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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 7 new columns ({'Democratic Republic of the Congo', 'Year', 'Gambia', 'United Republic of Tanzania', 'Egypt', "Côte d'Ivoire", 'Congo'}) and 1 missing columns ({'Date'}).

This happened while the csv dataset builder was generating data using

hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries/adolescent_birth_rate.csv (at revision 25721fdd06f0ed94ae2e5e5267b613de36f66c99), ['hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent-birth-rate.csv', 'hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent_birth_rate.csv', 'hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent_birth_rate__per_1000_women_.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Year: string
              Algeria: double
              Angola: double
              Benin: double
              Botswana: double
              Burkina Faso: double
              Burundi: double
              Cabo Verde: double
              Cameroon: double
              Central African Republic: double
              Chad: double
              Comoros: double
              Congo: double
              Côte d'Ivoire: double
              Democratic Republic of the Congo: double
              Djibouti: double
              Egypt: double
              Equatorial Guinea: double
              Eritrea: double
              Eswatini: double
              Ethiopia: double
              Gabon: double
              Gambia: double
              Ghana: double
              Guinea: double
              Guinea-Bissau: double
              Kenya: double
              Lesotho: double
              Liberia: double
              Libya: double
              Madagascar: double
              Malawi: double
              Mali: double
              Mauritania: double
              Mauritius: double
              Morocco: double
              Mozambique: double
              Namibia: double
              Niger: double
              Nigeria: double
              Rwanda: double
              Sao Tome and Principe: double
              Senegal: double
              Seychelles: double
              Sierra Leone: double
              Somalia: double
              South Africa: double
              South Sudan: double
              Sudan: double
              Togo: double
              Tunisia: double
              Uganda: double
              United Republic of Tanzania: double
              Zambia: double
              Zimbabwe: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 6818
              to
              {'Date': Value('string'), 'Algeria': Value('float64'), 'Angola': Value('float64'), 'Benin': Value('float64'), 'Botswana': Value('float64'), 'Burkina Faso': Value('float64'), 'Burundi': Value('float64'), 'Cabo Verde': Value('float64'), 'Cameroon': Value('float64'), 'Central African Republic': Value('float64'), 'Chad': Value('float64'), 'Comoros': Value('float64'), 'Djibouti': Value('float64'), 'Equatorial Guinea': Value('float64'), 'Eritrea': Value('float64'), 'Eswatini': Value('float64'), 'Ethiopia': Value('float64'), 'Gabon': Value('float64'), 'Ghana': Value('float64'), 'Guinea': Value('float64'), 