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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 13 new columns ({'2009', 'STATE', '2007', 'ANNUAL % GR', '2013', '2015', '2010', '2012', 'ANNUAL G.R', '2014', '2016', '2008', '2011'}) and 12 missing columns ({'POPULATION (2015)', 'POPULATION (2009)', 'AGE GROUP', 'POPULATION (2008)', 'proportion', 'POPULATION (2014)', 'POPULATION (2011)', 'POPULATION (2010)', 'POPULATION (2016)', 'POPULATION (2012)', 'POPULATION (2013)', 'POPULATION (2007)'}).
This happened while the csv dataset builder was generating data using
hf://datasets/electricsheepafrica/Nigeria-Population-and-Projections-by-state-2006-2016/population_projection.csv (at revision 8ad9577bfd100acb8dc00b92e3a05d65bcdd388b)
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 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, 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 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
STATE: string
POPULATION (2006): int64
ANNUAL % GR: double
ANNUAL G.R: double
2007: int64
2008: int64
2009: int64
2010: int64
2011: int64
2012: int64
2013: int64
2014: int64
2015: int64
2016: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1795
to
{'AGE GROUP': Value('string'), 'POPULATION (2006)': Value('int64'), 'proportion': Value('float64'), 'POPULATION (2007)': Value('int64'), 'POPULATION (2008)': Value('int64'), 'POPULATION (2009)': Value('int64'), 'POPULATION (2010)': Value('int64'), 'POPULATION (2011)': Value('int64'), 'POPULATION (2012)': Value('int64'), 'POPULATION (2013)': Value('int64'), 'POPULATION (2014)': Value('int64'), 'POPULATION (2015)': Value('int64'), 'POPULATION (2016)': Value('int64')}
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 1456, 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 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, 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 1702, 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 1833, 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 ({'2009', 'STATE', '2007', 'ANNUAL % GR', '2013', '2015', '2010', '2012', 'ANNUAL G.R', '2014', '2016', '2008', '2011'}) and 12 missing columns ({'POPULATION (2015)', 'POPULATION (2009)', 'AGE GROUP', 'POPULATION (2008)', 'proportion', 'POPULATION (2014)', 'POPULATION (2011)', 'POPULATION (2010)', 'POPULATION (2016)', 'POPULATION (2012)', 'POPULATION (2013)', 'POPULATION (2007)'}).
This happened while the csv dataset builder was generating data using
hf://datasets/electricsheepafrica/Nigeria-Population-and-Projections-by-state-2006-2016/population_projection.csv (at revision 8ad9577bfd100acb8dc00b92e3a05d65bcdd388b)
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.
AGE GROUP
string | POPULATION (2006)
int64 | proportion
float64 | POPULATION (2007)
int64 | POPULATION (2008)
int64 | POPULATION (2009)
int64 | POPULATION (2010)
int64 | POPULATION (2011)
int64 | POPULATION (2012)
int64 | POPULATION (2013)
int64 | POPULATION (2014)
int64 | POPULATION (2015)
int64 | POPULATION (2016)
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
0-4 | 22,594,967 | 0 | 23,329,699 | 24,088,323 | 24,871,615 | 25,680,378 | 26,515,439 | 27,377,655 | 28,267,908 | 29,187,110 | 30,136,202 | 31,116,156 |
5-9 | 20,005,380 | 0 | 20,655,905 | 21,327,584 | 22,021,103 | 22,737,175 | 23,476,531 | 24,239,929 | 25,028,151 | 25,842,004 | 26,682,322 | 27,549,964 |
10-14 | 16,135,950 | 0 | 16,660,651 | 17,202,414 | 17,761,793 | 18,339,362 | 18,935,713 | 19,551,455 | 20,187,219 | 20,843,657 | 21,521,441 | 22,221,265 |
15-19 | 14,899,419 | 0 | 15,383,911 | 15,884,157 | 16,400,671 | 16,933,979 | 17,484,630 | 18,053,187 | 18,640,231 | 19,246,365 | 19,872,209 | 20,518,404 |
20-24 | 13,435,079 | 0 | 13,871,954 | 14,323,036 | 14,788,785 | 15,269,679 | 15,766,211 | 16,278,889 | 16,808,238 | 17,354,800 | 17,919,135 | 18,501,820 |
25-29 | 12,211,426 | 0 | 12,608,511 | 13,018,508 | 13,441,838 | 13,878,933 | 14,330,241 | 14,796,225 | 15,277,361 | 15,774,143 | 16,287,079 | 16,816,694 |
30-34 | 9,467,538 | 0 | 9,775,399 | 10,093,270 | 10,421,478 | 10,760,359 | 11,110,259 | 11,471,537 | 11,844,562 | 12,229,718 | 12,627,398 | 13,038,009 |
35-39 | 7,331,755 | 0 | 7,570,165 | 7,816,328 | 8,070,496 | 8,332,928 | 8,603,894 | 8,883,671 | 9,172,546 | 9,470,815 | 9,778,782 | 10,096,763 |
40-44 | 6,456,470 | 0 | 6,666,418 | 6,883,194 | 7,107,018 | 7,338,120 | 7,576,738 | 7,823,114 | 8,077,503 | 8,340,163 | 8,611,364 | 8,891,384 |
45-49 | 4,591,293 | 0 | 4,740,590 | 4,894,743 | 5,053,907 | 5,218,248 | 5,387,932 | 5,563,134 | 5,744,034 | 5,930,815 | 6,123,671 | 6,322,797 |
50-54 | 4,249,219 | 0 | 4,387,393 | 4,530,060 | 4,677,366 | 4,829,463 | 4,986,505 | 5,148,653 | 5,316,075 | 5,488,940 | 5,667,427 | 5,851,717 |
55-59 | 2,066,247 | 0 | 2,133,436 | 2,202,810 | 2,274,440 | 2,348,399 | 2,424,763 | 2,503,611 | 2,585,022 | 2,669,080 | 2,755,872 | 2,845,486 |
60-64 | 2,450,286 | 0 | 2,529,963 | 2,612,231 | 2,697,175 | 2,784,880 | 2,875,437 | 2,968,939 | 3,065,482 | 3,165,164 | 3,268,087 | 3,374,357 |
