Jupyter-Agent
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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 3 new columns ({'Fertility Rate', 'Race', 'Birth Rate'}) and 3 missing columns ({'Birth Rates', 'Fertility Rates', 'Hispanic Origin'}).
This happened while the csv dataset builder was generating data using
hf://datasets/AdithyaSK/jupyter-agent-rl-10-data/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv (at revision 1f31f595153dd790938fdf1653197d746faf1461), [/tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-hispanic-origin-subgroup-united-states.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-hispanic-origin-subgroup-united-states.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/mirichoi0218/insurance/insurance.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/mirichoi0218/insurance/insurance.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1440.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1440.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_15.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_15.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_5.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_5.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_60.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_60.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_720.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_720.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/TradingHistory_ETC-USD.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/TradingHistory_ETC-USD.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/prkukunoor/TitanicDataset/titanic_data.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/prkukunoor/TitanicDataset/titanic_data.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/uciml/breast-cancer-wisconsin-data/data.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/uciml/breast-cancer-wisconsin-data/data.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/uciml/pima-indians-diabetes-database/diabetes.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/uciml/pima-indians-diabetes-database/diabetes.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/python3.12/site-packages/datasets/builder.py", line 1893, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Year: int64
Race: string
Live Births: int64
Birth Rate: double
Fertility Rate: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 843
to
{'Year': Value('int64'), 'Hispanic Origin': Value('string'), 'Live Births': Value('int64'), 'Birth Rates': Value('float64'), 'Fertility Rates': 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 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1895, 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 3 new columns ({'Fertility Rate', 'Race', 'Birth Rate'}) and 3 missing columns ({'Birth Rates', 'Fertility Rates', 'Hispanic Origin'}).
This happened while the csv dataset builder was generating data using
hf://datasets/AdithyaSK/jupyter-agent-rl-10-data/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv (at revision 1f31f595153dd790938fdf1653197d746faf1461), [/tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-hispanic-origin-subgroup-united-states.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-hispanic-origin-subgroup-united-states.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/cdc/nchs-natality-measures-for-females/nchs-natality-measures-for-females-by-race-and-hispanic-origin-united-states.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/mirichoi0218/insurance/insurance.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/mirichoi0218/insurance/insurance.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1440.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_1440.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_15.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_15.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_5.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_5.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_60.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_60.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_720.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/OHLCVT_ETC-USD_720.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/TradingHistory_ETC-USD.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/olmatz/etcusd-stock-market-kraken/TradingHistory_ETC-USD.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/prkukunoor/TitanicDataset/titanic_data.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/prkukunoor/TitanicDataset/titanic_data.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/uciml/breast-cancer-wisconsin-data/data.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/uciml/breast-cancer-wisconsin-data/data.csv), /tmp/hf-datasets-cache/medium/datasets/55716215024460-config-parquet-and-info-AdithyaSK-jupyter-agent-r-38930918/hub/datasets--AdithyaSK--jupyter-agent-rl-10-data/snapshots/1f31f595153dd790938fdf1653197d746faf1461/data/uciml/pima-indians-diabetes-database/diabetes.csv (origin=hf://datasets/AdithyaSK/jupyter-agent-rl-10-data@1f31f595153dd790938fdf1653197d746faf1461/data/uciml/pima-indians-diabetes-database/diabetes.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.