'Guinea-Bissau': Value('float64'), 'Kenya': Value('float64'), 'Lesotho': Value('float64'), 'Liberia': Value('float64'), 'Libya': Value('float64'), 'Madagascar': Value('float64'), 'Malawi': Value('float64'), 'Mali': Value('float64'), 'Mauritania': Value('float64'), 'Mauritius': Value('float64'), 'Morocco': Value('float64'), 'Mozambique': Value('float64'), 'Namibia': Value('float64'), 'Niger': Value('float64'), 'Nigeria': Value('float64'), 'Rwanda': Value('float64'), 'Sao Tome and Principe': Value('float64'), 'Senegal': Value('float64'), 'Seychelles': Value('float64'), 'Sierra Leone': Value('float64'), 'Somalia': Value('float64'), 'South Africa': Value('float64'), 'South Sudan': Value('float64'), 'Sudan': Value('float64'), 'Togo': Value('float64'), 'Tunisia': Value('float64'), 'Uganda': Value('float64'), 'Zambia': Value('float64'), 'Zimbabwe': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 7 new columns ({'Democratic Republic of the Congo', 'Year', 'Gambia', 'United Republic of Tanzania', 'Egypt', "Côte d'Ivoire", 'Congo'}) and 1 missing columns ({'Date'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries/adolescent_birth_rate.csv (at revision 25721fdd06f0ed94ae2e5e5267b613de36f66c99), ['hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent-birth-rate.csv', 'hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent_birth_rate.csv', 'hf://datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries@25721fdd06f0ed94ae2e5e5267b613de36f66c99/adolescent_birth_rate__per_1000_women_.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Date
string
Algeria
float64
Angola
float64
Benin
float64
Botswana
float64
Burkina Faso
float64
Burundi
float64
Cabo Verde
float64
Cameroon
float64
Central African Republic
float64
Chad
float64
Comoros
float64
Djibouti
float64
Equatorial Guinea
float64
Eritrea
float64
Eswatini
float64
Ethiopia
float64
Gabon
float64
Ghana
float64
Guinea
float64
Guinea-Bissau
float64
Kenya
float64
Lesotho
float64
Liberia
float64
Libya
float64
Madagascar
float64
Malawi
float64
Mali
float64
Mauritania
float64
Mauritius
float64
Morocco
float64
Mozambique
float64
Namibia
float64
Niger
float64
Nigeria
float64
Rwanda
float64
Sao Tome and Principe
float64
Senegal
float64
Seychelles
float64
Sierra Leone
float64
Somalia
float64
South Africa
float64
South Sudan
float64
Sudan
float64
Togo
float64
Tunisia
float64
Uganda
float64
Zambia
float64
Zimbabwe
float64
2000-01-01
4.24
82.08
70.47
53.3
66.28
44.37
92
75.33
78.1
137.78
49.64
16.66
128
50.82
57.21
97.26
62.53
37.06
78.74
70.52
71.88
89
82.24
8.45
86.53
85.59
101.07
60.39
20.35
14.83
94.26
76.14
125.34
66.06
26.94
69.24
52.96
28
174.39
73.38
55
99.3
60.73
54.3
3.36
93.22
78.91
55.56
2001-01-01
4.24
82.08
70.47
53.3
66.28
44.37
92
75.33
78.1
137.78
49.64
16.66
128
50.82
57.21
97.26
62.53
37.06
78.74
70.52
71.88
67.11
82.24
5.25
86.53
85.59
101.07
60.39
16.9
14.28
94.26
76.14
125.34
66.06
26.94
69.24
52.96
30
157.76
73.38
55
99.3
60.73
54.3
3.36
93.22
78.91
55.56
2002-01-01
4.24
82.08
63.2
60.65
66.28
44.37
92
75.33
78.1
140.28
49.64
16.66
145.33
50.82
57.21
97.26
59.12
37.06
85.12
70.52
58.42
45.22
76.44
2.04
92.39
85.59
101.07
60.39
18.56
16.23
94.26
36.93
162.17
77.04
22.3
69.24
51.62
29
