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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-CENSUS / TZA_2007-2008_ASCS_V01_EN_M_V01_A_OCS / variable [F73]
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
112475
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: R0651

Overview

Valid: 2926
Invalid: 0
Type: Discrete
Width: 3
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
011 Kondoa 6
0.2%
012 Mpwapwa 5
0.2%
013 Kongwa 12
0.4%
015 Dodoma Urban 21
0.7%
016 Bahi 10
0.3%
017 Chamwino 0
0%
021 Monduli 42
1.4%
023 Arusha 6
0.2%
024 Karatu 27
0.9%
025 Ngorongoro 12
0.4%
026 Longido 15
0.5%
027 Arusha Rural 34
1.2%
028 Meru 82
2.8%
031 Rombo 2
0.1%
032 Mwanga 41
1.4%
033 Same 142
4.9%
034 Moshi Rural 95
3.2%
035 Hai 199
6.8%
037 Siha 42
1.4%
041 Lushoto 32
1.1%
042 Korogwe 44
1.5%
043 Muheza 2
0.1%
044 Tanga 2
0.1%
045 Pangani 0
0%
046 Handeni 0
0%
047 Kilindi 14
0.5%
048 Mkinga 9
0.3%
051 Kilosa 35
1.2%
052 Morogoro 2
0.1%
053 Kilombero 6
0.2%
054 Ulanga 12
0.4%
055 Morogoro Urban 37
1.3%
056 Mvomero 56
1.9%
061 Bagamoyo 4
0.1%
062 Kibaha 13
0.4%
063 Kisarawe 2
0.1%
064 Mkuranga 14
0.5%
065 Rufiji 20
0.7%
066 Mafia 1
0%
071 Kinondoni 32
1.1%
072 Ilala 20
0.7%
073 Temeke 49
1.7%
081 Kilwa 1
0%
082 Lindi Rural 12
0.4%
083 Nachingwea 0
0%
084 Liwale 5
0.2%
085 Ruangwa 13
0.4%
086 Lindi Urban 0
0%
091 Mtwara Rural 1
0%
092 Newala 1
0%
093 Masasi 17
0.6%
094 Tandahimba 0
0%
095 Mtwara Urban 1
0%
096 Nanyumbu 2
0.1%
101 Tunduru 9
0.3%
102 Songea Rural 51
1.7%
103 Mbinga 35
1.2%
104 Songea Urban 55
1.9%
105 Namtumbo 35
1.2%
111 Iringa Rural 73
2.5%
112 Mufindi 31
1.1%
113 Makete 13
0.4%
114 Njombe 46
1.6%
115 Ludewa 36
1.2%
116 Iringa Urban 11
0.4%
117 Kilolo 26
0.9%
118 Njombe Mji 28
1%
121 Chunya 10
0.3%
122 Mbeya (R) 22
0.8%
123 Kyela 9
0.3%
124 Rungwe 6
0.2%
125 Ileje 42
1.4%
126 Mbozi 39
1.3%
127 Mbarali 184
6.3%
128 Mbeya Urban 15
0.5%
131 Iramba 11
0.4%
132 Singida Rural 4
0.1%
133 Manyoni 49
1.7%
134 Singida Urban 9
0.3%
141 Nzega 16
0.5%
142 Igunga 14
0.5%
143 Uyui 21
0.7%
144 Urambo 15
0.5%
145 Sikonge 2
0.1%
146 Tabora Urban 29
1%
151 Mpanda 7
0.2%
152 Sumbawanga Rural 30
1%
153 Nkasi 7
0.2%
154 Sumbawanga Urban 64
2.2%
161 Kibondo 8
0.3%
162 Kasulu 7
0.2%
163 Kigoma Rural 13
0.4%
164 Kigoma Urban 12
0.4%
171 Bariadi 3
0.1%
172 Maswa 15
0.5%
173 Shinyanga Rural 5
0.2%
174 Kahama 27
0.9%
175 Bukombe 4
0.1%
176 Meatu 2
0.1%
177 Shinyanga Urban 7
0.2%
178 Kishapu 2
0.1%
181 Karagwe 6
0.2%
182 Bukoba Rural 11
0.4%
183 Muleba 5
0.2%
184 Biharamulo 5
0.2%
185 Ngara 14
0.5%
186 Bukoba Urban 5
0.2%
187 Missenyi 1
0%
188 Chato 17
0.6%
191 Ukerewe 8
0.3%
192 Magu 31
1.1%
194 Kwimba 18
0.6%
195 Sengerema 2
0.1%
196 Geita 19
0.6%
197 Missungwi 43
1.5%
198 Ilemela 38
1.3%
201 Tarime 5
0.2%
202 Serengeti 7
0.2%
203 Musoma Rural 18
0.6%
204 Bunda 8
0.3%
205 Musoma Urban 6
0.2%
206 Rorya 2
0.1%
211 Babati 31
1.1%
212 Hanang 5
0.2%
213 Mbulu 5
0.2%
214 Simanjiro 32
1.1%
215 Kiteto 0
0%
511 Kaskazini-A 4
0.1%
512 Kaskazini-B 19
0.6%
521 Kati 43
1.5%
522 Kusini 21
0.7%
531 Magharibi 62
2.1%
541 Wete 6
0.2%
542 Micheweni 10
0.3%
551 Chake 0
0%
552 Mkoani 8
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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