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indicator_code
stringclasses
1 value
country_iso3
stringclasses
47 values
who_region
stringclasses
1 value
year
int64
1.96k
2.02k
dim1_type
stringclasses
1 value
dim1
stringclasses
1 value
dim2_type
stringclasses
1 value
dim2
stringclasses
1 value
value_numeric
float64
12
276k
value_low
float64
11
238k
value_high
float64
14
380k
value_display
stringlengths
10
25
last_updated
stringclasses
1 value
CM_03
GHA
AFR
1,972
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
25,673
23,618
28,120
25 673 [23 618-28 120]
2025-04-15T16:15:21.28+02:00
CM_03
ZWE
AFR
1,991
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
8,535
7,662
9,472
8535 [7662-9472]
2025-04-15T16:15:21.28+02:00
CM_03
CPV
AFR
1,996
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
261
221
300
261 [221-300]
2025-04-15T16:15:21.28+02:00
CM_03
ZWE
AFR
2,022
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
11,344
7,072
17,827
11 344 [7072-17 827]
2025-04-15T16:15:21.28+02:00
CM_03
CPV
AFR
1,990
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
279
241
319
279 [241-319]
2025-04-15T16:15:21.28+02:00
CM_03
GIN
AFR
1,994
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
19,109
17,057
21,517
19 109 [17 057-21 517]
2025-04-15T16:15:21.28+02:00
CM_03
CIV
AFR
2,003
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
32,221
28,853
35,766
32 221 [28 853-35 766]
2025-04-15T16:15:21.28+02:00
CM_03
MUS
AFR
2,015
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
119
110
127
119 [110-127]
2025-04-15T16:15:21.28+02:00
CM_03
SWZ
AFR
2,005
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
858
743
990
858 [743-990]
2025-04-15T16:15:21.28+02:00
CM_03
BDI
AFR
1,975
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
8,858
7,590
10,340
8858 [7590-10 340]
2025-04-15T16:15:21.28+02:00
CM_03
TZA
AFR
2,023
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
48,216
36,677
63,210
48 216 [36 677-63 210]
2025-04-15T16:15:21.28+02:00
CM_03
GNQ
AFR
2,008
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,601
1,198
2,069
1601 [1198-2069]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
1,965
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,385
2,074
2,732
2385 [2074-2732]
2025-04-15T16:15:21.28+02:00
CM_03
BFA
AFR
2,016
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
20,965
14,630
28,807
20 965 [14 630-28 807]
2025-04-15T16:15:21.28+02:00
CM_03
MWI
AFR
1,973
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
17,382
15,201
19,979
17 382 [15 201-19 979]
2025-04-15T16:15:21.28+02:00
CM_03
BFA
AFR
1,987
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
20,033
17,798
22,519
20 033 [17 798-22 519]
2025-04-15T16:15:21.28+02:00
CM_03
CMR
AFR
1,989
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
19,574
17,603
21,799
19 574 [17 603-21 799]
2025-04-15T16:15:21.28+02:00
CM_03
GIN
AFR
2,001
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
15,525
13,785
17,399
15 525 [13 785-17 399]
2025-04-15T16:15:21.28+02:00
CM_03
BEN
AFR
1,987
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
10,623
9,609
11,743
10 623 [9609-11 743]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
1,986
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,569
5,620
7,698
6569 [5620-7698]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
2,023
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,710
2,607
5,287
3710 [2607-5287]
2025-04-15T16:15:21.28+02:00
CM_03
KEN
AFR
1,971
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
23,632
21,034
26,390
23 632 [21 034-26 390]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
1,970
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,563
2,209
2,971
2563 [2209-2971]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
1,981
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,455
2,051
2,897
2455 [2051-2897]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
1,998
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,944
3,520
4,425
3944 [3520-4425]
2025-04-15T16:15:21.28+02:00
CM_03
SYC
AFR
2,016
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
16
14
18
16 [14-18]
2025-04-15T16:15:21.28+02:00
CM_03
TCD
AFR
2,006
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
21,167
18,310
24,276
21 167 [18 310-24 276]
2025-04-15T16:15:21.28+02:00
CM_03
CPV
AFR
2,001
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
209
182
237
209 [182-237]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
1,978
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
5,663
4,776
6,691
5663 [4776-6691]
2025-04-15T16:15:21.28+02:00
CM_03
MWI
AFR
2,005
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
16,708
15,127
18,349
16 708 [15 127-18 349]
2025-04-15T16:15:21.28+02:00
CM_03
TGO
AFR
1,985
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,981
6,194
7,881
6981 [6194-7881]
2025-04-15T16:15:21.28+02:00
CM_03
CIV
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
30,314
27,201
33,713
30 314 [27 201-33 713]
2025-04-15T16:15:21.28+02:00
CM_03
ETH
AFR
1,987
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
135,017
121,175
149,806
135 017 [121 175-149 806]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
1,989
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,595