141.12
73.38
55
99.3
60.73
54.3
2.86
93.22
78.91
54.63
2003-01-01
4.36
81.46
69.01
68
78.2
44.37
92
78.05
78.1
104.54
66
15.54
162.67
50.65
56.59
74.29
55.7
37.72
87.38
76.68
60.22
45.8
166.55
3.06
87.7
90.25
99.13
59.44
18.54
16.21
95.36
42.58
199
86.96
20.99
69.24
52.55
30.5
87.04
69.74
35.47
95.12
60.73
54.3
2.82
88.21
80.31
51.91
2004-01-01
4.48
82.2
62.26
53.83
68.85
48.23
92
76.41
81.76
130.07
57.16
14.42
180
50.48
56.53
77.69
63.09
41.17
83.32
72.13
62.01
41.99
74.08
4.08
88.16
85.56
189.57
65.18
18.34
16.19
96.47
38.57
110.63
72.23
21.44
65.66
52.6
27
76.56
66.11
38.78
90.95
68.52
52.9
2.84
82.14
81.04
55.11
2005-01-01
4.6
86.28
60.62
39.67
71.66
42.75
94
73.25
85.43
116.49
48.32
13.3
179.4
50.32
56.88
81.09
62.79
40.92
87.54
67.57
58.27
41.42
88.35
5.1
87.83
89.17
104.66
63.22
17.55
16.17
96.59
39.84
114.91
76.29
21.48
60.78
51.88
30
83.56
75.12
41.9
86.78
58.9
51.58
2.9
84.57
81.77
61.62
2006-01-01
5.11
92.34
60.93
25.5
70.84
37.28
42.85
71.71
89.1
102.91
45.06
12.19
178.8
46.4
51.92
58.12
62.48
42.68
80.3
67.53
54.54
40.26
83.78
4.53
80.28
86.8
103.31
67.3
16.92
16.15
96.7
41.53
119.2
75.42
20.19
55.92
50.2
27.98
81.46
74.78
45.01
84.26
49.29
49.64
2.88
84.9
78.82
54.44
2007-01-01
9
95.98
55.46
24.32
69.76
35.16
42.89
73.61
92.3
116
41.81
11.07
178.2
42.47
50.7
52.2
62.18
41.99
78.17
66.54
52.65
46.17
83.26
3.96
84.4
89.7
103.07
71.38
17.69
16.13
84.54
40.38
123.48
63.26
19.97
69.1
51.06
30.24
78.86
73.8
44.93
81.76
70.14
48.48
2.86
80.92
78.92
51.8
2008-01-01
4.41
99.61
57.09
23.14
68.68
33.04
42.08
69.22
93.93
112.23
38.55
9.95
177.6
38.46
47.44
46.28
58.02
39.36
83.16
65.54
54.16
38.22
77.69
3.38
86.12
82.3
102.83
66.42
16.95
16.11
85.13
39.22
116.43
69.63
20.77
70.37
49.8
32.15
78.27
72.82
44.85
82.26
49.04
42.75
2.75
76.13
79.03
56.92
2009-01-01
9.6
98.48
54.5
21.97
65.35
43.96
36.01
66.4
95.55
108.45
37.44
20.6
177
38.46
45.04
48.96
60.6
36.72
85.08
62.08
55.66
38.82
80.83
2.81
89.39
78.04
100.07
51.36
16.32
16.16
85.72
38.08
109.38
72.29
20.52
71.65
48.18
33.84
77.68
75.83
44.76
82.26
51.7
37.02
2.87
74.14
75.39
58.1
2010-01-01
4.56
94.1
49.75
20.79
66.28
43.96
38.62
67.34
229
119.68
36.34
10.28
176
38.46
42.94
47.9
60.08
37.54
84.86
59.81
57.17
39.41
75.76
4.82
81.33
79.02
97.31
50.77
15.27
15.57
86.2
39.16
105.88
63.6
20.98
74.14
46.48
27.62
69.42
78.84
57.71
82.26
58.76
45
2.86
67.82
140.7
58.76
2011-01-01
4.78
89.71
50.25
19.61
67.2
42.64
36.04
77.06
166.65
113.84
36
10.54
176
38.46
42.52
46.86
58.22
60
77.47
57.54
54.28
34.94
76.17
6.83
80.96
73.32
92.14
59.1
15.38
14.98
89.5
40.25
137.94
74.64
24.31
65.45
45.11
35.72
68.33
81.85
70.65
82.26
52.86
43.85
3.2
70.48
75.02
59.42
2012-01-01
9.1
89.04
48.14
18.76
99.6
37.86
32.84
63.14
104.29
108
42.39
10.54
176
38.46
42.1
31.74
56.36
37.1
81.76
54.06
51.4
44.26
76.19
8.85
80.03
72.31
94
76.95
15.23
14.38
92.79
42.98
170
75.13
22.02
56.75
40.58
34
68
81.43
45.36
82.26
46.94
43.26
3.34
73.14
71.66
60.12
2013-01-01
9.8
88.37
55.27
20.22
132
35.05
31.1
62.44
102.65
92.68
48.79
10.54
176
38.46
44.13
42.06
54.5
39.34
82.6
56.17
51.03
47.48
75.79
10.86
79.1
69.6
95.86
52.19
13.59
13.79
96.08
48.21
162
82.31
22.72
46.72
41.09
30
64.14
81.01
42.15
82.26
44.54
50.85
3.76
70.8
71.5
56.48
2014-01-01
