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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 8 new columns ({'used-auto_wow', 'auto-loan_wow', 'auto-loan', 'week_ending', 'source', 'used-auto', 'new-auto', 'new-auto_wow'}) and 8 missing columns ({'burden_band', 'rank', 'observation_date', 'premium_pct_of_median_income', 'state_name', 'naic_data_year', 'state_abbr', 'aibi_score'}).
This happened while the csv dataset builder was generating data using
hf://datasets/MonitorBankRates/us-bank-rate-averages/auto_loan_national.csv (at revision b34f455f7df2fbd2cf8de7d086ebe0c9022626e6), ['hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/aibi_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/auto_loan_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/cd_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/cd_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/credit_card_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hai_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hai_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hibi_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/money_market_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/money_market_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/mortgage_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/personal_loan_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/savings_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/savings_states.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/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
week_ending: string
new-auto: string
used-auto: string
auto-loan: double
new-auto_wow: double
used-auto_wow: double
auto-loan_wow: double
source: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1245
to
{'rank': Value('float64'), 'state_abbr': Value('string'), 'state_name': Value('string'), 'aibi_score': Value('float64'), 'burden_band': Value('string'), 'premium_pct_of_median_income': Value('float64'), 'naic_data_year': Value('int64'), 'observation_date': Value('string')}
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 8 new columns ({'used-auto_wow', 'auto-loan_wow', 'auto-loan', 'week_ending', 'source', 'used-auto', 'new-auto', 'new-auto_wow'}) and 8 missing columns ({'burden_band', 'rank', 'observation_date', 'premium_pct_of_median_income', 'state_name', 'naic_data_year', 'state_abbr', 'aibi_score'}).
This happened while the csv dataset builder was generating data using
hf://datasets/MonitorBankRates/us-bank-rate-averages/auto_loan_national.csv (at revision b34f455f7df2fbd2cf8de7d086ebe0c9022626e6), ['hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/aibi_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/auto_loan_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/cd_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/cd_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/credit_card_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hai_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hai_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/hibi_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/money_market_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/money_market_states.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/mortgage_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/personal_loan_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/savings_national.csv', 'hf://datasets/MonitorBankRates/us-bank-rate-averages@b34f455f7df2fbd2cf8de7d086ebe0c9022626e6/savings_states.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.
