Datasets:

Farmaanaa
/

bitcoin_price_timeseries

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 68520.9 was truncated converting to int64
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 2223, in cast_table_to_schema
                  arrays = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2224, in <listcomp>
                  cast_array_to_feature(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2086, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1949, in array_cast
                  return array.cast(pa_type)
                File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
                  return call_function("cast", [arr], options, memory_pool)
                File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Float value 68520.9 was truncated converting to int64
              
              The above exception was the direct cause of the following exception:
              
              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 1858, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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Timestamp string	Open int64	High int64	Low int64	Close int64	Volume float64
9/13/2024 4:00	57,854	57,864	57,835	57,835	1.353466
9/13/2024 3:59	57,854	57,854	57,854	57,854	0.252322
9/13/2024 3:58	57,875	57,875	57,842	57,842	1.271825
9/13/2024 3:57	57,875	57,877	57,875	57,877	0.28894
9/13/2024 3:56	57,876	57,876	57,876	57,876	0.00055
9/13/2024 3:55	57,881	57,881	57,870	57,870	0.12935
9/13/2024 3:54	57,855	57,888	57,854	57,888	2.362677
9/13/2024 3:53	57,890	57,890	57,855	57,855	3.441031
9/13/2024 3:52	57,904	57,904	57,890	57,892	0.484875
9/13/2024 3:51	57,910	57,917	57,910	57,914	0.040538
9/13/2024 3:50	57,903	57,912	57,903	57,905	0.249663
9/13/2024 3:49	57,913	57,913	57,897	57,897	0.251235
9/13/2024 3:48	57,939	57,939	57,913	57,913	0.002848
9/13/2024 3:47	57,890	57,940	57,890	57,940	0.454264
9/13/2024 3:46	57,916	57,916	57,890	57,890	0.100449
9/13/2024 3:45	57,922	57,922	57,922	57,922	0
9/13/2024 3:44	57,923	57,927	57,922	57,922	0.253365
9/13/2024 3:43	57,916	57,923	57,916	57,923	0.00646
9/13/2024 3:42	57,898	57,901	57,898	57,898	0.009563
9/13/2024 3:41	57,890	57,896	57,890	57,895	0.235827
9/13/2024 3:40	57,910	57,910	57,890	57,890	2.99283
9/13/2024 3:39	57,910	57,911	57,910	57,911	0.020907
9/13/2024 3:38	57,924	57,924	57,911	57,911	1.209555
9/13/2024 3:37	57,946	57,946	57,925	57,925	1.868069
9/13/2024 3:36	57,953	57,967	57,945	57,950	0.99992
9/13/2024 3:35	57,977	57,980	57,952	57,952	0.139981
9/13/2024 3:34	57,972	57,977	57,972	57,977	0.258649
9/13/2024 3:33	57,957	57,986	57,957	57,972	0.514723
9/13/2024 3:32	57,992	57,992	57,952	57,956	8.115338
9/13/2024 3:31	58,016	58,016	57,990	57,999	0.420039
9/13/2024 3:30	58,020	58,020	58,016	58,016	0.040576
9/13/2024 3:29	58,017	58,028	58,017	58,021	0.159991
9/13/2024 3:28	58,017	58,017	58,017	58,017	0.002402
9/13/2024 3:27	58,028	58,028	58,023	58,023	0.135526
9/13/2024 3:26	58,006	58,030	58,006	58,030	0.331418
9/13/2024 3:25	58,001	58,006	58,001	58,006	0.266883
9/13/2024 3:24	58,000	58,001	58,000	58,001	0.022015
9/13/2024 3:23	58,007	58,007	58,000	58,001	0.002949
9/13/2024 3:22	58,007	58,007	58,007	58,007	0.000612
9/13/2024 3:21	58,023	58,023	58,019	58,023	0.454692
9/13/2024 3:20	58,023	58,023	58,023	58,023	0.010511
9/13/2024 3:19	58,023	58,026	58,023	58,023	0.288338
9/13/2024 3:18	58,023	58,023	58,023	58,023	0.001224
9/13/2024 3:17	58,023	58,023	58,023	58,023	0.035912
9/13/2024 3:16	58,022	58,023	58,022	58,023	0.327427
9/13/2024 3:15	58,025	58,035	58,025	58,028	0.253993
9/13/2024 3:14	58,031	58,031	58,026	58,026	0.167864
9/13/2024 3:13	58,055	58,056	58,039	58,039	0.214047
9/13/2024 3:12	58,043	58,057	58,043	58,055	0.256982
9/13/2024 3:11	58,057	58,057	58,043	58,043	0.600667
9/13/2024 3:10	58,056	58,067	58,056	58,059	0.157989
9/13/2024 3:09	58,061	58,061	58,053	58,056	0.691012
9/13/2024 3:08	58,059	58,059	58,059	58,059	0.004582
9/13/2024 3:07	58,062	58,074	58,062	58,074	0.259771
9/13/2024 3:06	58,042	58,062	58,042	58,062	0.020174
9/13/2024 3:05	58,044	58,047	58,044	58,047	0.076389
9/13/2024 3:04	58,034	58,048	58,034	58,048	0.188889
9/13/2024 3:03	58,052	58,052	58,043	58,043	0.086412
9/13/2024 3:02	58,038	58,067	58,038	58,067	0.038747
9/13/2024 3:01	58,038	58,038	58,037	58,038	0.022378
9/13/2024 3:00	58,048	58,048	58,048	58,048	0.00326
9/13/2024 2:59	58,052	58,055	58,051	58,055	0.298292
9/13/2024 2:58	58,052	58,052	58,052	58,052	0.000726
9/13/2024 2:57	58,035	58,053	58,035	58,053	0.321316
9/13/2024 2:56	58,044	58,049	58,035	58,035	0.379525
9/13/2024 2:55	58,084	58,084	58,065	58,065	0.323446
9/13/2024 2:54	58,059	58,088	58,059	58,085	0.869788
9/13/2024 2:53	58,047	58,058	58,047	58,058	0.138252
9/13/2024 2:52	58,072	58,072	58,072	58,072	0
9/13/2024 2:51	58,072	58,072	58,072	58,072	0.110853
9/13/2024 2:50	58,072	58,076	58,072	58,072	0.018674
9/13/2024 2:49	58,072	58,072	58,072	58,072	0.001181
9/13/2024 2:48	58,066	58,072	58,066	58,072	0.255151
9/13/2024 2:47	58,066	58,069	58,066	58,067	0.253155
9/13/2024 2:46	58,079	58,079	58,073	58,073	0.088523
9/13/2024 2:45	58,098	58,100	58,077	58,077	0.366482
9/13/2024 2:44	58,087	58,087	58,087	58,087	0.045143
9/13/2024 2:43	58,093	58,093	58,089	58,090	0.003102
9/13/2024 2:42	58,084	58,093	58,084	58,092	0.283763
9/13/2024 2:41	58,093	58,093	58,084	58,084	0.003562
9/13/2024 2:40	58,062	58,098	58,062	58,098	1.042028
9/13/2024 2:39	58,095	58,095	58,084	58,087	0.153913
9/13/2024 2:38	58,078	58,098	58,078	58,098	1.310492
9/13/2024 2:37	58,058	58,080	58,058	58,080	0.319206
9/13/2024 2:36	58,077	58,078	58,058	58,058	0.275202
9/13/2024 2:35	58,071	58,080	58,071	58,080	6.659782
9/13/2024 2:34	58,074	58,074	58,066	58,066	0.25669
9/13/2024 2:33	58,041	58,073	58,041	58,073	0.019808
9/13/2024 2:32	58,041	58,046	58,041	58,041	0.131822
9/13/2024 2:31	58,016	58,041	58,010	58,041	0.288022
9/13/2024 2:30	58,041	58,041	58,041	58,041	0
9/13/2024 2:29	58,018	58,041	58,018	58,041	0.163678
9/13/2024 2:28	58,027	58,027	58,017	58,018	0.299779
9/13/2024 2:27	58,018	58,026	58,018	58,026	0.012601
9/13/2024 2:26	58,032	58,032	58,032	58,032	0.0034
9/13/2024 2:25	58,036	58,036	58,026	58,026	0.147052
9/13/2024 2:24	58,000	58,031	57,990	58,031	19.932578
9/13/2024 2:23	58,001	58,001	58,001	58,001	0.043661
9/13/2024 2:22	58,035	58,035	58,005	58,006	0.039097
9/13/2024 2:21	58,043	58,056	58,043	58,053	0.266632