4.66
86.66
53.32
34.17
65.26
32.24
29.86
69.55
101.01
98.44
55.18
10.54
176
38.46
44.13
40.08
53.51
41.06
75.54
58.28
48.85
37.9
75.38
10.86
81.94
67.84
91.12
46.33
12.39
13.2
104.19
53.44
154
66.03
21.68
92
37.09
28.5
74.41
80.59
38.94
82.26
44.54
46.71
4.18
68.11
71.34
55.57
2015-01-01
9.7
86.66
55.02
48.12
70.83
29.48
28.84
66.84
99.36
104.21
61.57
10.54
176
38.46
44.13
40.17
52.51
39.16
68.68
52.8
46.12
68
73.81
10.86
80.25
70.24
88.82
49.92
11.85
12.61
93.72
58.68
146
62.56
20.64
54.46
36.75
29
58.16
72.91
36.2
82.26
44.54
42.56
4.4
66.78
70.41
55.82
2016-01-01
5.16
86.66
55
22.72
63.3
29.48
29.94
64.14
98.16
92.65
67.97
10.54
176
38.46
44.13
40.25
51.52
38.47
62.18
47.33
43.39
42.55
71.92
10.86
78.56
67.47
86.52
53.5
11.84
12.02
92.28
63.91
128.8
60.1
20.5
50.87
35.82
32
52.33
65.22
36.2
82.26
44.54
40.98
4.06
57.92
69.48
56.08
2017-01-01
4.9
86.66
50.38
25.08
58.1
29.48
28.7
62.57
96.96
81.1
74.36
10.54
176
38.46
44.13
36.48
51.35
37.34
64.97
43.04
40.65
45.62
70.04
10.86
78.84
64.71
85.16
50.94
12.25
11.43
5.53
63.91
111.6
55.39
17.72
47.28
35.82
31.5
53.98
58.42
36.2
82.26
44.54
40.98
3.53
56.26
68.74
54.53
2018-01-01
9.1
86.66
46.6
24.44
54.6
29.48
26.44
59.8
96.16
71.16
74.36
10.54
176
38.46
44.13
36.48
51.18
39.34
67.76
43.04
37.92
46.78
65.93
10.86
76.69
68.84
81.2
48.38
12.02
10.84
24.77
63.91
94.4
48.62
16.05
43.22
35.06
33
52.94
58.42
36.2
82.26
44.54
40.98
3.24
56.26
68.74
62.6
2019-01-01
11
86.66
42.82
25.27
51.12
29.48
23.32
57.03
96.16
71.16
74.36
10.54
176
38.46
44.13
36.48
51.42
37.06
70.55
43.04
26.06
47.93
65.28
10.86
75.04
68.84
77.24
47.96
12
10.84
44.02
63.91
77.2
41.85
15.96
43.22
35.84
36
52.94
58.42
36.2
82.26
44.54
40.98
3.1
56.26
68.74
70.68
2020-01-01
11
86.66
0.79
25.27
47.08
29.48
20.2
54.26
96.16
71.16
74.36
10.54
176
38.46
44.13
36.48
51.42
34.78
65.47
43.04
22.23
49.08
64.62
10.86
75.04
68.84
74.9
47.96
11.82
10.84
63.26
63.91
76.69
38.25
15.87
43.22
35.84
29
52.94
58.42
36.2
82.26
44.54
40.98
5.1
56.26
68.74
78.75
2021-01-01
11
86.66
0.79
25.27
47.08
29.48
20.2
2.36
96.16
71.16
74.36
10.54
176
38.46
44.13
36.48
51.42
32.5
65.47
43.04
22.23
49.08
68.44
10.86
75.04
68.84
74.9
47.96
10.54
10.84
82.5
63.91
76.69
38.25
15.78
43.22
35.84
32
52.94
58.42
36.2
82.26
44.54
40.98
2.02
56.26
68.74
86.82
2022-01-01
11
86.66
0.79
25.27
47.08
29.48
20.2
2.36
96.16
71.16
74.36
10.54
176
38.46
44.13
36.48
51.42
32.5
65.47
43.04
22.23
49.08
68.44
10.86
75.04
68.84
74.9
47.96
10.32
10.84
82.5
63.91
76.69
38.25
15.78
43.22
35.84
23.5
52.94
58.42
36.2
82.26
44.54
40.98
2.02
56.26
68.74
86.82
null
0.26
14.64
10.83
53.3
12.45
2.07
92
13.08
22.86
26.23
7.66
2.35
128
5.12
3.06
3.14
9.71
0.45
17.8
13.67
8.11
89
11.07
0
17.36
14.09
24.95
17.74
0.73
0.42
9.86
76.14
23.19
5.85
0.86
5.12
3.94
1
174.39
3.86
55
21.68
6.35
4.96
0
16.37
7.32
2.58
null
0.26
14.64
10.83
53.3
12.45
2.07
92
13.08
22.86
26.23
7.66
2.35
128
5.12
3.06
3.14
9.71
0.45
17.8
13.67
8.11
45.225
11.07
0
17.36
14.09
24.95
17.74
0.61
0.62
9.86
76.14
23.19
5.85
0.86
5.12
3.94
1
157.755
3.86
55
21.68
6.35
4.96
0
16.37
7.32
2.58
null
0.26
14.64
7.5
60.65
12.45
2.07
92
13.08
22.86
26.99
7.66
2.35
145.333333
5.12
3.06
3.14
9.445
0.45
17.7
13.67
2.66
1.45
4.32
0
21.72
14.09
24.95
