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departement
stringclasses
6 values
site
stringlengths
4
21
total_hommes
float64
0
3.58k
total_femmes
float64
0
4.38k
total_individus
float64
10
7.95k
total_menages
float64
0
2.1k
vieux_hommes
float64
0
52
vieux_femmes
float64
0
78
total_vieux
float64
0
512
pers_avec_handicape
float64
0
47
femme_enceinte
float64
0
74
veuves
float64
0
13
orphelins
float64
0
10
pers_malades
float64
0
16
enfant_non_acc
float64
0
9
primaire_hommes
float64
0
283
primaire_femmes
float64
0
256
total_primaire
float64
0
1.89k
college_hommes
float64
0
95
college_femmes
float64
0
89
total_college
float64
0
840
lycee_hommes
float64
0
44
lycee_femmes
float64
0
17
total_lycee
float64
0
126
esa_source
stringclasses
1 value
esa_processed
stringdate
2026-04-15 00:00:00
2026-04-15 00:00:00
Bouenza
LOUTETE
1,205
1,659
2,864
802
52
78
130
7
5
11
0
3
0
250
250
521
95
89
195
44
11
61
HDX
2026-04-15
Niari
LOUVAKOU
106
82
188
45
0
5
5
1
7
0
0
0
3
0
0
0
0
0
0
0
0
0
HDX
2026-04-15
Brazzaville
NDUNDZIA MPUNGU
1,721
2,211
3,900
939
0
0
154
18
14
3
0
0
4
0
0
848
0
0
373
0
0
81
HDX
2026-04-15
Brazzaville
KISITO
2,373
3,831
6,166
1,398
0
0
113
10
2
0
0
0
0
0
0
293
0
0
144
0
0
23
HDX
2026-04-15
Bouenza
LOUDIMA
0
0
777
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
HDX
2026-04-15
Brazzaville
SAINTE RITA
726
988
1,714
483
0
0
237
9
2
1
0
0
0
0
0
369
0
0
189
0
0
28
HDX
2026-04-15
Pool
MOUKOMBO YALALA
38
54
92
31
5
13
18
0
0
0
0
0
0
16
10
26
5
5
10
0
0
0
HDX
2026-04-15
Brazzaville
MADIBOU
2,211
1,657
3,859
814
0
0
94
3
19
0
0
0
0
0
0
946
0
0
405
0
0
37
HDX
2026-04-15
Pool
LOUBIKOU
141
128
269
74
15
0
15
2
0
1
0
0
1
22
13
35
14
18
32
6
8
14
HDX
2026-04-15
Pool
MAKOUMBOU KINKALA
173
201
374
107
21
33
54
0
1
0
0
0
1
51
55
106
8
6
14
5
0
5
HDX
2026-04-15
#adm1+name+origin
#loc+name
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
HDX
2026-04-15
Niari
MAKABANA
101
85
186
46
0
0
0
1
3
1
0
1
1
33
20
53
13
3
16
4
2
6
HDX
2026-04-15
Bouenza
MADINGOU
1,044
1,140
2,184
592
42
73
115
4
10
13
3
1
0
209
178
391
94
77
171
21
17
38
HDX
2026-04-15
Brazzaville
SAINT PIERRE CLAVER 2
1,808
2,310
4,109
1,018
0
0
369
47
43
0
0
0
3
0
0
829
0
0
370
0
0
78
HDX
2026-04-15
Bouenza
MOUYONDZI
13
16
29
10
1
1
2
0
0
0
0
2
0
3
1
4
0
1
1
0
0
0
HDX
2026-04-15
Pool
Q. MABI
102
113
215
60
8
9
17
0
0
0
0
0
0
31
22
53
4
6
10
1
1
2
HDX
2026-04-15
Lekoumou
KEINKELE
9
14
23
12
0
0
2
0
0
0
0
0
0
5
0
3
2
0
5
0
0
0
HDX
2026-04-15
Bouenza
KINGOUE VILLAGE
235
249
484
141
11
17
28
1
9
0
0
4
9
23
30
53
9
3
12
0
1
1
HDX
2026-04-15
Pool
Q. MADIBA
86
81
167
44
8
0
8
0
0
0
0
0
0
28
23
51
6
5
11
1
2
3
HDX
2026-04-15
Pool
NTARI NGOUARI 2
122
123
245
138
7
0
7
0
0
0
0
0
0
31
32
63
4
7
11
0
0
0
HDX
2026-04-15
Bouenza
KINGOUE CENTRE
157
176
333
96
4
11
15
3
3
0
10
3
7
50
38
88
11
14
25
3
0
3
HDX
2026-04-15
Pool
WAYAKO
62
87
149
39
12
10
22
4
2
0
0
0
1
12
29
41
0
0
0
7
7
14
HDX
2026-04-15
Lekoumou
YOMI
169
166
335
142
18
18
36
0
0
0
0
0
8
18
24
42
14
7
21
0
0
0
HDX
2026-04-15
Pool
MASSOMBO
53
41
94
21
7
0
7
0
0
0
0
0
0
11
9
20
4
1
5
2
0
2
HDX
2026-04-15
Brazzaville
KINGOUARI
519
634
1,147
275
0
0
112
1
10
0
0
0
3
0
0
293
0
0
136
0
0
31
HDX
2026-04-15
Lekoumou
KIMBOTO
158
137
295
41
10
7
17
0
0
0
0
0
0
16
14
30
7
5
12
0
0
0
HDX
2026-04-15
Brazzaville
SAINT PAUL DE MADIBOU
3,478
4,091
7,569
1,669
0
0
296
18
74
0
0
0
0
0
0
531
0
0
254
0
0
14
HDX
2026-04-15
Lekoumou
KENGUE
7
3
10
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
HDX
2026-04-15
Bouenza
NKAYI
987
1,152
2,139
452
22
55
77
6
4
2
1
16
0
283
256
539
76
76
152
21
13
34
HDX
2026-04-15
Brazzaville
NDONA MARIE
3,575
4,376
7,950
2,098
0
0
512
23
45
3
2
0
0
0
0
1,888
0
0
840
0
0
126
HDX
2026-04-15
Pool
YALAVOUNGA
16
14
30
6
3
4
7
0
0
0
0
0
0
6
2
8
3
2
5
0
0
0
HDX
2026-04-15
Pool
NTARI NGOUARI 1
135
130
265
66
11
7
18
2
6
0
0
0
0
44
34
78
7
5
12
2
2
4
HDX
2026-04-15

