Measuring Living Standards within Cities, Dar es Salaam 2014-2015
Tanzania, 2014 - 2015
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Reference ID
TZA_2014_DAR-LSMS_v01_M
Producer(s)
World Bank
Collection(s)
Metadata
Created on
Jan 10, 2019
Last modified
Jan 30, 2020
Page views
75160
Downloads
19844
ward of the destination (s8_address_ward)
Data file: s8_residhistory_share
Overview
Valid:
2016
Invalid:
2596
Type:
Discrete
Decimal:
0
Start:
329
End:
330
Width:
2
Range:
1 - 90
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | azimio | 9 |
0.4%
|
| 2 | buguruni | 61 |
3%
|
| 3 | bunju | 55 |
2.7%
|
| 4 | buza | 10 |
0.5%
|
| 5 | chamazi | 5 |
0.2%
|
| 6 | changombe | 31 |
1.5%
|
| 7 | chanika | 15 |
0.7%
|
| 8 | charambe | 14 |
0.7%
|
| 9 | gerezani | 10 |
0.5%
|
| 10 | goba | 4 |
0.2%
|
| 11 | gongolamboto | 36 |
1.8%
|
| 12 | hananasifu | 4 |
0.2%
|
| 13 | ilala | 124 |
6.2%
|
| 14 | jangwani | 8 |
0.4%
|
| 15 | kariakoo | 128 |
6.3%
|
| 16 | kawe | 36 |
1.8%
|
| 17 | keko | 49 |
2.4%
|
| 18 | kibada | 1 |
0%
|
| 19 | kibamba | 5 |
0.2%
|
| 20 | kiburugwa | 8 |
0.4%
|
| 21 | kigamboni | 12 |
0.6%
|
| 22 | kigogo | 10 |
0.5%
|
| 23 | kijichi | 5 |
0.2%
|
| 24 | kijitonyama | 14 |
0.7%
|
| 25 | kilakala | 5 |
0.2%
|
| 26 | kimanga | 12 |
0.6%
|
| 27 | kimara | 38 |
1.9%
|
| 28 | kimbiji | 1 |
0%
|
| 29 | kinondoni | 80 |
4%
|
| 30 | kinyerezi | 1 |
0%
|
| 31 | kipawa | 18 |
0.9%
|
| 32 | kisarawe ii | 0 |
0%
|
| 33 | kisutu | 40 |
2%
|
| 34 | kitunda | 7 |
0.3%
|
| 35 | kivukoni | 44 |
2.2%
|
| 36 | kivule | 2 |
0.1%
|
| 37 | kiwalani | 9 |
0.4%
|
| 38 | kunduchi | 37 |
1.8%
|
| 39 | kurasini | 57 |
2.8%
|
| 40 | kwembe | 1 |
0%
|
| 41 | mabibo | 25 |
1.2%
|
| 42 | mabwepande | 7 |
0.3%
|
| 43 | magomeni | 36 |
1.8%
|
| 44 | majohe | 4 |
0.2%
|
| 45 | makangarawe | 6 |
0.3%
|
| 46 | makongo | 20 |
1%
|
| 47 | makuburi | 2 |
0.1%
|
| 48 | makumbusho | 28 |
1.4%
|
| 49 | makurumla | 4 |
0.2%
|
| 50 | manzese | 58 |
2.9%
|
| 51 | mbagala | 56 |
2.8%
|
| 52 | mbagala kuu | 12 |
0.6%
|
| 53 | mbezi | 31 |
1.5%
|
| 54 | mbezi juu | 14 |
0.7%
|
| 55 | mburahati | 10 |
0.5%
|
| 56 | mbweni | 14 |
0.7%
|
| 57 | mchafukoge | 13 |
0.6%
|
| 58 | mchikichini | 6 |
0.3%
|
| 59 | mianzini | 7 |
0.3%
|
| 60 | miburani | 8 |
0.4%
|
| 61 | mikocheni | 38 |
1.9%
|
| 62 | mjimwema | 3 |
0.1%
|
| 63 | msasani | 25 |
1.2%
|
| 64 | msigani | 0 |
0%
|
| 65 | msongola | 10 |
0.5%
|
| 66 | mtoni | 27 |
1.3%
|
| 67 | mwananyamala | 20 |
1%
|
| 68 | mzimuni | 2 |
0.1%
|
| 69 | ndugumbi | 2 |
0.1%
|
| 70 | pemba mnazi | 0 |
0%
|
| 71 | pugu | 19 |
0.9%
|
| 72 | sandali | 2 |
0.1%
|
| 73 | saranga | 3 |
0.1%
|
| 74 | segerea | 8 |
0.4%
|
| 75 | sinza | 37 |
1.8%
|
| 76 | somangila | 1 |
0%
|
| 77 | tabata | 40 |
2%
|
| 78 | tandale | 18 |
0.9%
|
| 79 | tandika | 73 |
3.6%
|
| 80 | temeke | 82 |
4.1%
|
| 81 | toangoma | 6 |
0.3%
|
| 82 | tungi | 1 |
0%
|
| 83 | ubungo | 73 |
3.6%
|
| 84 | ukonga | 29 |
1.4%
|
| 85 | upanga magharibi | 24 |
1.2%
|
| 86 | upanga mashariki | 20 |
1%
|
| 87 | vijibweni | 2 |
0.1%
|
| 88 | vingunguti | 38 |
1.9%
|
| 89 | wazo | 18 |
0.9%
|
| 90 | yombo vituka | 28 |
1.4%
|
| Sysmiss | 2596 |
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.