indicator_code stringclasses 1
value | country_iso3 stringclasses 47
values | who_region stringclasses 1
value | year int64 2k 2.02k | dim1_type stringclasses 1
value | dim1 stringclasses 1
value | dim2_type stringclasses 1
value | dim2 stringclasses 2
values | value_numeric float64 0 254 | value_low null | value_high null | value_display stringlengths 1 5 | last_updated stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
MDG_0000000003 | ETH | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.626911 | null | null | 0.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MOZ | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 8.756031 | null | null | 8.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MUS | AFR | 2,010 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.485558 | null | null | 0.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MWI | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 7.512672 | null | null | 7.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CIV | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 120.303864 | null | null | 120.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SEN | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 72.038773 | null | null | 72.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | TZA | AFR | 2,004 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 130.59903 | null | null | 130.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SEN | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 72.480591 | null | null | 72.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ETH | AFR | 2,002 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 3.142167 | null | null | 3.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 153.980103 | null | null | 154.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZMB | AFR | 2,005 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 6.3019 | null | null | 6.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NGA | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 21.917072 | null | null | 21.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | BFA | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 123.755913 | null | null | 123.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GNB | AFR | 2,017 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 84.462334 | null | null | 84.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | STP | AFR | 2,013 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.436715 | null | null | 1.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,009 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 17.958332 | null | null | 18.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CIV | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 120.72506 | null | null | 120.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GHA | AFR | 2,018 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 78.017853 | null | null | 78.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 147.076935 | null | null | 147.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GHA | AFR | 2,002 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 73.66642 | null | null | 73.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | LSO | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.45537 | null | null | 0.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NGA | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 5.474481 | null | null | 5.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GAB | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 8.452437 | null | null | 8.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GHA | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 80.308334 | null | null | 80.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,010 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 15.446062 | null | null | 15.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.195465 | null | null | 1.2 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 12.513864 | null | null | 12.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MWI | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 8.680347 | null | null | 8.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 141.487198 | null | null | 141.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SYC | AFR | 2,009 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 66.867638 | null | null | 66.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SEN | AFR | 2,017 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 70.449608 | null | null | 70.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | LSO | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.13484 | null | null | 1.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | LSO | AFR | 2,004 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 83.984863 | null | null | 84.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SEN | AFR | 2,010 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 90.76709 | null | null | 90.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CIV | AFR | 2,020 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 95.988129 | null | null | 96.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SSD | AFR | 2,002 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 176.911179 | null | null | 176.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MOZ | AFR | 2,002 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 178.654739 | null | null | 178.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SLE | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 137.628174 | null | null | 137.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,018 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 65.471298 | null | null | 65.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SWZ | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.635521 | null | null | 1.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NGA | AFR | 2,019 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 2.750451 | null | null | 2.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | BFA | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.217246 | null | null | 1.2 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SLE | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 11.202815 | null | null | 11.2 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | RWA | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.11372 | null | null | 0.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MUS | AFR | 2,022 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.744515 | null | null | 0.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZMB | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 135.900864 | null | null | 135.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZMB | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 5.071466 | null | null | 5.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MLI | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 24.762999 | null | null | 24.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.148337 | null | null | 1.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 68.682381 | null | null | 68.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZAF | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.035862 | null | null | 1.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GAB | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 97.891167 | null | null | 97.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | COM | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 74.699455 | null | null | 74.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | BEN | AFR | 2,010 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 94 | null | null | 94.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZAF | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 88.149345 | null | null | 88.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ETH | AFR | 2,009 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 94.553391 | null | null | 94.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | TGO | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 78.966515 | null | null | 79.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MUS | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.512681 | null | null | 0.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NAM | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 2.264406 | null | null | 2.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SEN | AFR | 2,005 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 4.640753 | null | null | 4.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | KEN | AFR | 2,018 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.343889 | null | null | 1.