electricsheepafrica/africa-chad-chad-operational-presence-2db67744

Chad Operational Presence | Africa (OCHA Chad)

743 rows - 1 Africa country/area - 2020 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 743 rows from OCHA Chad, covering Chad Operational Presence. 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.

Source-provided context: 3W as of June 2020

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

Dimension	Value
Rows	743
Countries/areas	1
First period	2020
Last period	2020
Indicators	0
Columns	24
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TCD	743	2020	2020	Chad

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.	e71ee616-e80f-49da-9e62-e2fb3f602fc9:supp-nat:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	TCD
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Chad
source_sheet	string	Source column from the original resource.	Supp_Nat
year	int64	Observation year.	2020
pcode1	string	Source column from the original resource.	#adm1+code
region	string	Source column from the original resource.	#adm1+name
cluster	string	Source column from the original resource.	#sector
acronyme	string	Source column from the original resource.	#org+acronym
nom_de_l_organisation	string	Source column from the original resource.	#org+name
type_d_organisation	string	Source column from the original resource.	#org+type
icones	string	Source column from the original resource.	``
source_period_start_year	int64	Start year inferred from source metadata.	2020
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.	2020
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	OCHA Chad
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Chad: Operational Presence
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	3W_TCD_Jun2020
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	682c3db6-e253-430f-a3f3-305ef079e2de
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	e71ee616-e80f-49da-9e62-e2fb3f602fc9
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/682c3db6-e253-430f-a3f3-305ef079e2de...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T22:51:43Z
lac	string	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-chad-chad-operational-presence-2db67744")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

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

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

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

• Source: OCHA Chad
• Publisher: OCHA Chad
• Portal: https://data.humdata.org
• Resource: 3W_TCD_Jun2020
• License: CC BY 4.0
• Retrieved/generated: 2026-08-11T00:04:48Z
• Hugging Face repo: electricsheepafrica/africa-chad-chad-operational-presence-2db67744

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

@misc{electric_sheep_africa_africa_chad_chad_operational_presence_2db67744_2020,
  title        = {Chad Operational Presence | Africa (OCHA Chad)},
  author       = {OCHA Chad},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/chad-operational-presence},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-chad-operational-presence-2db67744}}
}

License

Released under CC BY 4.0.

Original data is published by OCHA Chad. 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://data.humdata.org/dataset/chad-operational-presence