65-69 | 1,151,048 | 0 | 1,188,477 | 1,227,124 | 1,267,027 | 1,308,227 | 1,350,767 | 1,394,691 | 1,440,043 | 1,486,869 | 1,535,219 | 1,585,140 |
70-74 | 1,330,597 | 0 | 1,373,865 | 1,418,539 | 1,464,667 | 1,512,294 | 1,561,470 | 1,612,245 | 1,664,671 | 1,718,802 | 1,774,693 | 1,832,402 |
75-79 | 579,838 | 0 | 598,693 | 618,161 | 638,262 | 659,017 | 680,446 | 702,573 | 725,419 | 749,007 | 773,363 | 798,511 |
80-84 | 760,053 | 0 | 784,768 | 810,287 | 836,635 | 863,841 | 891,930 | 920,934 | 950,880 | 981,801 | 1,013,726 | 1,046,690 |
85+ | 715,225 | 0 | 738,482 | 762,496 | 787,290 | 812,891 | 839,324 | 866,617 | 894,797 | 923,894 | 953,937 | 984,956 |
TOTAL | 140,431,790 | null | 144,998,281 | 149,713,264 | 154,581,566 | 159,608,173 | 164,798,232 | 170,157,060 | 175,690,143 | 181,403,148 | 187,301,926 | 193,392,517 |
null | 2,845,380 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,178,950 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,902,051 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,177,828 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,653,066 | null | null | null | null | null | null | null | null | null | null | null |
null | 1,704,515 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,253,641 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,171,104 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,892,988 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,112,445 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,176,947 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,233,366 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,398,957 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,267,837 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,365,040 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,927,563 | null | null | null | null | null | null | null | null | null | null | null |
null | 4,361,002 | null | null | null | null | null | null | null | null | null | null | null |
null | 6,113,503 | null | null | null | null | null | null | null | null | null | null | null |
null | 9,401,288 | null | null | null | null | null | null | null | null | null | null | null |
null | 5,801,584 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,256,541 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,314,043 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,365,353 | null | null | null | null | null | null | null | null | null | null | null |
null | 9,113,605 | null | null | null | null | null | null | null | null | null | null | null |
null | 1,869,377 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,954,772 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,751,140 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,460,877 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,416,959 | null | null | null | null | null | null | null | null | null | null | null |
null | 5,580,894 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,206,531 | null | null | null | null | null | null | null | null | null | null | null |
null | 5,198,716 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,702,676 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,294,800 | null | null | null | null | null | null | null | null | null | null | null |
null | 2,321,339 | null | null | null | null | null | null | null | null | null | null | null |
null | 3,278,873 | null | null | null | null | null | null | null | null | null | null | null |
null | 1,406,239 | null | null | null | null | null | null | null | null | null | null | null |
null | 140,431,790 | 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 |
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Datacard: Nigeria Population and Projections (2006-2016)
Dataset Description
This collection consists of three cleaned datasets detailing Nigeria's population statistics from 2006 to 2016. The data is broken down by state and includes population projections, age group distributions, and sex ratios.
Source
Nigerian Bureau of Statistics (NBS)
Cleaned Datasets
1. population_projection.csv
- Description: Contains the base population in 2006 and annual projections for each state up to 2016.
- Columns:
STATE,POPULATION (2006),ANNUAL % GR,ANNUAL G.R,2007,2008, ...,2016
2. age_group.csv
- Description: Provides population counts broken down by age group for each state.
- Columns:
AGE GROUP,TOTAL,MALE,FEMALE,RURAL,URBAN
3. sex_ratio.csv
- Description: Details the male, female, and total population counts for each state from 2007 to 2016.
- Columns:
STATE,2007_MALE,2007_FEMALE,2007_TOTAL, ...,2016_MALE,2016_FEMALE,2016_TOTAL
Intended Use
These datasets are cleaned and structured for use in data analysis, visualization, and machine learning tasks. The clear formatting and consistent data types make them easy to load and work with in standard data science libraries like Pandas, Scikit-learn, and TensorFlow.
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