Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURE-CENSUS-SURVEYS / TZA_2002-2003_ASCS_V01_EN_M_V01_A_OCS / variable [F67]
agriculture-census-surveys

Agriculture Sample Census Survey 2002-2003

United Republic of Tanzania, 2004
Get Microdata
Reference ID
TZA_2002-2003_ASCS_v01_EN_M_v01_A_OCS
Producer(s)
National Bureau of Statistics, Office of Chief Government Statistician-Zanzibar
Collections
Agriculture Census and Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 24, 2019
Last modified
Oct 24, 2019
Page views
71893
Downloads
2599
  • Study Description
  • Data Description
  • Downloads
  • Data files
  • annual crop and
    vegetable
    production-long
    rainy
    seasonR072
  • annual crop and
    vegetable
    production-short
    rainy
    seasonR071
  • Cattle diseases
    R185
  • Cattle intake
    R183
  • Cattle offtake
    R184
  • Cattle
    population,
    intake and
    offtake R182
  • crop extension
    messages R152
  • crop extension
    services R151
  • crop storage
    R092
  • permanentperennial
    crops and fruit
    tree production
    R073
  • Goat diseases
    R195
  • Goat intake
    during 20022003
    R193
  • Goat offtake
    R194
  • Goat
    population,
    intake and
    offtake R192
  • Goat
    population,
    intake and
    offtake R092_1
  • Goat
    population,
    intake and
    offtakeR092_1
  • Livestock
    extension R291
  • Livestock
    extension
    service
    providers R292
  • Livestock Pest
    and Parasite
    control R220
  • Livestock
    product R250
  • marketing
    problem R102
  • marketing
    problem R103
  • Milk production
    R186
  • Milk production
    R196
  • access and use
    of resources
    R061
  • access to farm
    inputs and
    implements R121
  • access to
    functional
    Livestock
    StructuresaccessoriesR270
  • activities of
    the
    householdR022
  • Agroprocessing
    and
    by-productsR082
  • Animal
    contribution to
    crop production
    R171
  • Chicken
    diseases R240
  • credit for
    Agriculture
    purposesR13_1
  • erosion
    controlwater
    harvesting
    facilities R112
  • farm implements
    and assets used
    and owned by
    the household
    during
    2002-2003 R122
  • Fish farming
    R282
  • household
    information
    R031
  • Household
    information,
    Agriculture
    activities,
    Livestock
    informationR00
  • labour use R311
  • land
    accessownershiptenure
    R041
  • land use R051
  • livelihood
    constraints
    R162
  • livelihood
    constraintsR161
  • other Livestock
    R230
  • outlets for the
    sale of
    Livestock R260
  • related to
    respondent and
    household head
    R122_00
  • tree
    farmingagroforestry
    R142
  • use of
    secondary
    products R076
  • Pig
    diseasespestsconditions
    R215
  • Pig increase
    R213
  • Pig offtake
    R214
  • Pig population
    and production
    R212
  • Sheep diseases
    R205
  • Sheep intake
    R203
  • Sheep offtake
    R204
  • Sheep
    population,
    intake and
    offtake R202
  • R321
  • R331
  • R332
  • use of credit
    for agriculture
    purposes R130
  • use of credit
    for agriculture
    purposes R131
  • use of credit
    for agriculture
    purposes R132

District (District)

