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
97548
Downloads
20457
ward of the destination (s10_dtnwrd)
Data file: s10_activities_share
Overview
Valid:
2447
Invalid:
91537
Type:
Discrete
Decimal:
0
Start:
67
End:
68
Width:
2
Range:
1 - 90
Format:
Numeric
Questions and instructions
Literal question
Please indicate the ward of the destination
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | azimio | 11 |
0.4%
|
| 2 | buguruni | 43 |
1.8%
|
| 3 | bunju | 31 |
1.3%
|
| 4 | buza | 3 |
0.1%
|
| 5 | chamazi | 5 |
0.2%
|
| 6 | changombe | 2 |
0.1%
|
| 7 | chanika | 24 |
1%
|
| 8 | charambe | 4 |
0.2%
|
| 9 | gerezani | 1 |
0%
|
| 10 | goba | 9 |
0.4%
|
| 11 | gongolamboto | 18 |
0.7%
|
| 12 | hananasifu | 0 |
0%
|
| 13 | ilala | 3 |
0.1%
|
| 14 | jangwani | 3 |
0.1%
|
| 15 | kariakoo | 0 |
0%
|
| 16 | kawe | 27 |
1.1%
|
| 17 | keko | 362 |
14.8%
|
| 18 | kibada | 0 |
0%
|
| 19 | kibamba | 398 |
16.3%
|
| 20 | kiburugwa | 14 |
0.6%
|
| 21 | kigamboni | 47 |
1.9%
|
| 22 | kigogo | 17 |
0.7%
|
| 23 | kijichi | 18 |
0.7%
|
| 24 | kijitonyama | 27 |
1.1%
|
| 25 | kilakala | 3 |
0.1%
|
| 26 | kimanga | 22 |
0.9%
|
| 27 | kimara | 3 |
0.1%
|
| 28 | kimbiji | 17 |
0.7%
|
| 29 | kinondoni | 28 |
1.1%
|
| 30 | kinyerezi | 2 |
0.1%
|
| 31 | kipawa | 14 |
0.6%
|
| 32 | kisarawe ii | 81 |
3.3%
|
| 33 | kisutu | 5 |
0.2%
|
| 34 | kitunda | 49 |
2%
|
| 35 | kivukoni | 5 |
0.2%
|
| 36 | kivule | 1 |
0%
|
| 37 | kiwalani | 20 |
0.8%
|
| 38 | kunduchi | 5 |
0.2%
|
| 39 | kurasini | 233 |
9.5%
|
| 40 | kwembe | 1 |
0%
|
| 41 | mabibo | 32 |
1.3%
|
| 42 | mabwepande | 39 |
1.6%
|
| 43 | magomeni | 23 |
0.9%
|
| 44 | majohe | 5 |
0.2%
|
| 45 | makangarawe | 19 |
0.8%
|
| 46 | makongo | 20 |
0.8%
|
| 47 | makuburi | 14 |
0.6%
|
| 48 | makumbusho | 17 |
0.7%
|
| 49 | makurumla | 17 |
0.7%
|
| 50 | manzese | 6 |
0.2%
|
| 51 | mbagala | 6 |
0.2%
|
| 52 | mbagala kuu | 74 |
3%
|
| 53 | mbezi | 31 |
1.3%
|
| 54 | mbezi juu | 24 |
1%
|
| 55 | mburahati | 3 |
0.1%
|
| 56 | mbweni | 13 |
0.5%
|
| 57 | mchafukoge | 3 |
0.1%
|
| 58 | mchikichini | 38 |
1.6%
|
| 59 | mianzini | 4 |
0.2%
|
| 60 | miburani | 10 |
0.4%
|
| 61 | mikocheni | 12 |
0.5%
|
| 62 | mjimwema | 29 |
1.2%
|
| 63 | msasani | 40 |
1.6%
|
| 64 | msigani | 28 |
1.1%
|
| 65 | msongola | 18 |
0.7%
|
| 66 | mtoni | 2 |
0.1%
|
| 67 | mwananyamala | 11 |
0.4%
|
| 68 | mzimuni | 27 |
1.1%
|
| 69 | ndugumbi | 0 |
0%
|
| 70 | pemba mnazi | 28 |
1.1%
|
| 71 | pugu | 46 |
1.9%
|
| 72 | sandali | 10 |
0.4%
|
| 73 | saranga | 26 |
1.1%
|
| 74 | segerea | 26 |
1.1%
|
| 75 | sinza | 8 |
0.3%
|
| 76 | somangila | 40 |
1.6%
|
| 77 | tabata | 38 |
1.6%
|
| 78 | tandale | 3 |
0.1%
|
| 79 | tandika | 8 |
0.3%
|
| 80 | temeke | 6 |
0.2%
|
| 81 | toangoma | 27 |
1.1%
|
| 82 | tungi | 12 |
0.5%
|
| 83 | ubungo | 6 |
0.2%
|
| 84 | ukonga | 11 |
0.4%
|
| 85 | upanga magharibi | 0 |
0%
|
| 86 | upanga mashariki | 0 |
0%
|
| 87 | vijibweni | 10 |
0.4%
|
| 88 | vingunguti | 8 |
0.3%
|
| 89 | wazo | 8 |
0.3%
|
| 90 | yombo vituka | 5 |
0.2%
|
| Sysmiss | 91537 |
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.