The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 13 new columns ({'n_Killed', 'n_Not vaccinated', 'n_livestock', 'suspected_cases', 'dog_pop', 'n_Vaccinated', 'vax_coverage', 'n_wildlife', 'n_Known', 'Ward', 'n_Domestic dog', 'ward_mnth_yr', 'n_Unknown'}) and 8 missing columns ({'NO_OF_PEOPLE_BITTEN_REPEAT_COUNT', 'symptoms', 'ASSESSMENT_DECISION', 'reason_for_report', 'LFT_result', 'animal_environment', 'victim_environment', 'ANIMAL_OUTCOME'}).
This happened while the csv dataset builder was generating data using
hf://datasets/fair-forward/rabies_diagnosis_outbreak_prediction/encoded_outbreak.csv (at revision e958c172df344720054b781f6de21b55894c926c)
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Unnamed: 0: int64
ward_mnth_yr: string
n_livestock: int64
n_Domestic dog: int64
n_wildlife: int64
n_Unknown: int64
n_Known: int64
n_Not vaccinated: int64
n_Vaccinated: int64
n_Killed: int64
suspected_cases: int64
Ward: string
dog_pop: double
vax_coverage: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1928
to
{'Unnamed: 0': Value(dtype='int64', id=None), 'NO_OF_PEOPLE_BITTEN_REPEAT_COUNT': Value(dtype='int64', id=None), 'LFT_result': Value(dtype='int64', id=None), 'reason_for_report': Value(dtype='int64', id=None), 'symptoms': Value(dtype='int64', id=None), 'victim_environment': Value(dtype='int64', id=None), 'ANIMAL_OUTCOME': Value(dtype='int64', id=None), 'animal_environment': Value(dtype='int64', id=None), 'ASSESSMENT_DECISION': Value(dtype='int64', id=None)}
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 1321, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
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 13 new columns ({'n_Killed', 'n_Not vaccinated', 'n_livestock', 'suspected_cases', 'dog_pop', 'n_Vaccinated', 'vax_coverage', 'n_wildlife', 'n_Known', 'Ward', 'n_Domestic dog', 'ward_mnth_yr', 'n_Unknown'}) and 8 missing columns ({'NO_OF_PEOPLE_BITTEN_REPEAT_COUNT', 'symptoms', 'ASSESSMENT_DECISION', 'reason_for_report', 'LFT_result', 'animal_environment', 'victim_environment', 'ANIMAL_OUTCOME'}).
This happened while the csv dataset builder was generating data using
hf://datasets/fair-forward/rabies_diagnosis_outbreak_prediction/encoded_outbreak.csv (at revision e958c172df344720054b781f6de21b55894c926c)
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? Open a discussion for direct support.
Unnamed: 0
int64 | NO_OF_PEOPLE_BITTEN_REPEAT_COUNT
int64 | LFT_result
int64 | reason_for_report
int64 | symptoms
int64 | victim_environment
int64 | ANIMAL_OUTCOME
int64 | animal_environment
int64 | ASSESSMENT_DECISION
int64 |
|---|---|---|---|---|---|---|---|---|
0 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 |
1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
5 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
6 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
7 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
8 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
9 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
10 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
11 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
12 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
13 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
14 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
15 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 |
16 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
17 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
18 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
19 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
20 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
21 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
22 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 |
23 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
24 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
25 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
26 | 2 | 1 | 0 | 1 | 1 | 1 | 1 | 1 |
27 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
28 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
29 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
30 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
31 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
32 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 |
33 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 |
34 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
35 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
36 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
37 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
38 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
39 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 |
40 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
41 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
42 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
43 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
44 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
45 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
46 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 |
47 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
48 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
49 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 |
50 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
51 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
52 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
53 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
54 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
55 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
56 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
57 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
58 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
59 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
60 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
61 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 |
62 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
63 | 2 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
64 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
65 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
66 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
67 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
68 | 3 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
69 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
70 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
71 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
72 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
73 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
74 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
75 | 2 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
76 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
77 | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
78 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
79 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
80 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
81 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
82 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
83 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
84 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
85 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
86 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
87 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
88 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
89 | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
90 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 |
91 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
92 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
93 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
94 | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
95 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 |
96 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 |
97 | 2 | 1 | 0 | 1 | 0 | 1 | 0 | 1 |
98 | 2 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
99 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
End of preview.
Machine Learning Dataset for Rabies Diagnosis and Outbreak Prediction
Contact
Asa Emmanuel at asakalonga@gmail.com and Kennedy Lushasi at klushasi@ihi.or.tz
Dataset
This dataset will help in the real-time and remote diagnosis of rabies disease for humans and animals in low-resource settings. A time series approach can be applied to the outbreak dataset to predict the number of rabies cases likely to occur within an area after a given time interval. This approach can help with resource mobilization, too, such as identifying the number of vaccines required in a specific area at a given time. The number of observations from the two datasets is 12,684. There are three datasets for rabies diagnosis for animals and humans, with 7,081 and 4,585 observations, respectively. In the outbreak prediction dataset, 1,018 observations were accounted for.
Authors and Affiliations
Asa Emmanuel, Rebecca Chaula, Deogratias Mzurikwao, Joel Changalucha, Kennedy Lushasi
How to cite
You can cite all versions by using DOI 10.5281/zenodo.10068425.
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