rank float64 | state_abbr string | state_name string | aibi_score float64 | burden_band string | premium_pct_of_median_income float64 | naic_data_year int64 | observation_date string |
|---|---|---|---|---|---|---|---|
1 | LA | Louisiana | 165.9 | Severe | 2.87 | 2,022 | 2026-09-04 |
2 | FL | Florida | 142.1 | Severe | 2.28 | 2,022 | 2026-09-04 |
3 | NY | New York | 128.4 | High | 1.95 | 2,022 | 2026-09-04 |
4 | GA | Georgia | 123.4 | High | 1.96 | 2,022 | 2026-09-04 |
5 | MS | Mississippi | 123.2 | High | 2.18 | 2,022 | 2026-09-04 |
6 | MI | Michigan | 120.9 | High | 1.96 | 2,022 | 2026-09-04 |
7 | RI | Rhode Island | 119.1 | High | 1.79 | 2,022 | 2026-09-04 |
8 | TX | Texas | 118.9 | High | 1.87 | 2,022 | 2026-09-04 |
9 | SC | South Carolina | 116.3 | High | 1.92 | 2,022 | 2026-09-04 |
10 | NV | Nevada | 115.1 | High | 1.82 | 2,022 | 2026-09-04 |
11 | DC | District of Columbia | 108.9 | Moderate | 1.48 | 2,022 | 2026-09-04 |
12 | AR | Arkansas | 107.7 | Moderate | 1.86 | 2,022 | 2026-09-04 |
13 | DE | Delaware | 107.1 | Moderate | 1.64 | 2,022 | 2026-09-04 |
14 | OK | Oklahoma | 106.7 | Moderate | 1.8 | 2,022 | 2026-09-04 |
15 | WV | West Virginia | 105.9 | Moderate | 1.84 | 2,022 | 2026-09-04 |
16 | NM | New Mexico | 105.6 | Moderate | 1.79 | 2,022 | 2026-09-04 |
17 | NJ | New Jersey | 105.1 | Moderate | 1.47 | 2,022 | 2026-09-04 |
18 | CO | Colorado | 104.3 | Moderate | 1.51 | 2,022 | 2026-09-04 |
19 | AL | Alabama | 103.7 | Moderate | 1.76 | 2,022 | 2026-09-04 |
20 | AZ | Arizona | 102.9 | Moderate | 1.61 | 2,022 | 2026-09-04 |
21 | KY | Kentucky | 99.4 | Moderate | 1.69 | 2,022 | 2026-09-04 |
22 | CT | Connecticut | 98.9 | Moderate | 1.43 | 2,022 | 2026-09-04 |
23 | MO | Missouri | 97.8 | Moderate | 1.6 | 2,022 | 2026-09-04 |
24 | MD | Maryland | 95.7 | Moderate | 1.34 | 2,022 | 2026-09-04 |
25 | TN | Tennessee | 92.4 | Moderate | 1.52 | 2,022 | 2026-09-04 |
26 | MT | Montana | 91.7 | Moderate | 1.49 | 2,022 | 2026-09-04 |
27 | PA | Pennsylvania | 90.9 | Moderate | 1.44 | 2,022 | 2026-09-04 |
28 | CA | California | 88.3 | Moderate | 1.26 | 2,022 | 2026-09-04 |
29 | KS | Kansas | 88 | Moderate | 1.42 | 2,022 | 2026-09-04 |
30 | WY | Wyoming | 87 | Moderate | 1.39 | 2,022 | 2026-09-04 |
31 | NE | Nebraska | 86.3 | Moderate | 1.37 | 2,022 | 2026-09-04 |
32 | MA | Massachusetts | 86.1 | Moderate | 1.2 | 2,022 | 2026-09-04 |
33 | OR | Oregon | 85.1 | Moderate | 1.31 | 2,022 | 2026-09-04 |
34 | SD | South Dakota | 85 | Moderate | 1.36 | 2,022 | 2026-09-04 |
35 | AK | Alaska | 84.7 | Low | 1.24 | 2,022 | 2026-09-04 |
36 | IL | Illinois | 84.2 | Low | 1.3 | 2,022 | 2026-09-04 |
37 | NC | North Carolina | 84.1 | Low | 1.37 | 2,022 | 2026-09-04 |
38 | UT | Utah | 81.6 | Low | 1.19 | 2,022 | 2026-09-04 |
39 | WA | Washington | 79.9 | Low | 1.15 | 2,022 | 2026-09-04 |
40 | MN | Minnesota | 79.8 | Low | 1.19 | 2,022 | 2026-09-04 |
41 | OH | Ohio | 77.9 | Low | 1.27 | 2,022 | 2026-09-04 |
42 | IN | Indiana | 77.3 | Low | 1.26 | 2,022 | 2026-09-04 |
43 | VA | Virginia | 77.1 | Low | 1.13 | 2,022 | 2026-09-04 |
44 | IA | Iowa | 75 | Low | 1.2 | 2,022 | 2026-09-04 |
45 | ID | Idaho | 71.5 | Low | 1.13 | 2,022 | 2026-09-04 |
46 | ND | North Dakota | 71.4 | Low | 1.14 | 2,022 | 2026-09-04 |
47 | WI | Wisconsin | 71.4 | Low | 1.13 | 2,022 | 2026-09-04 |
48 | ME | Maine | 69.6 | Low | 1.12 | 2,022 | 2026-09-04 |
49 | VT | Vermont | 67.7 | Low | 1.05 | 2,022 | 2026-09-04 |
50 | HI | Hawaii | 66.8 | Low | 0.95 | 2,022 | 2026-09-04 |
51 | NH | New Hampshire | 64.7 | Low | 0.92 | 2,022 | 2026-09-04 |
null | US | United States (baseline) | 100 | Baseline | 1.56 | 2,022 | 2026-09-04 |
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End of preview.
