National Panel Survey 2012-2013, Wave 3
Tanzania, 2012 - 2013
Get Microdata
Reference ID
TZA_2012_NPS-R3_v01_M
Producer(s)
National Bureau of Statistics
Collection(s)
Metadata
Created on
Apr 28, 2015
Last modified
Jan 30, 2020
Page views
411539
Downloads
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- Data files
- AG_NETWORK
- AG_SEC_01
- AG_SEC_2A
- AG_SEC_2B
- AG_SEC_3A
- AG_SEC_3B
- AG_SEC_4A
- AG_SEC_4B
- AG_SEC_5A
- AG_SEC_5B
- AG_SEC_6A
- AG_SEC_6B
- AG_SEC_7A
- AG_SEC_7B
- AG_SEC_08
- AG_SEC_9A
- AG_SEC_9B
- AG_SEC_9C
- AG_SEC_10
- AG_SEC_11
- AG_SEC_12A
- AG_SEC_12B
- AG_SEC_A
- COM_SEC_A1A2
- COM_SEC_CB
- COM_SEC_CC
- COM_SEC_CD
- COM_SEC_CE
- COM_SEC_CF
- COM_SEC_CF_ID
- COM_SEC_CG
- ConsumptionNPS3
- FILTERS
- HH_SEC_A
- HH_SEC_B
- HH_SEC_C
- HH_SEC_D
- HH_SEC_E
- HH_SEC_F
- HH_SEC_G
- HH_SEC_H
- HH_SEC_I
- HH_SEC_J1
- HH_SEC_J2
- HH_SEC_J3
- HH_SEC_J4
- HH_SEC_K
- HH_SEC_L
- HH_SEC_M
- HH_SEC_N
- HH_SEC_O1
- HH_SEC_O2
- HH_SEC_P
- HH_SEC_Q1
- HH_SEC_Q2
- HH_SEC_R
- HH_SEC_S
- HH_SEC_U2
- HH_SEC_V
- LF_NETWORK
- LF_SEC_01
- LF_SEC_02
- LF_SEC_03
- LF_SEC_04
- LF_SEC_05
- LF_SEC_06
- LF_SEC_07
- LF_SEC_08
- LF_SEC_09
- LF_SEC_10
- LF_SEC_11A
- LF_SEC_11B
- LF_SEC_12
- LF_SEC_13A
- LF_SEC_13B
- LF_SEC_A
- HouseholdGeovars_Y3
- NPSY3.PANEL.KEY
- PlotGeovars_Y3
- Y3_weights
CROP NAME (zaoname)
Data file: AG_SEC_4A
Overview
Valid:
7934
Invalid:
0
Type:
Discrete
Start:
32
End:
47
Width:
16
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ALIZET | 1 |
0%
|
|
| ALIZETI | 245 |
3.1%
|
|
| BAMIA | 14 |
0.2%
|
|
| BILINGANYA | 5 |
0.1%
|
|
| BIRINGANI | 1 |
0%
|
|
| BOGA | 21 |
0.3%
|
|
| BOMA | 1 |
0%
|
|
| CHAINESE | 1 |
0%
|
|
| CHAINIZI | 2 |
0%
|
|
| CHOROKO | 85 |
1.1%
|
|
| DENGU | 29 |
0.4%
|
|
| FIGIRI | 1 |
0%
|
|
| FIWI | 22 |
0.3%
|
|
| HOHO | 2 |
0%
|
|
| JUNGUMAWE | 1 |
0%
|
|
| KABICHI | 7 |
0.1%
|
|
| KAHAWA | 1 |
0%
|
|
| KALANGA | 1 |
0%
|
|
| KARAMATA | 1 |
0%
|
|
| KARANA | 1 |
0%
|
|
| KARANGA | 466 |
5.9%
|
|
| KAROTI | 3 |
0%
|
|
| KIENYEJI | 1 |
0%
|
|
| KITUNGUU MAJI | 2 |
0%
|
|
| KUNDE | 236 |