Year int64 | Hispanic Origin string | Live Births int64 | Birth Rates float64 | Fertility Rates float64 |
|---|---|---|---|---|
1,989 | Central and South American | 72,443 | 28.3 | 95.8 |
1,989 | Cuban | 10,842 | 10 | 49.8 |
1,989 | Mexican | 327,233 | 25.7 | 106.6 |
1,989 | Other and unknown Hispanic | 65,502 | null | null |
1,989 | Puerto Rican | 56,229 | 23.7 | 86.6 |
1,990 | Central and South American | 83,008 | 27.5 | 102.7 |
1,990 | Cuban | 11,311 | 10.9 | 52.6 |
1,990 | Mexican | 385,640 | 28.7 | 118.9 |
1,990 | Other and unknown Hispanic | 56,307 | null | null |
1,990 | Puerto Rican | 58,807 | 21.6 | 82.9 |
1,991 | Central and South American | 86,908 | 28.3 | 105.5 |
1,991 | Cuban | 11,058 | 9.8 | 47.6 |
1,991 | Mexican | 411,233 | 27.6 | 114.9 |
1,991 | Other and unknown Hispanic | 54,053 | null | null |
1,991 | Puerto Rican | 59,833 | 23.3 | 87.9 |
1,992 | Central and South American | 89,031 | 27.5 | 104.7 |
1,992 | Cuban | 11,472 | 10.1 | 49.4 |
1,992 | Mexican | 432,047 | 27.4 | 113.3 |
1,992 | Other and unknown Hispanic | 51,152 | null | null |
1,992 | Puerto Rican | 59,569 | 22.9 | 87.9 |
1,993 | Central and South American | 92,371 | 26.3 | 101.5 |
1,993 | Cuban | 11,916 | 10.5 | 53.9 |
1,993 | Mexican | 443,733 | 26.8 | 110.9 |
1,993 | Other and unknown Hispanic | 48,296 | null | null |
1,993 | Puerto Rican | 58,102 | 21.5 | 79.8 |
1,994 | Central and South American | 93,485 | 24.9 | 93.2 |
1,994 | Cuban | 11,889 | 10.7 | 53.6 |
1,994 | Mexican | 454,536 | 26.1 | 109.9 |
1,994 | Other and unknown Hispanic | 47,876 | null | null |
1,994 | Puerto Rican | 57,240 | 20.8 | 78.2 |
1,995 | Central and South American | 94,996 | 24.2 | 89.1 |
1,995 | Cuban | 12,473 | 10.8 | 52.2 |
1,995 | Mexican | 469,615 | 25.8 | 109.9 |
1,995 | Other and unknown Hispanic | 47,860 | null | null |
1,995 | Puerto Rican | 54,824 | 19 | 71.3 |
1,996 | Central and South American | 97,888 | 22.5 | 84.2 |
1,996 | Cuban | 12,613 | 10.6 | 55.1 |
1,996 | Mexican | 489,666 | 26.2 | 110.7 |
1,996 | Other and unknown Hispanic | 46,309 | null | null |
1,996 | Puerto Rican | 54,863 | 17.2 | 66.5 |
1,997 | Central and South American | 97,405 | 21.3 | 80.6 |
1,997 | Cuban | 12,887 | 10 | 53.1 |
1,997 | Mexican | 499,024 | 25.3 | 106.6 |
1,997 | Other and unknown Hispanic | 45,001 | null | null |
1,997 | Puerto Rican | 55,450 | 17.2 | 65.8 |
1,998 | Central and South American | 98,226 | 21.7 | 83.5 |
1,998 | Cuban | 13,226 | 9.7 | 46.5 |
1,998 | Mexican | 516,011 | 24.6 | 103.2 |
1,998 | Other and unknown Hispanic | 49,849 | null | null |
1,998 | Puerto Rican | 57,349 | 17.9 | 69.7 |
1,999 | Central and South American | 103,307 | 21.7 | 84.8 |
1,999 | Cuban | 13,088 | 9.4 | 47 |
1,999 | Mexican | 540,674 | 24.2 | 101.5 |
1,999 | Other and unknown Hispanic | 50,132 | null | null |
1,999 | Puerto Rican | 57,138 | 18 | 71.1 |
2,000 | Central and South American | 113,344 | 21.8 | 85.1 |
2,000 | Cuban | 13,429 | 9.7 | 49.3 |
2,000 | Mexican | 581,915 | 25 | 105.1 |
2,000 | Other and unknown Hispanic | 49,056 | null | null |
2,000 | Puerto Rican | 58,124 | 18.1 | 73.5 |
2,001 | Central and South American | 121,365 | 21.7 | 82.2 |
2,001 | Cuban | 14,017 | 10.3 | 56.4 |
2,001 | Mexican | 611,000 | 24.7 | 105 |
2,001 | Other and unknown Hispanic | 47,901 | null | null |
2,001 | Puerto Rican | 57,568 | 17.7 | 71.7 |
2,002 | Central and South American | 125,981 | 22.5 | 86.5 |
2,002 | Cuban | 14,232 | 10.1 | 59.3 |
2,002 | Mexican | 627,505 | 24.3 | 103 |
2,002 | Other and unknown Hispanic | 51,459 | null | null |
2,002 | Puerto Rican | 57,465 | 16.5 | 65.6 |
2,003 | Central and South American | 135,586 | 23 | 89.7 |
2,003 | Cuban | 14,867 | 10 | 60.8 |
2,003 | Mexican | 654,504 | 24.6 | 103.7 |
2,003 | Other and unknown Hispanic | 48,972 | null | null |
2,003 | Puerto Rican | 58,400 | 15 | 60.6 |
2,004 | Central and South American | 143,520 | 22.1 | 87.4 |
2,004 | Cuban | 14,943 | 9.3 | 52.2 |
2,004 | Mexican | 677,621 | 24.8 | 104.5 |
2,004 | Other and unknown Hispanic | 49,044 | null | null |
2,004 | Puerto Rican | 61,221 | 16 | 66.8 |
2,005 | Central and South American | 151,201 | 22.7 | 90.5 |
2,005 | Cuban | 16,064 | 10.2 | 49.1 |
2,005 | Mexican | 693,197 | 24.5 | 104.5 |
2,005 | Other and unknown Hispanic | 61,703 | null | null |
2,005 | Puerto Rican | 63,340 | 17 | 69.8 |
2,006 | Central and South American | 165,321 | 23.8 | 95.6 |
2,006 | Cuban | 16,936 | 10.4 | 47.9 |
2,006 | Mexican | 718,146 | 24.6 | 105.6 |
2,006 | Other and unknown Hispanic | 71,742 | null | null |
2,006 | Puerto Rican | 66,932 | 17.5 | 71.6 |
2,007 | Central and South American | 169,851 | 24.6 | 100.1 |
2,007 | Cuban | 16,981 | 10.2 | 47.6 |
2,007 | Mexican | 722,055 | 23.9 | 102.8 |
2,007 | Other and unknown Hispanic | 85,404 | null | null |
2,007 | Puerto Rican | 68,488 | 17.1 | 70.3 |
2,008 | Central and South American | 155,578 | 26.1 | 109.1 |
2,008 | Cuban | 16,718 | 10.1 | 50.1 |
2,008 | Mexican | 684,883 | 21.7 | 92.6 |
2,008 | Other and unknown Hispanic | 115,045 | null | null |
2,008 | Puerto Rican | 69,015 | 16.4 | 67 |
No dataset card yet