MonitorBankRates U.S. Bank & Credit Union Rate Averages
Weekly national and state-level average interest rates for U.S. consumer deposit and lending products, computed by MonitorBankRates.com from the published rates of more than 8,000 FDIC-insured banks and NCUA-chartered credit unions, plus the MonitorBankRates Housing Affordability Index and Insurance Burden Indexes.
Source: MonitorBankRates.com (Monitor Bank Rates LLC), collecting rates since 2008. Coverage: United States, national and all 50 states + DC. Series start: March 2026 (daily averages; weekly snapshots published here). Update cadence: Weekly. License: CC BY 4.0 — free to use with attribution to "MonitorBankRates.com" and a link.
Files
| File | Scope | Contents |
|---|---|---|
savings_national.csv / savings_states.csv |
US / by state | Standard, high-yield, jumbo, credit union, business savings APY |
money_market_national.csv / money_market_states.csv |
US / by state | Standard, high-yield, jumbo, credit union, business money market APY |
cd_national.csv / cd_states.csv |
US / by state | CD APY for 3, 6, 12, 18, 24, 36, 48, 60-month terms |
checking_national.csv / checking_states.csv |
US / by state | High-yield, rewards, free, credit union, business checking APY |
mortgage_national.csv |
US | 30-year, 15-year, ARM, jumbo, FHA, VA mortgage APR |
auto_loan_national.csv |
US | New, used, and general auto loan APR |
personal_loan_national.csv |
US | Unsecured personal, debt consolidation, signature loan APR |
credit_card_national.csv |
US | Credit card APR by card type |
hai_national.csv / hai_states.csv |
US / by state | MBR Housing Affordability Index (MBR-HAI) score history |
hibi_states.csv |
by state | MBR Home Insurance Burden Index (annual) |
aibi_states.csv |
by state | MBR Auto Insurance Burden Index (annual) |
Rates are in percent (e.g. 2.855 = 2.855%). Deposit products are annual percentage yield (APY); lending products are
annual percentage rate (APR). Each row carries the observation date.
Methodology
MonitorBankRates collects published rates daily from each institution's own rate pages. An average is the simple mean of
every current, plausible published quote for a product classification across all institutions — not a survey sample and
not weighted by deposits. Products are classified into standard keys (for example, 12-month for any certificate with a
12-month term). State averages include institutions headquartered in the state or operating branches there.
The MBR Housing Affordability Index scores 100 when a median-income household can exactly afford the median-priced home at the current MBR average 30-year mortgage rate; higher is more affordable. It is recomputed daily from the mortgage average, ACS median income and home value, and standard underwriting assumptions.
The Home and Auto Insurance Burden Indexes score 100 at the U.S. average burden (premium as a share of median household income, blended with premium level); higher is a heavier burden. Premium data from NAIC, incomes from ACS. Updated annually.
Full methodology and live pages: https://www.monitorbankrates.com/datasets/
Citation
MonitorBankRates.com, U.S. Bank & Credit Union Rate Averages, Monitor Bank Rates LLC, 2026. https://www.monitorbankrates.com/datasets/
Also available
- Free MCP server for AI assistants (Claude, ChatGPT):
https://mcp.monitorbankrates.com/mcp - Licensed REST API for institutional use: https://www.monitorbankrates.com/bank-rate-data-api-competitive-intelligence-dashboard/
- Terms: https://www.monitorbankrates.com/api-terms/
Disclaimer
Rates change daily and are published by institutions without notice; verify with the institution before acting. MonitorBankRates.com is an independent rate aggregator, not a bank, lender, insurer, or financial adviser. Index scores are MonitorBankRates methodologies, not guarantees.
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