Datasets:
DataId int64 | SurveyId string | SurveyYear int64 | SurveyType string | DHS_CountryCode string | CountryName string | IndicatorId string | Indicator string | SDRID string | CharacteristicCategory string | CharacteristicLabel string | CharacteristicId int64 | IsTotal int64 | IsPreferred int64 | Value float64 | Precision int64 | CILow null | CIHigh null | DenominatorUnweighted float64 | DenominatorWeighted float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5,143,682 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Total 15-49 | Total 15-49 | 10,000 | 1 | 1 | 9.9 | 1 | null | null | null | 13,266 |
8,925,360 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 15-19 | 7,001 | 0 | 1 | 7.7 | 1 | null | null | null | 2,904 |
20,824,808 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 20-24 | 7,002 | 0 | 1 | 16.2 | 1 | null | null | null | 2,483 |
2,913,297 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 25-29 | 7,003 | 0 | 1 | 12.5 | 1 | null | null | null | 2,125 |
7,019,766 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 30-34 | 7,004 | 0 | 1 | 11 | 1 | null | null | null | 1,752 |
4,916,081 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 35-39 | 7,005 | 0 | 1 | 6.6 | 1 | null | null | null | 1,641 |
4,446,656 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 40-44 | 7,006 | 0 | 1 | 6.4 | 1 | null | null | null | 1,364 |
5,754,554 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (5-year groups) | 45-49 | 7,007 | 0 | 1 | 4.1 | 1 | null | null | null | 997 |
19,661,832 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (10-year groups) | 15-19 | 8,001 | 0 | 1 | 7.7 | 1 | null | null | null | 2,904 |
6,910,061 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (10-year groups) | 20-29 | 8,002 | 0 | 1 | 14.4 | 1 | null | null | null | 4,607 |
2,913,345 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (10-year groups) | 30-39 | 8,003 | 0 | 1 | 8.8 | 1 | null | null | null | 3,393 |
9,003,754 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (10-year groups) | 40-49 | 8,004 | 0 | 1 | 5.4 | 1 | null | null | null | 2,361 |
8,308,056 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (grouped) | 15-24 | 9,001 | 0 | 1 | 11.6 | 1 | null | null | null | 5,387 |
5,294,058 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (grouped) | 25-34 | 9,002 | 0 | 1 | 11.8 | 1 | null | null | null | 3,877 |
8,796,258 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Age (grouped) | 35-49 | 9,003 | 0 | 1 | 5.9 | 1 | null | null | null | 4,002 |
8,880,837 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Residence | Urban | 3,001 | 0 | 1 | 21.8 | 1 | null | null | null | 4,811 |
5,784,012 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Residence | Rural | 3,002 | 0 | 1 | 3.2 | 1 | null | null | null | 8,455 |
7,764,044 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education | No education | 4,000 | 0 | 1 | 0.2 | 1 | null | null | null | 1,946 |
2,913,421 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education | Primary | 4,001 | 0 | 1 | 3.7 | 1 | null | null | null | 8,211 |
2,913,389 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education | Secondary | 4,002 | 0 | 1 | 28.5 | 1 | null | null | null | 2,925 |
8,826,423 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education | Higher | 4,003 | 0 | 1 | 95.8 | 1 | null | null | null | 183 |
2,913,341 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education (2 groups) | No education or primary | 5,001 | 0 | 1 | 3 | 1 | null | null | null | 10,157 |
9,884,432 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Education (2 groups) | Secondary or higher | 5,002 | 0 | 1 | 32.4 | 1 | null | null | null | 3,109 |
2,913,385 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Wealth quintile | Lowest | 6,001 | 0 | 1 | 0.7 | 1 | null | null | null | 2,246 |
7,764,046 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Wealth quintile | Second | 6,002 | 0 | 1 | 0.7 | 1 | null | null | null | 2,274 |
2,913,343 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Wealth quintile | Middle | 6,003 | 0 | 1 | 1.3 | 1 | null | null | null | 2,329 |
8,681,473 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Wealth quintile | Fourth | 6,004 | 0 | 1 | 6.6 | 1 | null | null | null | 2,822 |
2,913,396 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Wealth quintile | Highest | 6,005 | 0 | 1 | 29.7 | 1 | null | null | null | 3,596 |
6,350,798 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Marital status | Never married | 16,000 | 0 | 1 | 17.1 | 1 | null | null | null | 3,353 |
4,458,710 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Marital status | Married or living together | 16,001 | 0 | 1 | 7.4 | 1 | null | null | null | 8,210 |
5,928,138 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Marital status | Widowed, divorced, separated | 16,002 | 0 | 1 | 8.1 | 1 | null | null | null | 1,703 |
256,137 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Western | 451,051 | 0 | 1 | 3.4 | 1 | null | null | null | 1,278 |
7,230,252 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Tabora | 451,052 | 0 | 1 | 3 | 1 | null | null | null | 737 |
20,004,280 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kigoma | 451,053 | 0 | 1 | 3.8 | 1 | null | null | null | 542 |
6,970,614 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Northern | 451,054 | 0 | 1 | 13.8 | 1 | null | null | null | 1,575 |