17.74
0.64
0.1
9.86
3.28
111.095
13.97
0.41
5.12
3.53
1
141.12
3.86
55
21.68
6.35
4.96
0
16.37
7.32
3.36
null
0.24
12.03
10.78
68
4.89
2.07
92
12.92
22.86
21.99
66
2.58
162.666667
4.346667
2.61
5.65
9.18
2.19
20.34
14.28
3.095
0
166.55
1.7
17.71
8.68
24.76
17.93
0.53
0.126667
11.7
2.82
199
21.92
0.39
5.12
4.41
1
18.56
3.03
2.5
18.72
6.35
4.96
0
13.91
6.09
2.51
null
0.22
6.63
10.19
45.333333
10.99
3.14
92
14.17
23.516667
25.4
36.725
2.81
180
3.573333
2.51
7.385
9.13
1.97
20.8
16.305
3.53
0
11.09
3.4
11.33
3.11
189.57
15.84
0
0.153333
13.54
2.82
22.15
18.9
0.49
2.6
4.89
0
24.78
2.2
2
15.76
14.87
10.27
0
2.35
6.195
1.35
null
0.2
6.91
8.97
22.666667
10.26
2.705
94
14.77
24.173333
22.8
7.45
3.04
179.4
2.8
3
9.12
8.593333
1.68
19.49
18.33
3.145
1.07
10.29
5.1
19.19
2.41
20.87
16.61
0.53
0.18
11.15
1.88
20.433333
11.11
0.44
2.19
4.64
1
24.59
7.03
1.935
12.8
10.03
7.04
0
3.75
6.3
3.05
null
0.16
12.77
7.26
0
2.57
2.27
1.33
13.33
24.83
20.2
5.766667
2.6
178.8
2.06
0.94
5.58
8.056667
1.25
19.11
10.79
2.76
1.51
6.26
3.825
9.46
7.78
17
16.68
0.53
0.206667
8.76
1.87
18.716667
10.99
0.42
1.78
4.15
1.02
17.08
8.62
1.87
10.545
5.19
4.72
0
10.05
5.07
2.92
null
9
12.045
7.88
0.082
1.895
1.43
1.56
12.7
26.04
28.61
4.083333
2.16
178.2
1.32
1.53
5.54
7.52
3.67
16.39
14.12
2.35
0.46
5.13
2.55
16.17
11.78
18.11
16.75
0.84
0.233333
8.71
1.76
17
5.38
0.25
4.6
4.21
2.04
13.64
8.39
2.39
8.29
10.11
4.87
0
1.22
6.225
1.03
null
0.02
11.32
7.63
0.164
1.22
0.59
1.47
10.37
25.93
28.625
2.4
1.72
177.6
0.94
1.22
5.5
8.45
2.95
12.33
17.45
2.753333
1.19
7.63
1.275
17.55
7.51
19.22
13.35
0.76
0.26
7.23
1.65
12.925
9.95
0.19
3.865
3.4
0.78
13.065
8.16
2.91
6.42
3.47
4.12
0
0.84
7.38
1.76
null
9.6
6.1
4.88
0.246
0.6
1.94
0.45
6.05
25.82
28.64
2.015
20.6
177
0.94
1.46
3.36
6.48
2.23
17.96
6.87
3.156667
0.77
7.25
0
11.2
5.33
18.16
7.6
0.77
0.12
5.75
1.54
8.85
10.56
0
3.13
3.69
1.09
12.49
6.953333
3.43
6.42
2.22
3.37
0
2.59
3.25
1.61
null
0.03
8.21
5.5
0.328
3.745
1
0.7
10.94
229
17.59
1.63
0.11
176
0.94
1.37
2.315
6.52
4.26
15.45
6.665
3.56
0.35
4.78
2.715
15.03
3.09
17.1
10.79
0.47
0.107778
5.52
1.9
5.69
4.07
0
1.59
2.2
1.13
16.85
5.746667
37.04
6.42
5.89
2
0
1.16
140.7
1.32
null
0.05
10.32
2.73
0.41
6.89
0.76
1.14
9.44
127.475
18.39
1.73
0.1
176
0.94
1.505
1.27
5.96
60
8.53
6.46
2.815
1.13
3
5.43
16.74
1.89
12.28
11.1
0.5
0.095556
7.67
2.26
87.845
8.75
0.11
1.55
2.22
1.18
5.85
4.54
70.65
6.42
4.38
2.7
0
1.865
5.52
1.03
null
9.1
10.48
2.01
0.4
69.445
0.96
0.84
7.5
25.95
19.19
13.835
0.1
176
0.94
1.64
0.07
5.4
0.91
16.43
1.73
2.07
0.66
6.57
8.145
15.805
1.37
11.315
76.95
0.37
0.083333
9.82
3.95
170
9.93
0.35
1.51
2.16
1
10.87
4.44
1.04
6.42
2.87
2.09
0
2.57
2.09
0.56
null
9.8
10.64
4.12
0.31
132
0.835
0.78
6.27
23.64
5.99
25.94
0.1
176
0.94
1.21
1.02
4.84
2.37
11.28
2.69
3.44
0.95
6.23
10.86
14.87
2.61
10.35
12.98
0.62
0.071111
11.97
18.94
162
14.7
0.76
1.44
2
1
9.96
4.34
1.04
6.42
2.27
3.14
0
0.59
2.88
1
null
0.12
10.66
4.62
24.215
6.76
0.71
0.86
6.95
21.33
8.715
38.045
0.1
176
0.94
1.21
0.63
4.943333
5.47
12.51
3.65
2.03
0.55
5.89
10.86
15.11
2.99
7.86
8.44
0.6
0.058889
14.48
33.93
154
5.79
0.525
92
1.7
2
11.2
4.24
1.04
6.42
2.27
2.97
0
2.38
3.67
1.12
null
9.7
10.66
2.04
48.12
4.67
0.73
1.03
