National Panel Survey 2014-2015, Wave 4
Tanzania, 2014 - 2015
Get Microdata
Reference ID
TZA_2014_NPS-R4_v03_M
Producer(s)
National Bureau of Statistics
Created on
Oct 10, 2017
Last modified
Oct 10, 2017
Page views
42406
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- Data files
- ag_filters
- 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_10
- ag_sec_11
- ag_sec_12a
- ag_sec_12b
- ag_sec_a
- hh_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_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_filters
- 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_11a
- lf_sec_11b
- lf_sec_12
- lf_sec_13a
- lf_sec_13b
- lf_sec_a
- npsy4.child.anthro
- npsy4.ea.offset
- LF_SEC_10
- 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
- consumptionNPS4
What was the main crop cultivated on this plot in long rainy season 2014 (NAME)? (ag3a_07_1)
Data file: ag_sec_3a
Overview
Valid:
3930
Invalid:
0
Type:
Discrete
Start:
48
End:
61
Width:
14
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ALIZETI | 41 |
1%
|
|
| BAMIA | 8 |
0.2%
|
|
| BOGA | 3 |
0.1%
|
|
| CHAI | 4 |
0.1%
|
|
| CHOROKO | 6 |
0.2%
|
|
| DENGU | 10 |
0.3%
|
|
| EMBE | 37 |
0.9%
|
|
| FIWI | 5 |
0.1%
|
|
| ILIKI | 2 |
0.1%
|
|
| KAHAWA | 35 |
0.9%
|
|
| KAKAO | 1 |
0%
|
|
| KARAFUU | 4 |
0.1%
|
|
| KARANGA | 79 |
2%
|
|
| KAROTI | 3 |
0.1%
|
|
| KISAMVU | 1 |
0%
|
|
| KOROSHO | 100 |
2.5%
|
|
| KUNDE | 7 |
0.2%
|
|
| MACHUNGWA | 15 |
0.4%
|
|
| MAGIMBI | 15 |
0.4%
|
|
| MAHARAGE | 170 |
4.3%
|
|
| MAHINDI | 1750 |
44.5%
|
|
| MAIDINI | 1 |
0%
|
|
| MAPERA | 1 |
0%
|
|
| MATANGO | 2 |
0.1%
|
|
| MATEMBELE | 5 |
0.1%
|
|
| MATOPETOPE | 1 |
0%
|
|
| MBAAZI | 20 |
0.5%
|
|
| MBOGAMBOGA | 1 |
0%
|
|
| MCHENZA | 1 |
0%
|
|
| MCHICHA | 4 |
0.1%
|
|
| MHOGO | 354 |
9%
|
|
| MIBUNI | 2 |
0.1%
|
|
| MIDIM | 1 |
0%
|
|
| MIGOMBA | 209 |
5.3%
|
|
| MIHOGO | 1 |
0%
|
|
| MILIMAU | 1 |
0%
|
|
| MIPAINA | 1 |
0%
|
|
| MIPINE | 1 |
0%
|
|
| MITI MBAO | 3 |
0.1%
|
|
| MITI YA KUNI | 1 |
0%
|
|
| MITI YA MBAO | 30 |
0.8%
|
|
| MITIKI | 1 |
0%
|
|
| MIWA | 7 |
0.2%
|
|
| MPERA | 1 |
0%
|
|
| MPESHENI | 1 |
0%
|
|
| MPUMGA | 1 |
0%
|
|
| MPUNGA | 428 |
10.9%
|
|
| MTAMA | 104 |
2.6%
|
|
| MUHOGO | 3 |
0.1%
|
|
| MWANI | 3 |
0.1%
|
|
| NANASI | 12 |
0.3%
|
|
| NAZI | 21 |
0.5%
|
|
| NDIZI | 34 |
0.9%
|
|
| NGANO | 5 |
0.1%
|
|
| NJUGU MAWE | 14 |
0.4%
|
|
| NYANYA | 15 |
0.4%
|
|
| NYANYA CHUNGU | 1 |
0%
|
|
| PAINA | 1 |
0%
|
|
| PAMBA | 100 |
2.5%
|
|
| PAPAI | 4 |
0.1%
|
|
| PARACHICHI | 4 |
0.1%
|
|
| PILIPILI HOHO | 1 |
0%
|
|
| SALADI | 1 |
0%
|
|
| STAFELI | 1 |
0%
|
|
| TANGAWIZI | 1 |
0%
|
|
| TIKITI MAJI | 2 |
0.1%
|
|
| TUMBAKU | 30 |
0.8%
|
|
| UFUTA | 66 |
1.7%
|
|
| ULEZI | 9 |
0.2%
|
|
| UWELE | 5 |
0.1%
|
|
| VIAZI MVIRINGO | 23 |
0.6%
|
|
| VIAZI VIKUU | 4 |
0.1%
|
|
| VIAZI VITAMU | 86 |
2.2%
|
|
| VITUNGUU | 5 |
0.1%
|
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.