Data file: Cattle population, intake and offtake R182

Overview

Valid: 47879
Invalid: 0
Type: Discrete
Width: 3
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
011 Kondoa 891
1.9%
012 Mpwapwa 306
0.6%
013 Kongwa 443
0.9%
014 Dodoma Rural 345
0.7%
015 Dodoma Urban 287
0.6%
021 Monduli 1813
3.8%
022 Arumeru 1680
3.5%
023 Arusha 246
0.5%
024 Karatu 1263
2.6%
025 Ngorongoro 1646
3.4%
031 Rombo 388
0.8%
032 Mwanga 784
1.6%
033 Same 539
1.1%
034 Moshi Rural 1040
2.2%
035 Hai 866
1.8%
036 Moshi Urban 0
0%
041 Lushoto 556
1.2%
042 Korogwe 312
0.7%
043 Muheza 139
0.3%
044 Tanga 214
0.4%
045 Pangani 54
0.1%
046 Handeni 171
0.4%
047 Kilindi 249
0.5%
051 Kilosa 155
0.3%
052 Morogoro Rural 78
0.2%
053 Kilombero 45
0.1%
054 Ulanga 87
0.2%
055 Morogoro Urban 33
0.1%
056 Mvomero 24
0.1%
061 Bagamoyo 111
0.2%
062 Kibaha 76
0.2%
063 Kisarawe 26
0.1%
064 Mkuranga 3
0%
065 Rufiji 43
0.1%
066 Mafia 257
0.5%
071 Kinondoni 126
0.3%
072 Ilala 31
0.1%
073 Temeke 115
0.2%
081 Kilwa 0
0%
082 Lindi Rural 10
0%
083 Nachingwea 8
0%
084 Liwale 0
0%
085 Ruangwa 0
0%
086 Lindi Urban 14
0%
091 Mtwara Rural 22
0%
092 Newala 23
0%
093 Masasi 33
0.1%
094 Tandahimba 10
0%
095 Mtwara Urban 2
0%
101 Tunduru 14
0%
102 Songea Rural 84
0.2%
103 Mbinga 270
0.6%
104 Songea Urban 62
0.1%
105 Namtumbo 46
0.1%
111 Iringa Rural 150
0.3%
112 Mufindi 334
0.7%
113 Makete 738
1.5%
114 Njombe 392
0.8%
115 Ludewa 305
0.6%
116 Iringa Urban 16
0%
117 Kilolo 247
0.5%
121 Chunya 222
0.5%
122 Mbeya Rural 321
0.7%
123 Kyela 422
0.9%
124 Rungwe 541
1.1%
125 Ileje 361
0.8%
126 Mbozi' 559
1.2%
127 Mbarali 298
0.6%
128 Mbeya Urban 298
0.6%
131 Iramba 800
1.7%
132 Singida Rural 1122
2.3%
133 Manyoni 300
0.6%
134 Singida Urban 438
0.9%
141 Nzega 776
1.6%
142 Igunga 863
1.8%
143 Uyui 400
0.8%
144 Urambo 246
0.5%
145 Sikonge 419
0.9%
146 Tabora Urban 240
0.5%
151 Mpanda 136
0.3%
152 Sumbawanga Rural 549
1.1%
153 Nkansi 334
0.7%
154 Sumbawanga Urban 461
1%
161 Kibondo 132
0.3%
162 Kasulu 176
0.4%
163 Kigoma Rural 55
0.1%
164 Kigoma Urban 5
0%
171 Bariadi 830
1.7%
172 Maswa 668
1.4%
173 Shinyanga Rural 867
1.8%
174 Kahama 884
1.8%
175 Bukombe 529
1.1%
176 Meatu 750
1.6%
177 Shinyanga Urban 638
1.3%
178 Kishapu 877
1.8%
181 Karagwe 254
0.5%
182 Bukoba Rural 213
0.4%
183 Muleba 174
0.4%
184 Biharamulo 456
1%
185 Ngara 124
0.3%
186 Bukoba Urban 64
0.1%
191 Ukerewe 640
1.3%
192 Magu 631
1.3%
193 Nyamagana 0
0%
194 Kwimba 705
1.5%
195 Sengerema 674
1.4%
196 Geita 625
1.3%
197 Misungwi 700
1.5%
198 Ilemela 255
0.5%
201 Tarime 906
1.9%
202 Serengeti 762
1.6%
203 Musoma Rural 471
1%
204 Bunda 555
1.2%
205 Musoma Urban 65
0.1%
211 Babati 1059
2.2%
212 Hanang 1015
2.1%
213 Mbulu 1215
2.5%
214 Simanjiro 1120
2.3%
215 Kiteto 457
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.
Back to Catalog
Food and Agriculture Organization of the United Nations

FOLLOW US ON

  • icon-facebook
  • icon-flickr
  • icon-instagram
  • icon-linkedin
  • icon-rss
  • icon-slideshare
  • icon-soundcloud
  • icon-tiktok
  • icon-tuotiao
  • icon-twitter
  • icon-wechat
  • icon-weibo
  • icon-youtube
  • FAO Organizational Chart
  • Regional Office for AfricaRegional Office for Asia and the PacificRegional Office for Europe and Central AsiaRegional Office for Latin America and the CaribbeanRegional Office for the Near East and North AfricaCountry Offices
  • Jobs
  • |
  • Contact us
  • |
  • Terms and Conditions
  • |
  • Scam Alert
  • |
  • Report Misconduct

Download our App

© FAO 2023