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electricsheepafrica/africa-sierra-leone-slihs2018-l-csv-2529148f

Slihs2018 L CSV | Africa (Statistics Sierra Leone) 211,951 rows - 1 Africa country/area - 2018 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 211,951 rows from Statistics Sierra Leone, covering Slihs2018 L CSV. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Official statistics datasets help analysts… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-sierra-leone-slihs2018-l-csv-2529148f.

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Slihs2018 L CSV | Africa (Statistics Sierra Leone)

211,951 rows - 1 Africa country/area - 2018 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 211,951 rows from Statistics Sierra Leone, covering Slihs2018 L CSV. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

This dataset covers Slihs2018 L CSV from Statistics Sierra Leone. Use the source and schema sections below to confirm definitions, units, and collection methodology before sensitive analytical use.

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: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows211,951
Countries/areas1
First period2018
Last period2018
Indicators0
Columns33
Source formatCSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
SL211,95120182018Sierra Leone

Indicators, Variables, Or Resource Contents

  • —This repo preserves one source tabular resource with its usable columns kept together.

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.res-648897395975485402:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.SL
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.Sierra Leone
yearint64Observation year.2018
clusterint64Source column from the original resource.1
hhnoint64Source column from the original resource.1
itemstringSource column from the original resource.3 or 4 piece sofa set
stratumint64Source column from the original resource.111
pweightdoubleSource column from the original resource.247.86473
b2_serialint64Source column from the original resource.2114
l1stringSource column from the original resource.no
l2doubleSource column from the original resource.``
l3adoubleSource column from the original resource.``
l3bdoubleSource column from the original resource.``
l3cdoubleSource column from the original resource.``
l3ddoubleSource column from the original resource.``
l4adoubleSource column from the original resource.``
l4bdoubleSource column from the original resource.``
l5adoubleSource column from the original resource.``
l5bdoubleSource column from the original resource.``
l6adoubleSource column from the original resource.``
l6bdoubleSource column from the original resource.``
source_period_start_yearint64Start year inferred from source metadata.2018
source_period_end_yearint64End year inferred from source metadata.2018
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2018
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.Statistics Sierra Leone
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.slihs2018_l.csv
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.slihs2018_l.csv
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.stats-sl-slihs2018-l-csv
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.res-648897395975485402
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://www.statistics.sl/images/StatisticsSL/Documents/SLIHS2018/SLI...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.other
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-09T11:46:10Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-sierra-leone-slihs2018-l-csv-2529148f")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "SL"]

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

  • —Canonical time field: year.
  • —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

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

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —Build time-series views and period-over-period comparisons
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_sierra_leone_slihs2018_l_csv_2529148f_2018,
  title        = {Slihs2018 L CSV | Africa (Statistics Sierra Leone)},
  author       = {Statistics Sierra Leone},
  year         = {2018},
  url          = {https://www.statistics.sl},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-sierra-leone-slihs2018-l-csv-2529148f}}
}

License

Released under Source-specific or other license.

Original data is published by Statistics Sierra Leone. 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.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://www.statistics.sl