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
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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
PLEASE LIST ALL CROPS CULTIVATED DURING THE LAST 12 MONTHS. (zaoname)
Data file: ag_sec_6b
Overview
Valid:
2488
Invalid:
0
Type:
Discrete
Start:
17
End:
34
Width:
18
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| CALPTUSI | 1 |
0%
|
|
| CHAI | 6 |
0.2%
|
|
| CHAKULA CHA MIFUGO | 2 |
0.1%
|
|
| CHAKULA MIFUGO | 3 |
0.1%
|
|
| CHIKICHI | 59 |
2.4%
|
|
| GRAVELIA | 1 |
0%
|
|
| GRAVELLA | 1 |
0%
|
|
| HAKUNA | 1 |
0%
|
|
| HAME | 1 |
0%
|
|
| ILIKI | 6 |
0.2%
|
|
| KAHAWA | 225 |
9%
|
|
| KAKAO | 8 |
0.3%
|
|
| KARAFUU | 12 |
0.5%
|
|
| KARITUSI | 1 |
0%
|
|
| KOROSHO | 274 |
11%
|
|
| KUNI | 2 |
0.1%
|
|
| KWEME | 5 |
0.2%
|
|
| MAGIMBI | 2 |
0.1%
|
|
| MAIDINI | 1 |
0%
|
|
| MAYUGWA | 1 |
0%
|
|
| MBAAZI | 17 |
0.7%
|
|
| MBUMU | 1 |
0%
|
|
| MBUYU | 8 |
0.3%
|
|
| MDALASINI | 7 |
0.3%
|
|
| MHOGO | 855 |
34.4%
|
|
| MIANZI | 13 |
0.5%
|
|
| MIAROBAINI | 3 |
0.1%
|
|
| MIBOYA | 1 |
0%
|
|
| MIEMBE | 1 |
0%
|
|
| MIGOMBA | 1 |
0%
|
|
| MIGUHA | 1 |
0%
|
|
| MIHUMLA | 1 |
0%
|
|
| MIHUMULA | 8 |
0.3%
|
|
| MIHUMURA | 2 |
0.1%
|
|
| MIJIMA | 1 |
0%
|
|
| MIJOHOLO | 1 |
0%
|
|
| MIJOHORO | 2 |
0.1%
|
|
| MIKALATUSI | 2 |
0.1%
|
|
| MIKARATUSI | 6 |
0.2%
|
|
| MIKESHIA | 1 |
0%
|
|
| MIKORA | 1 |
0%
|
|
| MIKUHUNGU | 1 |
0%
|
|
| MIKUYU | 1 |
0%
|
|
| MILINGOTI | 6 |
0.2%
|
|
| MIOMBORO | 1 |
0%
|
|
| MIPAINA | 3 |
0.1%
|
|
| MIPAINI | 1 |
0%
|
|
| MIPANI | 1 |
0%
|
|
| MIPINE | 1 |
0%
|
|
| MIPOGORO | 1 |
0%
|
|
| MIRONGE | 1 |
0%
|
|
| MISAGI | 1 |
0%
|
|
| MISAMBYA | 2 |
0.1%
|
|
| MISANA | 2 |
0.1%
|
|
| MISEDELEA | 1 |
0%
|
|
| MISENENE | 2 |
0.1%
|
|
| MISUFI | 1 |
0%
|
|
| MITAMBA | 1 |
0%
|
|
| MITI MBAO | 3 |
0.1%
|
|
| MITI YA DAWA | 6 |
0.2%
|
|
| MITI YA KIVULI | 1 |
0%
|
|
| MITI YA KUNI | 178 |
7.2%
|
|
| MITI YA MBAO | 321 |
12.9%
|
|
| MITI YA UZIO | 3 |
0.1%
|
|
| MITIKI | 5 |
0.2%
|
|
| MITUNDU | 3 |
0.1%
|
|
| MIUMULA | 2 |
0.1%
|
|
| MIWA | 144 |
5.8%
|
|
| MIYENZE | 1 |
0%
|
|
| MIYUMULA | 1 |
0%
|
|
| MJOHORO | 1 |
0%
|
|
| MKOBEKOBE | 1 |
0%
|
|
| MKONGE | 37 |
1.5%
|
|
| MKURUNGU | 1 |
0%
|
|
| MKWAJU | 19 |
0.8%
|
|
| MKWININI | 1 |
0%
|
|
| MNINGA | 5 |
0.2%
|
|
| MPINGO | 1 |
0%
|
|
| MPIRA | 4 |
0.2%
|
|
| MPULU | 2 |
0.1%
|
|
| MSAMBIA | 1 |
0%
|
|
| MSAMIAJI | 1 |
0%
|
|
| MTENDE | 1 |
0%
|
|
| MTI WA DAWA | 5 |
0.2%
|
|
| MTI WA KUNI | 6 |
0.2%
|
|
| MTI WA MBAO | 6 |
0.2%
|
|
| MTI WA MSINGISA | 1 |
0%
|
|
| MTI YA KUNI | 1 |
0%
|
|
| MUAROBAINI | 2 |
0.1%
|
|
| MUHUMULA | 1 |
0%
|
|
| MUHUMWA | 1 |
0%
|
|
| MVULE | 1 |
0%
|
|
| MWAROBAINI | 1 |
0%
|
|
| MYUGUYU | 1 |
0%
|
|
| NAZI | 131 |
5.3%
|
|
| NDIZI | 1 |
0%
|
|
| NDOU | 1 |
0%
|
|
| NGWARA | 1 |
0%
|
|
| NYUMBANI | 1 |
0%
|
|
| PAIN | 1 |
0%
|
|
| PAINA | 4 |
0.2%
|
|
| PAINI | 1 |
0%
|
|
| PILIPILI | 1 |
0%
|
|
| PILIPILI MANGA | 2 |
0.1%
|
|
| PINE(MITI YA MBAO) | 1 |
0%
|
|
| QUATAMALA | 1 |
0%
|
|
| UBUYU | 1 |
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.