End of preview.

Bitcoin Price Time Series Data

Dataset Overview

This dataset offers a detailed, time-stamped record of Bitcoin's price and trading volume. It is an invaluable resource for financial analysis, market forecasting, and research into the dynamics of the cryptocurrency market.

Data Source

The data was collected from a cryptocurrency exchange.

Data Preparation

The data has been meticulously cleaned and prepared for this dataset by farmaanaa.ir.

What's Included in the Dataset?

The dataset is provided in a CSV format and includes the following columns:

Column Name	Description	Data Type	Example
`Timestamp`	The exact date and time of the data point.	Date/Time	`9/13/2024 4:00`
`Open`	The price at the beginning of the time interval.	Float	`57854`
`High`	The highest price reached during the interval.	Float	`57864`
`Low`	The lowest price reached during the interval.	Float	`57835`
`Close`	The price at the end of the time interval.	Float	`57835`
`Volume`	The total trading volume during the interval.	Float	`1.35346619`

Usage Examples

This dataset can be used for various purposes, including but not limited to:

Algorithmic Trading: Developing and backtesting trading strategies.
Market Analysis: Identifying trends, support/resistance levels, and periods of high volatility.
Academic Research: Studying market behavior, efficiency, and the impact of external events on cryptocurrency prices.
Data Visualization: Creating real-time or historical charts of Bitcoin's price movements. license: cc-by-4.0

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