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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-CENSUS / TZA_2007-2008_ASCS_V01_EN_M_V01_A_OCS / variable [F58]
Agricultural-Census

Agriculture Sample Census Survey 2007-2008

United Republic of Tanzania, 2009
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Reference ID
TZA_2007-2008_ASCS_v01_EN_M_v01_A_OCS
Producer(s)
National Bureau of Statistics, Office of Chief Government Statistician-Zanzibar
Collections
Agricultural Censuses
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 24, 2019
Last modified
Oct 24, 2019
Page views
112473
Downloads
408
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • R00
  • R031
  • R041
  • R042
  • R051
  • R052
  • R053
  • R061
  • R062
  • R063
  • R064
  • R066
  • R091
  • R092
  • R093
  • R094
  • R095
  • R099
  • R104
  • R0651
  • R0831
  • R0910
  • R0911
  • R000
  • R031
  • R032
  • R041
  • R043
  • R071
  • R081
  • R098
  • R099
  • R101
  • R111
  • R111_4
  • R114
  • R422
  • R511
  • R522
  • R522_1
  • R621
  • R622
  • R910
  • R911
  • R917
  • R921
  • R926
  • R931
  • R941
  • R951
  • R954
  • R971
  • R972

District Identification (Dist_ID)

Data file: R051

Overview

Valid: 32940
Invalid: 0
Type: Discrete
Width: 3
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
011 Kondoa 5
0%
012 Mpwapwa 3
0%
013 Kongwa 0
0%
015 Dodoma Urban 0
0%
016 Bahi 0
0%
017 Chamwino 0
0%
021 Monduli 81
0.2%
023 Arusha 85
0.3%
024 Karatu 57
0.2%
025 Ngorongoro 23
0.1%
026 Longido 253
0.8%
027 Arusha Rural 279
0.8%
028 Meru 165
0.5%
031 Rombo 665
2%
032 Mwanga 560
1.7%
033 Same 678
2.1%
034 Moshi Rural 310
0.9%
035 Hai 340
1%
037 Siha 138
0.4%
041 Lushoto 826
2.5%
042 Korogwe 185
0.6%
043 Muheza 358
1.1%
044 Tanga 101
0.3%
045 Pangani 216
0.7%
046 Handeni 284
0.9%
047 Kilindi 298
0.9%
048 Mkinga 366
1.1%
051 Kilosa 340
1%
052 Morogoro 345
1%
053 Kilombero 421
1.3%
054 Ulanga 690
2.1%
055 Morogoro Urban 190
0.6%
056 Mvomero 359
1.1%
061 Bagamoyo 165
0.5%
062 Kibaha 300
0.9%
063 Kisarawe 477
1.4%
064 Mkuranga 357
1.1%
065 Rufiji 409
1.2%
066 Mafia 97
0.3%
071 Kinondoni 226
0.7%
072 Ilala 124
0.4%
073 Temeke 194
0.6%
081 Kilwa 0
0%
082 Lindi Rural 4
0%
083 Nachingwea 1
0%
084 Liwale 4
0%
085 Ruangwa 27
0.1%
086 Lindi Urban 0
0%
091 Mtwara Rural 1
0%
092 Newala 0
0%
093 Masasi 8
0%
094 Tandahimba 0
0%
095 Mtwara Urban 0
0%
096 Nanyumbu 0
0%
101 Tunduru 5
0%
102 Songea Rural 4
0%
103 Mbinga 0
0%
104 Songea Urban 0
0%
105 Namtumbo 2
0%
111 Iringa Rural 1
0%
112 Mufindi 6
0%
113 Makete 0
0%
114 Njombe 0
0%
115 Ludewa 3
0%
116 Iringa Urban 0
0%
117 Kilolo 10
0%
118 Njombe Mji 1
0%
121 Chunya 11
0%
122 Mbeya (R) 94
0.3%
123 Kyela 0
0%
124 Rungwe 483
1.5%
125 Ileje 186
0.6%
126 Mbozi 0
0%
127 Mbarali 2
0%
128 Mbeya Urban 1
0%
131 Iramba 0
0%
132 Singida Rural 0
0%
133 Manyoni 0
0%
134 Singida Urban 0
0%
141 Nzega 0
0%
142 Igunga 2
0%
143 Uyui 5
0%
144 Urambo 0
0%
145 Sikonge 0
0%
146 Tabora Urban 0
0%
151 Mpanda 16
0%
152 Sumbawanga Rural 10
0%
153 Nkasi 3
0%
154 Sumbawanga Urban 0
0%
161 Kibondo 842
2.6%
162 Kasulu 640
1.9%
163 Kigoma Rural 605
1.8%
164 Kigoma Urban 164
0.5%
171 Bariadi 2
0%
172 Maswa 0
0%
173 Shinyanga Rural 0
0%
174 Kahama 115
0.3%
175 Bukombe 9
0%
176 Meatu 9
0%
177 Shinyanga Urban 7
0%
178 Kishapu 2
0%
181 Karagwe 706
2.1%
182 Bukoba Rural 1019
3.1%
183 Muleba 900
2.7%
184 Biharamulo 903
2.7%
185 Ngara 1047
3.2%
186 Bukoba Urban 127
0.4%
187 Missenyi 1435
4.4%
188 Chato 1001
3%
191 Ukerewe 652
2%
192 Magu 893
2.7%
194 Kwimba 906
2.8%
195 Sengerema 819
2.5%
196 Geita 958
2.9%
197 Missungwi 1125
3.4%
198 Ilemela 434
1.3%
201 Tarime 714
2.2%
202 Serengeti 773
2.3%
203 Musoma Rural 407
1.2%
204 Bunda 695
2.1%
205 Musoma Urban 46
0.1%
206 Rorya 424
1.3%
211 Babati 87
0.3%
212 Hanang 28
0.1%
213 Mbulu 91
0.3%
214 Simanjiro 21
0.1%
215 Kiteto 0
0%
511 Kaskazini-A 437
1.3%
512 Kaskazini-B 398
1.2%
521 Kati 426
1.3%
522 Kusini 465
1.4%
531 Magharibi 304
0.9%
541 Wete 106
0.3%
542 Micheweni 197
0.6%
551 Chake 41
0.1%
552 Mkoani 100
0.3%
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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