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code
int64
1
456
level
stringclasses
2 values
district
stringlengths
4
15
area_km2
stringlengths
3
6
esa_source
stringclasses
1 value
esa_processed
stringdate
2026-04-27 00:00:00
2026-04-27 00:00:00
38
district
Bukedea
1,032
HDX
2026-04-27
21
district
Luwero
2,216
HDX
2026-04-27
366
district
Ibanda
969
HDX
2026-04-27
67
district
Butambala
403
HDX
2026-04-27
60
district
Kisoro
699
HDX
2026-04-27
83
district
Busia
734
HDX
2026-04-27
108
district
Kyankwanzi
2,466
HDX
2026-04-27
116
region
Northern Uganda
85,392
HDX
2026-04-27
93
district
Moroto
3,564
HDX
2026-04-27
55
district
Hoima
3,671
HDX
2026-04-27
79
district
Mukono
1,829
HDX
2026-04-27
104
district
Arua
4,343
HDX
2026-04-27
3
district
Isingiro
2,613
HDX
2026-04-27
69
district
Kyenjojo
2,357
HDX
2026-04-27
6
district
Lira
1,327
HDX
2026-04-27
19
district
Gomba
1,664
HDX
2026-04-27
64
district
Kamwenge
2,340
HDX
2026-04-27
96
district
Zombo
940
HDX
2026-04-27
110
district
Amudat
1,626
HDX
2026-04-27
8
district
Nwoya
4,601
HDX
2026-04-27
343
district
Lamwo
5,598
HDX
2026-04-27
1
district
Kalangala
451
HDX
2026-04-27
52
district
Kaabong
7,298
HDX
2026-04-27
16
district
Bukomansimbi
599
HDX
2026-04-27
348
district
Maracha
1572
HDX
2026-04-27
31
district
Jinja
677
HDX
2026-04-27
18
district
Masaka
1,158
HDX
2026-04-27
9
district
Amuru
3,588
HDX
2026-04-27
77
district
Kamuli
1,514
HDX
2026-04-27
17
district
Lwengo
1,024
HDX
2026-04-27
33
district
Mbale
517
HDX
2026-04-27
51
district
Dokolo
1,004
HDX
2026-04-27
66
district
Buliisa
1,108
HDX
2026-04-27
115
region
Eastern Uganda
39,479
HDX
2026-04-27
54
district
Oyam
2,190
HDX
2026-04-27
74
district
Buvuma
293
HDX
2026-04-27
12
district
Apac
2,947
HDX
2026-04-27
456
district
Sheema
696
HDX
2026-04-27
26
district
Kayunga
1,592
HDX
2026-04-27
100
district
Buhweju
748
HDX
2026-04-27
47
district
Moyo
1,902
HDX
2026-04-27
7
district
Alebtong
1,535
HDX
2026-04-27
39
district
Bukwo
524
HDX
2026-04-27
383
district
Kaberamaido
1,342
HDX
2026-04-27
43
district
Namutumba
810
HDX
2026-04-27
396
district
Amuria
2,578
HDX
2026-04-27
25
district
Sembabule
2,315
HDX
2026-04-27
101
district
Rubirizi
1,092
HDX
2026-04-27
95
district
Nebbi
1,915
HDX
2026-04-27
98
district
Kiryandongo
3,595
HDX
2026-04-27
59
district
Kibaale
4,242
HDX
2026-04-27
61
district
Mbarara
1,781
HDX
2026-04-27
90
district
Kapchorwa
352
HDX
2026-04-27
102
district
Mitooma
542
HDX
2026-04-27
91
district
Kween
850
HDX
2026-04-27
114
region
Central Uganda
61,403
HDX
2026-04-27
29
district
Mityana
1,524
HDX
2026-04-27
94
district
Napak
4,901
HDX
2026-04-27
85
district
Kalungu
812
HDX
2026-04-27
300
district
Kole
1,071
HDX
2026-04-27
32
district
Katakwi
2,306
HDX
2026-04-27
11
district
Pader
3,294
HDX
2026-04-27
53
district
Koboko
760
HDX
2026-04-27
73
district
Mayuge
1,073
HDX
2026-04-27
72
district
Iganga
1,017
HDX
2026-04-27
34
district
Tororo
1,192
HDX
2026-04-27
46
district
Kotido
3,620
HDX
2026-04-27
70
district
Kyegegwa
1,747
HDX
2026-04-27
438
district
Otuke
1,555
HDX
2026-04-27
57
district
Kabarole
1,810
HDX
2026-04-27
45
district
Gulu
3,433
HDX
2026-04-27
88
district
Soroti
1,366
HDX
2026-04-27
44
district
Adjumani
2,962
HDX
2026-04-27
75
district
Kibuku
481
HDX
2026-04-27
103
district
Bushenyi
844
HDX
2026-04-27
10
district
Agago
3,503
HDX
2026-04-27
40
district
Butaleja
653
HDX
2026-04-27
76
district
Pallisa
1,030
HDX
2026-04-27
23
district
Nakasongola
3,303
HDX
2026-04-27
87
district
Serere
1,495
HDX
2026-04-27
97
district
Masindi
3,932
HDX
2026-04-27
30
district
Nakaseke
3,461
HDX
2026-04-27
68
district
Mpigi
1,202
HDX
2026-04-27
117
region
Western Uganda
55,277
HDX
2026-04-27
107
district
Bundibugyo
848
HDX
2026-04-27
323
district
Kumi
1,003
HDX
2026-04-27
42
district
Manafwa
533
HDX
2026-04-27
89
district
Sironko
401
HDX
2026-04-27
80
district
Buikwe
1,206
HDX
2026-04-27
84
district
Ngora
637
HDX
2026-04-27
109
district
Kiboga
1,592
HDX
2026-04-27
63
district
Rukungiri
1,435
HDX
2026-04-27