3,175
4,082
3595 [3175-4082]
2025-04-15T16:15:21.28+02:00
CM_03
GIN
AFR
2,010
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
14,864
13,059
16,873
14 864 [13 059-16 873]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
1,989
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,750
5,794
7,928
6750 [5794-7928]
2025-04-15T16:15:21.28+02:00
CM_03
ETH
AFR
1,986
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
136,148
122,182
151,070
136 148 [122 182-151 070]
2025-04-15T16:15:21.28+02:00
CM_03
CPV
AFR
2,020
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
63
58
68
63 [58-68]
2025-04-15T16:15:21.28+02:00
CM_03
MUS
AFR
2,009
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
145
135
155
145 [135-155]
2025-04-15T16:15:21.28+02:00
CM_03
CMR
AFR
1,992
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
20,655
18,598
22,872
20 655 [18 598-22 872]
2025-04-15T16:15:21.28+02:00
CM_03
NER
AFR
2,019
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
34,680
28,192
43,198
34 680 [28 192-43 198]
2025-04-15T16:15:21.28+02:00
CM_03
GHA
AFR
1,996
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
24,609
22,534
26,663
24 609 [22 534-26 663]
2025-04-15T16:15:21.28+02:00
CM_03
MUS
AFR
1,975
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
562
532
593
562 [532-593]
2025-04-15T16:15:21.28+02:00
CM_03
ERI
AFR
1,984
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,304
2,888
3,755
3304 [2888-3755]
2025-04-15T16:15:21.28+02:00
CM_03
BDI
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
9,776
8,406
11,270
9776 [8406-11 270]
2025-04-15T16:15:21.28+02:00
CM_03
NER
AFR
1,972
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
16,682
14,279
19,475
16 682 [14 279-19 475]
2025-04-15T16:15:21.28+02:00
CM_03
GHA
AFR
2,022
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
19,084
15,764
22,927
19 084 [15 764-22 927]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
2,012
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,791
3,335
4,298
3791 [3335-4298]
2025-04-15T16:15:21.28+02:00
CM_03
NAM
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,449
1,252
1,680
1449 [1252-1680]
2025-04-15T16:15:21.28+02:00
CM_03
BWA
AFR
1,985
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,254
1,058
1,486
1254 [1058-1486]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
2,017
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,834
3,235
4,550
3834 [3235-4550]
2025-04-15T16:15:21.28+02:00
CM_03
ZWE
AFR
2,008
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
14,160
12,624
15,831
14 160 [12 624-15 831]
2025-04-15T16:15:21.28+02:00
CM_03
MOZ
AFR
2,003
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
30,305
26,973
33,726
30 305 [26 973-33 726]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
1,996
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,259
2,035
2,501
2259 [2035-2501]
2025-04-15T16:15:21.28+02:00
CM_03
GNB
AFR
2,002
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,851
2,422
3,315
2851 [2422-3315]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
1,992
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,395
2,122
2,697
2395 [2122-2697]
2025-04-15T16:15:21.28+02:00
CM_03
CIV
AFR
2,011
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
32,725
29,117
36,671
32 725 [29 117-36 671]
2025-04-15T16:15:21.28+02:00
CM_03
TGO
AFR
2,019
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,930
5,360
8,928
6930 [5360-8928]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
1,974
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,259
2,872
3,696
3259 [2872-3696]
2025-04-15T16:15:21.28+02:00
CM_03
UGA
AFR
2,013
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
33,449
29,026
38,717
33 449 [29 026-38 717]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
2,000
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,918
5,912
8,020
6918 [5912-8020]
2025-04-15T16:15:21.28+02:00
CM_03
MOZ
AFR
1,990
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
37,340
32,950
42,289
37 340 [32 950-42 289]
2025-04-15T16:15:21.28+02:00
CM_03
BEN
AFR
1,966
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
8,185
7,232
9,338
8185 [7232-9338]
2025-04-15T16:15:21.28+02:00
CM_03
NAM
AFR
1,977
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,317
1,090
1,579
1317 [1090-1579]
2025-04-15T16:15:21.28+02:00
CM_03
SEN
AFR
1,977
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
13,184
11,845
14,595
13 184 [11 845-14 595]
2025-04-15T16:15:21.28+02:00
CM_03
COG
AFR
2,018
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,507
2,127
5,728
3507 [2127-5728]
2025-04-15T16:15:21.28+02:00
CM_03
LBR
AFR
1,992
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
5,431
4,676
6,273
5431 [4676-6273]
2025-04-15T16:15:21.28+02:00
CM_03
LSO
AFR
2,023
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,601
1,139
2,189
1601 [1139-2189]
2025-04-15T16:15:21.28+02:00
CM_03
TGO
AFR
2,002
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
7,159
6,369
8,013
7159 [6369-8013]
2025-04-15T16:15:21.28+02:00
CM_03
BFA
AFR
1,998
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
21,453
18,902
24,309
21 453 [18 902-24 309]
2025-04-15T16:15:21.28+02:00
CM_03
MDG
AFR
2,012