Personnes déplacées du Pool | Africa (original)

Size category: n<1K - Formats: parquet - Sector: humanitarian_development - Engineered by Electric Sheep Africa

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.

Dataset context from the existing Hugging Face card: Personnes déplacées du Pool Publisher: HDX · Source: HDX · License: cc-by · Updated: 2025-08-27 Abstract Personnes déplacées du Pool Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-08-27. Geographic scope: COG. Curated into ML-ready Parquet format by Electric Sheep Africa. Dataset Characteristics Domain Forced displacement and migration Unit of observation Tabular records Rows (total) 41 Columns 26… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-personnes-deplacees-du-pool.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-personnes-deplacees-du-pool
Sector humanitarian_development
Topic tags humanitarian, hdx, electric-sheep-africa, displacement, hxl, internally-displaced-persons-idp, people-in-need-pin, cog
Modalities tabular, text
Formats parquet
Size category n<1K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2026-04-15 22:27:43+00:00
Inventory snapshot 2026-07-16T16:00:34Z

How To Read This Dataset

  • Start from the repository files and the dataset viewer when available.
  • Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-personnes-deplacees-du-pool")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • Exact schema, row counts, and source files should be inspected in the repository data files.
  • Metadata gaps from the inventory: country, upstream_publisher.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • Inspect schema and missingness before modeling.
  • Profile variables by geography, time, and subgroup columns where present.
  • Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_personnes_deplacees_du_pool_2026,
  title        = {Personnes déplacées du Pool | Africa (original)},
  author       = {original},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-personnes-deplacees-du-pool},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-personnes-deplacees-du-pool}}
}

License

Released under CC BY 4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

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


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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