Datasetpublic

electricsheepafrica/africa-burkina-faso-enquete-longitudinale-a-haute-frequence-sur-limpact-de-la-ee7f0fa9

Enquete Longitudinale a Haute Frequence Sur Limpact De La | Africa (Institut national de la statistique et de la démographie) 52 rows - 1 Africa country/area - 2019-2020 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 52 rows from Institut national de la statistique et de la démographie, covering Enquete Longitudinale a Haute Frequence Sur Limpact De La. It is published as ML-ready Parquet with consistent Hugging Face metadata… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-burkina-faso-enquete-longitudinale-a-haute-frequence-sur-limpact-de-la-ee7f0fa9.

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Dataset Card

Enquete Longitudinale a Haute Frequence Sur Limpact De La | Africa (Institut national de la statistique et de la démographie)

52 rows - 1 Africa country/area - 2019-2020 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 52 rows from Institut national de la statistique et de la démographie, covering Enquete Longitudinale a Haute Frequence Sur Limpact De La. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.

Source-provided context: Document, Report [doc/rep]

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: not detected.
—Time coverage basis: source metadata.
—Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	52
Countries/areas	1
First period	2019
Last period	2020
Indicators	0
Columns	56
Source format	ZIP

Geographic Coverage

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

Area	Rows	First year	Last year	Name
`BFA`	52	n/a	n/a	`Burkina Faso`

Indicators, Variables, Or Resource Contents

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

Schema

Column	Type	Description	Example
`source_record_id`	`string`	Stable row identifier assigned during Electric Sheep Africa engineering.	`bfa-insd-nada-48-59:r14-xlsx-cover-section-0:0`
`country_iso3`	`dictionary<values=string, indices=int8, ordered=0>`	ISO3 country or area code.	`BFA`
`country_name`	`dictionary<values=string, indices=int8, ordered=0>`	Country or area name.	`Burkina Faso`
`source_sheet`	`string`	Source column from the original resource.	`r14.xlsx::Cover-Section 0`
`column_1`	`string`	Source column from the original resource.	``
`republique_du_burkina_faso`	`string`	Source column from the original resource.	`MINISTERE DE L'ECONOMIE, DES FINANCES ET DU DEVELOPPEMENT`
`source_period_start_year`	`int64`	Start year inferred from source metadata.	`2019`
`source_period_end_year`	`int64`	End year inferred from source metadata.	`2020`
`source_period_label`	`dictionary<values=string, indices=int8, ordered=0>`	Source column from the original resource.	`2019-2020`
`source_provider`	`dictionary<values=string, indices=int8, ordered=0>`	Publishing organization.	`Institut national de la statistique et de la démographie`
`source_dataset`	`dictionary<values=string, indices=int8, ordered=0>`	Source dataset or package title.	`Enquête longitudinale à haute fréquence sur l’impact de la Covid-19 s...`
`source_resource`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource title, table name, or file name.	`Questionnaires des différents passages`
`source_package_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source package identifier.	`BFA-INSD-COVID2019-2020-v01`
`source_resource_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource identifier.	`bfa-insd-nada-48-59`
`source_url`	`dictionary<values=string, indices=int8, ordered=0>`	Original source URL or download URL.	`https://microdata.insd.bf/index.php/catalog/48/download/59`
`license_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source license identifier.	`other-open`
`retrieved_at`	`dictionary<values=string, indices=int8, ordered=0>`	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	`2026-08-07T23:10:20Z`
`d_1a`	`string`	Source column from the original resource.	``
`information_entretien_tentatives`	`string`	Source column from the original resource.	``
`tentative_d_appel`	`double`	Source column from the original resource.	``
`id_numero_telephone`	`double`	Source column from the original resource.	``
`id_personne`	`double`	Source column from the original resource.	``
`combien_votre_menage_a_t_il_paye_de_sa_poche_pour_articl`	`string`	Source column from the original resource.	``
`column_11`	`string`	Source column from the original resource.	``
`column_12`	`string`	Source column from the original resource.	``
`column_13`	`string`	Source column from the original resource.	``
`column_14`	`string`	Source column from the original resource.	``
`column_15`	`string`	Source column from the original resource.	``
`column_2`	`string`	Source column from the original resource.	``
`d_1`	`string`	Source column from the original resource.	``
`d_2`	`string`	Source column from the original resource.	``
`d_3`	`string`	Source column from the original resource.	``
`d_4`	`string`	Source column from the original resource.	``
`d_5`	`string`	Source column from the original resource.	``
`d_6`	`string`	Source column from the original resource.	``
`d_7`	`string`	Source column from the original resource.	``
`d_8`	`string`	Source column from the original resource.	``
`d_9`	`string`	Source column from the original resource.	``
`column_16`	`string`	Source column from the original resource.	``
`column_17`	`string`	Source column from the original resource.	``
`column_18`	`string`	Source column from the original resource.	``
`column_19`	`string`	Source column from the original resource.	``
`column_20`	`string`	Source column from the original resource.	``
`d_10`	`string`	Source column from the original resource.	``
`d_11`	`string`	Source column from the original resource.	``
`d_12`	`string`	Source column from the original resource.	``
`d_13`	`string`	Source column from the original resource.	``
`d_14`	`string`	Source column from the original resource.	``
`d_15`	`string`	Source column from the original resource.	``
`d_16`	`string`	Source column from the original resource.	``
`quand_avez_vous_recu_la_premiere_dose_du_vaccin_contre_l`	`string`	Source column from the original resource.	``
`column_9`	`string`	Source column from the original resource.	``
`de_quel_s_membre_s_du_menage_s_agissait_il_id_membre_sel`	`string`	Source column from the original resource.	``
`sur_10_personnes_dans_votre_collectivite_combien_seront`	`string`	Source column from the original resource.	``
`sur_10_personnes_dans_votre_collectivite_combien_ont_ete`	`string`	Source column from the original resource.	``
`column_4`	`string`	Source column from the original resource.	``

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-burkina-faso-enquete-longitudinale-a-haute-frequence-sur-limpact-de-la-ee7f0fa9")
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"] == "BFA"]

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

—No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
—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

—Source: Institut national de la statistique et de la démographie
—Publisher: Institut national de la statistique et de la démographie
—Portal: https://microdata.insd.bf
—Resource: Questionnaires des différents passages
—License: other-open
—Retrieved/generated: 2026-08-07T23:10:46Z
—Hugging Face repo: electricsheepafrica/africa-burkina-faso-enquete-longitudinale-a-haute-frequence-sur-limpact-de-la-ee7f0fa9

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

—Track mobility over time
—Compare routes or geographies
—Join with economic and population data
—Check missingness before modeling
—Use country_iso3 as the safest geography join key when present

Citation

bibtex

@misc{electric_sheep_africa_africa_burkina_faso_enquete_longitudinale_a_haute_frequence_sur_limpact_de_la_ee_2020,
  title        = {Enquete Longitudinale a Haute Frequence Sur Limpact De La | Africa (Institut national de la statistique et de la démographie)},
  author       = {Institut national de la statistique et de la démographie},
  year         = {2020},
  url          = {https://microdata.insd.bf/index.php/catalog/48/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-burkina-faso-enquete-longitudinale-a-haute-frequence-sur-limpact-de-la-ee7f0fa9}}
}

License

Released under other-open.

Original data is published by Institut national de la statistique et de la démographie. 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 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://microdata.insd.bf/index.php/catalog/48/related-materials