8,796,480 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kilimanjaro | 451,055 | 0 | 1 | 15.2 | 1 | null | null | null | 361 |
2,913,328 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Tanga | 451,056 | 0 | 1 | 10.8 | 1 | null | null | null | 706 |
15,785,304 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Arusha | 451,058 | 0 | 1 | 17 | 1 | null | null | null | 508 |
6,793,332 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Central | 451,059 | 0 | 1 | 4 | 1 | null | null | null | 1,336 |
4,806,646 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Manyara | 451,060 | 0 | 1 | 4 | 1 | null | null | null | 394 |
7,298,021 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Dodoma | 451,061 | 0 | 1 | 4 | 1 | null | null | null | 572 |
8,230,845 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Singida | 451,062 | 0 | 1 | 3.9 | 1 | null | null | null | 370 |
9,845,231 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Southern Highlands | 451,063 | 0 | 1 | 5.5 | 1 | null | null | null | 807 |
11,207,308 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Iringa | 451,064 | 0 | 1 | 11.1 | 1 | null | null | null | 245 |
20,159,145 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Njombe | 451,065 | 0 | 1 | 3 | 1 | null | null | null | 203 |
6,910,337 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Ruvuma | 451,066 | 0 | 1 | 3.2 | 1 | null | null | null | 360 |
19,967,153 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Lake | 451,067 | 0 | 1 | 5.1 | 1 | null | null | null | 3,463 |
2,913,408 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kagera | 451,068 | 0 | 1 | 4.7 | 1 | null | null | null | 612 |
8,088,215 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Mwanza | 451,069 | 0 | 1 | 6 | 1 | null | null | null | 859 |
256,160 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Mara | 451,070 | 0 | 1 | 5.6 | 1 | null | null | null | 523 |
7,191,947 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Shinyanga | 451,071 | 0 | 1 | 7.4 | 1 | null | null | null | 504 |
2,891,888 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Simiyu | 451,072 | 0 | 1 | 2.4 | 1 | null | null | null | 479 |
6,720,773 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Geita | 451,073 | 0 | 1 | 4 | 1 | null | null | null | 485 |
12,361,565 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Eastern | 451,074 | 0 | 1 | 24.4 | 1 | null | null | null | 2,457 |
5,248,933 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Dar es Salaam | 451,075 | 0 | 1 | 33.8 | 1 | null | null | null | 1,536 |
7,963,083 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Pwani | 451,076 | 0 | 1 | 7.5 | 1 | null | null | null | 285 |
2,891,902 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Morogoro | 451,077 | 0 | 1 | 9.2 | 1 | null | null | null | 636 |
6,819,111 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Southern | 451,078 | 0 | 1 | 4.5 | 1 | null | null | null | 700 |
4,831,111 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Lindi | 451,079 | 0 | 1 | 5 | 1 | null | null | null | 288 |
7,298,013 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Mtwara | 451,080 | 0 | 1 | 4.1 | 1 | null | null | null | 412 |
8,865,987 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | South West Highlands | 451,081 | 0 | 1 | 6.8 | 1 | null | null | null | 1,246 |
5,599,026 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Mbeya (before 2016) | 451,082 | 0 | 1 | 8.5 | 1 | null | null | null | 828 |
19,532,199 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Rukwa | 451,083 | 0 | 1 | 3.1 | 1 | null | null | null | 288 |
2,891,896 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Katavi | 451,084 | 0 | 1 | 3.8 | 1 | null | null | null | 130 |
7,155,372 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | Zanzibar | 451,085 | 0 | 1 | 16.2 | 1 | null | null | null | 404 |
2,891,910 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kaskazini Unguja | 451,086 | 0 | 1 | 2.1 | 1 | null | null | null | 56 |
2,891,901 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kusini Unguja | 451,087 | 0 | 1 | 4.9 | 1 | null | null | null | 35 |
8,088,210 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Mjini Magharibi | 451,088 | 0 | 1 | 27.8 | 1 | null | null | null | 201 |
5,954,699 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kaskazini Pemba | 451,089 | 0 | 1 | 6.4 | 1 | null | null | null | 56 |
7,191,949 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_EVU | Women who ever used the internet | COINUSWEVU | Region | ..Kusini Pemba | 451,090 | 0 | 1 | 5.6 | 1 | null | null | null | 55 |
5,143,683 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Total 15-49 | Total 15-49 | 10,000 | 1 | 1 | 8 | 1 | null | null | null | 13,266 |
8,925,361 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 15-19 | 7,001 | 0 | 1 | 6.5 | 1 | null | null | null | 2,904 |
20,824,809 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 20-24 | 7,002 | 0 | 1 | 12.8 | 1 | null | null | null | 2,483 |
2,913,298 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 25-29 | 7,003 | 0 | 1 | 9.8 | 1 | null | null | null | 2,125 |
7,019,767 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 30-34 | 7,004 | 0 | 1 | 9.1 | 1 | null | null | null | 1,752 |
4,916,082 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 35-39 | 7,005 | 0 | 1 | 5.3 | 1 | null | null | null | 1,641 |
4,446,657 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 40-44 | 7,006 | 0 | 1 | 4.9 | 1 | null | null | null | 1,364 |
