.0% | |
| `lighting_energy_source` | object | 32.8% | |
| `seasonal_variance_of_lighting_needs` | object | 32.8% | |
| `hours_per_day_that_electricity_is_needed_for_lighting` | float64 | 43.8% | 2.0 – 24.0 (mean 13.2778) |
| `proportion_of_time_lighting_is_available` | object | 43.8% | |
| `inadequate_electricity_for_lighting_constains_enterprise_productivity` | float64 | 43.8% | 0.0 – 1.0 (mean 0.6111) |
| `primary_source_of_electricity_for_lighting` | object | 43.8% | |
| `capacity_of_electricity_supply_used_for_lighting_wh_day` | float64 | 56.2% | 1.0 – 84.0 (mean 55.2857) |
| `unscheduled_interruptions_for_lighting_impact_enterprise_operations` | object | 43.8% | |
| `number_of_unscheduled_inturruptions_per_week_for_lighting` | float64 | 65.6% | 1.0 – 12.0 (mean 2.9545) |
| `cumulative_hours_per_week_of_unscheduled_interruptions_for_lighting` | float64 | 65.6% | 1.0 – 21.0 (mean 6.3864) |
| `appliances_for_lighting_have_been_unusable_or_damaged_because_of_voltage_issues` | object | 43.8% | |
| `accidents_from_electricity_supply_for_lighting` | object | 43.8% | |
| `payment_method_for_electricity_for_lighting` | object | 43.8% | |
| `monthly_flat_rate_paid_for_lighting_local_currency` | float64 | 71.9% | 50.0 – 12200.0 (mean 5246.3333) |
| `diesel_gasoline_lamp_used_for_lighting` | bool | 0.0% | |
| `lpg_lamp_used_for_lighting` | bool | 0.0% | |
| `biogas_lamp_used_for_lighting` | bool | 0.0% | |
| `other_lamp_used_for_lighting` | bool | 0.0% | |
| `no_other_source_used_for_lighting` | bool | 0.0% | |
| `enterprise_activities_includes_cooking` | bool | 0.0% | |
| `enterprise_activities_includes_space_heating` | bool | 0.0% | |
| `enterprise_activities_includes_water_heating` | bool | 0.0% | |
| `enterprise_activities_includes_other_heating` | bool | 0.0% | |
| `generator_power_source_for_heating` | object | 4.7% | |
| `accidents_from_electricity_supply_for_heating` | object | 0.0% | |
| `solar_lantern_typically_used` | bool | 0.0% | |
| `led_lamp_typically_used` | bool | 0.0% | |
| `phone_device_charger_typically_used` | bool | 0.0% | |
| `radio_typically_used` | bool | 0.0% | |
| `hair_clippers_typically_used` | bool | 0.0% | |
| `colour_tv_typically_used` | bool | 0.0% | |
| `satellite_dish_receiver_typically_used` | bool | 0.0% | |
| `boom_box_typically_used` | bool | 0.0% | |
| `stereo_sound_system_typically_used` | bool | 0.0% | |
| `broadband_router_typically_used` | bool | 0.0% | |
| `computer_typically_used` | bool | 0.0% | |
| `scanner_typically_used` | bool | 0.0% | |
| `inkjet_printer_typically_used` | bool | 0.0% | |
| `laser_printer_photocopier_typically_used` | bool | 0.0% | |
| `small_table_fan_typically_used` | bool | 0.0% | |
| `floor_fan_typically_used` | bool | 0.0% | |
| `ceiling_fan_typically_used` | bool | 0.0% | |
| `air_conditioner_typically_used` | bool | 0.0% | |
| `refrigerator_typically_used` | bool | 0.0% | |
| `freezer_typically_used` | bool | 0.0% | |
| `washing_machine_typically_used` | bool | 0.0% | |
| `vacuum_cleaner_typically_used` | bool | 0.0% | |
| `slow_cooker_typically_used` | bool | 0.0% | |
| `rice_cooker_typically_used` | bool | 0.0% | |
| `pressure_cooker_typically_used` | bool | 0.0% | |
| `single_ring_electric_hob_typically_used` | bool | 0.0% | |
| `4_ring_electric_hob_typically_used` | bool | 0.0% | |
| `electric_oven_typically_used` | bool | 0.0% | |
| `electric_grill_typically_used` | bool | 0.0% | |
| `small_microwave_oven_typically_used` | bool | 0.0% | |
| `large_microwave_oven_typically_used` | bool | 0.0% | |
| `toaster_typically_used` | bool | 0.0% | |
| `kettle_typically_used` | bool | 0.0% | |
| `water_heater_typically_used` | bool | 0.0% | |
| `shower_typically_used` | bool | 0.0% | |
| `convection_radiator_typically_used` | bool | 0.0% | |
| `portable_halogen_heater_typically_used` | bool | 0.0% | |
| `fan_heater_typically_used` | bool | 0.0% | |
| `wall_halogen_heater_typically_used` | bool | 0.0% | |
| `clothes_iron_typically_used` | bool | 0.0% | |
| `hair_dryer_typically_used` | bool | 0.0% | |
| `low_power_water_pump_typically_used` | bool | 0.0% | |
| `high_power_water_pump_typically_used` | bool | 0.0% | |
| `incubator_typically_used` | bool | 0.0% | |
| `pasteurizer_typically_used` | bool | 0.0% | |
| `sewing_machine_typically_used` | bool | 0.0% | |
| `power_loom_typically_used` | bool | 0.0% | |
| `low_power_potterís_wheel_typically_used` | bool | 0.0% | |
| `high_power_potterís_wheel_typically_used` | bool | 0.0% | |
| `pottery_kiln_typically_used` | bool | 0.0% | |
| `small_grain_mill_typically_used` | bool | 0.0% | |
| `large_grain_mill_typically_used` | bool | 0.0% | |
| `electric_handheld_drill_typically_used` | bool | 0.0% | |
| `small_drilling_machine_typically_used` | bool | 0.0% | |
| `large_drilling_machine_typically_used` | bool | 0.0% | |
| `lathe_typically_used` | bool | 0.0% | |
| `milling_machine_typically_used` | bool | 0.0% | |
| `belt_sander_typically_used` | bool | 0.0% | |
| `circular_saw_typically_used` | bool | 0.0% | |
| `panel_saw_typically_used` | bool | 0.0% | |
| `rip_saw_typically_used` | bool | 0.0% | |
| `chain_saw_typically_used` | bool | 0.0% | |
| `soldering_iron_typically_used` | bool | 0.0% | |
| `metal_arc_welding_machine_typically_used` | bool | 0.0% | |
| `other_appliance_typically_used` | bool | 0.0% | |
| `none_of_the_above_typically_used` | bool | 0.0% | |
| `solar_lantern_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `led_lamp_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `phone_device_charger_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `radio_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `hair_clippers_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `colour_tv_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `satellite_dish_receiver_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `boom_box_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `stereo_sound_system_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `broadband_router_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `computer_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `scanner_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `inkjet_printer_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `laser_printer_photocopier_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `small_table_fan_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `floor_fan_