3%
|
|
| KUNDE NENE | 2 |
0%
|
|
| KUNDE ZA ASILI | 1 |
0%
|
|
| MABILINGANYA | 2 |
0%
|
|
| MABOGA | 33 |
0.4%
|
|
| MAGIMBI | 122 |
1.5%
|
|
| MAHARAGE | 877 |
11.1%
|
|
| MAHINDI | 3085 |
38.9%
|
|
| MAHINDI. | 1 |
0%
|
|
| MAINDI | 1 |
0%
|
|
| MAJANI YA BOGA | 1 |
0%
|
|
| MAJANI YA KUNDE | 1 |
0%
|
|
| MAJANI YA MABOGA | 2 |
0%
|
|
| MANJANO | 1 |
0%
|
|
| MATAMA | 1 |
0%
|
|
| MATANGO | 3 |
0%
|
|
| MATELA | 1 |
0%
|
|
| MATEMBELE | 11 |
0.1%
|
|
| MATIKITI | 2 |
0%
|
|
| MATIKITI MAJI | 2 |
0%
|
|
| MBAAZI | 272 |
3.4%
|
|
| MBAAZI NDEFU | 1 |
0%
|
|
| MCHICHA | 20 |
0.3%
|
|
| MIHANDA | 3 |
0%
|
|
| MIHOGO | 16 |
0.2%
|
|
| MJUNGU MAWE | 1 |
0%
|
|
| MKUNDE | 1 |
0%
|
|
| MNAVU | 2 |
0%
|
|
| MPUNGA | 803 |
10.1%
|
|
| MTAMA | 315 |
4%
|
|
| MUHOGO | 19 |
0.2%
|
|
| MWANI | 8 |
0.1%
|
|
| NAMANGAYA | 1 |
0%
|
|
| NGANO | 23 |
0.3%
|
|
| NGOGWE | 2 |
0%
|
|
| NGWARA | 4 |
0.1%
|
|
| NJEGERE | 9 |
0.1%
|
|
| NJUGU | 8 |
0.1%
|
|
| NJUGU MAWE | 55 |
0.7%
|
|
| NJUGUMAWE | 7 |
0.1%
|
|
| NYANYA | 42 |
0.5%
|
|
| NYANYA CHUNGU | 1 |
0%
|
|
| NYANYA MSHUMAA | 1 |
0%
|
|
| NYANYACHUNGU | 3 |
0%
|
|
| PAMBA | 201 |
2.5%
|
|
| PARETO | 18 |
0.2%
|
|
| PAROTO | 1 |
0%
|
|
| PILIPILI | 2 |
0%
|
|
| SELENA | 1 |
0%
|
|
| SKUMA | 1 |
0%
|
|
| SOYA | 13 |
0.2%
|
|
| SPINACH | 2 |
0%
|
|
| SPINACHI | 5 |
0.1%
|
|
| SUKUMA | 1 |
0%
|
|
| SUKUMA WIKI | 2 |
0%
|
|
| SUKUMAWIKI | 1 |
0%
|
|
| TANGO | 6 |
0.1%
|
|
| TEMBELE | 1 |
0%
|
|
| TIKITI | 3 |
0%
|
|
| TIKITI MAJI | 1 |
0%
|
|
| TUMBAKU | 64 |
0.8%
|
|
| TUNGULE | 4 |
0.1%
|
|
| UFUTA | 113 |
1.4%
|
|
| ULEZI | 27 |
0.3%
|
|
| UPUPU | 1 |
0%
|
|
| UWELE | 74 |
0.9%
|
|
| UYOLE | 1 |
0%
|
|
| VIAAZI MVIRINGO | 1 |
0%
|
|
| VIAZI | 19 |
0.2%
|
|
| VIAZI MVIRINGO | 52 |
0.7%
|
|
| VIAZI ULAYA | 3 |
0%
|
|
| VIAZI VIKUU | 24 |
0.3%
|
|
| VIAZI VITAMU | 357 |
4.5%
|
|
| VIAZIVIKUU | 1 |
0%
|
|
| VITUNGUU | 4 |
0.1%
|
|
| VITUNGUU MAJI | 10 |
0.1%
|
|
| VITUNGUU SAUMU | 1 |
0%
|
|
| ZA ASILI | 1 |
0%
|
|
| ZA KUTAMBAA | 2 |
0%
|
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.