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
20,170
17,820
22,657
20 170 [17 820-22 657]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
1,980
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,618
3,230
4,073
3618 [3230-4073]
2025-04-15T16:15:21.28+02:00
CM_03
MDG
AFR
1,996
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
22,217
20,258
24,572
22 217 [20 258-24 572]
2025-04-15T16:15:21.28+02:00
CM_03
SYC
AFR
2,008
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
15
13
17
15 [13-17]
2025-04-15T16:15:21.28+02:00
CM_03
COG
AFR
2,000
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,491
3,020
4,030
3491 [3020-4030]
2025-04-15T16:15:21.28+02:00
CM_03
KEN
AFR
2,005
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
34,455
31,206
38,031
34 455 [31 206-38 031]
2025-04-15T16:15:21.28+02:00
CM_03
KEN
AFR
1,964
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
21,090
18,579
23,764
21 090 [18 579-23 764]
2025-04-15T16:15:21.28+02:00
CM_03
MLI
AFR
1,994
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
28,205
25,343
31,363
28 205 [25 343-31 363]
2025-04-15T16:15:21.28+02:00
CM_03
DZA
AFR
2,015
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
15,659
14,626
16,767
15 659 [14 626-16 767]
2025-04-15T16:15:21.28+02:00
CM_03
MRT
AFR
1,982
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
3,731
3,317
4,243
3731 [3317-4243]
2025-04-15T16:15:21.28+02:00
CM_03
NAM
AFR
1,981
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,299
1,100
1,525
1299 [1100-1525]
2025-04-15T16:15:21.28+02:00
CM_03
ERI
AFR
1,998
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
2,453
2,153
2,771
2453 [2153-2771]
2025-04-15T16:15:21.28+02:00
CM_03
MLI
AFR
1,973
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
31,918
28,121
36,263
31 918 [28 121-36 263]
2025-04-15T16:15:21.28+02:00
CM_03
NER
AFR
2,012
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
29,746
25,651
34,371
29 746 [25 651-34 371]
2025-04-15T16:15:21.28+02:00
CM_03
TZA
AFR
2,022
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
48,609
37,985
62,324
48 609 [37 985-62 324]
2025-04-15T16:15:21.28+02:00
CM_03
AGO
AFR
2,013
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
36,780
20,481
59,433
36 780 [20 481-59 433]
2025-04-15T16:15:21.28+02:00
CM_03
SWZ
AFR
1,990
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
776
651
919
776 [651-919]
2025-04-15T16:15:21.28+02:00
CM_03
GHA
AFR
2,002
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
24,955
22,882
27,059
24 955 [22 882-27 059]
2025-04-15T16:15:21.28+02:00
CM_03
LBR
AFR
1,967
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,516
5,611
7,597
6516 [5611-7597]
2025-04-15T16:15:21.28+02:00
CM_03
ZMB
AFR
1,972
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
8,002
6,981
9,089
8002 [6981-9089]
2025-04-15T16:15:21.28+02:00
CM_03
NAM
AFR
1,986
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,326
1,136
1,536
1326 [1136-1536]
2025-04-15T16:15:21.28+02:00
CM_03
TGO
AFR
1,984
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,903
6,129
7,799
6903 [6129-7799]
2025-04-15T16:15:21.28+02:00
CM_03
SWZ
AFR
1,999
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
863
754
991
863 [754-991]
2025-04-15T16:15:21.28+02:00
CM_03
LBR
AFR
1,999
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,196
5,480
6,981
6196 [5480-6981]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
2,014
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
7,355
5,988
8,874
7355 [5988-8874]
2025-04-15T16:15:21.28+02:00
CM_03
CIV
AFR
1,988
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
25,903
23,338
28,686
25 903 [23 338-28 686]
2025-04-15T16:15:21.28+02:00
CM_03
COM
AFR
1,987
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
1,045
872
1,249
1045 [872-1249]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
2,009
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
8,435
7,211
9,723
8435 [7211-9723]
2025-04-15T16:15:21.28+02:00
CM_03
CAF
AFR
1,990
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
6,799
5,850
7,982
6799 [5850-7982]
2025-04-15T16:15:21.28+02:00
CM_03
MLI
AFR
1,976
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_DAYS0-27
32,515
28,778
36,805
32 515 [28 778-36 805]
2025-04-15T16:15:21.28+02:00
End of preview. Expand in Data Studio

Africa — WHO GHO: Number of neonatal deaths

Indicator code: CM_03 HuggingFace slug: electricsheepafrica/africa-who-number-of-neonatal-deaths 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 "Number of neonatal deaths" (CM_03) across African nations, spanning 1955–2023. 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 1955 – 2023
Total rows 2,414
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_BTSX

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., CM_03)
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-number-of-neonatal-deaths")
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_cm_03,
  title     = {WHO Global Health Observatory: Number of neonatal deaths},
  author    = {World Health Organization},
  year      = {2023},
  url       = {https://www.who.int/data/gho/data/indicators/indicator-details/GHO/CM_03},
  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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