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `ceiling_fan_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `air_conditioner_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `refrigerator_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `freezer_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `washing_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `vacuum_cleaner_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `slow_cooker_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `rice_cooker_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `pressure_cooker_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `single_ring_electric_hob_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `4_ring_electric_hob_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `electric_oven_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `electric_grill_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `small_microwave_oven_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `large_microwave_oven_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `toaster_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `kettle_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `water_heater_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `shower_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `convection_radiator_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `portable_halogen_heater_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `fan_heater_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `wall_halogen_heater_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `clothes_iron_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `hair_dryer_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `low_power_water_pump_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `high_power_water_pump_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `incubator_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `pasteurizer_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `sewing_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `power_loom_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `low_power_potterís_wheel_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `high_power_potterís_wheel_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `pottery_kiln_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `small_grain_mill_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `large_grain_mill_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `electric_handheld_drill_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `small_drilling_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `large_drilling_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `lathe_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `milling_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `belt_sander_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `circular_saw_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `panel_saw_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `rip_saw_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `chain_saw_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `soldering_iron_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `metal_arc_welding_machine_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `other_appliance_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `none_of_the_above_desired_if_electricity_were_adequate` | bool | 0.0% | |
| `most_important_appliance_for_productive_activity_rank_1` | object | 0.0% | |
| `most_important_appliance_for_productive_activity_rank_2` | object | 0.0% | |
| `most_important_appliance_for_productive_activity_rank_3` | object | 0.0% | |
| `most_important_appliance_for_productive_activity_rank_4` | object | 0.0% | |
| `most_important_appliance_for_productive_activity_rank_5` | object | 0.0% | |
| `how_electricity_would_be_paid_for` | object | 0.0% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `number_of_rooms_used` | 0.0 | 6.0 | 1.8906 | 2.0 |
| `number_of_staff_camp_residents` | 1.0 | 5.0 | 1.7969 | 2.0 |
| `approximate_monthly_revenue_local_currency` | 12.0 | 100000.0 | 25000.5938 | 20000.0 |
| `months_of_operation` | 0.0 | 12.0 | 11.4531 | 12.0 |
| `days_per_week_of_operation` | 3.0 | 7.0 | 6.1484 | 6.0 |
| `hours_per_day_of_operation` | 2.0 | 19.0 | 12.1562 | 12.0 |
| `hours_per_day_that_electricity_is_needed_for_lighting` | 2.0 | 24.0 | 13.2778 | 14.0 |
| `inadequate_electricity_for_lighting_constains_enterprise_productivity` | 0.0 | 1.0 | 0.6111 | 1.0 |
| `capacity_of_electricity_supply_used_for_lighting_wh_day` | 1.0 | 84.0 | 55.2857 | 84.0 |
| `number_of_unscheduled_inturruptions_per_week_for_lighting` | 1.0 | 12.0 | 2.9545 | 2.0 |
| `cumulative_hours_per_week_of_unscheduled_interruptions_for_lighting` | 1.0 | 21.0 | 6.3864 | 5.0 |
| `monthly_flat_rate_paid_for_lighting_local_currency` | 50.0 | 12200.0 | 5246.3333 | 5700.0 |

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 210 column(s) with >80% missing values were removed: `area_of_land_irrigated_square_metres`, `area_of_land_that_needs_to_be_irrigated_square_metres`, `months_of_the_year_that_irrigation_is_needed`, `importance_of_ict_and_entertainment_inc_charging_to_success_of_activities`, `importance_of_motive_power_to_success_of_activities`, `importance_of_heating_to_success_of_activities`.... 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from Practical Action (inactive) and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `importance_of_lighting_to_success_of_activities`, `lighting_energy_source`, `seasonal_variance_of_lighting_needs`, `hours_per_day_that_electricity_is_needed_for_lighting`, `proportion_of_time_lighting_is_available`, `inadequate_electricity_for_lighting_constains_enterprise_productivity`, `primary_source_of_electricity_for_lighting`, `capacity_of_electricity_supply_used_for_lighting_wh_day`....
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/re4r-project-assessment-phase-survey-gihembe-enterprises) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_re4r_project_assessment_phase_survey_gihembe_enterprises,
title = {RE4R Project Assessment Phase Survey (Enterprises)},
author = {Practical Action (inactive)},
year = {2023},
url = {https://data.humdata.org/dataset/re4r-project-assessment-phase-survey-gihembe-enterprises},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*