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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 2 new columns ({'word', 'freq'}) and 2 missing columns ({'ISO code', 'Language Name'}).
This happened while the csv dataset builder was generating data using
hf://datasets/chrisjay/ratman-stopword-lists-for-african-languages/af_frequency_list.csv (at revision 72de778bde0f0b8f1d7cce7a390e7ba1b5cc961f)
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
freq: int64
word: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 475
to
{'ISO code': Value(dtype='string', id=None), 'Language Name': Value(dtype='string', 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 2 new columns ({'word', 'freq'}) and 2 missing columns ({'ISO code', 'Language Name'}).
This happened while the csv dataset builder was generating data using
hf://datasets/chrisjay/ratman-stopword-lists-for-african-languages/af_frequency_list.csv (at revision 72de778bde0f0b8f1d7cce7a390e7ba1b5cc961f)
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.
ISO code
string | Language Name
string |
|---|---|
adh | Dhopadhola |
af | Afrikaans |
alz | Alur |
am | Amharic |
anu | Anywak |
bxk | Lubukusu |
cce | Cicopi |
de | German |
dag | Dagbani/Dagbanli |
dga | Dagaare |
dje | Zarma |
ee | Ewe |
en | English |
ff | Fulfulde |
fr | French |
gjn | Gonja |
gur | Gurene |
guz | Ekegusii |
ha | Hausa |
kam | Kikamba |
kdj | Ngakarimojong |
keo | Kakwa |
ki | Gikuyu |
kln | Kalenjin |
kpz | Sabinyi |
kr | Kanuri |
laj | Leblango |
lgg | Lugbarati |
lgg-official | Lugbarati (Official) |
lg | Luganda |
lko | Olukhayo |
lsm | Lusamia |
luc | Aringati |
luo | Dholuo |
lwg | Oluwanga |
mas | Maa |
mer | Kimîîru |
mhi | Ma'di |
myx | Lumasaaba |
nle | Olunyala |
nr | isiNdebele |
nso | Sepedi |
nuj | Lunyole |
nyn | Chichewa |
nyn | Runyankore |
nyu | Chinyungwe |
om | Afan Oromo |
pt | Portuguese |
rw | Kinyarwanda |
so | Somali |
ss | siSwati |
st | Sesotho |
sw | Kiswahili |
teo | Ateso |
tn | Setswana |
toh | Gitonga |
tsc | Xitswa |
ts | Xitsonga |
ttj | Rutooro |
tuv | Ng'aturkana |
ve | Tshivenda |
xh | isiXhosa |
xog | Lusoga |
yo | Yoruba |
zne | Zande |
zu | isiZulu |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
null | null |
Dataset Card for Stopword Lists for African Languages
Dataset Summary
Context:
Some words, like “the” or “and” in English, are used a lot in speech and writing. For most Natural Language Processing applications, you will want to remove these very frequent words. This is usually done using a list of “stopwords” which has been complied by hand.
Content:
This project uses the source texts provided by the African Storybook Project as a corpus and provides a number of tools to extract frequency lists and lists of stopwords from this corpus for the 60+ languages covered by ASP.
Included in this dataset are the following languages:
- Afrikaans: stoplist and word frequency
- Hausa: stoplist and word frequency
- Lugbarati: word frequency only
- Lugbarati (Official): word frequency only
- Somali: stoplist and word frequency
- Sesotho: stoplist and word frequency
- Kiswahili: stoplist and word frequency
- Yoruba: stoplist and word frequency
- isiZulu: stoplist and word frequency
Files are named using the language’s ISO code. For each language, code.txt is the list of stopwords, and code_frequency_list.txt is word frequency information. A list of ISO codes the the languages associated with them may be found in ISO_codes.csv.
Acknowledgements:
This project therefore attempts to fill in the gap in language coverage for African language stoplists by using the freely-available and open-licensed ASP Source project as a corpus. Dual-licensed under CC-BY and Apache-2.0 license. Compiled by Liam Doherty. More information and the scripts used to generate these files are available here.
Inspiration:
This dataset is mainly helpful for use during NLP analysis, however there may some interesting insights in the data.
- What qualities do stopwords share across languages? Given a novel language, could you predict what its stopwords should be?
- What stopwords are shared across languages?
- Often, related languages will have words with the same meaning and similar spellings. Can you automatically identify any of these pairs of words?
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Dataset Structure
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This dataset was shared by @rtatman
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