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | RWA | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.292385 | null | null | 0.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GHA | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 73.254555 | null | null | 73.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GAB | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 7.520197 | null | null | 7.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NGA | AFR | 2,005 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 11.114876 | null | null | 11.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | UGA | AFR | 2,013 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.589224 | null | null | 0.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,009 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 152.208221 | null | null | 152.2 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SYC | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 2 | null | null | 2.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NAM | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 63.914902 | null | null | 63.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZWE | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.165601 | null | null | 1.2 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | BFA | AFR | 2,004 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 126.708847 | null | null | 126.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CAF | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 133.344849 | null | null | 133.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MRT | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 125.997749 | null | null | 126.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GIN | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 19.107601 | null | null | 19.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CIV | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 4.951 | null | null | 5.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | RWA | AFR | 2,005 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.442784 | null | null | 0.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | COM | AFR | 2,002 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 7.660958 | null | null | 7.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | LSO | AFR | 2,017 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 90.7705 | null | null | 90.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MWI | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.888143 | null | null | 1.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | STP | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 133.59372 | null | null | 133.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MDG | AFR | 2,011 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 16.74299 | null | null | 16.7 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ERI | AFR | 2,008 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 75.973183 | null | null | 76.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CAF | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 182.641769 | null | null | 182.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,016 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.894745 | null | null | 0.9 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | SYC | AFR | 2,001 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1 | null | null | 1.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZWE | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 0.559319 | null | null | 0.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CAF | AFR | 2,017 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 11.522906 | null | null | 11.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | MDG | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 9.456204 | null | null | 9.5 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NAM | AFR | 2,020 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 40.798016 | null | null | 40.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GMB | AFR | 2,018 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 64.784584 | null | null | 64.8 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CAF | AFR | 2,015 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 19.020761 | null | null | 19.0 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZWE | AFR | 2,014 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.119834 | null | null | 1.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | ZMB | AFR | 2,003 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 6.088158 | null | null | 6.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | COD | AFR | 2,006 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 9.384544 | null | null | 9.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | LBR | AFR | 2,005 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 10.288589 | null | null | 10.3 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | CPV | AFR | 2,007 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.595307 | null | null | 1.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | DZA | AFR | 2,018 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 9.1 | null | null | 9.1 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | TCD | AFR | 2,010 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 17.588417 | null | null | 17.6 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | GNB | AFR | 2,012 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS15-19 | 106.389481 | null | null | 106.4 | 2025-05-06T16:35:10.26+02:00 |
MDG_0000000003 | NAM | AFR | 2,009 | SEX | SEX_FMLE | AGEGROUP | AGEGROUP_YEARS10-14 | 1.54498 | null | null | 1.5 | 2025-05-06T16:35:10.26+02:00 |
Africa — WHO GHO: Adolescent birth rate (per 1000 women)
Indicator code: MDG_0000000003
HuggingFace slug: electricsheepafrica/africa-who-adolescent-birth-rate
Source: WHO Global Health Observatory
License: CC BY 4.0 — WHO Open Data
Dataset Description
This dataset contains country-level observations for the WHO GHO indicator "Adolescent birth rate (per 1000 women)" (MDG_0000000003) across African nations, spanning 2000–2023. It is part of the Electric Sheep Africa collection — a unified, ML-ready repository of African data.
Data is sourced directly from the WHO Global Health Observatory OData API and repackaged as Parquet files with a consistent schema. All values are drawn from NumericValue (the float-precision field), not the display string. Confidence interval bounds (value_low, value_high) are included where available.
Coverage
| Countries | 47 African nations |
| Years | 2000 – 2023 |
| Total rows | 1,279 |
| Region filter | WHO AFRO (ParentLocationCode = 'AFR') |
Countries included: AGO, BDI, BEN, BFA, BWA, CAF, CIV, CMR, COD, COG, COM, CPV, DZA, ERI, ETH, GAB, GHA, GIN, GMB, GNB … and 27 more
Sub-dimensions
- SEX: SEX_FMLE
When an indicator is stratified (e.g., by sex or age group), each unique combination of country × year × dimension produces a separate row. Filter on dim1 / dim2 for the stratum you need, or aggregate across strata.
Schema
| Column | Type | Description |
|---|---|---|
indicator_code |
string | GHO indicator code (e.g., MDG_0000000003) |
country_iso3 |
string | ISO 3166-1 alpha-3 country code |
who_region |
string | WHO region code (always AFR here) |
year |
int | Observation year |
value_numeric |
float | Point estimate (primary ML target) |
value_low |
float | Lower confidence bound (if available) |
value_high |
float | Upper confidence bound (if available) |
value_display |
string | Formatted display string, e.g. "58.3 [57.7–59.0]" |
dim1_type |
string | Dimension 1 type, e.g. SEX, RESIDENCEAREATYPE |
dim1 |
string | Dimension 1 value, e.g. SEX_BTSX, RURAL |
dim2_type |
string | Dimension 2 type (if present) |
dim2 |
string | Dimension 2 value (if present) |
last_updated |
string | WHO data last-updated timestamp |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-who-adolescent-birth-rate")
df = ds["train"].to_pandas()
# Both-sexes, national level only
national = df[df.get("dim1", "").str.endswith("_BTSX") | df.get("dim1", pd.Series()).isna()]
# Time series for one country
kenya = df[df["country_iso3"] == "KEN"].sort_values("year")
Citation
@misc{who_gho_mdg_0000000003,
title = {WHO Global Health Observatory: Adolescent birth rate (per 1000 women)},
author = {World Health Organization},
year = {2023},
url = {https://www.who.int/data/gho/data/indicators/indicator-details/GHO/MDG_0000000003},
note = {Repackaged by Electric Sheep Africa}
}
Repackaged by Electric Sheep Africa from WHO GHO open data. Original data © World Health Organization, licensed CC BY 4.0.
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