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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / RWA_2019_RSAS_V01_EN_M_V01_A_OCS / variable [F14]
agricultural-surveys

Rwanda Seasonal Agriculture Survey 2019

Rwanda, 2018 - 2019
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Reference ID
RWA_2019_RSAS_v01_EN_M_v01_A_OCS
Producer(s)
National Institute of Statistics of Rwanda
Collections
Agricultural Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Feb 04, 2021
Last modified
Feb 04, 2021
Page views
13916
Downloads
278
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • rwa-sas-seasonA_Crop
    production
  • rwa-sas-SeasonA_PartIII_Fertilizers_Pesticides
  • rwa-sas-SeasonA_PartIV_Agricultural
    practice
  • rwa-sas-SeasonA_PartV_Land
    Tenure
  • rwa-sas-seasonA-Screening
  • rwa-sas-seasonB_Crop
    production
  • rwa-sas-SeasonB_PartIII_Fertilizers_Pesticides
  • rwa-sas-SeasonB_PartIV_Agricultural
    practice
  • rwa-sas-SeasonB_PartV_Land
    Tenure
  • rwa-sas-seasonB-Screening
  • rwa-sas-seasonC_Crop
    production
  • rwa-sas-SeasonC_PartIII_Fertilizers_Pesticides
  • rwa-sas-SeasonC_PartIV_Agricultural
    practice
  • rwa-sas-SeasonC_PartV_Land
    Tenure
  • rwa-sas-seasonC-Screening

1.2 District (s1q2)

Data file: rwa-sas-SeasonC_PartV_Land Tenure

Overview

Valid: 5400
Invalid: 0
Type: Discrete
Decimal: 0
Width: 10
Range: 11 - 57
Format: Numeric

Questions and instructions

Categories
Value Category Cases
11 Nyarugenge 40
0.7%
12 Gasabo 92
1.7%
13 Kicukiro 0
0%
21 Nyanza 276
5.1%
22 Gisagara 420
7.8%
23 Nyaruguru 292
5.4%
24 Huye 196
3.6%
25 Nyamagabe 304
5.6%
26 Ruhango 168
3.1%
27 Muhanga 280
5.2%
28 Kamonyi 128
2.4%
31 Karongi 104
1.9%
32 Rutsiro 292
5.4%
33 Rubavu 120
2.2%
34 Nyabihu 308
5.7%
35 Ngororero 188
3.5%
36 Rusizi 104
1.9%
37 Nyamasheke 12
0.2%
41 Rulindo 80
1.5%
42 Gakenke 144
2.7%
43 Musanze 484
9%
44 Burera 384
7.1%
45 Gicumbi 240
4.4%
51 Rwamagana 88
1.6%
52 Nyagatare 52
1%
53 Gatsibo 176
3.3%
54 Kayonza 28
0.5%
55 Kirehe 60
1.1%
56 Ngoma 0
0%
57 Bugesera 340
6.3%
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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