5.68
19.02
11.44
50.15
0.1
176
0.94
1.21
1.26
5.046667
1.91
6.72
2.77
1.685
68
4.74
10.86
12.505
2.85
8.205
10.235
0.56
0.046667
9.65
48.92
146
5.47
0.29
1.07
1.46
1
5.43
3.315
1.29
6.42
2.27
2.8
0
2
3.37
1.145
null
0.02
10.66
2
0.32
2.59
0.73
0.8
4.41
15.27
8.375
62.255
0.1
176
0.94
1.21
1.89
5.15
1.87
4.36
1.89
1.34
0.57
4.72
10.86
9.9
2.635
8.55
12.03
0.55
0.034444
4.43
63.91
110.7025
2.41
0
1.075
1.19
1
3.32
2.39
1.29
6.42
2.27
3
0
2.33
3.07
1.17
null
0
10.66
2.67
0.15
2.76
0.73
1.06
2.9
11.52
5.31
74.36
0.1
176
0.94
1.21
0.53
4.48
0.86
5.753333
1.63
0.995
0.48
4.7
10.86
6.92
2.42
6.76
10.28
0.7
0.022222
5.53
63.91
75.405
4.32
0.29
1.08
1.19
1
4.4
1.18
1.29
6.42
2.27
3
0
1.09
2.9
1.15
null
9.1
10.66
2.23
0.39
2.205
0.73
0.98
3.013333
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
3.81
0.67
7.146667
1.63
0.65
16.68
3.81
10.86
9.92
2.05
8.48
8.53
0.65
0.01
5.8975
63.91
40.1075
3.535
0.31
0.37
0.89
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
22.5675
null
11
10.66
1.79
0.32
1.65
0.73
0.7
3.126667
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
1.113333
8.54
1.63
0.79
32.88
4.45
10.86
7.08
2.05
10.2
6.27
0.77
0.01
6.265
63.91
4.81
2.75
0.283333
0.37
4.25
3
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
43.985
null
11
10.66
0.79
0.32
1.21
0.73
0.42
3.24
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
1.556667
3.32
1.63
0.66
49.08
5.09
10.86
7.08
2.05
5.04
6.27
0.53
0.01
6.6325
63.91
3.05
1.87
0.256667
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
5.1
1.09
2.9
65.4025
null
11
10.66
0.79
0.32
1.21
0.73
0.42
2.36
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
2
3.32
1.63
0.66
49.08
6.06
10.86
7.08
2.05
5.04
6.27
0.35
0.01
7
63.91
3.05
1.87
0.23
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
86.82
null
11
10.66
0.79
0.32
1.21
0.73
0.42
2.36
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
2
3.32
1.63
0.66
49.08
6.06
10.86
7.08
2.05
5.04
6.27
0.73
0.01
7
63.91
3.05
1.87
0.23
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
86.82
null
0.26
14.64
10.83
53.3
12.45
2.07
92
13.08
22.86
26.23
7.66
2.35
128
5.12
3.06
3.14
9.71
0.45
17.8
13.67
8.11
89
11.07
0
17.36
14.09
24.95
17.74
0.73
0.42
9.86
76.14
23.19
5.85
0.86
5.12
3.94
1
174.39
3.86
55
21.68
6.35
4.96
0
16.37
7.32
2.58
null
0.26
14.64
10.83
53.3
12.45
2.07
92
13.08
22.86
26.23
7.66
2.35
128
5.12
3.06
3.14
9.71
0.45
17.8
13.67
8.11
45.225
11.07
0
17.36
14.09
24.95
17.74
0.61
0.62
9.86
76.14
23.19
5.85
0.86
5.12
3.94
1
157.755
3.86
55
21.68
6.35
4.96
0
16.37
7.32
2.58
null
0.26
14.64
7.5
60.65
12.45
2.07
92
13.08
22.86
26.99
7.66
2.35
145.333333
5.12
3.06
3.14
9.445
0.45
17.7
13.67
2.66
1.45
4.32
0
21.72
14.09
24.95
17.74
0.64
0.1
9.86
3.28
111.095
13.97
0.41
5.12
3.53
1
141.12
3.86
55
21.68
6.35
4.96
0
16.37
7.32
3.36
null
0.24
12.03
10.78
68
4.89
2.07
92
12.92
22.86
21.99
66
2.58
162.666667
4.346667
2.61
5.65
9.18
2.19
20.34
14.28
3.095
0
166.55
1.7
17.71
8.68
24.76
17.93
0.53
0.126667
11.7
2.82
199
21.92
0.39
5.12
4.41
1
18.56
3.03
2.5
18.72
6.35
4.96
0
13.91
6.09
2.51
null
0.22
6.63
10.19
45.333333
10.99
3.14
92
14.17
23.516667
25.4
36.725
2.81
180
3.573333
2.51
7.385
9.13
1.97
20.8
16.305
3.53
0
11.09
3.4
11.33
3.11
189.57
15.84
0
0.153333