5,754,555 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (5-year groups) | 45-49 | 7,007 | 0 | 1 | 3.8 | 1 | null | null | null | 997 |
19,661,833 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (10-year groups) | 15-19 | 8,001 | 0 | 1 | 6.5 | 1 | null | null | null | 2,904 |
6,910,316 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (10-year groups) | 20-29 | 8,002 | 0 | 1 | 11.4 | 1 | null | null | null | 4,607 |
2,913,439 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (10-year groups) | 30-39 | 8,003 | 0 | 1 | 7.3 | 1 | null | null | null | 3,393 |
9,003,755 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (10-year groups) | 40-49 | 8,004 | 0 | 1 | 4.4 | 1 | null | null | null | 2,361 |
8,308,057 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (grouped) | 15-24 | 9,001 | 0 | 1 | 9.4 | 1 | null | null | null | 5,387 |
5,294,063 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (grouped) | 25-34 | 9,002 | 0 | 1 | 9.5 | 1 | null | null | null | 3,877 |
8,796,259 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Age (grouped) | 35-49 | 9,003 | 0 | 1 | 4.8 | 1 | null | null | null | 4,002 |
8,880,836 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Residence | Urban | 3,001 | 0 | 1 | 18.1 | 1 | null | null | null | 4,811 |
5,784,013 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Residence | Rural | 3,002 | 0 | 1 | 2.3 | 1 | null | null | null | 8,455 |
7,764,045 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education | No education | 4,000 | 0 | 1 | 0.1 | 1 | null | null | null | 1,946 |
2,913,422 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education | Primary | 4,001 | 0 | 1 | 2.4 | 1 | null | null | null | 8,211 |
2,913,390 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education | Secondary | 4,002 | 0 | 1 | 23.8 | 1 | null | null | null | 2,925 |
8,826,424 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education | Higher | 4,003 | 0 | 1 | 94.1 | 1 | null | null | null | 183 |
2,913,342 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education (2 groups) | No education or primary | 5,001 | 0 | 1 | 2 | 1 | null | null | null | 10,157 |
9,884,433 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Education (2 groups) | Secondary or higher | 5,002 | 0 | 1 | 27.9 | 1 | null | null | null | 3,109 |
2,913,386 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Wealth quintile | Lowest | 6,001 | 0 | 1 | 0.5 | 1 | null | null | null | 2,246 |
7,764,047 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Wealth quintile | Second | 6,002 | 0 | 1 | 0.4 | 1 | null | null | null | 2,274 |
2,913,374 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Wealth quintile | Middle | 6,003 | 0 | 1 | 0.9 | 1 | null | null | null | 2,329 |
8,681,502 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Wealth quintile | Fourth | 6,004 | 0 | 1 | 4.7 | 1 | null | null | null | 2,822 |
2,913,397 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Wealth quintile | Highest | 6,005 | 0 | 1 | 24.9 | 1 | null | null | null | 3,596 |
6,350,840 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Marital status | Never married | 16,000 | 0 | 1 | 14.9 | 1 | null | null | null | 3,353 |
4,458,711 | TZ2015DHS | 2,015 | DHS | TZ | Tanzania | CO_INUS_W_U12 | Women who used the internet in the past 12 months | COINUSWU12 | Marital status | Married or living together | 16,001 | 0 | 1 | 5.7 | 1 | null | null | null | 8,210 |
Communication — Africa (DHS Program) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help researchers examine disease burden, service delivery, risk factors, outcomes, and public-health program performance.
Dataset context from the existing Hugging Face card: Communication — Africa Source: DHS Program — The Demographic and Health Surveys Indicator category: Communication Publisher: ICF / DHS Program (funded by USAID) Coverage: 30 African countries · 2015–2024 · 82,242 rows Surveys: 49 completed DHS/MIS/AIS surveys · Indicators: 44 About The DHS Program conducts nationally representative household surveys across Africa and the developing world, providing data on population, health, HIV, nutrition, and malaria. This dataset… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-dhs-communication.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-dhs-communication |
| Sector | health |
| Topic tags | dhs, demographic-health-survey, communication, tabular |
| Modalities | tabular, text |
| Formats | parquet |
| Size category | 10K<n<100K |
| Countries | Africa-wide or source-defined African coverage |
| ISO3 coverage | not declared |
| Last modified on HF | 2026-05-07 03:47:41+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-dhs-communication")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: country, upstream_publisher.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: Electric Sheep Africa metadata inventory
- Publisher/source attribution: Public dataset metadata
- License: CC BY 4.0
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-dhs-communication
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_dhs_communication_2026,
title = {Communication — Africa (DHS Program) | Africa (Electric Sheep Africa metadata inventory)},
author = {Public dataset metadata},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-dhs-communication},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-dhs-communication}}
}
License
Released under CC BY 4.0.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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