Size of Uganda districts in square kilometers

Publisher: Code for Africa · Source: OpenAfrica · License: cc-by · Updated: 2023-11-30


Abstract

This dataset contains humanitarian and development data records covering Africa (multiple countries), comprising 116 observations across 6 variables.

Each row in this dataset represents subnational administrative unit observations. Data was last updated on OpenAfrica on 2023-11-30. Geographic scope: Africa (multiple countries).

Curated into ML-ready Parquet format by Electric Sheep Africa.


Dataset Characteristics

Domain Humanitarian and development data
Unit of observation Subnational administrative unit observations
Rows (total) 116
Columns 6 (1 numeric, 5 categorical, 0 datetime)
Train split 92 rows
Test split 23 rows
Geographic scope Africa (multiple countries)
Publisher Code for Africa
OpenAfrica last updated 2023-11-30

Variables

Geographicdistrict (Abim, Masaka, Nakapiripirit).

Identifier / Metadatacode (range 1.0–456.0), esa_source (HDX), esa_processed (2026-04-27).

Otherlevel (district, region), area_km2 (1,592, 2,346, 1,158).


Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-ict-all")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Column Type Null % Range / Sample Values
code int64 0.0% 1.0 – 456.0 (mean 93.5172)
level object 0.0% district, region
district object 0.0% Abim, Masaka, Nakapiripirit
area_km2 object 0.0% 1,592, 2,346, 1,158
esa_source object 0.0% HDX
esa_processed object 0.0% 2026-04-27

Numeric Summary

Column Min Max Mean Median
code 1.0 456.0 93.5172 64.5

Curation

Raw data was downloaded from OpenAfrica 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. 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 Code for Africa and has not been independently validated by ESA.
  • Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
  • Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{openafrica_africa_ict_all,
  title     = {Size of Uganda districts in square kilometers},
  author    = {Code for Africa},
  year      = {2023},
  url       = {https://open.africa/dataset/size-of-uganda-districts-in-square-kilometers},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.

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