13.54
2.82
22.15
18.9
0.49
2.6
4.89
0
24.78
2.2
2
15.76
14.87
10.27
0
2.35
6.195
1.35
null
0.2
6.91
8.97
22.666667
10.26
2.705
94
14.77
24.173333
22.8
7.45
3.04
179.4
2.8
3
9.12
8.593333
1.68
19.49
18.33
3.145
1.07
10.29
5.1
19.19
2.41
20.87
16.61
0.53
0.18
11.15
1.88
20.433333
11.11
0.44
2.19
4.64
1
24.59
7.03
1.935
12.8
10.03
7.04
0
3.75
6.3
3.05
null
0.16
12.77
7.26
0
2.57
2.27
1.33
13.33
24.83
20.2
5.766667
2.6
178.8
2.06
0.94
5.58
8.056667
1.25
19.11
10.79
2.76
1.51
6.26
3.825
9.46
7.78
17
16.68
0.53
0.206667
8.76
1.87
18.716667
10.99
0.42
1.78
4.15
1.02
17.08
8.62
1.87
10.545
5.19
4.72
0
10.05
5.07
2.92
null
9
12.045
7.88
0.082
1.895
1.43
1.56
12.7
26.04
28.61
4.083333
2.16
178.2
1.32
1.53
5.54
7.52
3.67
16.39
14.12
2.35
0.46
5.13
2.55
16.17
11.78
18.11
16.75
0.84
0.233333
8.71
1.76
17
5.38
0.25
4.6
4.21
2.04
13.64
8.39
2.39
8.29
10.11
4.87
0
1.22
6.225
1.03
null
0.02
11.32
7.63
0.164
1.22
0.59
1.47
10.37
25.93
28.625
2.4
1.72
177.6
0.94
1.22
5.5
8.45
2.95
12.33
17.45
2.753333
1.19
7.63
1.275
17.55
7.51
19.22
13.35
0.76
0.26
7.23
1.65
12.925
9.95
0.19
3.865
3.4
0.78
13.065
8.16
2.91
6.42
3.47
4.12
0
0.84
7.38
1.76
null
9.6
6.1
4.88
0.246
0.6
1.94
0.45
6.05
25.82
28.64
2.015
20.6
177
0.94
1.46
3.36
6.48
2.23
17.96
6.87
3.156667
0.77
7.25
0
11.2
5.33
18.16
7.6
0.77
0.12
5.75
1.54
8.85
10.56
0
3.13
3.69
1.09
12.49
6.953333
3.43
6.42
2.22
3.37
0
2.59
3.25
1.61
null
0.03
8.21
5.5
0.328
3.745
1
0.7
10.94
229
17.59
1.63
0.11
176
0.94
1.37
2.315
6.52
4.26
15.45
6.665
3.56
0.35
4.78
2.715
15.03
3.09
17.1
10.79
0.47
0.107778
5.52
1.9
5.69
4.07
0
1.59
2.2
1.13
16.85
5.746667
37.04
6.42
5.89
2
0
1.16
140.7
1.32
null
0.05
10.32
2.73
0.41
6.89
0.76
1.14
9.44
127.475
18.39
1.73
0.1
176
0.94
1.505
1.27
5.96
60
8.53
6.46
2.815
1.13
3
5.43
16.74
1.89
12.28
11.1
0.5
0.095556
7.67
2.26
87.845
8.75
0.11
1.55
2.22
1.18
5.85
4.54
70.65
6.42
4.38
2.7
0
1.865
5.52
1.03
null
9.1
10.48
2.01
0.4
69.445
0.96
0.84
7.5
25.95
19.19
13.835
0.1
176
0.94
1.64
0.07
5.4
0.91
16.43
1.73
2.07
0.66
6.57
8.145
15.805
1.37
11.315
76.95
0.37
0.083333
9.82
3.95
170
9.93
0.35
1.51
2.16
1
10.87
4.44
1.04
6.42
2.87
2.09
0
2.57
2.09
0.56
null
9.8
10.64
4.12
0.31
132
0.835
0.78
6.27
23.64
5.99
25.94
0.1
176
0.94
1.21
1.02
4.84
2.37
11.28
2.69
3.44
0.95
6.23
10.86
14.87
2.61
10.35
12.98
0.62
0.071111
11.97
18.94
162
14.7
0.76
1.44
2
1
9.96
4.34
1.04
6.42
2.27
3.14
0
0.59
2.88
1
null
0.12
10.66
4.62
24.215
6.76
0.71
0.86
6.95
21.33
8.715
38.045
0.1
176
0.94
1.21
0.63
4.943333
5.47
12.51
3.65
2.03
0.55
5.89
10.86
15.11
2.99
7.86
8.44
0.6
0.058889
14.48
33.93
154
5.79
0.525
92
1.7
2
11.2
4.24
1.04
6.42
2.27
2.97
0
2.38
3.67
1.12
null
9.7
10.66
2.04
48.12
4.67
0.73
1.03
5.68
19.02
11.44
50.15
0.1
176
0.94
1.21
1.26
5.046667
1.91
6.72
2.77
1.685
68
4.74
10.86
12.505
2.85
8.205
10.235
0.56
0.046667
9.65
48.92
146
5.47
0.29
1.07
1.46
1
5.43
3.315
1.29
6.42
2.27
2.8
0
2
3.37
1.145
null
0.02
10.66
2
0.32
2.59
0.73
0.8
4.41
15.27
8.375
62.255
0.1
176
0.94
1.21
1.89
5.15
1.87
4.36
1.89
1.34
0.57
4.72
10.86
9.9
2.635
8.55
12.03
0.55
0.034444
4.43
63.91
110.7025
2.41
0
1.075
1.19
1
3.32
2.39
1.29
6.42
2.27
3
0
2.33
3.07
1.17
null
0
10.66
2.67
0.15
2.76
0.73
1.06
2.9
11.52
5.31
74.36
0.1
176
0.94
1.21
0.53
