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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 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
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