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National Panel Survey 2015-2016

Uganda, 2015 - 2016
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Reference ID
UGA_2015_UNPS_v02_M
Producer(s)
Uganda Bureau of Statistics
Metadata
DDI/XML JSON
Created on
Dec 05, 2019
Last modified
Sep 07, 2022
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L1name (district_name)

Data file: gsec1

Overview

Valid: 3305
Invalid: 0
Type: Discrete
Start: 16
End: 28
Width: 13
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
Abim 11
0.3%
Adjumani 1
0%
Agago 22
0.7%
Alebtong 39
1.2%
Amolatar 14
0.4%
Amuria 10
0.3%
Amuru 3
0.1%
Apac 62
1.9%
Arua 105
3.2%
Bududa 18
0.5%
Bugiri 37
1.1%
Buhweju 25
0.8%
Buikwe 68
2.1%
Bukedea 20
0.6%
Bukomansimbi 11
0.3%
Bulambuli 18
0.5%
Bushenyi 24
0.7%
Busia 11
0.3%
Butaleja 22
0.7%
Butambala 10
0.3%
Buvuma 5
0.2%
Buyende 51
1.5%
Dokolo 27
0.8%
Gomba 1
0%
Gulu 52
1.6%
Hoima 65
2%
Ibanda 74
2.2%
Iganga 40
1.2%
Isingiro 46
1.4%
Jinja 65
2%
Kaabong 31
0.9%
Kabale 30
0.9%
Kabarole 52
1.6%
Kaberamaido 1
0%
Kalangala 3
0.1%
Kaliro 10
0.3%
Kalungu 29
0.9%
Kampala 183
5.5%
Kamuli 38
1.1%
Kamwenge 3
0.1%
Kanungu 10
0.3%
Kapchorwa 1
0%
Kasese 59
1.8%
Katakwi 21
0.6%
Kayunga 36
1.1%
Kibaale 45
1.4%
Kiboga 24
0.7%
Kibuku 1
0%
Kiruhura 17
0.5%
Kiryandongo 3
0.1%
Kisoro 33
1%
Kitgum 8
0.2%
Koboko 37
1.1%
Kole 56
1.7%
Kotido 30
0.9%
Kumi 43
1.3%
Kween 10
0.3%
Kyankwanzi 8
0.2%
Kyegegwa 23
0.7%
Kyenjojo 57
1.7%
Lamwo 1
0%
Lira 51
1.5%
Luuka 14
0.4%
Luwero 30
0.9%
Lwengo 69
2.1%
Lyantonde 4
0.1%
Manafwa 73
2.2%
Maracha 22
0.7%
Masaka 16
0.5%
Masindi 15
0.5%
Mayuge 53
1.6%
Mbale 16
0.5%
Mbarara 62
1.9%
Mitooma 13
0.4%
Mityana 56
1.7%
Moroto 11
0.3%
Moyo 32
1%
Mpigi 31
0.9%
Mubende 45
1.4%
Mukono 47
1.4%
Nakapiripirit 19
0.6%
Nakaseke 12
0.4%
Nakasongola 1
0%
Namayingo 31
0.9%
Namutumba 9
0.3%
Napak 9
0.3%
Nebbi 46
1.4%
Ngora 2
0.1%
Ntoroko 11
0.3%
Ntungamo 63
1.9%
Nwoya 1
0%
Otuke 14
0.4%
Oyam 60
1.8%
Pader 14
0.4%
Pallisa 24
0.7%
Rakai 74
2.2%
Rukungiri 40
1.2%
Serere 20
0.6%
Sheema 16
0.5%
Sironko 28
0.8%
Soroti 45
1.4%
Ssembabule 28
0.8%
Tororo 48
1.5%
Wakiso 117
3.5%
Yumbe 18
0.5%
Zombo 35
1.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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