4.48
0.86
5.753333
1.63
0.995
0.48
4.7
10.86
6.92
2.42
6.76
10.28
0.7
0.022222
5.53
63.91
75.405
4.32
0.29
1.08
1.19
1
4.4
1.18
1.29
6.42
2.27
3
0
1.09
2.9
1.15
null
9.1
10.66
2.23
0.39
2.205
0.73
0.98
3.013333
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
3.81
0.67
7.146667
1.63
0.65
16.68
3.81
10.86
9.92
2.05
8.48
8.53
0.65
0.01
5.8975
63.91
40.1075
3.535
0.31
0.37
0.89
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
22.5675
null
11
10.66
1.79
0.32
1.65
0.73
0.7
3.126667
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
1.113333
8.54
1.63
0.79
32.88
4.45
10.86
7.08
2.05
10.2
6.27
0.77
0.01
6.265
63.91
4.81
2.75
0.283333
0.37
4.25
3
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
43.985
null
11
10.66
0.79
0.32
1.21
0.73
0.42
3.24
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
1.556667
3.32
1.63
0.66
49.08
5.09
10.86
7.08
2.05
5.04
6.27
0.53
0.01
6.6325
63.91
3.05
1.87
0.256667
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
5.1
1.09
2.9
65.4025
null
11
10.66
0.79
0.32
1.21
0.73
0.42
2.36
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
2
3.32
1.63
0.66
49.08
6.06
10.86
7.08
2.05
5.04
6.27
0.35
0.01
7
63.91
3.05
1.87
0.23
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
86.82
null
11
10.66
0.79
0.32
1.21
0.73
0.42
2.36
7.97
3.87
74.36
0.1
176
0.94
1.21
0.53
2.78
2
3.32
1.63
0.66
49.08
6.06
10.86
7.08
2.05
5.04
6.27
0.73
0.01
7
63.91
3.05
1.87
0.23
0.37
4.25
1
3.94
1.18
1.29
6.42
2.27
3
0
1.09
2.9
86.82

Adolescent Birth Rate for African Countries | Africa (World Health Organization)

Size category: n<1K - Formats: not declared - Sector: health - Engineered by Electric Sheep Africa

size sector downloads license

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: Adolescent birth rate (per 1000 women) Dataset Description This dataset provides country-level data for the indicator "3.7.2 Adolescent birth rate (per 1000 women)" across African nations, sourced from the World Health Organization's (WHO) data portal on Sustainable Development Goals (SDGs). The data is presented in a wide format, where each row represents a date (yearly) and each column represents a country. Values have been interpolated to fill missing years. Original… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries
Sector health
Topic tags biology, medical
Modalities not declared
Formats not declared
Size category n<1K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2025-06-25 23:46:19+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/Adolescent-Birth-Rate-for-African-Countries")
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, modality, format, license, language.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

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_adolescent_birth_rate_for_african_countries_2026,
  title        = {Adolescent Birth Rate for African Countries | Africa (World Health Organization)},
  author       = {WHO public data},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/Adolescent-Birth-Rate-for-African-Countries}}
}

License

Released under Source-specific or other license.

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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